Containment model library of the Apros process simulation software: An overview of development and validation work

The paper focuses on the modeling features of ACON and the related validation work which includes the calculations of nearly 50 experiments performed in various test facilities. The validation methodology is discussed and the validation calculations are summarized as a validation matrix.

Progress in Nuclear Energy 116 (2019) 28–45 Contents lists available at ScienceDirect Progress in Nuclear Energy journal homepage: www.elsevier.com/locate/pnucene Containment model library of the Apros process simulation software: an overview of development and validation work T Ari Sildea,∗, Jukka Ylijokia, Esa Ahtinenb a b VTT Technical Research Centre of Finland Ltd., VTT, P.O.Box 1000, FI-02044, Finland Fortum Nuclear Services Ltd., Fortum Power and Heat Oy, Keilalahdentie 2-4, 02150, Espoo, Fortum HQ Campus Keilalahti, Finland A R T I C LE I N FO A B S T R A C T Keywords: Nuclear safety Nuclear safety analyses Containment modelling Apros Validation Containment thermalhydraulics The Apros CONtainment model library (ACON) is an add-on product of the Apros® (Advanced Process Simulation Environment) Nuclear software cooperatively developed by VTT and Fortum ACON is suitable for comprehensive simulation of containment phenomena during nuclear reactor design basis accidents and, to some extent, severe accidents The lumped parameter approach applied enables flexible modeling of various containment/ compartment systems ACON is a suitable tool for both safety analysis use and accurate training simulator purposes with real time calculation speed The Apros containment model can be used fully separately, or a containment simulation can be coupled with other thermal-hydraulic calculation to create a complete simulation model of a power plant, including e.g the reactor and turbine systems Modeling of relevant engineering safety features is also included The paper focuses on the modeling features of ACON and the related validation work which includes the calculations of nearly 50 experiments performed in various test facilities The validation methodology is discussed and the validation calculations are summarized as a validation matrix The paper provides a detailed presentation of selected validation cases, in which the main studied phenomena are related to general containment thermal-hydraulics, spray effects, blowdown modeling, steam condensation on a structure, steam stratification in containment, and ice melting with associated natural circulation flow Finally, an example of applications is described Severe accident containment phenomena are out of the scope of this paper The results of the validation demonstrate that Apros can be used for analyses of containment thermal-hydraulic behavior including related aspects of engineering safety systems in various containment geometries Introduction The main objective of the paper is to highlight the features and validation process of the nuclear power plant containment modeling of the Apros® Nuclear (Advanced Process Simulation Environment) software developed in cooperation between VTT and Fortum Apros is a commercial simulation software utilized in over 25 countries worldwide (Apros, 2015; Silvennoinen et al., 1989) The Apros platform provides an environment for configuring and running simulation models of industrial processes, such as combustion and nuclear power plants The Apros CONtainment library (ACON) is part of the Apros Nuclear package (Fig 1) The ACON library is developed mainly for analyzing containment phenomena during nuclear reactor accidents, but the applied lumped parameter approach also ensures a flexible modeling of various types of containment/compartment systems outside the nuclear industry ACON ∗ also includes the modeling capabilities for all relevant engineering safety features and accident management hardware One powerful characteristic of Apros is that the containment calculation can be coupled (integrated) with a complete simulation model of a power plant, including e.g the reactor, turbine and automation systems, with their interactions The main period of development of ACON was during the end of the 1990s, but some code modifications and enhancements were also made later Basic verification of the ACON models was performed mainly by the code developers and involved different kinds of testing and code reviews The main validation process of ACON started in the early 2000s Nearly 50 calculation cases concerning various experiments including the separate effect, coupled effect and integral tests have been calculated so far (Silde, 2015) In addition, the validation and testing include several code-to-code comparison exercises/benchmarks Corresponding author E-mail address: ari.silde@vtt.fi (A Silde) https://doi.org/10.1016/j.pnucene.2019.03.031 Received November 2018; Received in revised form 26 February 2019; Accepted 17 March 2019 Available online 06 April 2019 0149-1970/ © 2019 The Authors Published by Elsevier Ltd This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/) Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig Main features of the Apros simulation environment A = flow area [m2] ρ = density of the mixture [kg/m3] w = velocity of the mixture [m/s] p = node pressure [Pa] h = specific enthalpy of the mixture [J/kg] t = time [s] z = coordinate value [m] Si, Sj, Sk = source term of mass, momentum and energy, respectively Overview of modeling features 2.1 General The Apros containment code uses a so-called lumped parameter approach The compartments/rooms of the simulated containment can be divided into an arbitrary number of homogeneous control volumes (nodes) connected by flow paths (branches) for steam-gas mixture and liquid water A containment node consists of three separate phases: gas, mist droplets and liquid water pool The mist droplets may be formed due to volumetric condensation (fog), or from the liquid share due to the flashing process of blowdown water Liquid droplets may also be introduced by a boundary condition sources The mist droplets are always in a thermalequilibrium with the gas phase, whereas the water pool may be in a thermal non-equilibrium state in which the pool mass and enthalpy (temperature) are solved to determine the pool properties The right-side terms of Eqs (1)–(3) describe the sources of mass, momentum and energy In the mass equation, the source terms include the additional mass flows into/from the system The source term of the momentum equation contains all pressure losses across the flow paths The enthalpy source term consists of all heat flows and the pressure derivative with respect to time The pressure derivative term appears in the enthalpy source term, because the enthalpy is used instead of the internal energy, i.e 2.2 Governing equations ∂p ∂u ∂h = −v ∂t ∂t ∂t The LP