Miscellaneous problems in maritime navigation, transport and shipping  marine navigation and safety of sea transportation

Weintrit & T Neumann

WiĞniewski & P Kaczmarek 2 Baltic Navigation in Ice in the Twenty First Century

Maritime University of Szczecin, Poland

The updated Cyclone II program was utilized to analyze numerous cases of ships encountering developed cyclones, providing navigators with crucial recommendations for safe navigation around tropical cyclones Three specific scenarios were identified in which vessels might enter cyclone-affected areas, prompting commanders to consider essential guidelines for safely passing through or avoiding these hazardous weather conditions.

– vessel – cyclone encounter, where if on opposite course, the most effective is course alteration;

– when the ship overtakes the cyclone, speed reduction is the most effective action;

– when the vessel and the cyclone are on crossing routes (30 ÷ 90°), a slight decrease in speed or a slight course alteration or both actions can be effective

MAX WIND 110 KT GUSTS 135 KT

64 KT 90NE 45SE 30SW 75NW

50 KT 120NE 90SE 60SW 100NW

34 KT 225NE 200SE 100SW 200NW

50 KT 120NE 100SE 70SW 100NW

34 KT 225NE 200SE 120SW 180NW

50 KT 120NE 100SE 70SW 100NW

34 KT 225NE 200SE 120SW 180NW

50 KT 120NE 100SE 70SW 100NW

34 KT 225NE 200SE 120SW 180NW

50 KT 120NE 120SE 70SW 100NW

34 KT 225NE 225SE 120SW 180NW

Four ship positions for 12.00 (20.08.2009) a ship at the port road of New York travelling to

Brazil, vessel B in the position ĳ = 15.07qN,

O 9.9qW on the way to N York, ship in the Mona Passage ĳ = 18.04°N,

O 4.98qW on the way to Europe, ship in the actual position D ĳ = 40°N,

O = 040qW on the way to N York, and the position of the cyclone ĳc = 22.1°N,

O = 061qW at the same time and day

In connection with weather forecasts for the next

12, 24, 36, 48, and 72 hours, cyclone positions were taken from messages and then future ship’s positions were calculated

Ship A departed from New York after receiving a cyclone warning, entering crucial data into the "Cyclone II" computing program This included the ship's position, intended course to Brazil at a ground speed of 15 knots, and an estimated speed of 13 knots Additionally, data regarding the cyclone's location, course, and speed were input, along with forecasts for the cyclone at 12, 24, 36, 48, and 72 hours.

The calculation results indicate that the ship pro- ceeds to a dangerous course sector 149q - 197q,

1254.7 Nm from the eye of the cyclone, and after

In 43.7 hours, the vessel will reach its closest point of approach (CPA) at 234 nautical miles from the cyclone Using the cyclone's position from a 72-hour forecast, which shows the predicted path of the cyclone, the captain adjusts the ship’s course to a course over ground (COG) of 180 degrees and plans to reassess the vessel's and cyclone's positions in 12 hours.

The calculations and relative positions of the ship in relation to the cyclone are illustrated in Figure 2, showing results after 24 hours After 48 hours, the ship successfully navigates past the cyclone and adjusts its course with a new course over ground (COG) of 130 degrees, ensuring a safe distance of 328.4 nautical miles from the cyclone's eye as depicted in Figure 3, while returning to Brazil.

Finally, the ship extends its distance covered by 210Nm, maintaining a speed of 13.2 kn, i.e and will prolong the voyage by 16 hours to pass by the cyclone

Ship B, currently located at 51.07°N, 059.9°W and en route to New York with a course over ground of 230° and a speed of 23 knots, is on a potentially hazardous trajectory It is estimated that in 37.8 hours, the vessel will reach its closest point of approach, approximately 129.2 nautical miles from the cyclone's influence, facing winds of 34 knots To ensure safety, the ship must reduce its speed to below 19.1 knots.

To circumvent the cyclone-affected region, the vessel will detour by 72 nautical miles (equivalent to three times 24 nautical miles), maintaining a speed of 19.1 knots This diversion extends the estimated voyage duration by approximately 3 hours and 40 minutes.

On August 20, 2009, Ship (C) was navigating the Mona Passage en route to Europe while conducting tests to safely bypass Cyclone Bill The data indicated that the vessel was on the edge of a hazardous zone (331q to 55q), maintaining a course over ground (COG) of 055q at a speed of 13 knots By inputting cyclone forecast data into the Cyclone II program for up to 72 hours, the ship's commander determined that if the ship continued at 13 knots, it would remain on course and enter a safe zone after 12 hours, with a closest point of approach of 333.4 nautical miles from the cyclone's eye Consequently, no adjustments to speed or course were necessary, ensuring that the distance and voyage time would not be extended.

On August 20, 2009, at 12:00 UTC, ship (D) was located at 40°N, 39.15°W, heading towards New York with a course over ground (COG) of 270° With a speed of 13.0 knots, simulations indicated that within 48 hours, the vessel would approach a dangerous sector between 272° and 358°, sailing at a distance of 907.16 nautical miles from the eye of Cyclone Bill Visual representations of this simulated situation are provided in Figures 7, 8, and 9 for August.

22 nd 2009 The ship, sailing one day on course COG

The ship adjusted its course from 230q to COG 288q, extending the original rhumb line route by approximately 104 nautical miles, which resulted in an additional travel time of 8 hours Successfully maneuvering around the cyclone, the vessel maintained a safe distance of 338 nautical miles from the outer dangerous area, where wave heights reached 4.0 meters Simulations of the cyclone and the ship's position were conducted to analyze the situation.

15 jections for the next 72 hours, we get a positive result confirming cyclone avoidance

In a collision scenario involving a vessel and a cyclone on opposing courses, altering the course of the ship (Ship A) proves to be the most effective strategy Merely reducing speed does not yield positive results, particularly when the cyclone is moving at a speed of 10 knots.

To effectively manage a ship overtaking a cyclone, reducing the ship's speed relative to the cyclone's movement is the most advantageous strategy This approach minimizes the duration of the journey and likely results in lower fuel consumption.

In certain situations, a vessel may anticipate that its planned route will intersect with a cyclone's path; however, it does not enter the cyclone-affected area and maintains its speed and course, as seen with vessel C.

Figure 1 Graphic illustration of the cyclone path, based on weather report and calculations for ship A, heading for Brazil

Figure 2 Graphic picture of cyclone and ship A positions, after

24 hour travelling time, and calculation results

4 With the projected route of the vessel and the cyclone path are likely to cross each other (30 ÷

90q), and when the probability of vessel entry in- to the area of cyclone influence, slight ship’s speed decrease or small course alteration ('COG

40q) can be effective, as illustrated by the case of ship D, or both changes mentioned above may be made

Figure 3 Graphic picture of ship A and cyclone positions after

48 hours in relation to course alteration to 130 degrees

Figure 4 Graphic picture of cyclone track according to received data and calculations for ship B, heading for New York (20- 08-2009, 1200 UTC)

Figure 5 Graphic picture of cyclone track according to received data and calculation results for ship C, Mona Passage, ship proceeding to Europe (20-08-2009, 1200 UTC)

Figure 6 Graphic picture of cyclone and ship C positions during the voyage and calculation results

Figure 7 Graphic results of cyclone track according to message and calculation results for ship D after 48 travel hours from

Figure 8 Graphic picture of cyclone and ship D positions according to the message on 22-08-2009, after altering course

Figure 9 Graphic picture of cyclone and ship D positions after

12 hours after altering course to 288 degrees, voyage to to New York

[1] Chomski J., WiĞniewski B., Medyna P Analysis of ship routes avoiding tropical cyclones Sympozjum Nawig- acyjne Wyd AMW Gdynia 2008

[2] Medyna P., WiĞniewski B., Chomski J Methods of avoiding tropical cyclone of hurricane Fabian Scientific Journals Maritime University of Szczecin 2010, 20(92) p.p.92-97

[3] WiĞniewski B Radio fax Charts in sea navigation (in Polish)

[4] WiĞniewski B., Potoczek W., ChoáaĞciĔski A OkreĞlenie sektora kursów niebezpiecznych przy omijaniu cyklonu tropikalnego z wykorzystaniem programu komputerowego

Budownictwo OkrĊtowe i Gospodarka Morska, nr 11- 12/1990

[5] WiĞniewski B., Chomski J., Drozd A., Medyna P Omijanie cyklonu tropikalnego w Īegludze oceanicznej InĪynieria Morska i Geotechnika, nr 5/2001, s.296-300

[6] WiĞniewski B., Kaczmarek P Avoidance of tropical cyclones using the Cyclon II program Scientific Journals Maritime University of Szczecin 2010, 22(94) pp.71-77

Weather Routing and Meteorological Aspects Miscellaneous Problems in Maritime Navigation, Transport and Shipping – Marine Navigation and Safety of Sea Transportation – Weintrit & Neumann (ed.)

The Baltic Sea, while relatively small globally, serves as a vital shipping route During winter, particularly in the Gulf of Bothnia, navigation is significantly hindered by ice To facilitate maritime trade, port states typically provide icebreaker services as part of their infrastructure In contrast, private icebreaker services, such as those operated by Gazprom, are unique to Russia.

On the area of the Gulf of Bothnia – the severe region of the Baltic Sea, in general, Swedish and Finn- ish icebreakers are in charge

This study investigates the anticipated changes in navigation obstruction by ice due to climate change over the next 90 years of the 21st century.

The observed in XX century changes of climate, especially a rise of the mean air temperature induced more intensive interest in climate modeling and

2 Baltic Navigation in Ice in the Twenty First Century

Sztobryn 3 Storm-surges Indicator for the Polish Baltic Coast

Stanisáawczyk 4 Polish Seaports – Unfavorable Weather Conditions for Port Operation (Applying Methods

Institute of Meteorology and Water Management, Maritime Branch in Gdynia, Poland

Storm surges in the Baltic Sea coastal zone vary in size based on regional factors and are increasingly influenced by climate change, resulting in more dynamic weather phenomena To assess the risk of storm surges across different areas, a new storm-surges indicator was developed, which evaluates the South Baltic water regions based on hydro-meteorological and local conditions This indicator, denoted as “W,” correlates the frequency of storm surges at specific stations with maximum wind velocities and peak sea levels during those events The indicator was analyzed for the Polish coastal zone from 1955 to 2008, aiming to enhance research and forecasting capabilities The findings indicate significant regional changes in hydrometeorological conditions over time.

Approximately 500 km of the coastline is under threat due to varying wind conditions The coastline's irregular route leads to differing levels of exposure for individual sections, resulting in distinct meteorological and hydrodynamic regimes Despite significant equalization efforts along the coastline, certain areas remain uniquely affected by their specific wind direction exposures.

Storm surges in the Baltic Sea coastal zone vary in size and characteristics based on local conditions Key factors influencing these surges include the configuration of the coastline, the bathymetry of the nearby sea basin, and the exposure of specific coastal areas to prevailing winds Notably, the most dramatic changes in water surface levels occur during stormy conditions, including off-shore or on-shore winds that can reach hurricane-like intensity.

Active depressions typically move eastward from the Atlantic Ocean, bringing well-developed low-pressure troughs and frontal systems As these fronts approach the coast, they are accompanied by gale-force backing winds, which shift to veering winds after passing The pressure gradient steepens significantly, causing the wind to intensify from gale-force to hurricane force In the forefield of a depression, strong southern winds prevail, while the winds behind the fronts typically veer Notably, the winds in the forefield are offshore concerning the southern coasts of the North and Baltic Seas.

This situation normally causes sea level oscillations

Over the past century, the mean sea level and frequency of storm surges in the southern Baltic Sea have significantly risen Data from 1950 to 2008 indicates a notable increase in storm surges in Świnoujście, highlighting the changing coastal dynamics in the region.

1950/1951 (from August 1950 to July 1951) to

2007/2008, when maximum occurrence of storm surges is for the autumn – winter months, from No- vember to January – February

The storm surges are not a regular annual event

Their number may vary as in the case of ĝwinoujĞcie

The frequency of storm surges in the Southern Baltic Sea has shown a significant upward trend, with occurrences rising from none to as many as twelve The linear trend in Świnoujście is represented by the equation y = 1.6407 + 0.0619*x, indicating a clear increase in storm surge events By the end of the 20th century, the threat of storm surges had nearly doubled compared to the mid-20th century Between 1950 and 1979, there were 72 recorded storm surges, while from 1980 to 2008, this number surged to 129.

The distribution of annual sea level maxima along the Polish coast, specifically in Świnoujście on the western side and Gdańsk on the eastern side, has undergone changes between 1955 and 2008 Analyzing the frequency distribution of annual sea level maxima in Gdańsk, categorized into 10 cm intervals, reveals significant variations across two distinct periods from 1955 onward.

1981 and of 1982-2008 illustrates the changes oc- curred in the period of issue

550 560 570 580 590 600 610 620 630 640 650 660 670 fr e q ue nc y [ % ] sea level [cm]

Figure 2 Frequency distribution of annual sea level maxima (for 10 cm intervals, e.g 550-559, ect.), GdaĔsk, 1955-1981 and 1982-2008

14 n u m b e r of s tor m sur g es years number of storm surges trend

Figure 1 Long term variation of number of storm surges in ĝwinoujĞcie, 1955-2008 (from 1950/1951 to 2007/2008)

The annual sea level maxima in Gdańsk fluctuated between 570 cm, the defined alarm level, and 644 cm, with the most common values falling between these two extremes.

Between 1955 and 2008, the annual sea level maxima exhibited significant trends From 1955 to 1981, the most common peak values were between 600 and 610 cm, accounting for 22% of occurrences, followed closely by values ranging from 560 to 600 cm The maximum sea level recorded during this period reached between 630 and 640 cm However, from 1982 to 2008, there was a noticeable shift towards higher sea levels, with the most frequent peaks now occurring between 590 and 600 cm, while the maximum annual sea level rose to the range of 640-650 cm.

The frequency distribution of annual sea level maxima in Świnoujście is analyzed for two distinct periods: 1955-1981 and 1982-2008, as illustrated in Figure 3 Notably, the sea level maxima distribution in Świnoujście reveals significant differences between these two time frames.

