numerical computation of a large scale jet fire of high pressure hydrogen in process plant

MODELING AND ANALYSIS Numerical computation of a large-­scale jet fire of high-­pressure hydrogen in process plant Chang Bong Jang1 & Seungho Jung2 1Korea Occupational Safety and Health Agency, 400 Jongga-ro, Jung-gu, Ulsan, Korea and Safety Engineering, Ajou University, Suwon, Korea 2Environmental Keywords Flame, heat radiation, hydrogen, jet fire, temperature Correspondence Seungho Jung, Environmental and Safety Engineering, Ajou University, Worldcupro 206, Yeongtong-gu, Suwon, Korea E-mail: processsafety@ajou.ac.kr Funding Information No funding information provided Received: 23 May 2016; Revised: 10 October 2016; Accepted: 11 October 2016 Energy Science and Engineering 2016; 4(6): 406–417 Abstract Due to numerous hazardous chemicals to handle, the process plant industry has a higher risk of fire, explosion, and toxic release than other industries Reviewing the accidents at process plants in the past, it is clear that fire accidents occur with the highest frequency, leading this study to consider accidental fire scenarios at process plants For the scenario of an incident, a jet fire involving a massive amount of hydrogen gas to be processed or delivered at the process plant has been selected The analysis of incident outcome resulting from the hydrogen jet fire has been implemented through the computational fluid dynamics simulation methodology Kameleon FireEx Based on the outcome of this simulation, the consequences of a jet fire with high temperature and heat radiation are analyzed and evaluated In addition, the results from Phast ver 7.11 simulation for the same scenario are presented for comparison and further validation doi: 10.1002/ese3.143 Introduction Hydrogen is the most abundant element on the Earth and can be obtained from water and natural gas Once hydrogen is used as fuel, it returns back to the form of water, which makes it ecologically crucial in the production of cleaner fuels The ideal method of producing hydrogen involves the use of renewable energy sources like solar power or wind power, but as these methods result in considerable cost of production, hydrogen is often produced using fossil fuel [1, 2] In South Korea, the annual production of hydrogen amounts to about 9.3 million Nm3, and a significant portion of this is produced as byproduct gas Hydrogen is mostly consumed in petrochemical plants, with only about 15% used in other industries In particular, the rate of hydrogen consumption in the energy industry is about 1%, representing a very minor portion of consumption [2] Hydrogen consumed in a process plant is usually treated and delivered under high pressure In these conditions, once hydrogen is leaked from equipment and immediately 406 ignited, it creates a jet fire, which generally seems to result in less damage compared to explosion or toxic release However, if the facilities and devices installed around the equipment in the process plant are congested, a severe secondary accident may occur due to the jet fire Analyses of past accidents have shown that fire accidents represent a primary cause of numerous large-­scale accidents [3–5] Moreover, at a process plant, fire represents one of the frequent accident types [6] Yet, recent studies on the risk of hydrogen gas have been mostly related to explosions of hydrogen charge facilities [7, 8] Preliminary studies on hydrogen fires have been performed to evaluate the flame behavior of small-­scale jet fires [9, 10] In contrast to the aforementioned studies, here, numerical analysis was performed of hydrogen jet fire in a complex, large-­scale structure within an industrial process plant to realistically predict its substantial effects Thereafter, through the outcome of computation, the influence of the flame intensity on surrounding process facilities and devices was evaluated and analyzed Following various © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung references, computational fluid dynamics (CFD) simulations are available for various conditions such as congestion of the facility and devices, turbulence, obstacles, and weather effects; their results are very similar to the actual outcome [11–13] Numerical Simulation For the hydrogen jet fire analysis, the Kameleon FireEX (KFX) CFD code developed by ComputIT for fire analysis was used KFX applies a precise code based on fire and gas diffusion within a complex structure and is now widely used as a safety analysis code in various industrial fields The Combustion Model (1) Here, Rliq is a source due to the liquid phase transition, ρ is the density of gas, the — symbol represents time-­ averaged quantities, and the ″ and ~ symbols are fluctuation and mean of Favre-­averaged quantities Species mass fraction equations ( ( ) ) 𝜕𝜌Ỹ 𝜄 𝜕𝜌̃uj Ỹ 𝜄 𝜕 𝜕 + =− 𝜌Y𝜄 V𝜄j − 𝜌u��j Y��𝜄 + 𝜌̄R̃ 𝜄 + 𝜌R̃ liq,𝜄 𝜕t 𝜕xj 𝜕xj 𝜕xj (2) In this equation, Yι is the species mass fraction and Vιj is the molecular diffusion velocity of species ι in the direction j In addition, Rι is a chemical source term and Rliq,ι is a source due to the liquid phase transition which is not considered since hydrogen is all gaseous phase in the study Momentum equations ( ) 𝜕𝜌̃ui 𝜕𝜌̃uj ũ i 𝜕p 𝜕 + =− + 𝜏ij − 𝜌u��j u��i + 𝜌fi + 𝜌F̃ liq,i 𝜕t 𝜕xj 𝜕xi 𝜕xj ( 𝜏𝜄j = 𝜇 𝜕 ũ i 𝜕 ũ j + 𝜕xj 𝜕xi ) ( ) ( 𝜕 u� ) 𝜅 + 𝜅− 𝜇 𝛿ij 𝜕x𝜅 Enthalpy equations ( ) ) ) 𝜕 ( 𝜕 ( ) 𝜕 ( 𝜕T 𝜕 �� �� − 𝜌̃uj ẽT 𝜌̃eT + 𝜌̃uj ẽT = (𝜏ij − p)uj + k𝜄 𝜕t 𝜕xj 𝜕xj 𝜕xj 𝜕𝜒j + Qgs + QRad + 𝜌S̃ liq The governing equations, eqs. (1–7) of KFX, determine the mass conservation (eq. 1), the mass species fractional equation (eq. 2), momentum conservation along the coordinate direction using Navier–Stokes equations (eq. 3), and total energy equation for compressible gas flows (eq. 5) 𝜕𝜌 𝜕𝜌̃uj + = 𝜌R̃ liq 𝜕t 𝜕xj Here, fi are mass forces by which the gas is influenced, τij is the tension [N/m2], k is the second viscosity coefficient, and δij is the Kronecker delta The Eddy Dissipation Concept (EDC) is used for turbulent combustion Its basis is physical consideration of the structure of turbulent flow The mixing on molecular level, which is a necessity for chemical reactions to occur, is located in structures where turbulent kinetic energy is dissipated into heat due to action of viscous forces on the local strain [14] eT = e + ui uj ∑ e= Y𝜄 e𝜄 (T) (6) (7) 𝜄 In this equation, Qgs is the heat transport form solid to gas phase, QRad is the net radiative transfer to the gas phase, S̃ liq is the net heat transfer for the liquid phase, k𝜄 is the conductivity, eT is the total energy, and e is the total internal energy The Turbulence Model For turbulent flow, KFX uses the extended formula of the conventional k  −  ε formula for buoyancy and some low-­Reynolds numbers The modeled equation for k and ε is presented in eq. (8), and the rate of dissipation of turbulent kinetic energy ε is given in eq. (9) [11] ) ( ) ( ( ) 𝜇eff 𝜕k 𝜕 𝜌̃ui k 𝜕 𝜌k 𝜕 + = + P − 𝜌𝜀 + B (8) 𝜕t 𝜕xi 𝜕xi 𝜎k 𝜕xi ) ( ) ( ( ) 𝜇eff 𝜕𝜀 𝜕 𝜌̃ui 𝜀 𝜕 𝜌𝜀 𝜕 𝜀 + = + C1 f1 P 𝜕t 𝜕xi 𝜕xi 𝜎𝜀 𝜕xi k (9) 𝜀 𝜀2 − C2 f2 𝜌 + C1 C2 B k k ) ( 𝜕 ũ i 𝜕 ũ j 𝜕 ũ j + P = 𝜌𝜈t (10) 𝜕x 𝜕x 𝜕x j i �� 𝜌�� g ̃ B = 𝜌u i i (3) (5) 𝜇t = C�D f𝜇 𝜌 k2 𝜀 ] −2.5 fu = exp + Rt ∕50 i (11) (12) [ (4) © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd (13) 407 CFD for Large-scale Hydrogen Jet fire Rt = 𝜌k2 𝜇𝜀 𝜇eff = 𝜇𝜄 + 𝜇t C B Jang & S Jung √ (14) CD = 0.09, 𝜎k = 1.0, 𝜎𝜀 = 1.3, C1 = 1.44, C2 = 1.92 (16) The accuracy and utility of KFX have been verified through numerous experiments and on-­the-­job projects, and the simulation has shown relatively satisfactory outcome compared to actual experiments [11–13, 15] Incident Outcome of a High-­Pressure Hydrogen Leak While it is one of the essential materials for production in a petrochemical process plant, hydrogen is simultaneously produced as a byproduct within the production process In the case of oil-­refinery processing, hydrocracking, heavy oil (H-­ Oil), and desulfurization units require hydrogen, and the general naphtha reforming unit produces