solution principle of ACON is a simplified form from the approach used in the one-dimensional homogenous thermal-hydraulic model of Apros (Hänninen, 1989) One simplification is that ACON does not consider two-phase flow, i.e the gas and liquid phases of the system are solved separately and the interaction between phases takes place only via heat and mass transfer processes through the interface inside nodes The simulated thermal-hydraulic system is described with the differential equations for conservation of mass, momentum and energy Because the gas flow is homogeneous, the equations are applied for the mixture flow, and therefore only three equations are used (for mass) ∂Aρw ∂Aρ = Si + ∂z ∂t (for momentum) (for energy) A∂p ∂Aρw = Sj + ∂z ∂t ∂Aρwh ∂Aρh = Sk + ∂z ∂t (4) where v is the specific volume [m /kg] and u is the specific internal energy [J/kg] Mass flow rate in the junctions between the nodes is calculated from the momentum conservation equations A uniform temperature in each node is solved from the energy balances For pressure solution, also the mass balances are needed The pressure, flows, and enthalpies of the system are solve implicitly Because all the terms, such as material properties of water, steam and non-condensable gases cannot be calculated implicitly, the iteration procedure must be used One simplification of the LP system is that the convection term ∂Aρw 2/ ∂z typical in the conservation equation of momentum of one-dimensional flow models is missing in Eq (2) This simplification means in practice that the momentum of flows is not transferred across the node In the implicit solution algorithm the pressures, flows and enthalpies of the flow system are solved implicitly The commonly used staggered mesh discretization scheme is employed The integration method applied is the implicit Euler Because not all terms can be calculated implicitly, the iteration procedure has been used (Hänninen, 1989) (1) (2) (3) where 29 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al plug inside the pipes Table The most important phenomena modeled in ACON Modeling phenomenon/system Steam/non-condensable gas mixture thermodynamics (water vapor, O2, N2, H2, CO2, He) Water droplets (mist) Intercell flow of gas, liquid sump water, droplets Buoyancy effect in gas flow Heat and mass transfer at different interfaces: gas-structure, gas-ice, gas-sump, gas-droplets Heat transfer at sump-structure interface Thermal radiation heat transfer Heat conduction inside heat structure Condensate film flow on vertical structure Ice condenser Internal and external spray system Water pool (sump): homogenous or thermally stratified Nodes with different shape BWR suppression pool including vent pipes Coupling of containment and other thermalhydraulic calculation Explicit sources and sinks: water vapor, liquid water, non-condensables, dry energy Pump, valve, heat exchanger Hydrogen combustion Hydrogen recombiners Hydrogen igniters Fission products and aerosols General concentration solution for FP's and boron 2.3.3 Heat and mass transfer The containment system includes various types of interfaces, where heat and mass transfer are of importance and should, therefore be modeled Heat transfer between containment and other thermal-hydraulic system such reactor cooling system can also be modeled The principles of calculation for heat and mass transfer phenomena in ACON are similar at all gas–surface interfaces such as on a structure, ice, water pool, or droplets Total heat transfer rate is the sum of convective heat transfer, latent heat flow caused by condensation/evaporation processes and radiative heat transfer The calculation is based on Nusselt's theory using the heat and mass transfer analogy The Nusselt number for both natural and forced convection flow is calculated, and as a default the higher of the two values is used in the heat and mass transfer calculation However, the user is allowed to override the default assumption In the mass transfer modeling, the so-called mass diffusion theory, in which water vapor diffuses through the boundary layer and condenses on the surface, is applied Alternatively, the Uchida correlation is available High vapor condensation rate reduces the thermal and mass layers in size due to the suction effect of the condensation process (Corradini, 1983) The reduction in the boundary layer increases the heat and mass transfer coefficients, which are also taken into account in ACON using so-called Ackermann's approximate correction method (Ryti, 1968) In the case of a gas–liquid interface, such as on water pool and spray droplets, a separate interface temperature and its effect on steam partial pressure is iteratively calculated due to its strong effect on heat and mass transfer processes The principal numerical method used in the iteration of the interface temperature is the Secant method If the trials of the Secant iterations are unsuccessful, subsequent trials are conducted using the Regula-Falsi method At the gas–structure interface, the effect of condensate water film is taken into account as a film resistance, or alternatively, its influence is calculated in more detail using so-called water tracking model, in which the water film is allowed to flow down from one structure to another Heat transfer between a flowing water film and a structure (e.g wall condensate, water film caused by external spray cooling) is calculated using the theory presented by Covelli et al (1982) The heat transfer calculation at the “stagnant” liquid–structure interface (e.g in a sump) is based on Nusselt correlations for laminar and turbulent natural convection in fluid (Ryti, 1968b) Remarks For water elevation calculation Discrete or continuous AECL or Areva types Can be simulated with discrete burning model Available only in Apros SA package FP's available only in Apros SA 2.3 Modeled phenomena The license of the basic ACON package includes the models associated with the general containment thermal-hydraulics, hydrogen behavior and related engineering safety features (Silde and Ylijoki, 2017) (Table 1) Particular severe accident models, such as the behavior of aerosols and fission products, are available only in the Apros SA module, which requires a separate license 2.3.1 Steam/non-condensable gas mixture thermodynamics ACON calculates the thermodynamics of a gas mixture including water vapor and six non-condensable gases (oxygen, nitrogen, hydrogen, helium, carbon monoxide and carbon dioxide) Air is represented by a mixture of oxygen and nitrogen The gas space in each node is perfectly mixed Steam is treated as a real gas and the noncondensable gases comply the ideal gas law 2.3.4 Sump and suppression pool In the default approach, a water sump or a suppression pool consists of a single-phase liquid having a uniform temperature However, a user can activate the so-called pool stratification