GdaĔsk, but the frequencies of the annual sea level maxima in 1982-2008 haves been shifted also to the higher values

Figure 3 Frequency distribution of annual sea level maxima

(for 10 cm intervals, e.g 550-559 ect.), ĝwinoujĞcie, 1955-

In Świnoujście, the annual sea level maxima fluctuated between 580 cm and 669 cm, with the alarm level set at 580 cm From 1955 to 2008, the maximum sea levels consistently ranged between 580 cm and 590 cm, indicating a notable stability in the annual values during this period.

630-640 cm to 660-670 cm Distribution of the annual mean sea level (frequencies) indicates also an increase in their amount in a last period and trend of changes is also growing

Recent findings indicate that the threat of storm surges along coastlines is expected to increase in the near future This growing risk highlights the urgent need for more accurate forecasts and comprehensive information regarding storm surges, flooding, and coastal erosion hazards.

2.1 Storm surges indicator for the Polish coast

Proper classification of storm surge conditions allows for effective risk comparison across diverse and often distant areas The "W" indicator has been developed to support research in climate, weather forecasting, navigation, and port operation planning The primary objective is to create innovative methods to mitigate hazards associated with increasing storminess and rising sea levels Research also focuses on assessing the storm surge threat to various regions of the Polish Baltic coastal zone and the correlation between regional indicators and climate variability Accurate classification of regions based on surge occurrence conditions enables a thorough assessment of threats to different water areas and facilitates future seasonal storm surge forecasting.

A comprehensive analysis has identified the key factors influencing storm surges along the Polish sea coast, focusing on both meteorological and hydrological elements The study examined the correlation between maximum surge heights and various parameters, including atmospheric circulation, pressure, wind speed and direction, as well as temperature differences between water and air, along with the mean monthly air temperature in Świnoujście over specific years Significant correlation coefficients were established, leading to the selection of critical parameters that determine the magnitude of storm surges This research culminated in the development of a storm surge indicator concept.

The "W" indicator correlates with the frequency of storm surges recorded at regional stations, as well as the peak wind speeds and maximum sea levels associated with those specific storm surges.

The storm surges indicator “W” comprises the parameters specified below; thus:

Ferdynus 5 Analysis of Hydrometeorological Characteristics in Port of Kulevi Zone

This study employs complex climatology methods to analyze the long-term weather patterns at seven Polish sea ports: Elbląg, Gdańsk, Hel, Łeba, Ustka, Kołobrzeg, and Świnoujście Utilizing data from OGIMET, the research covers the period from 2000 to 2009, allowing for a detailed understanding of the annual weather state structure in these locations.

Weather conditions that hinder port operations include negative air temperatures, cloudiness, precipitation, and strong winds occurring simultaneously By assessing the frequency of these adverse weather conditions, climatograms are created for each port, depicting their occurrence throughout the decades of a given year.

Unfavorable weather conditions for operations in Polish sea ports primarily occur in autumn, winter, and early spring, particularly in Ustka and Gdańsk However, these adverse conditions are infrequent, with an annual occurrence of less than 1% in the ports discussed, indicating generally favorable conditions for port activities The most challenging weather is typically observed in late December, the third week of January, and the second and third weeks of February, as well as the first week of April.

34 difficult When minus temperatures are accompanied by strong wind and precipitation then icing of vessels and cargo handling facilities can be observed

Hydrological and meteorological phenomena significantly impact ports and navigation, influenced by specific thresholds of meteorological elements Utilizing complex climatology to present hydro-meteorological data can simplify the evaluation of climatic conditions, aiding in the identification of periods characterized by either adverse or favorable weather for port operations.

Basic theory regarding methods of complex climatology as well as its detailed description can be found in work by Olszewski (1967) and WoĞ (1970,

1977a and b) This analysis makes use of partially modified weather classification proposed by Marsz

In 1992, a classification system was established, along with a comprehensive description of the procedures for handling input data Detailed insights into this methodology are available in the author's previous works from 1994, 1996, and 1997 The interpretation of these processes is elaborated upon by Ferdynus, Marsz, and Styszyńska.

The classified period is defined by specific daily elements, including mean minimal and maximal air temperature (T), overall cloudiness (N), total atmospheric precipitation (R), and mean and maximum wind speed (V) Each day is represented by four figures—TNRV—resulting in a total of 486 possible weather conditions in this classification system (9×3×2×9).

Fig 1 Location of the meteorological stations used in his study

The data used above were taken from 7 ports

(Fig.1) from the ten-year period 2000 – 2010 Daily values of meteorological elements originate from

OGIMET data sets consist of averaged daily synoptic observations that have undergone rigorous verification In instances of uncertainty, these data were cross-referenced with information from ECA&D and corrected as needed to ensure accuracy.

Symbols Partitions Name of weather _

R 0 RR = 00 mm no precipitation or precipitation < 0,1 mm

V 0 0,0 < v av < 1,5 m/s calm or light air

2 1,6 < v av < 7,9 m/s, light breeze with v max 11 m/s periods of strong breeze

4 8,0 < v av < 16,9 m/s, strong breeze with v max 17 m/s periods of gale

5 8,0 < v av < 16,9 m/s, strong breeze v max 30 m/s with periods of storm

7 17,0 < v av < 29,9 m/s, storm with periods v max 30 m/s of hurricane

The examined ports are categorized based on their geographic location, including those situated in the Vistula Lagoon region, the Gulf of Gdańsk, open sea ports, and those found in the Szczecin Lagoon area.

Ports can be categorized based on their morphological features into several types: those located in bays and gulfs, such as Gdańsk's North Port; ports near river mouths like Ustka and Kołobrzeg; river and canal ports including Świnoujście and Elbląg; and ports situated on the open sea, exemplified by Hel Additionally, ports can be differentiated by their size, particularly in terms of cargo handling capacity.

35 the port area) then we can talk about big and small ports

Weather elements significantly impacting port operations include low air temperature, strong winds, and cloud cover The combination of these factors can severely hinder efficiency This article categorizes these adverse weather conditions, highlighting their negative effects on port operations as outlined in Table 1.

Weather conditions classified as Group A are particularly detrimental to port operations, as they involve the simultaneous presence of all four adverse weather elements Group B features three of these elements, while Group C includes two, both of which hinder port efficiency Conditions that do not fit into these categories are considered neutral and are designated as Group D.

The ports analyzed are located within the same climatic zone, with a maximum latitude difference of only 1° Therefore, the variations in the frequency of specific weather groups can be attributed solely to local conditions.

The port of Elbląg, positioned at 54°10'N and 019°23'E, is the largest port on the Vistula Lagoon, located 6 km upstream from its mouth This regional port offers services for coastal navigation, catering to both merchant vessels transporting coal, building materials, sand, and broken stone, as well as passenger and tourist boats.

In 2008, the port of Elbląg saw a significant decline, with only 14 vessels, totaling 4.6 thousand GRT, making calls—ten times fewer than in 2005 The total cargo handling for the year amounted to 5,700 tons, which included 1,700 tons of steel constructions and 4,000 tons of sand.

The transport of passengers amounted to 39909 people In 2008 cargo handling and passenger transport in the port of Elbląg reached totally 4000 tons and 32899 people respectively (Rocznik Stat- ystyczny Gospodarki Morskiej 2009)

The analysis of climatogram drawn for Elbląg

(Fig 2) indicates that in the years 2000 – 2009 the type of weather from Group A is observed very seldom, accounting to only 1.0% in the first decade of

In December and the first decade of April, the weather types recorded were 6314 and 5314, respectively Notably, these two decades represent the only instances throughout the year where these specific weather types were observed.

Gegenava & G Khaidarov 6 Hydro-meteorological Characteristics of the Montenegrin Coast

Batumi State Maritime Academy, Batumi, Georgia

The paper builds upon the previous work titled "New Black Sea Terminal of Port Kulevi and its Navigating Features," presented at the 8th International Navigational Symposium in Gdynia, Poland, 2009 It focuses on enhancing navigation safety in the Port of Kulevi through a comprehensive analysis of the region's hydrometeorological characteristics The port faces challenges due to prevailing winds from the East and West, persistent sea conditions, and the currents of the river Khobi, compounded by the lack of protective hydrotechnical structures These factors allow waves and sediments from the Rioni and Khobi rivers to enter the navigation channel This paper aims to analyze these hydrometeorological conditions to inform technical decisions that will improve navigation safety in Port Kulevi.

44 criteria of safety safe maximal wind speed – 15 m/s, noted in Port Regulations

Maximal indicators of the wind force more than

15 ɦ/s, are fixed in (See Tab.9.):

The duration of the maximal indicators of the wind is between 4 – 6 – 8 hours Than, with the change of the wind direction the speed decreases to the average indicators of – 3 5 ɦ/s – 5.0 ɦ/s

The longer wind is detected from West, ESE, and East They may blow during 2-3 days, sometimes for 5 days, in the period of June-October

Table 1 Period of time collection and working out data on the wind condition

I Half-Year II Half-Year Annual Summer Autumn Winter Spring Monthly Weekly

Wind Direction ESE E SSE WNW W WSW SSW ENE S

Wind Direction ESE E WNW WSW SSW W SSE NNW S ENE

Wind Direction ESE E SSE WNW W NNW

Wind Direction E ESE WNW WSW SSW W NNW SSE ENE S

Wind Direction ESE WNW WSW W SSE E SSW S NNW

*) average speed (from the maximal); **) maximal speed (from the maximal); ***) direction in the maximal wind

Table 9 Maximal indicators of the wind force

Indicators September October November December

January February March April June July August

Figure 1 Prevailing direction of the wind in I Half-Year - A -

Figure 2 Prevailing direction of the wind in II Half-Year - B -

Figure 3 Prevailing direction of the wind in An- nual – ǹ - 16.07.08 – 31.07.09

The stormy season typically occurs from November to March, with November being the peak month, averaging seven storms and reaching a maximum of 14 Summer months, particularly July and August, experience the fewest storms Storms tend to last longer in November and December, averaging about five days or 117 hours On average, there are around 15-17 days with strong winds, where speeds exceed 15-17 m/s, with the most common stormy winds originating from the East.

The predominant dangerous winds originate from the western and south-western quarters, occurring more than 70% of the time Stormy winds from these directions are observed in 13-15% of instances, with strong stormy winds exceeding speeds of 18 m/s primarily coming from the south-west.

The average annual temperature is 14.2°C, with August being the hottest month, averaging 23.3°C and reaching a maximum of 37.3°C Conversely, January and February are the coldest months, with average temperatures of 6-7°C and a minimum temperature of -10°C recorded in February.

Precipitation Maximal amount of precipitation is in August-September (240-250 ɦɦ, on average, absolute minimum – 614 ɦɦ – in September) Abso- lute 24-hours maximum – 268 ɦɦ Average annual amount of precipitation – 1661 ɦɦ

Fogs are most commonly observed in the spring, with March recording the highest average annual occurrence of foggy days, totaling about three On average, there are 18 foggy days each year, with some years experiencing as many as 37 foggy days.

Tyaguns can occur in heavy seas with wave heights of 3-5 meters and winds from the western quarter at speeds of 7-9 m/s, primarily during the cold months from October to February Typically, only weak tyaguns and initial indicators are observed, with amplitude levels reaching up to 10 decibels, which are lower in summer and higher in winter The strength of a tyagun is influenced by wave height; for instance, a wave height of 0.25 meters corresponds to a force 1 tyagun, while a height of 1.25 meters results in force 2 (3.5 m/s) and so forth The duration of tyaguns ranges from 12 to 83 hours, with force 1 events lasting no more than 24 hours, whereas force 4-5 events can persist for 66-72 hours.

Water Temperature The highest temperature is detected in July-August (average temperature 24- 25°, maximal - 29, 4°), the average temperature in the coldest months – January-March is 7-9°, the lowest – 2, 8° (February)

The salinity of water significantly influences hydrodynamic processes along the shore and affects navigation in the area At Kulevi shore, the average water salinity measures 14.25.

46 prm, which increases in the winter, at the lowest cost

(the average salinity - more than 15 prm, maxsi- mum19, 7prm) The lowest salinity observed in May and June, during the spring flood Rion-discharge

(average salinity - the order of 11-13 prm, the minimum 4,85 prm)

Heavy Sea Wave situation in Port of Kulevi zone is determined by the wind waves and swell

The repeatedness of the West and North-West roughness are change only by 2, 5% and 9% The

During the spring-summer period, the occurrence of south-west winds rises to 35-40% In contrast, the winter months experience heightened wave activity due to the strong influence of west winds, resulting in wave heights averaging around 2.0 meters, which is a 2.0% increase compared to the winter season The warm season notably showcases the maximum wave parameters, particularly influenced by these conditions.

South-West of waves, the action of the South-

The predominant winds in the region include western, southern, and western directions, which significantly influence wave characteristics Typically, the maximum wave parameters are associated with wind-generated waves, exhibiting larger dimensions compared to swell waves On average, wind waves occur 36-48% of the time each month.

Currents There are two major types of current: sea current, caused with the water circulation in the

Black Sea (in the presented case – from South to

In the Kulevi port zone, currents are categorized into wind, countervailing, and draining currents Countervailing currents arise from wind surges and flow seaward, while draining currents are influenced by the River Khobi and also move towards the sea These dynamics are particularly pronounced during sustained heavy winds from the West and South-West, typically exceeding 12 knots.

18 hours) wave – along shore currents arise, which direction is constant, and speed reaches 1,0-1,5ɦ/s

The maximum speed is in the region of the 5 meters isobaths The wind with the constant speed direction and force is necessary for wind current formation

Table 10 Wind with the constant speed direction and force

The analysis of the currents resulted in the following, period from 09.06.09:

1 When ship moves in the channel from receiving buoy to swinging room (swinging pool) zone ʋ1

(Fig.4) she is influences the vector of the constant Northern current (sector 330 0 – 10 0 ), force

0.6 – 1.3 kn., depending on the season (See

Table 11 Wind direction depending on the season

When a ship maneuvers stern-first to port within the swinging room zone (ʋ2), the southward current begins to exert its influence This phenomenon arises from the interaction between the persistent northern and western currents of the Khobi River.

Contributes to this in our opinion three factors:

Encounter of tow, different waters streams – Northern Sea and Western fresh water;

The western current is deflected southward due to the formation of local circulation patterns, which align with the overall southern direction This change is attributed to the artificial expansion of the Khobi River mouth and the construction of a fendering wall on the left bank, designed to prevent erosion and the sliding of sandy soil.

The constant Northern current interacts with the wrecks located in the southern part of the channel, creating a local turn that aligns with the overall southward direction.