hydrogen as a byproduct gas The production reaction of hydrogen in a naphtha reforming unit is as shown below: Cn Hm (Naptha) + nH2 O → nCO + (2n + m) ∕2 H2 (17) CH4 + H2 O → CO + 3H2 (18) CO + H2 O → CO2 + H2 (19) For heavy oil upgrading of crude oil, a massive amount of high-­temperature and high-­pressure hydrogen gas is consumed Therefore, many chemical factories have installations to produce hydrogen gas from raw materials like naphtha to fulfill their hydrogen requirements autonomously Since numerous installations and devices within such processing plants are gathered in a limited space, this is regarded as a high-­ risk process If the hydrogen gas leaks and causes a fire, it may cause severe defects in surrounding facilities and devices, leading to simultaneous accidents [16–18] In general, the treatment of hydrogen at a process plant is carried out under a high pressure of over 160 kgf/cm2 In a scenario where hydrogen leaks from a pipe to cause an accident, its speed at the leak point is greater than the speed of sound, as computed by eqs. 20 and 21 [19] 408 Pa PCF ≤ P1 P1 + (𝛾 − 1)Ma2 𝛾 +1 (21) (15) In these equations, P is the production of turbulent kinetic energy by the mean motion, B is a buoyancy, 𝜇t is a turbulence diffusion coefficient, Rt is a turbulent Reynolds number, f1, f2 are the functions in the low-­Reynolds number model, and fu is a low-­Reynolds number correction factor The constants in the turbulence model are as follows: SC = PCF = Ma P1 (20) Here, Sc is the sonic or supersonic flow in the pipe, Pa is the ambient pressure, P1 is the pressure before the hole, PCF is the choked pressure, γ is the heat capacity ratio, and Ma is the Mach number In the case study, it is a choked flow due to high pressure, so that an equivalent leak position was used instead of the actual leak position The distance between them in this study is around 0.6 m The inlet conditions must also contain some information on the turbulence energy level and the dissipation of turbulence energy Such information may be obtained from experiments or by resolving the under-­ expanded jet structure by numerical calculations A similar problem also exists for the jet’s entrainment of ambient fluid, which is neglected in the method since the near-­ field effects of entrainment are smaller than further downstream The minimum ignition energy of hydrogen is 0.018 mJ; considering the minimum ignition energy of typical hydrocarbon – methane (0.28 mJ), propane (0.25 mJ), and butane (0.26 mJ) – hydrogen’s minimum ignition energy is about 13.9–15.6 times lower [20] This makes it easily ignitable within only a few seconds after a leakage The radiation on KFX is solved by an enhanced version of the discrete transfer model [21] The basic concept of this model is that radiation exchange is calculated by integration of radiation absorption and emittance along a huge number of rays (lines) throughout the calculation domain From the boundary of a box inside the calculation domain, rays are sent at a discrete number of directions from each control volume surface on the enclosing box CFD Modeling Description The process to be simulated in this study is residue-­ hydro-­desulfurization (RHDS) or Hyvahl, which consumes a large amount of high-­pressure hydrogen within an oil refinery This process is carried out to reduce the concentration of metal, asphaltenes, nitrogen, and sulfur from vacuum residue (VR) from a crude distillation unit (CDU), vacuum gas oil (VGO), or atmosphere residue (AR) from a lower CDU Furthermore, it produces hydrotreated (HDT) residue by bringing about a chemical reaction, and it is a high-­risk chemical process under the operation conditions of 643–703 K and 160–170 kgf/cm2 [17] The general RHDS process within an oil refinery is described in Figure 1 For the simulation scenario, the analytical data on jet fire accidents from process plants © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung (A) (B) Figure 1 Illustration of the simulated process and leak point: (A) isometric