model, in which the pool is divided into two different vertical layers which have their own mass and energy balances The heat transfer between the water layers takes place only through heat conductance Mass flow between the layers takes place if the mass inventory or density of the lowest layer changes 2.3.2 Intercell flows The flow of gas and liquid water between adjacent nodes is simulated by connecting the nodes with specific flow paths called branches in the Apros terminology The gas flow is driven by the pressure difference and the buoyancy effect The flow loss coefficient may be a constant value including all possible frictional and form loss terms across the flow path, or alternatively, the loss coefficient can be internally calculated from a discharge coefficient according to the theory of isentropic compressible flow In the latter case, also chocked flow is checked Gas flow may also carry fog droplets from one node to another Flow of liquid water between the adjacent sumps is calculated by the Bernoulli mechanical energy balance equation Valve and pump components can be connected to branches in order to drive and control both the gas and liquid water flows The specific model for suppression pool vent pipes calculates the vent clearing processes including e.g the acceleration and movements of a water 2.3.5 Blowdown and other sources The ACON calculates the node thermodynamic conditions during blowdown release with the pressure flash model, which allows the blowdown fluid to flash into steam based on the total node pressure (Fig 2) The mass fraction of flashed steam is xstm = hbld − h′ h′′ − h′ (5) where hbld is the specific enthalpy of fluid which enters the node, and h′′ and h′ are the specific enthalpies of saturated vapor and liquid water in total pressure, respectively An input parameter defines that part of the liquid share, which is transferred directly to droplets (called the droplet fraction and marked as X in Fig 2) The rest of the liquid share goes directly to the sump Because the droplets are assumed to be in thermal 30 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al 2.3.8 Node shape If very exact calculation of water elevation inside a compartment is required, an approach in which the nodes have a constant cross section may not always be satisfactory in all geometries ACON has the capability to define node geometry in three different ways: using a constant cross section, a varied cross section area as a function of node height and a varied node volume as a function of node height With these options, the water elevation in various containment geometries can be solved precisely Validation process 3.1 General Development of ACON started in the early 1990s when the principle models and the “heart” of the solution system were coded During the 2000s, the main work has proceeded by adding the modeling capabilities of engineering safety systems relevant to various containment types and geometries At this time, the preliminary validation process was also initiated Nearly 50 experiments performed in Finnish and international test facilities have been calculated so far In addition, about 10 code-to-code comparison cases have been carried out Most of the validation calculations are performed in the framework of the Finnish National Research Program, SAFIR, funded by the National Nuclear Waste Management Fund (VYR) and VTT Fig Principles of modeling blowdown flashing equilibrium with the node atmosphere, their influence on node pressure and temperature is minor However, if the node atmosphere tends to become superheated, droplets evaporate and drive the humidity towards the balance The default value of the droplet fraction in ACON is 0.2, which means that 20% of the liquid share of blowdown is transferred to droplets The default value is found to be suitable for most typical blowdown situations A user may modify the droplet fraction This is recommended e.g in a case when subcooled water flows “slowly” from systems (which are in equal pressure) to the containment In this case, a droplet fraction of zero (or close to zero) may yield the most reasonable results It is always recommended that a user should check the result's sensitivity to the droplet fraction if there is a source of liquid blowdown 3.2 Methodology Verification of ACON ensures that the program is coded properly and that it produces the intended results The code developers mainly perform the basic verification and preliminary code testing involving the test calculations and code reviews The aim of the validation calculations is to ensure and demonstrate that ACON has an appropriate capability to simulate the containment thermal-hydraulic phenomena and related effects of engineering safety systems and accident management hardware during accidents/incidents The ACON validation methodology contains two steps (Silde, 2015) Firstly, the selected experiments conducted in test facilities are calculated in order to validate the code itself Secondly, the validity of changes made between the different code versions is checked by calculating always a certain set of experiments/transients with the new code version, and by comparing the results to those obtained by the earlier versions The comparison demonstrates how the new modifications affect the code results and ensures that the changes made between the versions are valid and not include any errors or other undesirable features The both steps of the validation process include the calculations against the experimental data and the comparison calculations (benchmarks) against the results of well-validated other codes The ideal aim of the validation would be that all validation cases are calculated with all code versions Unfortunately, this is not possible due to limited resources and time Therefore, only the validation cases assumed to be the most representative are calculated in the version validation process Some of the validation calculations are carried out as blind-calculations, i.e without knowing the experimental measurements beforehand, but the most calculations are carried out as openexercises Both the code developers and pure code users have participated in the validation process in two different organizations, at VTT and Fortum, in order to ensure that the validation calculations are performed independently and objectively One important aim of the validation process has been to provide essential exercise and experience to young code users, needed in applying the code to real plant applications The choice of suitable values for some critical input parameters may have a remarkable influence on the simulation results The input values used in ACON validation calculations are mostly based on the best-estimate approach If the best-estimate values are not known, the default 2.3.6 Spray systems Modeling of both internal and external spray systems is included