In other words the following takes place:

The Khobi River's western current interacts with the steady northern flow, causing a portion of the western vector to shift northward However, the majority of the flow is redirected southward, influenced by the stronger northern current.

Figure 4 Influences the vector current when ship moves in the channel and swinging room

The sediment dynamics in the Port of Kulevi zone are primarily influenced by the consistent drainage of the Khobi River, averaging approximately 300,000 m³ per year, with flood periods potentially increasing this to 450 m³/s (around 40,000 m³ in 24 hours) Additionally, sediment contributions from the Rioni River can range from 80,000 to 200,000 m³ annually Most sediment accumulation occurs in the inner water area and along the channel from 0 to 700 meters, with a notable increase in sediment retention as the water area widens from 300 to 500 meters, leading to significant sediment buildup in the inner region and minimal accumulation within the channel itself.

ûurþiü & S Šoškiü

Pastusiak 8 Methods of Iceberg Towing

Gdynia Maritime University, Gdynia, Poland

High vessel traffic in various global regions has prompted maritime nations to produce high-quality nautical charts, enabling safe navigation with the aid of GPS While this is effective in well-charted areas, many regions remain inadequately surveyed, rendering position-fixing systems ineffective In such cases, relying on a vessel's hydroacoustic equipment becomes essential to identify safe routes amidst potential hazards.

The author's objective was to address issues related to unsurveyed regions, focusing on the reliability of chart information and the contribution of the vessel's autonomous hydroacoustic equipment to navigation safety Additionally, the author examined the safety parameters maintained by the research vessel.

Table 1 Groups of charts and position error of charted features

Group (band) Scale Position error of charted feature (m)

Overview 1:700,000 or smaller 700 or more

Reliability of charts content was described by date of a survey when source data came from Actu- ally used descriptions like “unsurveyed” region,

“poorly examined”, “inaccurately examined”, ”fully examined” should be correlated with presently being introduced meaning like Zones of Confidence ZOC

Zones of Confidence pertain to the detection and measurement quality of seabed features, highlighting the significant risk of omitting navigational hazards from charts Despite their importance, Zones of Confidence have not been universally applied to all charts, particularly in electronic charts of inadequately surveyed areas.

The ZOC category "U" indicates "unclassified" vessels, which necessitate the use of the best scale charts for their intended voyages In this context, a comprehensive search was conducted for world chart resources relevant to the Murchisonfjorden region in Nordaustlandet.

Figure 1 (a) Surveyed region in Isvika (contour line indicates edge of surveyed lane) (b) Isvika survey region on Svalbard

Table 2 Coverage of Isvika region by charts

Source Scale / Bands SOLAS Kind of chart

UKHO general Official paper, ARCS

ECDIS Service Full Official Electronic

Transas Marine 1:200,000 Unofficial Electronic TX-97

SevenCs GmbH Harbour Unofficial Electronic

2.1.3 Sources of origin of the chart

For purpose of this work reviewed, taken into consideration and subsequently divided charts as follows: official, unofficial, „other – bathymetric“ and

Official nautical charts, as mandated by SOLAS Chapter V Regulation 2.2 (IMO 2004), are specialized maps or publications issued by government-authorized Hydrographic Offices, designed to meet marine navigation needs These charts ensure systematic updates in accordance with IMO requirements and include a Zones of Confidence scale to enhance navigational safety.

Unofficial charts were of commercial destination

The informational content of unofficial charts shares a common origin with charts issued by Hydrographic Offices; however, these unofficial charts do not meet SOLAS requirements and lack systematic updates Often, they include additional commercial information Therefore, vessels using unofficial charts must also possess up-to-date official charts, at a minimum in paper format, to ensure navigational safety.

Unofficial bathymetric charts hold scientific significance, aiming to provide a reliable depiction of sea depths and bottom relief These charts are often created without adhering to the hydrographic survey standards outlined in the IHO publication (IHO 2008) and are typically produced by individuals lacking qualifications in hydrography or the creation of official nautical charts Most of these charts fail to account for necessary corrections, such as sea level adjustments relative to Chart Datum and the vertical positioning of sounder or echo-sounder transducers Additionally, the accuracy of the soundings is neither assessed nor factored into the depth reductions.

Bathymetric charts, often associated with hydrographic niches, serve as valuable resources for understanding the sea bottom relief in specific regions In the absence of more comprehensive hydrographic data, these charts can be instrumental for initial voyage planning in hydrographic surveys.

Informational content allowed to grant them class from „Coastal” till „Approach” Appointment of ZOC class for each „other - bathymetric“ unofficial chart required individual assessment

"Other non-bathymetric charts, while lacking reliable depth presentation and detailed sea bottom relief, still held scientific value due to the information they provided The sources of data regarding the sea bottom were often unknown, yet these charts were classified as ZOC class 'Overview.' Although the ZOC scale was not crucial for voyage planning, these charts offered valuable insights for navigational purposes."

The reliability of information content has improved with the introduction of the new ZOC scale, which replaces data on the date of the last hydrographic survey in the specified region It is anticipated that the implementation of this new reliability scale for chart information will require an extended period to fully establish its effectiveness.

It was due to necessity to re-assess date of hydrographic survey and corellated informations on actual charts that not corresponded with new precise scale of ZOC

When planning a voyage in unsurveyed or poorly surveyed areas, it is crucial to consider the navigational chart coverage of the region This involves assessing three key elements: the chart's scale, the scale of reliability (ZOC), and the reliability of the information sources used to create the chart.

To enhance navigation, it is essential to assess external support methods by examining available world chart resources alongside the charts on board the vessel A quality scale of support has been introduced to evaluate this external navigation assistance effectively This scale compares the charts in use with the planned navigation type, as outlined by UKHO in 2009.

UKHO 2010; Jeppesen Norway A/S 2010; IC-ENC

Table 3 Assessment of external support

The Kind Scale categorizes levels from one to five, indicating a gradual decrease in alignment with the established norm Each level reflects a distinct degree of deviation, with level one being the closest to the norm and level five representing the furthest departure This structured approach allows for a clear understanding of how different charts compare in relation to the standard benchmark.

Sum of Maximum possible 24 scores scores

For easy assessment of the external support to the navigation available on board a vessel introduced relative coefficient of the external support Ce expressed by Equation 1:

C e O (1) where Ce - the coefficient of the external protection

The quality ratings for charts are categorized as follows: O represents official chart support with scores ranging from 0 to 6, U indicates unofficial chart support also scored from 0 to 6, B refers to quality ratings from bathymetric charts scored from 0 to 6, and N denotes support from other non-bathymetric charts, similarly rated from 0 to 6.

The comparison in between potential and actual support on board the vessel can indicate possibility and/or necessity of improvement of the external support quality

The Isvika survey region, located in the southeastern part of Murchisonfjorden on Nordaustlandet (79°58'N, 18°33'E), features a rocky seabed partially covered by glacial sediments External sources, including UKHO (2007) and the Norwegian Hydrographic Service, indicate that this area has not undergone systematic surveys, necessitating cautious navigation due to its irregular sea bottom and the potential presence of uncharted dangerous banks Depth changes are almost vertical, with small depths appearing unexpectedly even at 50-100 meters, requiring heightened vigilance During surveys, the radar indicated visible dangers, such as the coastline, at approximately 0.05 nautical miles, yet the most significant threats were the unknown shallow depths nearby Consequently, a chart scale of 1:10,000, suitable for harbor navigation, is recommended for survey work in the Isvika region.

Marchenko & K Eik 9 Ice Management – From the Concept to Realization

Ye Frolov, Ye.U Mironov, G.K Zubakin, Yu.P Gudoshnikov, A.V Yulin, V.G Smirnov & V Buzin

Arctic and Antarctic Research Institute, Saint-Petersburg, Russia

The Russian Arctic is witnessing increased industrial activity, including traditional navigation and the development of new offshore hydrocarbon deposits This surge has led to the introduction of advanced production platforms and high-capacity tankers, necessitating a comprehensive information and logistics system for effective "Ice Management" (IM) to ensure safety in ice-infested waters Russia has accumulated significant experience in supporting ice navigation, with various IM components already implemented in practice This paper summarizes this experience and discusses the development of IM for the Shtokman Gas Condensate Field.

76 system was established in the late 1980s It was mainly based on the “Automated Ice and Informa- tional System for the Arctic” alternatively known as

“North” (Ȼɭɲɭɟɜ ɢ ɞɪ., 1977; Ɏɪɨɥɨɜ ɢ ɞɪ 2003)

Infrastructure of the “North” system is presented by territorial hydrometeorological centers (Mur- mansk, Arkhangelsk, Dikson, Tiksi, Pevek), regional centers for receiving and processing satellite data

(Moscow, Yakutsk, Khabarovsk) AARI is the leading center of the “North” system

The modern Russian system for monitoring sea ice in Arctic waters enables the collection, processing, and distribution of ice information to clients in near real-time, supported by a centralized Ice and Hydrometeorological center.

The main source of data on the state of the ice cover in the Arctic and the freezing seas is a satellite remote sensing (information comes from satellites

NOAA, Fengyun and EOS (Terra, Aqua), RADAR-

SAT1, Envisat) Surface-mounted receiving complex of AARI in Saint Petersburg is equipped with stations for receiving satellite information (Telonics,

USA and ScanEx, UniScan-36, Russia) and provides satellite images in the real time

The environmental state of the Arctic can be assessed through various sources, including a network of polar hydrometeorological stations, expeditionary research vessels, and automatic meteorological buoys placed on drifting ice in the Arctic Ocean Additionally, both domestic and foreign centers specializing in hydrometeorological and ice information contribute valuable data for understanding this critical region.

Center of Ice and Hydrometeorological Infor- mation is in charge of:

Composing review and detailed ice charts;

Making long-term ice and weather forecasts;

Making medium- and short-term ice, meteorological and hydrological forecasts;

Elaborating recommendations on navigation at performance of the marine activities

Transfer of the real-time information products

Information delivery to customers is facilitated through both conventional and satellite communication channels For large ships and icebreakers equipped with INMARSAT systems and electronic cartographic navigation systems (ECNIS/ECDIS), specialized technology developed by AARI is employed to ensure effective transmission.

The fundamental principle of the system is to create all information products at a centralized unit, utilizing specialized Automated Work Places (AWP), which are then directly delivered to the Captain's conning bridge, ensuring efficient access for the End User.

The AWP system is a sophisticated technological framework designed for the monitoring and forecasting of atmospheric and hydrospheric conditions, aimed at enhancing marine activities.

Arctic and in the freezing seas of Russia” (“AK-

The "AKMON" system enables tailored monitoring of environmental conditions based on the unique physical and geographical features of a work area, addressing the specific needs of customers Onboard, the vessel's captain can access a visual representation of ice conditions alongside a navigation map, enhancing situational awareness and safety during operations.

Comprehensive marine operations in icy conditions reveal that merely providing data on current and forecasted hydrometeorological and ice conditions is insufficient for the effective and safe operation of complex technical systems, such as production platforms and unloading terminals, as well as transportation systems like oil product tankers and tanker-platform systems.

Given the high maintenance costs of facilities and the potential environmental risks, such as the 2010 Gulf of Mexico accident, it is crucial to conduct a series of interconnected informational and logistical activities These activities should be grounded in an information management system to facilitate effective decision-making in the complex Arctic environment.

The IM system involves continuous monitoring of ice conditions, forecasting potential risks, and providing recommendations for effective decision-making The final steps of the IM system include activating measures to suspend marine operations, such as halting production and unloading activities on platforms, rescheduling routes for tankers, or employing technical solutions to mitigate ice hazards, like towing icebergs to safe distances away from platforms.

The "ice management" system is not a novel concept, as global practices, particularly in Russia, have gained valuable experience in ice navigation using various classes of icebreakers and drilling platforms in frigid seas To mitigate risks and safeguard vessels, floating and stationary platforms, and terminals from the hazardous effects of ice and icebergs, effective ice condition management (IM) is essential.

Countries and organizations in the Arctic have begun implementing various information management (IM) systems, currently tailored to specific local operations and activities.

Following examples illustrate the most successful cases in the IM system arrangement:

Ice management in the region of Great Banks of Newfoundland, where drilling platforms and FPU

77 function, with use of different methods to change the drift of icebergs (Comprehensive…, 2005)

Ice management to support high-latitudinal experimental drilling in the drifting ice of the Central

Arctic Basin (“ACEX-2004" project) with a mobile drilling platform (ɘɥɢɧ, 2007)

Ice management to support work in the ice of special unloading equipment for loading oil tankers near the port of Varandei (south-eastern Bar- ents Sea)

Ice management to support work in the ice of special unloading equipment for loading oil tankers in De-Kastri (“Sakhalin-1” Project) (Herbert,

Ice management to support loading of oil tankers near the complex “Vityaz” (“Sakhalin-2” Project, phase 1)

4 THE CONCEPT OF THE IM SYSTEM’S

STRUCTURE (IM STRUCTURE BY THE

EXAMPLE OF THE SHTOKMAN GAS

The previously mentioned examples of the IM system's arrangement share a common drawback, as they were tailored for specific marine operations or localized areas, thus limiting their effectiveness to the requirements of those operations However, the expanding range of activities in the Arctic necessitates the development of a more universal approach.

IM system In this particular case, universality means the possibility to adjust the system, based on common arrangement principles, to any operation and any region of the Arctic

The primary goal of the "Ice Management" system is to ensure the safety of vessels and offshore facilities operating in challenging meteorological conditions, particularly in the presence of sea ice and icebergs.

The main common principles of the arranging ice management system are:

The system should be structured in such a way that to provide high reliability level under any environmental conditions and any conditions of functioning;

IM system should decrease frequency of interaction of offshore objects with ice formations

The system should be able to reduce ice loads on the objects when it is impossible to avoid them;

Ice management activities must prioritize facility safety, minimize idle time, enable secure disconnection, expedite removal, and ensure safe reconnection.

According to the international standard ISO

19906 (2009), the ice management system should consist of the following subsystems:

1 Subsystem for monitoring and forecasting the ice cover state and distribution of icebergs;

2 Subsystem for evaluation of potentially dangerous ice phenomena and ice formations;

3 Subsystem, using various technical means for ef- fecting the ice cover and icebergs;

4 Subsystem for preparing the facility to a hazardous situation and ensuring its disconnection and removal

OF IM SYSTEM (BY THE EXAMPLE OF SGCF)

Bulavinov, R Pinchuk, S Pudovikov & C Boller 12 Conditions of Carrying Out and Verification of Diagnostic Evaluation in a Vessel

According to European Standard EN 1712, ultrasonic testing is mandatory for thin-walled welded joints with wall thicknesses exceeding 8 mm, while components with thicknesses less than 8 mm must undergo X-ray inspection.