view, (B) for top view has been evaluated [4] As the most frequent accident type, 13 jet fire accidents has been found at a pipework, with the major cause observed as a “leaking coupling or flange” due to a mechanical problem Therefore, the potential hazard of a hydrogen pipe has been confirmed and selected for the scenario The leak point is a welded area of the reducer of a pipe used to transfer hydrogen, and the inner pressure and temperature of the pipe are 161.8 barg and 333 K, respectively The size of the leak hole at the welded area of the reducer is 0.00157 m2, and the leakage rate is 15.0 kg/sec Using the aforementioned leak conditions, the proposed form of the leak point, leakage direction, and wind condition are illustrated in Figures 2 and The leakage direction is in the Z-­direction from the lower area of the reducer (Fig. 2) The inputs for scenario simulation are shown in Table 1 The grid is the most influential factor on the outcome of simulation Since the effect of damage by a jet fire is generally smaller than accidents caused by explosion or toxic release, the grid density of the domain where flame propagation is expected will be high KFX creates this grid using a grid generator, and based on vertical and horizontal sizes of domain to be calculated, it decides on the number of grids independently [22] In this study, the grid dimensions applied for the jet fire analysis were 148, 163, and 52 m on the X-­axis, ­Y-­axis, and Z-­axis, respectively Following this, to compute Figure 2 Specific position of (A) the hydrogen leak point and (B) the features of the reducer Figure 3 Boundary conditions applied in the simulation the outcome of jet fire within this domain, the grid was created Figure 4 indicates the grids in the X-­axis, Y-­axis, and Z-­axis created for the simulation, and the dense grid was generated in the fire zone domain around the leak position Using this step with the KFX grid generator, 514,371 grids were created © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd 409 CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung Table 1 Grid form generated within the simulation domain of residue-­hydro-­desulfurization Area (m2) Discharge rate (kg/sec) Duration (sec) Wind Pasquill category Temperature (K) 0.00157 15.0 60 Velocity Direction 2.03 m/sec Angle U V 79° −0.3835 −1.97 F 294.8 Figure 4 Grid form generated within the simulation domain of residue-­ hydro-­desulfurization Grid sensitivity analyses have been carried out to ensure grid independence in this work and other researches using KFX [23] The boundary condition is also one of the important factors in the simulation [22] In this study, various values were entered to set the boundary conditions as follows: The wind direction was 79°, the atmospheric stability was assumed to be very stable, (F), the wind speed was 2.03 m/ sec at a height of 10 m (Fig. 3), and the atmospheric temperature was 294.8 K Figure 5 shows grids on each X, Y, Z-­axis created by KFX grid generator White lines in the figure represents locked grid line at the leak position and black lines unlocked grid lines Smooth and stretch was performed to the direction of domain boundary For jet release case, the smallest control volume is generated at the leak point, and gradually increased toward the boundaries In the simulation process, the equations of continuity, momentum, k  -­  ε, components and energy equations are solved by SIMPLE algorithm temperature, and radiant heat As the outcome of the simulation, this study presents the flame propagation step, governing domain, and temperature and radiation heat due to the jet fire Jet Flame Simulation Results The outcomes required to estimate the damage or cause of a fire accident may be categorized as flame, 410 Figure 5 Grid X, Y, Z-­axis created by the Kameleon FireEX grid generator for simulation As one of the results of the jet fire simulation involving the immediate ignition of leaked high-­pressure hydrogen, the flame propagation step is shown in Figure 6 This © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung Figure 6 Propagation of the jet fire reflected from the ground in the process plant figure indicates the rapid expansion of flame; there was a rapid volumetric expansion within 3 sec, and from to 9 sec, the propagated flame showed irregular volumetric expansion Furthermore, after 9 sec, the average volumetric expansion of flame reached the equilibrium Although there was a slight difference due to wind, after about 9 sec, most of the jet fire maintained similar form of flame and volume The proposed flame domain of the jet fire is illustrated in Figure 7 Based on the propagation direction of the flame, each flame showed a different form The maximum height (+Z) of flame among them was 22 m in Figure 7B, of which complex geometries are intentionally removed to clearly show the height only for the purpose of display The maximum size on the X-­ axis was 47 m, and the maximum size on the Y-­axis was 30 m (Fig. 7C) When a jet fire occurs due © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd 411 CFD for Large-scale Hydrogen Jet fire (A) C B Jang & S Jung (B) (C) Figure 7 Footprint and three-­dimensional features of propagation of the jet fire in the process plant to leakage of high-­ pressure hydrogen, this flame may have an extreme thermal effect on facilities and devices around the leak point, thereby causing secondary accidents This may lead to escalation into a large-­ scale accident Temperature The temperature distribution of the jet fire computed through the simulation was categorized by height and is shown in Figure 8 Here, the height of the region of interest was set from to 5 m in the +Z direction, and this height was again segmented by 1 m The result in Figure 8 indicates that the region around the leak point had the highest temperature The maxima of temperature at each height were 2191.16 K at 1 m, 2197.41 K at 2 m, 2143.47 K at 3 m, 2087.21 K at 4 m, and 2028.62 K at 5 m, revealing that all maxima of temperature exceeded 2000 K The area of temperature distribution at 1 m high was the widest, showing that the facilities and devices in this region are most affected by heat In addition, centered on the melting temperature of iron, 1811 K, the temperature distribution form and size were minutely segmented, as shown in Figures 9 and 10 These two figures indicate that the domain under temperature distribution within the melting point range of iron was fairly wide; the maximum height range was from 4.8 to 10 m in the +Z direction (Fig. 10B), the maximum width range from the leak point was 17 m in the ±Y direction (Fig. 10A), and the maximum length range was 18 m in the ±X direction (Fig. 10A) 412 Radiant Flux To evaluate the value of radiant heat and the jet fire’s effect on it, in the simulation domain, the points of interest – monitoring points (MPs) – were set as shown in Table 2 Each MP was set based on the leak point (coordinates: X:56.6, Y:73.6, Z:2.8), human height, and the positional density of process facilities and devices Each MP was set at 2 m high and 4 m high with a certain displacement in the X-­axis and Y-­axis direction The detailed coordinates and values of MPs are in Table 2 Table 2 shows that there are three MPs at 2 m high, with a distance from MP to MP 10 at 21.7 m There are four MPs at 4 m above from the leak point, and the distance between MP 14 and MP 16 is 18 m For the outcome of the simulation, the radiant heat at each MP was evaluated When the radiant heat reaches 15.8 kW/m2, an operator within a structure may not function, and this heat may be delivered to other devices and under a radiant heat of 19.9 kW/m2, humans may feel pain within 2 sec and under a radiant heat of 37.5 kW/m2, facilities and devices can be damaged [24, 25] The aforementioned standard of damage was compared with the outcome of this damage, and all MPs in this simulation had radiant heat values over 100 kW/m2 (Fig. 11) This value has the worst effect on humans, facilities, and devices, and facilities and devices