Operation of an internal spray system is simulated with the complete mixing droplet model The droplet temperature is assumed to be otherwise uniform, except that the temperature of an infinitely thin surface interface is solved iteratively due to its strong influence on heat and mass transfer Change of droplet size, temperature, material properties, vertical and horizontal velocities and their effects on heat and mass flow are updated during the fall Five different classes with different droplet sizes can be included As default, all spray water is injected to the atmosphere, but a user-specified part of the spray water may be injected directly onto structure surfaces Three different internal spray models with different accuracy levels are available The external spray modeling covers a one-dimensional calculation of energy balance of external water film on the dome outside the structure, where the temperature, thickness, velocity and heat transfer coefficient of the water film are determined as a function of angular position of the semi-hemispherical dome structure (Covelli et al., 1982) The evaporation of water film is also considered 2.3.7 Ice condenser The ice condenser (IC) modeling is based on the Westinghouse-type system/design Ice is located in vertical cylindrical columns having a user-specified diameter and height Ice is assumed to be at a uniform temperature, i.e heat conduction inside the ice is not considered Both axial and radial ice melting are modeled Different types of ice condenser doors are included The positive pressure difference across the lower inlet, intermediate and top deck doors of IC pushes them open The spring forces, gravity and inertia effect are also taken into account in calculating the door movements 31 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Table (continued) Table Validation matrix of the Apros containment code Experiment/benchmark Experiment/benchmark PANDA test ST4.1 CONAN experiment EREC test no GEKO test series GEKO-E and GEKO-F IRSN CARAIDAS spray test Marviken BWR experiment MXII (no 18) MISTRA containment spray experiments MASP-1 and MASP-2 MISTRA tests HM 2-1 and HM 32 MISTRA ISP-47 NUPEC experiment M-7-1 (ISP35) PAR test calculation against the AREVA data PAR test calculation against the AECL data PPOOLEX test PCC-6 POOLEX tests STB-20 and STB21, PPOOLEX tests STR-9 and STR-11 PPOOLEX test WLL-5-2 THAI experiment HM-2 THAI experiment TH24 PACOS Px1.2 test Studied phenomena Studied phenomena - Steam condensation rate on a duct wall - Local heat fluxes to a duct wall - Forced convection heat and mass transfer - Pressure in bubbler condenser containment - Air mass concentration in SG box - Gas temperatures in SG box, BC shaft, BC air volume and air trap - Water temperature in the water tray - MELCOR comparison - Total heat flow to the condenser PANDA test T1.1 - Droplet diameter as a function of falling height (condensation/evaporation on droplets) - Drywell and wetwell pressures - Gas temperature of drywell and wetwell - Water pool temperature in wetwell - Air and steam mass flow from - drywell into wetwell - Pressure - Gas temperatures - Steam concentrations - Steam condensation - Gas temperature - Helium concentrations (stratification) - Effect of PARs on stratification - Steam condensation on the walls - Pressure - Steam and helium concentration profile (stratification) - Gas temperature profile (stratification) - Pressure - Gas temperature - Helium concentration in dome - Spray effects - Efficiency of AREVA type recombiners - Hydrogen concentration Gas temperature Recombination rate of PARs Condensate flow rate in PCCS Flow rate through the NCG line Drywell and wetwell pressure Water temperature in the PCC pool Water temperature in wetwell pool Steam mass fraction in PCCS PCC pipe temperatures Pool temperatures (stratification) - Steam condensation on a wall Pressure Gas temperatures Wall temperature Pressure Gas temperatures Hydrogen concentrations (stratification) Pressure Gas temperatures Steam concentrations (stratification) Dissolution of concentration Gas velocities Dome pressure Gas temperatures Inner wall temperatures Flow velocities Spray effects - - - PANDA ISP-42 - PPOOLEX test STR-4 COCOSYS benchmark - COCOSYS benchmark - COPTA BWR benchmark - TOSQAN sump test T201 TOSQAN spray test 101 VICTORIA no 13 VICTORIA no 29 VICTORIA no 42 VICTORIA no 50 HAMBO, GSIM benchmark Pressure Total cooling rate in cooler Total cooling power of the cooler Gas temperatures Steam and helium concentration profiles in vessel (stratification) Steam and helium concentrations in the cooler Condensate mass in the cooler Cooling water outlet temperature in the cooler tubes Flow rate in PCCs feed line Total PCC condensate flow rate in the drain lines PCCS drum temperatures Drywell and wetwell pressures Drywell and wetwell gas temperatures Wetwell pool temperature Steam and helium concentrations in the drywells and wetwells Drywell pressure Water mass in the wetwell Helium concentration in the drywell Pressure difference between the drywell and wetwell Liquid mass in the RPV Gas temperature distribution in the drywells and wetwells Wall temperature in drywell Water temperatures (stratification) in the wetwells Drywell and wetwell pressure Drywell and wetwell gas temperature Suppression pool layer temperatures Sump evaporation rate Pressure Gas temperature Pool temperature Pressure Gas temperature Droplet size Droplet falling velocity Pressure Gas temperatures Natural circulation flow Ice melting Pressure Gas temperatures Natural circulation flow Pressure Gas temperatures Natural circulation flow (Ice melting) Pressure Gas temperatures Natural circulation flow Function (movements) of ice condenser doors Licensing calculations for Loviisa IC containment (LLOCA, SLB sequences) Pressure Gas temperature Suppression pool temperature Pressure Gas temperature Suppression pool temperature (continued on next page) 32 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al 3.5 Examples of validation cases Table (continued) Experiment/benchmark SARNET Generic Containment benchmark Studied phenomena - SUPLES benchmark - This section presents the results of selected validation cases including calculations for tests performed in the simple one-room test facilities and in the multi-room geometries representative of BWR Mark II, PWR large dry and PWR ice condenser containments The main studied phenomena of the described cases are related to general containment thermal-hydraulics, spray effects, blowdown modeling, steam condensation on a structure, steam stratification in containment, and ice melting with associated natural circulation flow Pressure Gas temperatures Relative humidity Hydrogen concentrations Pool water temperature Mass and heat transfer rate at pool surface Pool surface temperature Effect of radiation heat transfer Effect of heat structure