X-ray testing offers numerous benefits, including exceptional sensitivity to tiny inclusions, widespread acceptance in the shipbuilding industry, and automatic documentation of inspection outcomes However, it also presents challenges such as radiation protection concerns and time-consuming inspection processes, highlighting the need for more cost-effective alternatives.

Fraunhofer-IZFP's Sampling Phased Array technology enhances flaw detectability in thin-walled welded joints through a tomographic approach to ultrasonic phased array signal processing This technology enables high-quality imaging of welded joints and effective identification of material flaws Additionally, its real-time ultrasonic imaging provides a superior alternative to X-ray testing, offering faster inspection speeds and improved documentation of results.

The basic principles of Sampling Phased Array are presented in the paper and several application results obtained on welded joints of marine objects are presented

92 in general has the following advantages and disadvantages [2]

Table 2: Advantages and disadvantages of ultrasonic testing

Testing of thick-walled Acoustic coupling (surface components is possible contact) is required without limitations Limitations due to surface

Evaluation of flaw size, type, roughness are possible orientation can be obtained High requirements on

Fast, cost-effective testing with inspection staff due to immediate conclusion about rather complex calibration indication of UT instrument

Automated or half-automated Limitations on flaw inspection and evaluation can detectability due to be implemented suboptimal insonification

NEW!: Imaging techniques like position or flaw phased array allow orientation documentation and quantitative evaluation of inspection results

For being able to replace x-ray by ultrasonic testing the following tasks must be solved:

Equal or better flaw detectability of relevant flaws compared to x-ray

Fast representation and evaluation of inspection results

Cost-efficient implementation of inspection system and inspection procedure

Mobile inspection system for in-situ applications

The novel ultrasonic inspection technique rapidly coming into industrial application is phased array [3,

Phased array testing enhances ultrasonic testing (UT) of welded joints by delivering extensive information through its beam steering capability This integration of mechanical scanning with electronic beam steering improves flaw detectability by insonifying the welds from multiple angles.

Phased array techniques, while advantageous for beam steering over a wide angle range and benefiting from a finite signal-to-noise ratio, may face limitations in spatial resolution in the far field and inspection speed in specific applications.

Sampling Phased Array (SPA) technology developed by Fraunhofer IZFP is a next step in Phased

Array technology enables rapid synthesis of phased array ultrasonic signals for various angles of incidence, allowing for precise focusing at all depths within the probe's near field Additionally, it utilizes back projection and overlapping techniques to effectively reconstruct the volume from the elementary wavelets generated.

SPA according to synthetic aperture focusing technique (SAFT) principles offers the best possible image reconstruction quality

The SPA technique offers the following practical advantages:

1 Ultra-fast virtual beam sweep for arbitrary angle range

2 Improved sensitivity and resolution in the near field of the transducer

Sampling Phased Array technology revolutionizes 2D and 3D imaging by utilizing cylindrical or spherical waves that propagate omnidirectionally, unlike traditional Phased Array techniques that direct sound fields at various angles This innovative approach allows for efficient data acquisition through the firing of individual array elements or the application of defocusing delay laws, enabling a wide angle range to be captured in a single shot.

Ultrasonic signals collected from each probe position for every array element are utilized as input data for image reconstruction This reconstruction process is executed using the SAFT algorithm.

The sound field of array elements is highly divergent, resulting in each A-scan signal capturing overlapping echo signals from various reflectors in different volume positions The reconstructed image from a linear array represents a cut plane perpendicular to the insonification surface, known as a sector scan For each point in this plane, the propagation times from the transmitting elements to the receiving elements are calculated.

The amplitude values from all A-scans with match- ing propagation times are added up in each image point [6]

Figure 1: Defocused transmission and sector image reconstruction by SPA

Thus all angles of incidence and focal depths within the near field of the transducer can be real- ized even after one single transmitting/receiving act

The implementation of the SPA principle allows for virtual sound beam steering at every volume point, significantly enhancing inspection speed by adjusting for all angles of incidence and focal depths Additionally, synthetic focusing contributes to this improved efficiency.

93 near field of the UT transducer by the SAFT principle improves sensitivity and resolution (Figure 2)

Figure 2: Principle of image reconstruction by SPA

Thus for weld inspection the material flaws can be represented in tomographic quality that allows their exact sizing (Figure 3)

Figure 3: Tomographic Image of an inclined lying crack

Modern instrument engineering, including advanced signal processors and computers, provides enhanced computational power for SPA image reconstruction and processing, surpassing traditional phased array systems in both speed and quality This allows for the implementation of versatile reconstruction techniques in portable manual flaw detectors.

Figure 4: Manual ultrasonic tomograph A1550 IntroVisor by ACSYS

Ultrasonic testing offers significant benefits, particularly through its potential for automation, enabling rapid and cost-effective inspection solutions tailored for industrial applications.

4 ULTRASONIC IMAGING SYSTEMS AS REPLACEMENT FOR X-RAY IMAGING

Using position-related data from a manipulator or encoder wheel, the ultrasonic image can be reconstructed to accurately represent the inspected area, akin to an X-ray film.

The Sampling Phased Array technique, enhanced by advanced image processing methods such as the eRDM technique, delivers exceptionally sharp and high-contrast images for the detection of welding defects Inspection results can be evaluated by assessing equivalent flaw sizes, utilizing calibration on artificial defects like notches or side-drilled holes, or through innovative image processing algorithms that enable rapid quantitative flaw sizing.

Especially for thin-walled welded joints the Sam- pling Phased Array technique offers specific advantages due to improved sensitivity and resolution in the near field of array transducer

Figure 5: Semi-automated SPA systems with 2D and 3D imaging capabilities

Figure 6: Ultrasonic inspection results on the weld seem with a wall thickness of 6 mm with an elongated cavity in conventional and Sampling Phased Array mode

The current state of standardization of ultrasonic

Phased Array testing in Europe is significantly behind schedule when compared to state of the art technology Codes required like ISO DIS 13588 are in preparation phase

Fraunhofer IZFP has successfully implemented innovative phased array techniques for the industrial sector, specifically as an alternative to X-ray testing for heat exchanger pipes in power plants This advanced method is tailored for the assessment of thin-walled pipes and adheres to the TĩV Sỹd specifications for ultrasonic testing.

Despite novelty of the testing method it could be shown that the ultrasonic imaging provides equivalent performance and reliability like established testing procedures

Charchalis 13 Determination of Ship’s Angle of Dynamic Heel Based on Model Tests

Gdynia Maritime University, Gdynia, Poland

This paper addresses challenges in measuring energetic characteristics and vessel performance during sea trials, highlighting how external conditions affect hull resistance and propeller efficiency It examines the impact of weather on test results and gas turbine engine characteristics, and discusses methods for normalizing measurements to standard conditions Additionally, the paper outlines the preparation of propulsion characteristics and analyzes the uncertainty associated with torque measurements.

Figure 1 Block diagram of a vessel

Figure 2 Resistance characteristics of a hull: 1 nominal ambient conditions (design); 2 degraded ambient conditions: 3 improved ambient conditions

Vessel resistance is assessed during the design phase using computational methods and experimental model trials, which inform the selection of the propulsive system This resistance is calculated under standard navigational conditions; however, factors such as displacement, draught, hull condition, and external environments continuously alter during operation.

This leads to a change (deterioration) in resistance characteristics and a change in the type of main engine load when the same vessel speed is developed

Understanding resistance characteristics and the evaluation of specific conditions that influence their values is crucial for diagnosing the performance of propulsion system components and their propulsive capabilities Figure 2 presents sample resistance characteristics for a vessel functioning under varying operational conditions.

Vessel propellers function under a variety of conditions, influenced by factors such as changes in propeller draught due to displacement, permanent draught alterations, and the angle of incoming water during wave navigation Additionally, the condition of the propeller blade surface, particularly increased roughness, can impact performance Understanding the interaction between the hull and propeller is crucial for evaluating propeller operating conditions at the rear of a vessel hull This relationship is illustrated by the hydrodynamic characteristics of a propeller as shown in Fig 3.

Figure 3 Hydrodynamic characteristics of a propeller: - free propeller characteristics in undisturbed water velocity field; - - - - characteristics of the working propeller after the ship's hull

5 THE INFLUENCE OF EXTERNAL CONDITIONS ON ENGINE CHARACTERISTICS

The propulsive system of a vessel functions under a wide range of varying conditions, influenced by factors such as displacement, draught, operational region, hydrometeorological conditions, and the state of the hull, propeller, and engines Timely diagnosis of a vessel's propulsive system requires careful consideration of these changing operating conditions.

5.1 The influence of atmospheric parameters

Atmospheric conditions significantly impact the performance of various engine types, particularly gas turbine engines These engines require substantial amounts of air to operate effectively, with an excess air coefficient ranging from 3.6 to 5, which is crucial for maintaining optimal operational processes.

The air demand for engines operating at 18-25 kg/kWh highlights the critical impact of atmospheric conditions on engine performance Variations in temperature, pressure, and humidity significantly affect the physical properties of air, including density, viscosity, heat capacity, and the gas constant Understanding these influences is essential for optimizing engine regulation and overall performance.

Atmospheric conditions can significantly impact engine performance, potentially leading to inadequate engine efficiency and complicating diagnostic processes due to inconsistent measurement conditions.

5.1.1 The influence of incoming air temperature

Changes in incoming air temperature are due to the fact that vessels are exploited in various regions, or even climate zones, various seasons of the year, and day times

The standard ambient temperature is typically set at 288 K, but in the Baltic Sea region, it can vary between 238 K and 308 K These significant temperature fluctuations impact engine performance, necessitating careful evaluation under varying conditions Higher incoming air temperatures reduce air mass flow due to decreased density, which affects engine efficiency and operation.

The decrease in engine power affects various metrics related to engine and compressor efficiency When operating near calculated load ranges, a rise in air temperature results in a slight improvement in compressor efficiency This enhancement is attributed to an increase in sound speed and a decrease in Mach number, which improve transitional flow conditions and consequently reduce hydraulic losses.

As the incoming air temperature decreases, compressor efficiency declines, resulting in higher fuel consumption for the unit Figure 4 demonstrates how compressor efficiency and effective work vary with air temperature across different compression values These relationships reveal that optimal compression experiences linear changes in both compressor efficiency and work.

Figure 4 The properties of changes in compressor efficiency and its effective work depending on air temperature and compression:

The optimum range of efficiency;

- The optimum range of effective work

The larger the difference in temperature, the larger the differences in the changes of optimum values

5.1.2 The influence of atmospheric pressure changes

Atmospheric pressure changes are relatively minor compared to temperature fluctuations, typically ranging from 96 to 104 kPa, with a maximum relative change of up to 10% from standard pressure (101.3 kPa) Consequently, the impact of pressure variations on engine performance is less significant than that of temperature However, changes in air pressure and density at the engine inlet result in proportional adjustments across all engine control cross-sections An increase in atmospheric pressure enhances air mass, subsequently boosting engine power, while other factors such as temperature, rotational speed, compression, efficiency, and fuel consumption remain unaffected.

5.1.3 The influence of change in air humidity

Air humidity can vary significantly, impacting gas engine performance due to changes in air mass and thermal properties Increased humidity raises gas capacity but reduces incoming air density, resulting in decreased airflow through the engine This reduction in airflow has a more pronounced effect than the increase in heat capacity, ultimately causing a drop in engine power Additionally, incoming air may contain water droplets, such as sea spray, with the degree of moisture determined by the water and vapor content relative to the mass of dry air.

(1) where m ps - dry air mass

Fig 5 illustrates an example of change in engine performance when the change in moistening degree is within the range 0,01 – 0,07

5.2 Calculating the measured values to the so- called model atmosphere

For changeable conditions during vessel engine exploitation, it is necessary to relate the test results to the so-called model atmosphere (po = 101,325 kPa and To (8,15 K)

Figure 5 Influence of changes in incoming air humidity on turbine engine characteristics

Changes in temperature, pressure, rotational speed and power relative to atmospheric conditions are presented in the following relationships: reduced engine power

(2) reduced pressure p zr ozm ozm p p 101325

(4) reduced rotational speed n zr ozm zm T n 288,15

To effectively prepare the propulsive characteristics of a vessel, it is essential to understand the resistance characteristics of the hull, represented as R = f(v), alongside the freewheeling propeller characteristics and the specifications of the propulsive engines Additionally, the torque transmission elements must be evaluated The hydrodynamic performance of propellers is characterized by parameters such as the thrust coefficient (KT), torque coefficient (KQ), and power coefficient (Kp), all of which are functions of the advance ratio (J).

Coefficients which characterize hull and propeller cooperation t – suction coefficient

The determination of propulsive characteristics relies on identifying the operational area for a free-wheeling propeller based on hydrodynamic characteristics This area is mapped in T-n, Q-n, and N-n coordinate systems, indicating constant values of the advance coefficient J and propeller rotational speed n Subsequently, resistance and propulsion engine characteristics are plotted on corresponding graphs, aligned with measurement sites such as the propeller cone or output shaft clutch for torque and power, and the vessel hull or propeller cone for resistance characteristics and propeller parameters This alignment is crucial for assessing the efficiency of components involved in torque transfer, as well as the overall efficiency of the hull and propellers Ultimately, propulsive characteristics provide a comprehensive understanding of the principles guiding the selection of propulsion system elements.

Mironiuk & A PawlĊdzio 14 Propulsive and Stopping Performance Analysis of Cellular Container Carriers

Polish Naval Academy, Gdynia, Poland

This article presents initial research on the dynamic impact of airflow on a ship model of the 888 project type, conducted at the Polish Naval Academy's test stand The study compares measurement results with theoretical calculations regarding dynamic heel angles, following guidelines from the Polish Register of Shipping (PRS) and the International Maritime Organization (IMO) A key focus of the research is the determination of the heeling moment caused by wind Findings indicate that the criteria for assessing the ship's dynamic stability, as defined by PRS and IMO, incorporate a safety margin.