in this domain may receive severe secondary damage, possibly leading to a critical accident © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung (A) 1m height (B) m height (C) m height Figure 9 Volume of distribution of 1811  K as a result of jet fire simulation: (A) isometric view, (B) top view Figure 8 Temperature distribution (top view) at each height of 1, 3, 5 m from the ground around the leak point Comparison with the Phast Results As the Process Hazard Analysis Software Tool (Phast) by DNVGL is widely used for jet fire and flare simulations in the chemical and petrochemical industry, version 7.11 was used for comparison of its heat radiation results with those of KFX for the same scenario The program uses a model based on Chamberlain and Johnson’s model for heat radiation calculation from a jet fire It is important to validate simulated results with experiments, but experimental results are usually difficult to obtain; thus, we chose the newest Phast version because the program has been extensively validated with real flare and jet fire experiments, such as Chamberlain, Johnson, Bennett, and Thornton field tests [23] The software was also compared with a H2 jet fire experiment with modification [26] For Phast, input values are as following: • 900 kg H2 inventory with 60-sec fixed duration release (to match the 15.0 kg/sec discharge rate); • 2.03 m/sec wind speed with F air stability; and • 400  kW/m2 maximum surface emissive power (default) From the calculation, some important values were reported as follows: • Jet velocity: 1272.5 m/sec; • Fraction of heat radiated: 0.14; and • Surface emissive power: 344 kw/m2 For comparison, varying heat radiation results from KFX were averaged for 1 min Phast gives a definitive result for each MP because Phast does not assume effects from surrounding equipment or flame propagation; rather, it uses a definitive cone shape for its jet fire Phast cannot handle obstacles, heat reflection from surrounding © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd 413 CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung Figure 10 Volume size of distribution of 1811 K: (A) size through the top view and (B) size through the side view on the Y-­axis Table 2 Monitor point (MP) and coordinate within the simulation domain Coordinate Type X-­axis (m) Y-­axis (m) Z-­axis (m) Leak position MP MP MP MP 10 MP 14 MP MP MP 16 56.6 48.3 56.4 70 56 62.3 67.7 73.4 73.6 72 72 72 72 72 72 72 2.8 2 4 4 geometry, and so on The heat radiation results are shown in Figure 12 The results of the comparison are shown in Table 3 and exhibit good agreements within ±50% except for MP 14 The reason for the difference in the MP 14 results is the hindrance effect because MP 14 is located right behind a structure, and therefore receives less heat radiation This shows that the KFX CFD code can give better predictions in case of a complex geometry where accurate predictions are needed 414 Conclusions The aim of this study was to apply the CFD modeling on a hydrogen jet fire during the RHDS process in an oil refinery, where a large amount of high-­pressure hydrogen is consumed, to compute the flame, temperature, and radiant heat As a result of simulation, the volume of the hydrogen jet fire expanded rapidly from ignition to 3 sec, expanded irregularly from to 9 sec, and fell under the equilibrium state after 9 sec to maintain a steady form of the flame Thereafter, the maximum height of the flame was 22 m (+Z), the maximum width was 30 m (±Y), and the maximum length was 47 m (±X) To evaluate the temperature distribution by flame in more detail, the height under the influence of flame was segmented by 1 m from to 5 m in the +Z direction As a result, the area of temperature distribution at the domain from the ground to 1 m high was the widest The domino effect related to the temperature of flame was also evaluated by analyzing the domain of 1811 T – the melting point of iron To analyze the maximum range of this domain, the maximum height range of 10 m (+Z), the maximum width range of 17 m (±Y), and the maximum length range of 18 m (±X) were evaluated For evaluation of radiant heat, the regions affected by the flame at 2 m © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd C B Jang & S Jung CFD for Large-scale Hydrogen Jet fire Figure 11 Monitoring points (MPs) to show the effect of radiant heat: (A) MP location 2 m above the ground, (B) 4 m above the ground Figure 12 Intensity radii for jet Fire by Phast for the monitoring points (2, 4 m height) From inside – Red: 200 kW/m2; Green: 100 kW/m2; Blue: 200 kW/m2 © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd 415 CFD for Large-scale Hydrogen Jet fire C B Jang & S Jung Table 3 Heat radiation results from Kameleon FireEX (KFX) and Phast MP Origin MP MP MP MP MP 10 MP 14 MP 16 Coordinates for Phast (moved) Heat radiation (kW/m2) X-­axis (m) Y-­axis (m) Z-­axis (m) KFX (averaged) Phast −0.2 −8.3 5.7 11.1 13.4 −0.6 16.8 −1.6 −1.6 −1.6 −1.6 −1.6 −1.6 −1.6 2.8 2 4 4 N.A 158 240 162 206 261 132 171 N.A 223 344 208 157 116 334 99 kI conductivity P production of turbulent kinetic energy [W/m3] p absolution pressure[pa] Qgs heat transport from solid to gas phase QRad,f net radiative transfer to the gas phase Rι chemical source term Rliq rate of liquid to gas phase transition Rt turbulent Reynolds number Sliq net heat transfer from the liquid phase Yι species mass fraction Vιj molecular diffusion velocity of species ι in the direction j Greek letters high and 4 m high were selected, and seven MPs were set as the points of interest The results indicated that the radiant heat at all MPs exceeded 100 kW/m2 By comparing the outcome of radiant heat with the standard damage level, the outcome of the study indicated that the radiant heat effect has critical consequences for humans, facilities, and devices A comparison of the results with those of Phast 7.11 was presented to show that the present approach exhibited good agreement with the tool Furthermore, the approach can be superior in regions where obstacles play an important role Finally, the risk analysis methodology for jet fire using CFD in this study provided a preliminary virtual analysis of the consequences of a high-­risk fire accident extracted through the qualitative risk assessment of a process plant with a great deal of hazardous material under high pressure and high temperature Thus, it may be applied to generate contingency plans or prepare safety measures Furthermore, it fundamentally reflects the outcome of accidents in the design stage of processing, allowing for the efficient application of passive fire protection (PFP) to prevent and minimize secondary accidents that may occur during firefighting Nomenclature B buoyancy C1, C2 constant in k-ε model CD discharge coefficient eT total internal energy [J/kg] Fliq exchange of momentum between liquid and gas phase f1,  f2 functions in low Reynolds number model fi mass forces which the gas is influenced fu low-Reynolds number correction factor g gravitational acceleration [m/sec2] k turbulent kinetic energy [J/kg] 416 δ Kronecker delta ε dissipation of the turbulent kinetic energy [W/ m3] κ second viscosity coefficient μeff effective diffusion coefficient μt turbulence diffusion coefficient ρ gas density [kg/m3] τij tensor [N/m2] Subscripts eff effective i, j index ι species liq liquid phase Superscripts — ″ ~ mean, time-averaged quantities fluctuation, Favre-averaged quantities mean, Favre-averaged quantities References  1 Hord, J 1978 Is hydrogen a safe fuel? Int J Hydrogen Energy 3:157–176  2 Lim, H 2014 The direction and prospect of hydrogen fuel cells industry Korea Gasnewspaper Co Ltd Available at: http://www.gasnews.com/news/articleView html?idxno=67327  3 Alileche, N., V Cozzani, G Reniers, and L Estel 2015 Thresholds for domino effects and safety distances in the process industry: a review of approaches and regulations Reliab Eng Syst Saf 143:74–84  4 Gomez-Mares, M., L Zarate, and J Casal 2008 Jet fires and the domino effect Fire Saf J 43:583–588  5 