nodalisation Gas flow pattern Hydrogen recombination rate in PARS Mass of steam and non-condensable gases Mass of fog droplets Effects of fog droplets on pressurisation Mass transfer to fog droplets due to bulk condensation Wall heat transfer contributions (convection, radiation, condensation) Heat transfer coefficient at wall and pool surfaces Wall temperature Pressure Gas temperature Blowdown modeling 3.5.1 Single-droplet spray tests at the IRSN CARAIDAS facility An example of separate effect tests are the single-droplet spray tests conducted at the IRSN CARAIDAS facility (Malet and Vendel, 2009; Malet et al., 2011) The tests address the condensation and evaporation processes on mono-sized spray drops in a simple geometry Hence, the tests were focused on studying the droplet characteristics, not general thermahydraulic behavior The main aim of the Apros calculation was to ensure that the mass transfer (condensation/evaporation) modeling of the spray module is valid 3.5.1.1 Test arrangements The height and inner diameter of the cylindrical facility are m and 0.6 m, respectively The atmospheric pressure, temperature and relative humidity, and also initial drop size have been varied test by test: … 5.4 bar, 20 … 141.6 °C, 3.0 … 87%, 295 … 673 μm, respectively Mono-sized spray droplets are injected into the top of the facility The test series consist of the evaporation and condensation tests In the evaporation tests, droplets are injected into an atmosphere where the humidity is relatively low (20% or less), and droplets evaporate continuously as they fall In the condensation tests, cold droplets are injected into an atmosphere of high humidity Steam condenses on drops in the early stage of drop fall, and the drop size increases, whereas in the later stage during the fall the drops start evaporating and the droplet size decreases There are optical measurements of drop size at three different elevations downwards from the drop generator, i.e the net condensation/evaporation mass of droplets can be estimated Steady-state thermodynamic conditions and very good homogeneity along the height of the vessel were reached during the tests values are used as often as possible If the input deck used yields undesirable calculation results, sensitivity runs are carried out in order to determine the main reasons for the deviations 3.3 Validation matrix The validation matrix of ACON is based on the Containment Code Validation Matrix (CCVM) presented by the OECD/NEA/CSNI task group (CSNI, 2014) CCVM describes a basic set of available experiments and related phenomena suitable for code validation ACON's validation matrix consists of the containment experiments categorized as separate effect, integral, or combined effect tests according to CSNI (2014) Certain separate phenomena are studied in the first type of tests In the integral tests, the main aim is to investigate the integral behavior of the system In the combined tests, the intention is to study both separate effects and the integral behavior In containment tests, the gap between the “separate effect” and “integral” is not always so straightforward (CSNI, 2014) Only those phenomena ranked “major” (the most important) in CCVM are included in the ACON validation matrix Table summarizes the validation matrix of ACON describing the experiment under consideration, the code version used for the validation case and the main features/phenomena studied Also selected benchmark calculation cases, in which the ACON results are compared to those of some other codes are shown 3.5.1.2 Calculation model and assumptions Because the atmosphere in the tests was well mixed, use of one-node nodalization is justified A high vapor condensation rate reduces thermal and mass transfer boundary layers in size and the heat and mass transfer coefficients increase due to the suction effect of the condensation process (Corradini, 1983) By contrast, high evaporation rate decreases the coefficients These effects are considered in ACON by using the Ackermann's approximate method to correct the heat and mass transfer coefficients (Ryti, 1968) One aim of the calculations was also to check the validity of the correction method 3.5.1.3 Calculation results Comparison of calculation results to measured drop size in two evaporation tests, in which the evaporation rate was relatively low or high, is shown in Fig The X-axis of the Figure illustrates the distance from the nozzle Fig shows calculations with and without Ackermann's correction The results indicate that when the vaporization rate was low, the droplet size was slightly overestimated and the evaporation rate was underestimated, particularly in the lower part of the facility (Z = 4.39 m) (Silde, 2011) In the high-evaporation cases (such as EVAP18), Apros predicted the droplet size extremely well at all elevations of measurements Furthermore, the disappearing of highly evaporated drops could be modeled satisfactorily If the evaporation rate was high, the best agreement was achieved when using Ackermann's correction, whereas in the low-evaporation cases the correction had only a minor influence on the simulation results 3.4 Documentation Extensive documentation is an important part of the validation procedure The ACON model features, initial condition, relevant input values used and the results of all validation calculations are documented in the research/project reports of VTT and Fortum The ACON user's guide provides the instructions and hints needed in constructing the input of the simulation model The code reference manual describes the phenomenological (physical and chemical) models and related equations implemented in ACON code (Silde and Ylijoki, 2017) A successful code validation requires that the choice of physical model options, default input values and used correlations including their validity ranges, are also justified and documented (Silde, 2004) 33 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig Droplet diameter in the low evaporation test EVAP13 (left) and in the high evaporation test EVAP18 (right) 3.5.2 Liquid blowdown experiment MX-II (no 18) at Marviken facility The main aim of the validation task was to simulate overall thermalhydraulic behavior in a large-scale containment geometry during blowdown in large break LOCA In condensation tests, a drop size increase due to condensation occurred within a fall distance of about 0.5 m, after which the drops started evaporating and the drop size decreased Fig shows the calculation results in two condensation tests with a low and a high condensation rate The general trend was that Apros predicted the drop size very well at a short distance Z = 2.51 m from the spray generator In the lower position, the drop size was slightly overpredicted, because the drop evaporation rate was underpredicted However, the simulation results were mostly within the error bar