Fig 1 Facility for tests on dynamic impact of wind

In ship model testing, openings are strategically placed in the stem and stern frame at the flotation line to limit drift caused by airflow, establishing a fixed axis of rotation However, this axis is not static, as it varies with wind dynamics, making its location vital for determining the heeling moment According to the IMO’s stability code, the heeling moment's lever is calculated as the distance from the center of the topside projected area to the center of the underwater hull projection on the symmetry plane, or approximately to the vessel’s half draught depth Consequently, measurements and calculations of dynamic angles of heel must align with IMO recommendations, leading to varying results.

The model is equipped with a sensor that accurately measures heeling and trim angles to within 0.01 degrees The sensor's signals are transmitted via cable to a computer, and the impact of these cables on the model's performance is negligible due to their minimal weight and small cross-sectional area.

3 PROBLEM OF GEOMETRIC AND DYNAMIC SIMILARITY SCALE

Solving the geometric and dynamic similarity scale problem has consisted in meeting given conditions

The ship model was created at a 1:50 scale, allowing for straightforward calculations of all geometric quantities The righting levers curve of the model adhered to the principle of geometric similarity The heeling moment is expected to correlate proportionally with the vessel's righting levers, meaning that the ratio of the maximum value of the ship's righting levers to the wind-affected heeling moment's lever should remain consistent for both the model and the actual ship.

GZ m w m wo o max max (1) where the „o” subscript refers to the vessel, while the „m” subscript refers to the model Figure 2 makes a graphical mapping of the (1) dependence

Fig 2 Determination of wind affected heeling moment lever’s value for ship model

Wind pressure on a vessel is influenced by the heeling moment caused by the wind It is essential to define this pressure according to an appropriate dynamic scale that corresponds to the model The pressure value must reflect the dynamic effects on the actual object.

103 on the vessel has been accepted in accordance with

IMO and PRS regulations (IMO Instruments,1993,

In 2008, PRS 2007 established that the static wind pressure for ships operating in unrestricted water areas is 504 Pa, while dynamic wind pressure is set at 756 Pa, which is 1.5 times greater This dynamic pressure corresponds to a specific wind velocity, which can be calculated through various methods, including the relationship with dynamic pressure.

A pressure value of 756 Pa corresponds to an airspeed of 35 m/s, given a density of 1.2 kg/m³ According to published references (Wiliński & Siemianowski 1993), the wind velocity associated with a pressure of 756 Pa is approximately 29 m/s during a squall.

To accurately determine the air speed for the ship, it is essential to recalculate this speed for the model Various methods can be employed for these recalculations, one of which is the use of Euler coordinates (GrobyĞ 1998).

The pressure of 756 Pa and the speed of 32 m/s both defined for the ship gives the wind velocity of

4,52 m/s, i.e the velocity that should have impact on the model

In case the following dependence on the wind affected heeling moment is applied (PRS 2008):

The formula for calculating the moment (M) involves the topside projected area (Fw) in square meters and the distance (zw) from the center of the wind projected area to the waterline, measured at a height of T/2 above the basic plane under specific load conditions Additionally, the angle of heel (M) and the wind velocity (vw) at the height of the wind projected flank's geometric center are essential components of this calculation.

In 2008, the wind velocity at a height of 10 meters above the waterline, denoted as v10, is measured at 4.51 m/s, which is equivalent to 10 knots This measurement is applicable for ships operating in unrestricted water areas.

The proposed solutions for addressing dynamic similarity scale align closely with the results of air flow speed measurements, suggesting that the calculations for wind velocity have likely been performed accurately.

The study's program was implemented in multiple stages, beginning with the determination of air flow speed distribution at the research stand Air flow speed measurements were conducted at 18 different points, with results from the measurements generated solely by the large fans presented in Table 1 The average air flow speed impacting the model was recorded at 4.52 m/s.

Table 1 Results of measurements of air flow speed

Measurement Place of measurement and Average value height [cm] value of speed[m/s] [m/s]

The next phase of the research focuses on determining the dynamic angle of heel, with tests conducted at the stand for heel angles of 6°, 15°, and 18° towards the windward side of the ship These angle values are derived from weather criteria calculations performed for the type 888 ship project, in compliance with IMO and PRS regulations.

The fans operated at a constant velocity while recording the heel angles, which correspond to the consistent characteristics of the heeling moment The results of the measured heel angles are illustrated in Figure 3.

Fig.3 Measurements of dynamic angle of heel after deflecting model towards windward shipboard to angle of: a) 6 o ; b) 15 o ; c) 18 o

Table 2 presents the results of the measurements conducted at the stand, revealing that the highest dynamic angle of heel was recorded when the model was tilted 18 degrees toward the windward side.

Table 2 Values of dynamic angles of heel

Angle of heel towards windward shipboard -6 -15 -18

Artyszuk 15 Coalescence Filtration with an Unwoven Fabric Barrier in Oil Bilge Water Separation

This article reviews key correlations among the main characteristics of fully cellular container carriers, utilizing a comprehensive statistical analysis of the global fleet based on data from the Lloyds Register of Ships' 'Sea-web' database and specialized data-processing algorithms It examines critical parameters such as ship size, including length, displacement, deadweight, gross tonnage, and trade-specific capacity (TEU), as well as ratios of main dimensions, speed, and propulsion power The research aims to provide essential information for ship designers, waterway engineers, and ship operators involved in port and fleet development, emphasizing navigation safety and efficiency The identified relationships impact ship resistance, propulsive performance, seakeeping, and maneuverability Additionally, the study develops a mathematical model to analyze ship stopping behavior in both coasting and crash scenarios, relevant for ocean and harbor maneuvers.

Figure 2 DWT/TEU ratio vs ship's length (c/c)

Figure 3 Gross tonnage/DWT ratio vs ship's length (c/c)

Figure 4 Ship's breadth/draught ratio vs ship's length (c/c)

Figure 5 Ship's length/breadth ratio vs ship's length (c/c)

The analysis of deadweight tons relative to TEU capacity reveals significant variations in TEU arrangements among ships measuring up to 200 meters in length Additionally, there is a consistent ratio of gross tonnage to deadweight, averaging around 0.83 The average beam-draught ratio is approximately 2.7, while the length-beam ratio stands at 6.6; however, the latter exhibits a higher variability of about r1.2 compared to r0.3 for the beam-draught ratio.

5 linear trends of L/B (for ships over 200m) probably constitute the design trends of particular shipyards

Most cellular container carriers are equipped with a single screw propeller and a single main engine, with 99% of the fleet adhering to this standard Among these, 83% utilize fixed pitch propellers (FPP), while 17% employ controllable pitch propellers (CPP) Propulsion is primarily achieved through direct drive systems, which account for 83% of vessels, with the remaining 17% using geared drives (either mechanical or electric) It's important to note that FPPs and direct drives are not inherently linked, as 96% of ships with FPPs use direct drive, whereas geared drive is prevalent in 78% of ships with CPPs.

Figures 6-9 present key insights into propulsion dynamics, highlighting that smaller ships generally have lower service speeds, with a maximum limit of 25 knots observed for larger vessels, which is economically viable Figure 7 illustrates the relationship between ship length and allowable speed increase through the nondimensional Froude number (F nL = v serv / (gL)), which indicates that as speed increases, hull resistance rises significantly due to wave-making resistance, thereby increasing power demand and fuel consumption The Froude number remains relatively constant between 0.2 and 0.3, but for larger ships, it tends to cluster around 0.25, indicating a more consistent performance in this size category.

The effective horsepower (EHP) significantly influences brake horsepower (BHP), and it is theoretically proportional to the square of a ship's length and the cube of its speed Therefore, the optimal method for evaluating a ship's installed and reported BHP is to implement a 'relative power index.'

(1) where U = water density (1.025t/m 3 ); L[m]; v serv [m/s]; BHP[kW]

The relative power index can be connected with the inverse of hull resistance coefficient, but already after incorporating the total propulsion efficiency

Precisely, it defines in rather general terms the ratio of power demand to the actually installed power

A higher value indicates a reduced horsepower margin, suggesting that the ship's hull fairing is more effective in terms of propulsion and hydrodynamic performance This relationship aligns with the principles outlined in Equation 1.

The Admiralty formula demonstrates that larger ship hulls are generally more efficient, as illustrated in Figure 8, with additional power being an uncommon necessity.

Figure 7 Froude number vs ship's length (c/c)

Figure 8 Index of relative horse power vs ship's length (c/c)

Figure 9 illustrates the revolutions per minute (rpm) of the main engine, which is applicable to all direct drive ships In later sections, 'rpm' will refer more broadly to the general rotational speed of the propeller and engine, with the specific unit varying based on the intended application.

The collection includes 79% of ships, although some data on rpm is missing In direct drive systems, the engine and propeller share the same rpm, which is crucial for propulsion and stopping analysis However, propeller rpms, essential for this analysis, are seldom reported or retrievable from electronic databases, which are typically tailored for economists and managers rather than technical research.

Figure 9 Main engine (direct drive propeller) service rpm vs ship's length (c/c)

The nominal main engine RPM, as illustrated in Figure 9, is adjusted to reflect the typical main engine service output, incorporating the operational margin In this study, the NCO/MCO level is set at 80% The recalibration adheres to fundamental design principles, ensuring that 100% MCO, equivalent to BHP, is attained at the nominal RPM This is essential for achieving higher ship speeds compared to the previously mentioned service speed, which is specifically associated with the service RPM.

0 (2) where n serv = service rpm (engine/propeller rotative speed); n n = nominal rpm

To analyze propulsive and stopping behavior effectively, it is essential to identify the geometric and hydrodynamic parameters of the hull and propeller, which can be achieved using established propeller design diagrams This study utilizes the work of van Lammeren et al (1969), specifically referencing the original curves for the optimum diameter of the B4.70 propeller series, applicable to full-scale container ships with a Reynolds number around 5 x 10^7 Future research may also explore charts for 5-bladed propellers, commonly found on container vessels.

The backward identification method, utilizing a constant wake fraction of w = 0.3 and thrust deduction factors of t p = 0.15, has led to significant findings These results, illustrated in Figures 10-14, encompass critical parameters such as propeller diameter (D), propeller pitch ratio (P/D), propeller open-water efficiency (K P), and the propeller advance ratio.

Figure 10 Propeller diameter/ship's length ratio vs ship's length (c/c)

Figure 11 Propeller pitch ratio vs ship's length (c/c)

Figure 12 Open-water propeller efficiency vs ship's length

Figure 10 illustrates an estimate of propeller diameter expressed non-dimensionally as a fraction of the ship's draught The ship's hull resistance coefficient, referenced to the product of the ship's length and draught (LT), has been calculated using a specific formula.

Figure 13 Propeller advance ratio vs ship's length (c/c)

Figure 14 Ship resistance coefficient vs ship's length (c/c)

The thrust coefficient $ k_T $ is determined by the propeller efficiency $ K_P $, advance ratio $ J $, and propeller torque coefficient $ k_Q $ Once $ J $ is identified, $ k_Q $ can be calculated using the Taylor parameter $ B_P $ This parameter represents the optimal combination of $ J $ and $ k_Q $ that maximizes efficiency given the constraints of horsepower, RPM, and the ship's speed, making it essential for effective propeller design.

Hull designs for larger ships demonstrate significant effectiveness, as illustrated in Figure 14 Beyond a certain ship size, this effectiveness in terms of hull resistance coefficient remains nearly constant.

Gutteter-GrudziĔski

Optimization of Hybrid Propulsion Systems

MI-SE@MALTA, MARSEC-XL Foundation, Senglea, Malta

Powertrain hybridization allows for the integration of multiple power sources, leading to reduced fuel consumption and emissions However, marine hybrid vessels face limited opportunities for free energy recovery due to their operating profiles To achieve fuel savings, it is essential to optimize component operating points through proper sizing tailored to expected usage This study employs a multi-objective genetic algorithm to optimally size propulsion components, aiming to minimize both fuel consumption and installation weight for a hybrid motoryacht in a day cruise scenario.

Achieving fuel savings in marine hybrid systems is feasible by properly sizing components to enhance overall operating efficiency for specific scenarios To accurately define fuel consumption for a given scenario, it is essential to utilize a model of the hybrid system that incorporates the scenario's power demand as its input.

The optimal sizing of the hybrid system is simply the tip of the iceberg in the hybrid design process

Essential for the correct sizing is the demand profile, on whose realism the accuracy of the sizing will depend

The power demand timeline for marine hybrids encompasses two key components: propulsion demand and hotel load demand Unlike automotive hybrids, marine hybrids experience a more substantial hotel load, as motoryachts must cater to onboard users for extended durations.

To accurately assess fuel consumption, it's essential to analyze the interaction between the prime mover, energy storage system (ESS), and power demands This necessitates a comprehensive model of the hybrid system that accounts for all power flows among its various components.

This model was built in Simulink, since no simulation tool was readily available for marine vessels

A sixty-foot motoryacht was evaluated using available trials data, leading to the proposal of a parallel hybrid configuration This design includes the addition of a battery bank and an electric motor/generator linked to each diesel engine via a gearbox By implementing this system, the separate diesel generator can be eliminated, allowing the hotel load to be powered directly from the main battery bank and engines.

The propulsive power demands are represented as a Look-Up Table (LUT), which translates speed demands into power timelines Similarly, the diesel engine is modeled using a two-dimensional LUT based on its performance chart, where engine speed and power inputs yield instantaneous specific fuel consumption (SFC) The cumulative fuel consumption is calculated by integrating the SFC values Additionally, the electric machine's performance characteristics are defined, with power distribution managed by a central control logic.

This steady-state modeling is valid since the quantities of interest (power flows and operating points) are required over a long period of time

Transient response is not a primary focus when determining fuel consumption scenarios The batteries are simulated using Simulink’s integrated battery model, which includes representations for Lithium-ion, Lead-acid, and Nickel Metal Hydride batteries.

Figure 2 Complete Simulink model of parallel hybrid setup

The central control logic manages the power required from the electrical machine and diesel engine based on propulsion and hotel load demands, while also considering the current operating conditions of the components Maintaining the batteries' state of charge within specified limits is crucial for optimal performance.

Hybrid vehicle design focuses on meeting specific performance criteria In parallel automotive hybrids, the internal combustion engine (ICE) is designed to handle cruising speeds, ensuring that maximum speed can be maintained in top gear This requirement influences the sizing of the electric motor, which, along with the transmission system, affects the vehicle's acceleration capabilities Initially, the ICE is assumed to manage steady-state rolling and air resistances, allowing the electric drive to fulfill the acceleration requirements By analyzing the power needed for acceleration and considering the contribution of the ICE at low speeds, the size of the electric motor can be optimized.