Salzano, E., and V Cozzani 2005 The analysis of domino accidents triggered by vapor cloud explosions Reliab Eng Syst Saf 90:271–284 © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd C B Jang & S Jung  6 Darbra, R., A Palacios, and J Casal 2010 Domino effect in chemical accidents: main features and accident sequences J Hazard Mater 183:565–573  7 Kikukawa, S., H Mitsuhashi, and A Miyake 2009 Risk assessment for liquid hydrogen fueling stations Int J Hydrogen Energy 34:1135–1141  8 Zhiyong, L., P Xiangmin, and M Jianxin 2010 Harm effect distances evaluation of severe accidents for gaseous hydrogen refueling station Int J Hydrogen Energy 35:1515–1521  9 Brennan, S., D Makarov, and V Molkov 2009 LES of high pressure hydrogen jet fire J Loss Prev Process Ind 22:353–359 10 Deimling, L., V Weiser, A Blanc, N Eisenreich, G Billeb, and A Kessler 2011 Visualisation of jet fires from hydrogen release Int J Hydrogen Energy 36:2360–2366 11 Vembe, B., K Rian, J Holen, N Lilleheie, B Grimsmo, and T Myhrvold 2001 Kameleon FireEx 2000 theory manual Computational Industry Technologies AS, Trondheim, Norway 12 Evanger, T., and T Holmås 2005 Kameleon FireEx – an Advanced Computational System for Calculation of Fire Structure Interaction Fabig Technical Newsletter 13 Magnussen, B., T Evanger, B Vembe, N Lilleheie, B. Grimsmo, B Velde et al 2010 SPE International Conference on Health, Safety, and the Environment in Oil and Gas Exploration and Production Norway 14 Byggstöyl, S., N Lilleheie, and B Magnussen 1987 Strategy for Inclusion of Chemical Kinetics into the Eddy Dissipation Concept in IX Task Leaders MeetingEnergy Conservation in Combustion, IEA 15 Vembe, B., N Lilleheie, J Holen, B Magnussen, B Velde, G Linke et al 1998 International Gas Research Conference 1998, Pp 429–437 CFD for Large-scale Hydrogen Jet fire 16 Antonioni, G., G Spadoni, and V Cozzani 2009 Application of domino effect quantitative risk assessment to an extended industrial area J Loss Prev Process Ind 22:614–624 17 Korea Occupational Safety and Health Agency 2008 Manual for Petrochemical unit screening technique Korea 18 Mingguang, Z., and J Juncheng 2008 An improved probit method for assessment of domino effect to chemical process equipment caused by overpressure J. Hazard Mater 158:280–286 19 American Institute of Chemical Engineers Center for Chemical Process Safety 2000 Guidelines for chemical process quantitative risk analysis New York, U.S 20 Glassman, I 1996 Combustion Academic Press, San Diego, CA 21 Shah, N G 1979 Jet Fire Computational Fluid Dynamic Simulations: Validation from an Industrial & Consultancy Perspective These Imperial College London (University of London) 22 Computational Industry Technologies 2014 KFXTM furcifer user manual Computational Industry Technologies, Norway 23 Malkeson, S P., T Jones, and R English 2015 The computation of radiation heat transfer 25th International Colloquium on the Dynamics of Explosions and Reactive Systems, Leeds, UK, 2015 24 American Petroleum Institute Division of Refining 1982 Guide for pressure-relieving and depressuring systems Washington, D.C USA 25 Kayes, P., and B Mundial 1985 Manual of industrial hazard assessment techniques Technica 26 Lutostansky, E., L Creitz, S Jung, J Schork, D Worthington, and Y Xu 2013 Modeling of underground hydrogen pipelines Process Saf Prog 32:212–216 © 2016 The Authors Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd 417 ... calculated by integration of radiation absorption and emittance along a huge number of rays (lines) throughout the calculation domain From the boundary of a box inside the calculation domain, rays are... Footprint and three-­dimensional features of propagation of the jet fire in the process plant to leakage of high- ­ pressure hydrogen, this flame may have an extreme thermal effect on facilities and... analysis of the consequences of a high- ­risk fire accident extracted through the qualitative risk assessment of a process plant with a great deal of hazardous material under high pressure and high