of the measurements In the condensation tests, Ackermann's corrections had no noticeable influence on the simulation results, because the mass transfer rate was relatively small compared to that of the evaporation tests Simulation results of the pure condensation phase could not be compared extensively to the test data, since only one drop size measurement was made in the part of the vessel where the condensation occurred In order to assess droplet behavior near the injection location with the best possible accuracy, the use of a small system time step (of the order of 0.1 s or less) was recommended The results also leaded to the recommendation that the Ackermann's correction should be always used in ACON simulations for spray cases The overall conclusions of the calculations of spray tests at the Caraidas facility and the large dry NUPEC test facility (Ylijoki et al., 2018; Harti, 2005) were that ACON is able to model the basic physics of spray droplet heat and mass transfer phenomena reasonably well, and that the model is suitable for simulation of containment spray systems in real plant applications 3.5.2.1 Test arrangements The Marviken full-scale BWR test facility includes a reactor pressure vessel, a discharge pipe to the containment, drywell rooms of the containment building, a wetwell with the suppression pool and vent pipes leading the gas into the wetwell water pool (Fig 5) When the pressure in the drywell increases as a consequence of the primary coolant discharge, the steam-gas mixture flows from room 104 via four down flow channels to the vent pipe header (106) and finally via vent pipes to the wetwell pool The total volume of the drywell is 1978 m3, the volume of the wetwell pool is 561 m3 and the volume of the wetwell atmosphere is 1583 m3 3.5.2.2 Calculation model and assumptions The Marviken containment building consists of several partly separated compartments, thus forming a complex system of air-steam mixture flow paths Therefore, the drywell in the simulation model is divided into five separate volume nodes (Fig 6): DRY1, DRY2, DRR, DRY111 and DEAD The area of the 28 open vent pipes is 1.98 m2 The walls and other massive solid structures of the containment have been modeled with heat structures (Hänninen, 2003) Pressure and liquid temperature in the pressure vessel were 46.6 bar and 237–259 °C, respectively The diameter of the discharge pipe was 280 mm and the duration of the blowdown was 170 s Total initial Fig Droplet diameter in the low condensation test COND1 (left) and in the high condensation test COND10 (right) 34 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig Simulation nodalization of the Marviken containment (Hänninen, 2003) how fast the drywell air flowed into the wetwell On the other hand, the air flow rate was dependent on the modeling accuracy of the drywell Regarding the air flow, it was particularly important how the gas flows to/from the dead-end room 124 (denoted as DEAD in Fig 6) were arranged The wetwell pressure was slightly overestimated in the calculation As long as the discharge was active, the calculated pressure difference between the drywell and the wetwell was slightly too low By increasing the pressure loss coefficient in the vent pipes, the pressure difference became larger but then the drywell pressure became too high The reason for the too low pressure difference may be the relatively simple modeling of the vent flow into the pool The complex 3-D phenomena and consequent losses at the vent pipe outlet were not taken into account in the LP containment modeling All steam flowing through the vent pipes is assumed to condense in the pool The air flow from the pool into the wetwell gas space has some steam content (humidity) corresponding to the saturation state at pool temperature As in the case of pressures, the temperatures represent those in the volume DRY1 and in the room 111 The calculated drywell temperature was after the first 10 s very close to the measured data (Fig 8) The calculated wetwell gas temperature increased much faster than the measured temperatures, but later on remained below the measured data The too fast temperature increase in the wetwell at the beginning indicates the problem of the lumped parameter model The use of the averaged quantities in the control volumes causes the too-fast spreading of the hot air-steam mixtures By using a denser nodalization, the results could be improved slightly, but the basic problem remains As a parametric study, the transient was modeled so that the vent pipe header was separated from the volume DRY3 to its own control volume In this case, the temperature of the header increased somewhat more slowly than in volume DRY1, but it had no effect on the overall containment behavior The temperature in the wetwell still behaved as in Fig The calculated pool temperature remained on a clearly higher level than the measured value throughout the experiment, which implies that the calculated energy flow through the vent pipes to the pool, particularly in the beginning of the transient, must be higher than in an actual situation The reason for the overpredicted flow rates is assumed to be the too-fast mixing tendency of the containment model numerical solution The LP approach used assumes full mixing properties in every calculation volume The steam released in the blowdown spreads throughout the drywell and through vent pipes into the wetwell much too fast The spreading of steam can be restricted somewhat with denser nodalization, but the basic problem of the numerical solution remains The conclusion of the validation calculation was that the complexity of Marviken containment makes the simulation of air and steam flow rather difficult using the LP approach Accumulation and purging of air Fig Outline of the Marviken containment (Marviken, 1977) amount of water in the wetwell suppression pool was 550 000 kg, corresponding to a submerged depth of 2.81 m of the vent pipes The measured discharge mass flow and the corresponding enthalpy are given as an input to the containment calculation (Fig 7) 3.5.2.3 Calculation results The multi-room geometry of the Marviken plant made the simulation of the air and steam flows rather complex However, the general time histories of the drywell and wetwell pressures and temperatures were predicted quite well (Fig 8) (Hänninen, 2003) During the simulation, it was found that the pressure increase in the drywell and the wetwell was dependent on 35 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig Measured discharge mass flow (left) and specific enthalpy (right) (Hänninen, 2003) from the dead-end compartment above the pressure vessel had a great influence on the pressure behavior of the drywell and wetwell However, the Apros-SUPLES benchmark (Hänninen et al., 2003) and the Marviken validation calculation indicated that the blowdown modeling of Apros