For an Energy Storage System (ESS), the power requirement must exceed the motor's power rating to account for conversion inefficiencies The energy requirement is influenced by the driving pattern and its regeneration potential By considering these inefficiencies along with the desired initial and final capacities, the stored energy requirement can be determined Following this, simulations are conducted to calculate metrics such as fuel consumption, allowing for iterative design improvements to enhance system performance (Ehsani et al 2010).

While the design focuses on meeting specific specifications, factors like fuel consumption, emissions, and system weight remain secondary concerns beyond the designer's direct control Although intuitive design and experience can guide improvements in these areas, they are not treated as primary objectives in the design process.

Optimization is a targeted process that directly addresses an objective to identify its extreme value, whether maximum or minimum This approach allows for intentional goal-setting and design, rather than treating objectives as mere secondary outcomes of the design process.

Classical optimization techniques would involve the use of mathematical tools such as the Newton-

Raphson and steepest descent methods necessitate a mathematical equation for problem description, which is challenging when quantifying fuel consumption in various scenarios Additionally, these methods are designed for continuous and linear functions, making them inadequate for problems involving discrete component availability, where traditional optimization techniques fall short.

Genetic algorithms, inspired by natural processes, serve as powerful optimizers that function without needing extensive knowledge of specific problems They work directly with problem descriptors, treating the underlying functions as black boxes and relying solely on the returned values This simulation-based approach proves highly effective for optimizing hybrid vehicles, as demonstrated in studies by Desai & Williamson (2009) and Jain et al.

The search space for a hybrid setup encompasses all potential combinations of components, from which the ideal configuration is selected In this genetic analogy, the term "chromosome" refers to the descriptor of the component configuration Each chromosome within the search space corresponds to a solution in the objective space.

This maps the chromosome to the objective value of interest such as fuel consumption

Upadhyay, Y Amani & R Burke 18 Modelling of Power Management System on Ship by Using Petri Nets

SUNY Maritime College, Bronx, NY, USA

This paper introduces an innovative ship propulsion drive system, highlighting the significant power requirements that range from a few megawatts for small cruise ships to hundreds of megawatts for large cargo vessels Traditional combustion drives are deemed unsustainable and environmentally harmful, prompting the proposal of an electric drive system powered by hydrogen fuel cells These fuel cells, developed using offshore renewable energy sources such as wind, wave, and solar power, currently have a power handling capacity of 100 kW, which limits their application in high-power propulsion systems The paper details a drive scheme that integrates multiple modular hydrogen fuel cell drives to achieve variable power outputs, discussing various propulsion system options and the factors influencing their selection Additionally, it explores how these modular drives can effectively manage torque and power requirements, while also reducing the overall volume and weight of the ship, allowing for optimized storage and reform systems This research presents a significant advancement in harnessing hydrogen fuel cells for large-scale applications, paving the way for future developments in marine propulsion technology.

134 travel 400km, a modern combustion vehicle needs

24-kg of gas, 8-kg of hydrogen in hydrogen combustion engine and 4-kg of hydrogen in a fuel cell, electric drive vehicle

A hydrogen fuel cell is an innovative device that transforms hydrogen into electricity, producing only pure water and heat as byproducts Recent advancements in fuel cell technology have led numerous automotive manufacturers to launch new models of hydrogen-powered vehicles As the market for hydrogen fuel cells continues to grow, prices are expected to drop significantly, surpassing initial projections by the Department of Energy (DOE) Figure 1 illustrates the pricing trends associated with hydrogen fuel cells.

Fig 1 Price Trend for Hydrogen Fuel Cell

To showcase the viability of a hydrogen-based economy, a model cargo ship with a capacity of 16 to 22 megawatts should be developed, utilizing hydrogen fuel cells along with onboard hydrogen reforming, production, and storage capabilities.

To supplement hydrogen, we propose an aerody- namic cargo model ship with retrieving solar panels and small onboard wind turbines to produce power needed for in house hydrogen reformers

Hydrogen production and dispensing are facilitated through small-scale platforms that integrate solar, wind, and wave energy conversion technologies The electric energy generated from these renewable sources is utilized to split water into hydrogen and oxygen Additionally, these platforms feature fueling stations and limited hydrogen storage capabilities, exemplified by the Marine Energy and Refueling Ports (MERP) concept.

Using technology developed for automobile hydrogen refueling stations and applying it to Marine

Energy and Refueling Port (MERP) is feasible, however, more studies need to be conducted to relate the two systems Here are a few proposed models:

The initial model is designed for coastal regions where a hydrogen pipeline is integrated into the existing infrastructure, facilitating energy delivery to urban and coastal areas This system can seamlessly incorporate Mobile Energy Refueling Points (MERPs), which can include compact storage and fueling stations.

The second model emphasizes a decentralized, small-scale local supply chain for hydrogen shipping, promoting total dependence on renewable energy sources like tidal, wind, solar, and, when feasible, wave energy.

Designing mobile hydrogen-producing ships equipped with wind turbines and hydrogen reformers presents an innovative solution for sustainable energy These vessels can harness strong winds to generate hydrogen, while also functioning as mobile refueling stations during transit.

Marine energy and refueling ports are designed as discreet, small islands located along coastlines or in offshore regions, optimizing the capture of energy from wind, waves, and tidal currents for maximum efficiency.

An MERP will incorporate a compatible hydrogen reformer, low-pressure hydrogen storage, and a fueling station Additionally, it will feature a vertical axis wind turbine, a vertical axis tidal turbine, photovoltaic panels, and the essential electronics for control and conversion.

Fig 2 Marine Energy & Refueling Port

Electric drives for ships are highly advanced and can be easily integrated with hydrogen fuel cells This paper presents a design that illustrates how automotive technology can be adapted for ship design, highlighting the potential for innovation in marine propulsion systems.

Combustion drives are unsustainable and environmentally harmful for the future of ship propulsion In contrast, the proposed electric drive system offers significant advantages, making it a more eco-friendly alternative.

Efficient and Improved life cycle cost High Power/volume and Power/weight ratio i.e high payload of vessel Less propulsion noise and vibrations Ease of speed control

All-electric ships powered by fossil fuels represent a modern advancement in marine design, enabling effective and efficient propulsion through on-board electric power By converting auxiliary systems that typically rely on steam, hydraulic, or pneumatic energy to electrical power, these "single bus" ships can dynamically allocate energy based on their mission profiles Electric propulsion technology is increasingly utilized across various vessel types, including cruise ships, ferries, drilling vessels, thruster-assisted floating production facilities, shuttle tankers, cable and pipe layers, icebreakers, supply vessels, and naval ships.

135 many different configurations available for the propulsion systems.

In traditional all-electric ship designs, engine-generators produce and distribute electric power for both auxiliary and main propulsion systems While this system offers efficiency comparable to conventional non-electric drives, the high costs associated with generators, motors, and static drives can be significant However, the operational benefits and enhanced design flexibility provided by this approach justify the additional expenses.

Fig.3 On-ship Power generation distribution and Propulsion

Fig.4 Different Propulsion drive configurations

In these configurations, all generators contribute power to a common bus, which then supplies energy to the ship propeller via transformers and converters, as illustrated in Figure 3.

Typically, for twin-screw ships, each propeller is controlled by a single motor drive as shown in fig

Common schemes for E-Ship propulsion include a two-winding motor with redundant converters, where the additional winding is powered by a separate power electronic converter.

Tandem motor with redundant converters, and fig.4

Krþum, A Gudelj & L Žižiü 19 Logical Network of Data Transmission Impulses in Journal-Bearing Design

University of Split, Faculty of Maritime Studies, Split, Croatia

The electrical power system of a ship comprises power generators, consumers, and a distribution system, all interconnected through a control system, whether hardwired or via field bus This integration allows for advanced functionalities within the overall control system A key component of this system is the Power Management System (PMS), which consists of various control stations that can operate collaboratively or independently during emergencies The PMS encompasses essential equipment such as engines, generators, switchboards, and automation controls that execute calculation algorithms, ensuring efficient power management onboard.

The future design of ships will necessitate advanced modeling and simulation techniques to effectively integrate complex systems for total ship production Additionally, the control architecture for power distribution systems must be hierarchical, distributed, and easily adaptable to enhance efficiency and functionality.

The complete logistics chain of this control architecture will be modeled using Colored Petri Nets (CPN), linking efficient agents for the autonomous management of complex distributed systems with those responsible for power management system control.

This article discusses the foundational concepts of Petri Nets and explores the cooperation and optimization processes among agents using CPN Tools It highlights the interdependencies among agents, primarily through information exchange and directives The objective is to create a model that facilitates the study of complex systems and validates the integrated control architecture The findings indicate that the CPN model serves as an effective simulation environment, significantly improving the power management systems on ships.

Figure 1 Typical Power electric system

As a graphical and mathematical tool, Petri nets

Dicesare, 1991., have been successfully used in communication protocols and automated manufacturing systems, in which they offer a flexibility to simulate discrete even systems Therefore, we choose to use

Petri nets serve as an effective modeling tool for multi-agent systems within ship power systems By enhancing Petri net models to incorporate power system dynamics, we aim to capture the impact of information exchange among agents.

Figure 1 illustrates synchronous generators (power sources) transformers, power panels, bus transfer units and interconnecting cable used for delivering power to the loads

Equipment failures can result in significant overcurrent situations To mitigate damage during such abnormalities and reduce their impact on the overall electrical power system, protective devices are essential (Krcum, 2005).

2.1 Basic theory about Petri Nets

PN is a graphical and mathematical modeling tool which can be used as a visual communication aid

Basically, PN is a bipartite graph consisting of two types of nodes, places and transitions, connected by arcs

Petri net is a 6-tuple Murata, 1989.:

I - an input incidence matrix, n m , :Tu oP ^ `0,1

- is a weight function, m 0 - initial marking

Places and transitions v P T are calling nodes and denote states and events in the DES A transition tT is enabled at a marking m p iff

In a Petri net, transitions are activated based on their input places, represented as $x_t$, and the weights of the arcs connecting these places to the transition, denoted as $w_{I,p,t}$ When a transition $t$ satisfies the enabled condition, it can fire, resulting in a loss of tokens from its input places and a corresponding gain of tokens in its output places.

In a Petri net (PN) consisting of m places and n transitions, the incidence matrix W is defined as an n x m matrix, where the elements are determined by the relationships between transitions and places Specifically, the elements a_ij represent the weight of the arc from place i to transition j, while w_p_t indicates the weight of the arc from transition j to place i It is important to note that if all arcs in the PN have a weight of 1, the incidence matrix simplifies the analysis of the system's behavior.

The input matrix (I) and output matrix (O) comprehensively define the structure of a Petri net In the absence of self-loops, the structure can be solely represented by the weight matrix (W) The incidence matrix facilitates an algebraic representation of the Petri net's marking evolution, transitioning from marking m_k_p to marking m_k_1_p.

2.2 Informal Description of Colored Petri Nets

Colored Petri nets (CPNs) enhance traditional Petri nets by allowing for more complex modeling capabilities They utilize colored tokens, which can represent a wide range of information that influences transition firing Each place in a CPN is linked to specific color sets, defining the types of tokens it can contain Transitions can be programmed with unique constructs and functions, enabling precise control over their firing conditions Additionally, input and output arcs may incorporate expressions and functions, further enriching the modeling process.

For a transition to be enabled the input arcs expressions need to bind successfully with the tokens present in the input places and the transition guard

The tokens are placed in the respective output places

CPNs, or Colored Petri Nets, represent a higher-order net class that provides a memory state regulated by tokens, as noted by Garcia (2008), Kristensen (1998), and Jensen (2007) These nets are particularly beneficial for fault diagnosis and investigation within control systems, offering significant advantages compared to traditional Finite State Machines (FSMs) and Petri Nets (PN), according to Garcia (2008).

Figure 2 The overview of MAS for the PPS

In a multi-agent system (MAS), agents are classified into seven categories based on their associated electric components: generator agents (GA), gas turbine agents (TA), load agents (LA), propelling system agents (PA), breaker agents (BrA), switches agents (SwitchA), and bus agents (BusA).

A generator agent can receive current information of the corresponding generator in the power system

This information consists of generation capacity, real/reactive power output, generation cost, fault alarm, etc

Agents LA and PA aim to ensure that the appropriate load is supplied in the PPS, with the propelling system given the highest priority due to the significance of the load.

The loads with higher priorities are more important than the load with the lower priorities, and need to be restored prior to the loads with lower priority

The circuit breaker agent (BrA) communicates with the corresponding breaker in the power supplier layer, receiving its status and sending control signals as needed.

A bus agent is responsible for overseeing the real-time data of its associated bus within the power system BusA actively communicates with neighboring agents to gather and update relevant information about its bus, subsequently sharing this updated data with adjacent agents to ensure accurate and efficient information flow.

Wierzcholski 20 Optimum Operation of Coastal Merchant Ships with Consideration of Arrival Delay Risk

Institute of Mechatronics, Nanotechnology & Vacuum Technique, Koszalin University of Technology, Poland

This paper discusses the implementation of a logical network for data transmission impulses in the optimal design of journal bearings, focusing on key operating parameters including load capacity, friction forces, friction coefficient, and bearing wear.

The efficient operation of slide journal-bearing systems in the maritime industry necessitates careful selection of journal shapes, bearing materials, surface roughness, and other characteristics that influence load-carrying capacity and process control The integration of artificial intelligence in micro-bearing technology facilitates the development of logical network models for data transmission, enabling the creation of simplified graphical representations of anticipated processes This paper focuses on the application of logical network analysis in the design of slide journal bearings.

In slide journal bearing systems we have the input vector U(A,B,C,D,…) in multi-dimension space

The vector components represent different characteristics of micro-bearing journals, including various shapes such as cylindrical, conical, spherical, and parabolic Additionally, the vector accounts for a range of micro-bearing surface roughness levels and radial clearances, denoted by n=1,2,…, highlighting the diverse parameters that influence micro-bearing performance.

In slide journal-bearing the output electronic impulse vector Y leads for example to such components as: load carrying capacity, friction force, friction coefficients, micro-bearing wear

4 THE LOGICAL NETWORK TOOLS FOR

Here are presented the tools of LNAS occurring in micro-bearing electronic network and in computer science [6],[7],[8]

We assume the following nods as connection boxes: union (sum) mechanism, intersection mechanism which choices common properties of two impulses, a mechanism which negates each impulse

Above mechanisms are presented and explained in Fig.2

Figure 2 Input impulse A and B going into nods and output impulse Y outgoing from the nods

5 ABOUT THE TRANSMISSION OF IMPULSES

FOR SLIDE JOURNAL BEARING DESIGN

5.1 Now for a one device we assume following expression:

Y(A,B,C,D)=[a(AC)B]{[ (aCB) D] A}, (1) where: A,B,C,D –input impulses, Y(A,B,C,D)- output impulse of first kind

In practical cases we have a lot input impulses

Tribo-topology scheme of (LNAS)1 for the formula (1) is presented graphically in Fig.3

Figure 3 Tribo-topology logical network analysis scheme (LNAS) 1 : Y=[a(AC)B]{[ (aCB) D] A} for seven connections

By virtue of the set theory the expression (1) we can transform in following form [4]:

{[aA(aCB)]{[ (aCB) A ](AD) } { {[aA(aCB)][ (aCB) A ](AD) { {(aAA)(aCB)(AD) {

{X(aCB)(AD) { {(aCB)(AD) (2) Hence we have finally:

Symbol Y denotes total impulses space

In Fig 4 for A,B,C,D –input impulses, the output impulse Y treated as the result (3) is showed in the graphical form

Fig.4 Tribo-topology logical network analysis scheme (LNAS) 1eq : Y{(aCB)(AD) for three connections

The equivalent scheme (LNAS)1eq, illustrated in Fig 4, is simpler than the original scheme (LNAS)1 shown in Fig 3, as it features only three connections between the two variable nodes, compared to the seven connections in (LNAS)1 This reduction in connections highlights the efficiency of the (LNAS)1eq design.

147 more proper und more productive network of transmission impulses

In the calculation of slide bearings and HDD micro bearings, we utilized a sequence of interconnected data derived from experimental AFM measurements The simplicity of the geometry and the logical architecture of these data connections significantly impact the convergence of computer calculations for essential exploitation parameters This highlights the importance of our proposed solution compared to other methods.

More examples of the proposed system had been described in the last authors and his research team pa- pers [8],[9],[10]

5.2.Now we are going to show the not effective case of the presented input electronic impulses method of second kind We take into account the next output impulse:

Y(E1,E2,F1,F2), (4) and we assume following expression:

Y=[a(E1E2) F1][a (F1aF2) E1], (5) where: E1,E2,F1,F2 –input electronic impulses, Y- output impulse

On the ground of the simple set theory we can transform expression (5) into the following form:

A new Tribo-Topological scheme of network

(LNAS)2 described by the formula (5) is presented in Fig.5

Figure 5.Tribo-topology logical network analysis scheme

In Fig 6 is presented the equivalent scheme

(LNAS)2eq described by the formula (7) for

Figure 6.Tribo-topology logical network analysis scheme (LNAS) 2 for seven connections:

The origin network scheme (LNAS)1 shown in Fig 5 and the equivalent scheme (LNAS)2eq illustrated in Fig 6 feature an identical number of connections, with arrows indicating the direction of impulse transmission.

Figure 7 illustrates the pressure distribution and load-carrying capacity of a conical slide microbearing, derived from numerical calculations of the modified Reynolds equation conducted using Matlab 7.2 Professional.

Figure 7 The pressure distributions in conical micro-bearings caused by the rotation in circumferential direction where conical inclination angle Jp o

The left side of Figure 7 illustrates the perspective from the film's origin, while the right side depicts the view from the film's end The output vector includes the film end coordinates, with Mk=3.678 representing the pressure in the two upper regions.

The analysis involves 148 pressure distributions, with a maximum pressure value (pmax) of Mk=3.705 for two lower distributions Key components include load carrying capacities in the longitudinal (Cz) and transverse (Cy) directions Input parameters consist of a relative eccentricity ratio of Oc=0.4 for the upper distributions and Oc=0.3 for the lower distributions, alongside a cone radius of R=0.001 m The dimensionless bearing length is L=1, with a bearing length of bc, and the cone journal operates at an angular velocity of Z=565.5 s⁻¹ Additionally, the oil dynamic viscosity is measured at K=0.03 Pas.

The final calculation indicator Y 1D is defined as a combination of three key elements: the output impulses from two different types of networks, various transmission impulses, and a modified partial differential Reynolds equation that outlines the distribution of pressure and load carrying capacity.

Such indicator is defined in the following form:

Corollary 2 states that the optimal calculation indicator is achieved by minimizing the sum of output impulses in a logical network for data transmission in journal bearing design This approach is particularly effective when identifying the operational parameters of journal bearings through acoustic emission methods.

Corollary 3 highlights the impact of variable, often interdependent impulses on the behavior of slide journal bearing systems By examining the design variables of these bearings, we can assess their influence on bearing stiffness and the natural frequencies of the bearing shaft.

Corollary 4 highlights the significance of the supporting structure, including the stator, housing, and base plate, in influencing the natural frequencies and mode shapes of the slide journal bearing system.

This paper presents innovative results in logical network analysis for data transmission impulses related to journal bearing design These findings, illustrated through graphical representations and grounded in mathematical set theory, serve as valuable tools for artificial intelligence and computational methods in maritime transport.

Presented paper establish the scheme of calculation algorithm of hydrodynamic pressure and carrying capacity changes in journal-bearings for various journal shapes and for various geometries

The findings allow for an examination of the dynamic behavior of journal bearing systems through the resolution of Reynolds' equation and motion equations across various degrees of freedom This analysis reveals that the dynamics of journal bearings are influenced not only by design variables but also by existing motor parameters.

This paper was supported by Polish Ministerial Grant 3475/B/T02/2009/36 in years 2009-2012

[1] Bharat Bhushan: Nano-tribology and nanomechanics of MEMS/NEMS and BioMEMS, BioNEMS materials and devices Microelectronic Engineering 84, 2007, pp.387-412

[2] Jang G H., Seo C.H., Ho Scong Lee: Finite element model analysis of an HDD considering the flexibility of spinning disc-spindle, head-suspension-actuator and supporting structure Microsystem Technologies, 13, 2007, pp.837-847

[3] Kącki E.:Partial differentia equationsin physical and technical problems (In polish).WNT Warszawa 1968

[4] Kuratowski K.: Introduction into set thepry and topology (in polish) PWN Warszawa 1970,

[5] Ralston A:A First Course in Numerical Analysis (in Polish),PWN,Warszawa 1971

[6] Wierzcholski K.: Enhancement of memory capacity in HDD micro- bearing with hyperbolic journals, Journal of Kones Powertrain and Transport, Warsaw 2008, Vol.15, No.3, pp.555-560

[7] Wierzcholski K.: Bio and Slide Bearings, their Lubrication by Non-Newtonian Oils and Applications in Non- Conventional Systems, Vol.1, Gdansk Univ.of Technology, GRANT UNI EU: MTKD-CT-2004-517226

[8] Wierzcholski K.: Fuzzy Logic Tools in Intelligent Micro- Bearing Systems.(in English) XIII Journal of Applied Computer Science, vol.17 No.2,2009, pp.123-131

[9] Wierzcholski K., Chizhik S., Trushko A., Zbytkowa M., Miszczak A.: Properties of cartilage on macro and nano- level Advances in Tribology, vol 2010, Hindawi Publish- ing Corporation, New York: http://www.hindawi.com/apc.aspx?n$3150

Takashima, B Mezaoui & R Shoji 21 Digital Multichannel Electro-Hydraulic Execution Improves the Ship’s Steering Operation

Towards the Model of Traffic Flow on the Southern Baltic Based on Statistical Data

Puszcz & L Gucma 23 Incidents Analysis on the Basis of Traffic Monitoring Data in Pomeranian Bay

This paper explores the analysis of ship traffic in the Southern Baltic by utilizing historical AIS data from HELCOM It employs statistical methods to assess the spatial distribution and parameters of ship traffic, presenting probabilistic models that enhance understanding of maritime movement in selected areas The findings are valuable for safety and risk analysis, contributing to the development of comprehensive models for ship traffic flows in the region.

Figure 1 Ship calls top selected sea ports in the Baltic Sea Re- gion in 2008 [source: GUS]

Figure 2 Analyzed area- approach to ĝwinoujĞcie

2.2 Navigational conditions ĝwinoujĞcie Roads, the inner part of Pomorska Bay, is approached from the N or E channels, passing respectively, W or S of Oder Bank (54°21'N

014°25'E), known locally as Odrzana Bank; the shoal area, which is extensive with a least depth of

4.8m, white sand, is fairly steep-to, except on its N side The navigation channel is 32nm long with a varying width of 180-200m and a depth of 14.3m

The port entrance is protected by breakwaters

The weather in the temperate zone features strong northeast winds that create heavy seas in the bay While the port remains largely ice-free throughout the year, challenges may arise from early January to mid-March.

3 STATISTICAL MODEL OF SHIPS TRAFFIC

3.1 Spatial distribution of ships traffic

The theory of ship traffic flow analyzes the movement of multiple vessels within a designated traffic lane over a specific time frame A key parameter in this analysis is the distribution, which indicates the position of a ship's hull in relation to the axis of the track.

The vessel's center of gravity, waterline shape, and course information are essential for defining distribution A straightforward method to describe traffic streams involves characterizing them with a specific resolution It's important to recognize that distribution types vary depending on the track section, whether straight or curved The most commonly utilized distribution is the normal distribution, represented by its probability density function (PDF).

In the context of maritime navigation, the equation Q e z (4) defines key parameters such as 'y,' representing the distance to the axis, 'm,' which is the average distance of ships from the waterway axis, and 'V,' the standard deviation of this distance Additionally, it incorporates the gamma function ī(p) and the beta function ȕ(p, q), along with other distribution parameters including a, p, q, ȕ, and Į.

The width of traffic flow is crucial for accurate assessment, as it directly influences the characteristics of traffic streams Understanding the distribution of lane widths is essential for effectively describing these traffic patterns.

3.2 Time distribution of ships traffic

This study aims to develop a statistical model that characterizes ship traffic flow by analyzing parameters based on the time of day and year The findings can be applied to simulation models for traffic flow parameters, enhancing the ability to predict future traffic trends in the studied region.

The intensity of vessel traffic is a crucial input parameter for modeling ship behavior Various factors influence vessel traffic along the fairway, which changes over time and depends on the length of the track This variability causes vessel movement to become a random process, necessitating the use of probabilistic models for accurate description.

The seaway can be depicted on a timeline, highlighting the random events of ships transitioning through the center Analyzing the random stream of vessels involves examining the distribution of the number of vessels passing through a specific point in time (ΔT), the distribution of time intervals between vessels, and the distribution of local vessel speeds.

The number of ships passing given point of the waterway in case when vessels have freedom of se- lecting speed and manoeuvre can be described as

Poisson distributed stochastic process where probability of appearance of X=n ships in 't time is:

Probability, that in 't time no ship will appear is:

Accurately determining the precise path and corresponding speed of vessels is essential for characterizing traffic streams The findings should be presented in a manner that is universally applicable and can serve as input for maritime models To effectively represent a vessel's trajectory and speed within a model, specific parameters must be established.

1 Describe the spatial distribution of vessels in a certain section;

2 Describe the lateral vessel speed distribution of vessels in a certain section;

3 Describe the vessel speed distribution on a certain location;

4 Take into account that the 3 distributions mentioned above depend on:

Type of waterway segment (straight / bend)

Width of the (for that specific vessel type and size) navigable waterway;

Wind speed and wind direction;

Current speed and current direction;

5 Describe the mutual dependence between two spatial successive distributions (to connect the different sections, in order to assemble an individual vessel path and correct speed development)

The main factors affecting the movement of vessels in relation to the axis of the traffic lane are the size of the vessels, meteorological conditions

The experience of the officer is influenced by factors such as waves and wind, while the intensity of shipping traffic is significantly affected by the market's economic conditions and the current season.

The study focused on analyzing the traffic distribution in relation to the traffic lane axis at Świnoujście Harbour The methodology employed involved identifying the distribution type of specific parameters.

Information on traffic received from the AIS (for the period 01.2008–02.2009) is used

Data is divided on the season, day or night time and type of traffic (inbound or outbound)

Grouped samples studied separately as separate random variables

Defined a random variable as the location of the vessel in relation to the axis of the track

The data collected was processed using the middle line method, which applies to both the bends and straight sections of the fairway This technique references the center of the track segments, approximating them based on the length of each section.

The sections of the vessel are shaped either partially circular or rectangular Using data regarding the course, the waterline, and the geometric center of the waterline, the coordinates of the vessel's extreme points (both right and left) are determined Subsequently, their distances from the track axis, which serves as the reference axis, are calculated These corresponding distributions are then aligned using distance tables.

The analysis focused on a specific dataset related to the approach to Świnoujście, using the midpoint of the navigation channel as the origin for calculations Mean values represent the average distances from this midpoint, with the gate's midpoint located centrally between buoys 7 and 8, ensuring they align with the assigned gate Other gates were established using a similar methodology.

Figure 3 Method for the measure of the track, the track center line approximation to the polygon and the track division into sections [4]

4.1.1 Average vessel path and speed

Gucma & K Marcjan 24 Model of Time Differences Between Schedule and Actual Time of Departure of Sea Ferries

This paper presents a preliminary analysis of grounding incidents aimed at enhancing navigational safety management systems, specifically in the Pomeranian Bay area Utilizing AIS data, a grounding incidents model was developed, focusing on key factors such as the vessel's distance from hazardous depths and the draught-to-depth ratio, which are critical in understanding navigational incidents.

The region located between 55°N and 00°N, encompassing Bornholm, Rügen, and the approach to Świnoujście, is recognized as a coastal area characterized by relatively shallow depths in certain locations.

Figure 4 Regions with depth of 10 m or less extends around the Rügen Island, around Bornholm close to

Polish and German shore and also north of approach to ĝwinoujĞcie

Figure 4 Map of selected area with isobaths.[5]

A model for assessing grounding incidents in a specific area utilizes AIS data, which provides both static and dynamic information about ships and their positions This data-driven approach enables effective analysis and determination of grounding risks in maritime environments.