is sound and the code works reliably in the suppression pool applications 3.5.3 Steam condensation on the wall: PPOOLEX test WLL-5-2 The main objective of the validation task was to check that the steam condensation and heat transfer to a wall structure is modeled correctly in ACON Furthermore, the capability to model the general thermal-hydraulics in a simplified suppression pool geometry was studied 3.5.3.1 Test arrangements The POOLEX test facility is located at Lappeenranta University of Technology (LUT) in Finland (Fig 9) (Laine et al., 2008) The primary component of the test facility is a cylindrical stainless steel vessel with a free volume of 31 m3 The cylinder is divided into the drywell and wetwell compartments, separated by an intermediate deck The free volume of the drywell is 13 m3 The facility also includes a suppression pool system with a vent pipe The steam condensation was measured by collecting condensate in two gutters, located on different vertical positions of a drywell wall In test WLL-5-2, a relatively constant steam injection rate (470–550 g/s) takes place for 240 s The injected steam is saturated, Fig The PPOOLEX facility (Laine et al., 2008) having an injection pressure of 6.5 bar and a specific enthalpy around 2680 … 2730 kJ/kg The facility was dried out before the test by blowing hot dry air through the facility Because the initial humidity in the facility was not measured, the Apros calculations included some sensitivity studies with Fig Drywell and wetwell pressures (left) and gas temperatures (right) in the Marviken blowdown experiment (Hänninen, 2003) 36 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig 10 Condensate mass in the lower gutter on the drywell wall in the PPOOLEX test WLL-5-2 (Luukka and Silde, 2010) 3.5.4 Steam stratification at the THAI facility (test TH24) The goal of the THAI tests of the series TH24 was to study the dissolution of steam stratification under the presence of natural convection (Freitag et al., 2016) The tests provided data for both CFD and LP models in order to develop simulation capabilities in a containment atmosphere of nuclear reactor containments The benchmark exercise was of special interest, because it included both the blind and open calculations VTT participated in the blind exercise using the Apros code (ACON) The main aim of the Apros simulation was to study the capability of the LP code to model very challenging stratification and dissolution processes by utilizing the experiences gained from the relevant previous exercises varied humidity 3.5.3.2 Calculation model and assumptions A simple three-cell nodalization is used in the simulation: one node for drywell and wetwell, and one node representing an environment to model heat losses there (Luukka and Silde, 2010) A suppression pool including one vent pipe is modeled in the wetwell Three gas flow paths exist between the drywell and wetwell: a vent pipe, a vacuum breaker and a leakage hole in the intermediate deck door The liner of the wall, ceiling, floor, and flange, and the lumped mass of pipe connections and valves, etc., are modeled as heat structures 3.5.3.3 Calculation results From the validation point of view, the most important measured variable of this test was the amount of condensate water collected from the lower wall segment of the drywell to the gutter (Fig 10) Because the initial humidity was not measured in the test, three Apros simulations were performed with a varying initial humidity of the drywell The facility was dried out before the test, and hence, the low humidity value was considered to represent the most realistic value The results in Fig 10 show that Apros simulated the condensate mass rather well The best agreement was obtained with very low initial humidity (1%) Generally speaking, the initial humidity appeared to have only a small influence on the condensate mass The initial humidity determines the initial mass of steam and air in the facility The mass of air did not change during the test Therefore, as the initial humidity is higher, the initial air mass is lower and also the partial pressure of non-condensable air remains lower This effect can clearly be seen in Fig 11, in which the calculated drywell pressures with varied initial humidity levels are compared to the measurements Best agreement was obtained once again assuming 1% initial humidity A general conclusion of this validation task is that Apros heat and mass transfer modeling on a wall structure works well and gives reliable results Similar conclusions were obtained also in the ACON calculation of steam condensation test ISP-47 at the MISTRA facility (Silde, 2007) The greatest deviation between the simulation and measurements was observed in wetwell gas temperature, which increased too fast in the simulation The reason for this was probably the same as in the simulation of the Marviken test no 18 described above: the calculated energy flow through the vent pipe(s) to the pool, particularly at the beginning of the transient, is probably higher than in the experiment 3.5.4.1 Test arrangements The THAI test vessel has volume, height and diameter of 60 m3, 9.2 m and 3.2 m, respectively (Fig 12) (Freitag et al., 2016) The steel vessel is thermally insulated and the walls are equipped with heating/cooling mantles in three vertical sections The vessel space also includes an open inner cylinder A sump compartment is located at the bottom of the vessel The test TH24 is preceded by the preheating phase, in which the vessel pressure and gas temperature increase to 1.2 bar and around 90 °C, respectively During the main steam injection phase, which takes place for 500 s saturated steam (35 g/s) is injected into the upper part of the vessel where a stratification layer is evolved Due to steam condensation on the wall and to ensure isobaric conditions beyond the main steam injection phase, the steam injection continues at a low rate of 3.8 g/s and the steam stratification layer was later mixed by a thermal convection induced by heating of the lower and middle heating mantles on the wall The upper mantle is simultaneously cooled The natural circulation motion is upwards near the wall and downwards inside the inner cylinder of the vessel (Fig 12) 3.5.4.2 Calculation model and assumptions A specific “pseudo-3D” nodalization concept has been developed for ACON to capture the main natural circulation flow path with associated stratification phenomena (Fig 13) The vessel is modeled by 28 vertical node levels, each of which is further divided into horizontal nodes The lowest and highest parts of the vessel are modeled by own nodes Due to the certain simplifications of numerical solution of an LP code, it is impossible to model a forced convection steam jet directly However, 37 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig 11 Drywell pressure in the PPOOLEX test