Application written in C# [3] consists of three sections:

The initial section analyzes data obtained from the AIS, documenting the navigation routes of vessels within the specified area This information is organized and recorded into the relevant database tables for further processing.

6m depth or more are taken into account

Figure 5 Database table with AIS dynamic data

The second section analyzes the vessel's individual positions based on their proximity to water depths It focuses on depths that are less than 140% of the vessel's draught, recording the lowest depth and the shortest distance to these critical depths.

Figure 6 A diagram of lowest depth and distance selection

The third section of the program focuses on a model for position extrapolation, utilizing dynamic data to identify both the previous position (ĳ(t0), Ȝ(t0)) and the subsequent position (ĳ(tn), Ȝ(tn)) of the vessel near a hazardous depth.

Positions are considered valid only if the time difference from the reference position (ĳ(tr), Ȝ(tr)) is under 6 minutes The extrapolation algorithm computes each position every second, determining the distance from the depth relative to the previous, reference, and subsequent positions This process identifies the vessel's position that is nearest to the shallowest depth in its vicinity.

In maritime navigation, the latitude (ĳi) at time ti is determined relative to the vessel's previous and reference positions, while the longitude (Ȝi) corresponds to position number i within the same timeframe Additionally, the Course Over Ground (COGj) at time tj is crucial for accurate positioning and navigation.

Vj - speed of the vessel in time tj, r – number of extrapolated positions between previous position and reference position of the vessel dt t dCOG t

The result of the analysis of grounding incidents on the area between 13 0 00’E - 15 0 00’E and 54 0 00’N -

55 0 00 ’ N within 6 month time period (1 th January

Between January 1, 2008, and June 30, 2008, a total of 230 grounding incidents were identified using a specific algorithm Figure 7 illustrates the analyzed area, highlighting the positions of vessels categorized by the D/T ratio Additionally, the 10m and 12m iso-baths are indicated to represent areas of shallow depth.

All the ports and their surroundings were excluded from the examined area

Figure7 Grounding incidents on selected area from 01.01.2008 to 30.06.2008

The relationship between vessel draught and water depth is critical for safe navigation, as illustrated in Figure 8 A total of 42 vessels were navigating in areas where the water depth was less than their draught, posing significant risks Additionally, 188 vessels were operating near depths that could potentially compromise their safe passage.

Figure 8 Number of vessels close to depth with assigned ratio

Three ships navigated a perilous depth, maintaining a distance of 2 cables or less It's important to note that this distance is measured from the calculated depth to the vessel's antenna position, which means the actual distance from the depth could be even less than 2 cables Figure 9 illustrates the distances of the ships to the depth, with experts indicating a critical distance of 0.7 cables.

When navigating open waters, maintaining a safe distance from dangerous depth contours is crucial, as getting too close can lead to risky situations or grounding incidents.

Figure 9 Number of vessels approaching to dangerous depth with assigned distance

Most vessels that approach dangerous depths typically measure between 101m and 160m in length, with the majority ranging from 101m to 120m and having a draught of 5-7m These depths are primarily found in coastal areas, indicating that some port surroundings may not be adequately protected.

Figure 10 Number of grounding incidents based on vessel length

The results of grounding incidents provide crucial insights into areas with shallow water where vessels navigate dangerously close The locations identified by the model closely align with actual grounding accidents in the analyzed region These findings will contribute to the development of a navigational safety management system, as detailed in [1] While further verification of the model's outcomes is necessary, preliminary validation shows a significant correlation between calculated grounding incidents and real occurrences in the studied area.

Gucma L., Marcjan K 2011 The Incident Based System of Navigational Safety Management of on Coastal Areas Pro- ceedings of the 8th International Probabilistic Workshop

Przywarty M 2008 Models of Ships Groundings on Coastal Areas Journal of Konbin Vo-lume 5, Number 2 / 2008

ECMA International 2006 C# Language Specification (4th ed.)

In 2009, HELCOM published a report detailing shipping accidents in the Baltic Sea region, highlighting the need for improved maritime safety measures The report is accessible online, providing valuable insights into the frequency and nature of these incidents For more information, visit the HELCOM map service and the topography resource on the Baltic Sea.

Safe Shipping and Environment in the Baltic Sea Region Miscellaneous Problems in Maritime Navigation, Transport and Shipping – Marine Navigation and Safety of Sea Transportation – Weintrit & Neumann (ed.)

Gucma & M Przywarty 25 Simplified Risk Analysis of Tanker Collisions in the Gulf of Finland

This paper explores the time discrepancies between scheduled and actual departure times of sea ferries at the Świnoujście Harbour, utilizing data collected during port measurements A comprehensive model of vessel traffic in the southern Baltic Sea was developed based on this information Following this, a simulation experiment was conducted to verify the model, identifying potential sea accident scenarios and encounter situations The results of this simulation are valuable for assessing navigational safety in the region.

The following results were obtained:

Mean difference between actual and scheduled time of departure: 4min;

Maximum difference between actual and scheduled time of departure: 34min;

Minimum difference between actual and scheduled time of departure: -9min (ferry unberthed be- fore scheduled time);

Histogram of the differences between actual and scheduled time of departure is presented in Figure 2

Figure 2 Histogram of the differences between actual and scheduled time of departure of Ferries in the ĝwinoujĞcie Har- bour

According to characteristics of a random variable, calculated parameters and on the basis of the histogram following theoretical distributions were chosen for further analysis

Parameters: m – shape parameter (positive integer) ȕ – continuous scale parameter (ȕ>0) Ȗ – continuous location parameter

(Ȗ Ł 0 yields the two-parameter Erlang distribution)

Parameters: ı – continuous parameter (ı>0) μ – continuous parameter Ȗ – continuous location parameter

(Ȗ Ł 0 yields the two-parameter Lognormal distribution) Domain:

Parameters: ı – continuous scale parameter (ı>0) μ – continuous location parameter

Parameters: Į – continuous shape parameter (Į>0) ȕ – continuous scale parameter (ȕ>0) Ȗ – continuous location parameter

(Ȗ Ł 0 yields the two-parameter Log-Logistic distribution) Domain:

Parameters: k – continuous shape parameter ı – continuous scale parameter

Domain: for k 0 for k = 0 Probability Density Function: where

Due to domain restriction to the positive numbers concerning some of the chosen distribution the following modification of time differences was performed:

The variables used in the analysis include $ d_m $, which represents the difference between the actual and scheduled departure times for distribution fitting, $ d_t $, indicating the overall difference between actual and scheduled departure times, and $ d_{t \text{min}} $, denoting the minimum difference recorded, which is -9 minutes.

Parameters of fitted distribution are presented in the Table 1 Histograms of the time differences and the fitted distributions are presented in Figure 3

Table 1 Parameters of fitted distributions

Erlang Lognor mal Logistic Log- Logistic Gene ralized Extreme Value

Figure 3 Histograms of the time differences and the probability density functions of fitted distributions

The goodness of fit analysis was performed using the Kolmogorov-Smirnov Test and the Anderson-Darling Test Both tests indicated that the Generalized Extreme Value Distribution was the most suitable theoretical distribution for the data.

4 APPLICATION OF THE MODEL TO NAVIGATIONAL SAFETY ASSESSMENT

The selected distribution was utilized to simulate sea ferry traffic to and from Świnoujście Harbour, forming a crucial component of the microscopic model for ship traffic within the navigational safety assessment framework A diagram illustrating the fully developed stochastic model of this navigational safety assessment is shown in Figure 4 (Gucma & Przywarty, 2007).

Figure 4 Diagram of fully developed stochastic model of navigational safety assessment

Waypoints were determined through a combination of sea chart analysis, AIS data sourced from the Helcom database (2006, 2007), and personal seamanship experience To simulate route variability, two-dimensional normal distributions were utilized.

The layout of the simulated routes is illustrated in Figure 6, while the navigational safety assessment model was developed using Delphi language Additionally, Figure 7 showcases the model's interface, which facilitates the input of initial data and enables simulation monitoring.

Figure 5 Distributions of waypoints coordinates

The navigational safety assessment model enables the identification of simulated coordinates for incidents such as collisions, groundings, and fires, facilitating a streamlined evaluation of the consequences of maritime accidents (Gucma & Przywarty, 2007).

A ferry traffic simulation experiment was conducted to validate the developed model, which accurately reflects the time differences between scheduled and actual departure times at Świnoujście Harbour Given the rarity of sea accidents involving ferries, the study focused on analyzing encounter situations The findings of this experiment are illustrated in Figure 8.

Figure 8 Positions of simulated encounter situations involving sea ferries on routes to and from ĝwinoujĞcie Harbour

Additionally, during the simulation positions of simulated groundings, collisions and fires were established These positions are shown in Figure 8

Particular results are presented in table 2

Figure 9 Positions of simulated groundings collisions and fires

Table 2 Particular results of simulation experiment

Mean number of accidents per year

Mean time between accidents

Grounding 25 10 x 5 years 0,5 2 years Encounter situation involving ferry

The developed model for analyzing time discrepancies between scheduled and actual departure times of sea ferries in Świnoujście Harbour effectively simulates the scheduled traffic of ships This model has been validated for its application in simulating the traffic of sea ferries operating on routes to and from Świnoujście Harbour.

To confirm the possibility of its use in other ports, further investigation is needed

This paper was created with support of EfficienSea project; partially EU founded Baltic Sea Region Programme 2007-2013

In 2004, Gucma L conducted a study on the probabilistic characteristics of ship traffic flow in the waterway between Szczecin and Świnoujście, published in the Scientific Notebooks of the Maritime University of Szczecin Following this, in 2005, Gucma explored risk modeling related to ship collision factors with fixed port and offshore structures, further contributing to maritime safety research at the Maritime University of Szczecin.

Gucma L.Przywarty M 2007 Probabilistic method of ships navigational safety assessment on large sea areas with consideration of oil spills possibility International Probabilistic Symposium Ghent

Gucma L.Przywarty M 2007 The model of oil spills due to ships collisions in Southern Baltic area Proc of Trans-Nav Conference Gdynia

Helcom Report on shipping accidents in the Baltic Sea area for the year 2005 Helsinki Commission Baltic Marine Envi- ronment Protection Commission (HELCOM) Draft 2006

Helcom Report on shipping accidents in the Baltic Sea area for the year 2006 Helsinki Commission Baltic Marine Envi- ronment Protection Commission (HELCOM) Draft 2007.

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Safe Shipping and Environment in the Baltic Sea Region Miscellaneous Problems in Maritime Navigation, Transport and Shipping – Marine Navigation and Safety of Sea Transportation – Weintrit & Neumann (ed.)

In recent years, maritime traffic in the Gulf of Finland has surged, largely due to the growth of Russian oil exports from ports like Primorsk.

Prior to the recent economic recession, Russia experienced a consistent annual increase in oil exports, a trend projected to continue in the future (Kuronen et al 2008, Helcom 2010) This rising volume of oil transportation raises significant concerns regarding the potential for oil spills, particularly given the Gulf of Finland's highly vulnerable marine ecosystem.

Historic shipping accident analyses reveal that groundings, collisions, and fires are the predominant accident types globally (Soares 2001) In the Gulf of Finland, characterized by shallow waters and numerous islands, groundings and ship-ship collisions occur most frequently (Kujala et al 2009) This highlights the critical concern addressed in this paper regarding the risks posed by oil tankers in ship-ship collision incidents.

The model discussed in this paper emphasizes the growing societal shift towards science-based, risk-informed decision-making, a concept endorsed by organizations like the IMO and IALA Within the maritime sector, the Formal Safety Assessment serves as a crucial framework to support this initiative.

2 OUTLINE OF RISK ASSESSMENT METHODOLOGY

The risk assessment methodology is rooted in the commonly accepted framework of the Formal Safety Assessment (FSA) (Kontovas and Psaraftis, 2005) The conceptual FSA-methodology is shown in Fig

Identifying hazards is the first step in the risk management process, followed by a thorough analysis of the associated risks Once the risks are assessed, various risk control options are established, and their effectiveness should be evaluated using a structured risk analysis method.

Họnninen, P Kujala, J Ylitalo & J Kuronen

The Method of Optimal Allocation of Oil Spill Response in the Region of Baltic Sea

Gucma, W Juszkiewicz & K àazuga 28 Modeling of Accidental Bunker Oil Spills as a Result of Ship’s Bunker Tanks Rupture –

Massive oil spills, like the Torrey Canyon (1976) and Exxon Valdez (1989), draw significant public concern due to their devastating environmental impact, yet smaller spills from vessel collisions and pipeline ruptures occur more frequently Effective oil spill response is crucial for controlling marine pollution and protecting coastlines, necessitating the deployment of cleanup equipment A major challenge in these cleanup efforts is balancing the costs of cleanup against the potential damage incurred This paper presents a method for the optimal allocation of resources in oil spill responses and strategies for cost optimization.

Figure 2 Amount of oil transported to and from the Baltic Sea via the Great Belt during 2000-2008 (SHIPPOS 2000-2007 and

2 METHOD OF OPTIMAL ALLOCATION OF

2.1 Response resources allocation at Baltic Sea

In the event of an oil spill, prompt response with adequate cleanup equipment is crucial to safeguarding the marine environment and reducing cleanup costs and damage.

Baltic Sea region every country is equipped with their own response resources Picture below (Fig.3) shows location of those equipment

Figure 3 Response resources at Baltic Sea (HELCOM database)

The model utilizes statistical data, including frequency, volume, type, location, weather conditions, and sea-state of oil spill events, to analyze historical data for the Baltic Sea region This analysis identifies key input parameters, such as the necessary number and type of response equipment and the expected travel times for transporting this equipment from a facility to the spill site Travel times are influenced by the distance to the spill, the type of equipment, and prevailing weather and sea conditions Once the required data is gathered, it is employed to simulate an oil spill using the PISCES II simulator.

Figure 4 Model of optimal allocation

3 COST OPTIMIZATION OF ALLOCATION OF ANTI POLLUTION RESOURCES

It is assumed that the fixed costs of opening facility site and the operating costs of the equipment are

Bąk & K Ludwiczak

Tiêu đề	Miscellaneous Problems in Maritime Navigation, Transport and Shipping
Tác giả	Adam Weintrit, Tomasz Neumann
Trường học	Gdynia Maritime University
Thể loại	edited book
Năm xuất bản	2011
Thành phố	Gdynia

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Số trang	241
Dung lượng	5,86 MB