WLL-5-2 (Luukka and Silde, 2010) in Fig 13) where the jet region is divided radially into two internal nodes Steam is injected into the innermost zone The inner zone is surrounded by a node representing a “stagnant” ring zone To prevent too strong gas entrainment from the nodes below, there are no flow path connections between the jet zone and the node below it the earlier ISP-47 exercise demonstrated that with additional input and specific nodalization of the jet zone, it is possible to mimic the jet and plumes and their associated atmosphere entrainment also within an LP code (Allelein et al., 2007) Learning from this experience, a specific Apros nodalization for the jet region is built up (indicated as red color Fig 12 Configuration and selected instrumentation of the THAI vessel (Freitag et al., 2016) 38 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig 15 Apros blind simulation (APRVTT) and experimental (EXPBT) steam concentration profile as a function of vessel height at t = 500 s (Freitag et al., 2016) nodalization concept is constructed properly 3.5.5 Ice melting and natural circulation flow in ice condenser containment (VICTORIA test no 42) The main purpose of this validation case was to study the modeling capability for the natural circulation flow through the ice condenser sections and ice melting in a Loviisa-type ice condenser containment The general containment thermal-hydraulics behavior was also investigated Fig 13 Apros nodalization for TH24 3.5.4.3 Calculation results Experimental and blind-simulation results concerning the steam volume fraction above the steam injection elevation at two different elevation (H = 7.7 m and H = 8.7 m) are shown in Fig 14 As the steam injection started, the steam concentration above the injection elevation increased rapidly Apros could predict qualitatively the stratification process, but the maximum steam concentration was slightly underestimated The duration of steam dissolution at 8.7 m was overpredicted At t = 500 s, when the main steam injection was reduced to a minimum flow rate, the steam stratification was probably at the maximum extension (Freitag et al., 2016) Comparison of the Apros simulation results with the measurement showed that the dimension of the steam stratification cloud was well captured in the Apros simulation (Fig 15) The general conclusion of the Apros validation calculation was that the steam stratification, as well as the mixing of steam until t = 700 s were well predicted The later mixing of stratification was overpredicted, most probably due to an overprediction of the convective loop and associated gas mixing In any case, the blind simulation results were promising and demonstrated that the challenging stratification phenomena can also be modeled and captured with the ACON LP code, if the user experiences from other activities are utilized and if the 3.5.5.1 Test arrangements The VICTORIA facility is a test facility for The Loviisa Ice Condenser Containment (ICC) with the linear scaling of 1:15, which gives a volume scaling of 1:3375 (Hongisto et al., 1991; Hongisto, 1995) (Fig 16) The facility was constructed at the Hydraulic Laboratory of IVO Free volume of the facility is about 25 m3 and it is equipped with two ice condenser sections and concrete structures (Hongisto, 1995) In VICTORIA test no 42, the facility was preheated to a temperature of around 50 °C before the actual experiment The ice condenser doors are forced open to study the global natural convection flow through the ice condenser sections In test no 42, the ice loading is asymmetric, i.e one ice condenser is full of ice and the other one is empty, i.e there is initially ice only in one ice condenser section A constant steam release of g/s occurs into the lower compartment 3.5.5.2 Calculation model and assumptions The Apros 34-cell nodalization consists of nodes for the lower compartment, nodes for both ice condenser sections, nodes for the upper compartment, and 15 other nodes (Fig 17) Both ice condenser sections are modeled Fig 14 Experimental and calculated steam concentration above the steam injection location at 7.7 m (left hand side) and at 8.7 m (right hand side) APRVTT indicates Apros results from the blind simulation and APRVTT-O from the open simulation EXPBT is the measured value 39 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al geometry reasonably Apros also simulates the main natural circulation flow qualitatively well The early-phase flow rate was also predicted accurately, but the later change in flow rate as the ice melts was not fully captured This indicates the difficulties in modeling the free flow area and related friction effects through the ice bed correctly, because the ice is modeled as a lumped mass, and hence the local 3-D melting configuration cannot be modeled Applications This section provides a brief overview of how ACON has been applied to analysis tasks relating to licensing analyses of a nuclear containment system (Apros, 2016) Both Loviisa VVER units 1&2 have a Western-type double-layer ice condenser containment based on the Westinghouse design Due to the unique containment design and emergency safety features, Fortum originally built their own experimental VICTORIA containment facility to study different thermal-hydraulic and heat and mass transfer phenomena, and also to produce an extensive amount of code validation data (Hongisto et al., 1991; Hongisto, 1995) The development and validation of the Apros containment code at Fortum has been performed against selected VICTORIA experiments and also against parallel results obtained by another well-validated German COCOSYS containment code (COCOSYS, 2018) The general structure of the Loviisa containment system can be seen in Fig 21 and Fig 22 The Loviisa Ice Condenser Containment (LICC) is divided into five separate main compartments: Lower Compartment (LC), two ice condenser sections (XL), upper compartment (UC), deadended compartments (DE) and outer annulus (OA) The total volume of the containment including the outer annulus is about 80 000 m3 Inside LICC there is 9300 m3 of reinforced concrete with a surface area of 17 500 m2 For the steel structures the corresponding numbers are 500 m3 and 50 000 m2 Fig 22 shows the two cross-sectional containment sectors relative to the ice condensers The primary circuit of the reactor together with the steam generators and the pressurizer is located in the lower compartment (LC) Due to this design feature, any postulated coolant or steam leak potentially challenging the containment integrity will be released into the lower compartment The resulting pressure increase will force the air and steam to flow through the ice condensers to the upper compartment (UC) The ice condenser has baskets which contain arrays of the cylindrical ice tubes The ice melts and absorbs energy, thus limiting the containment pressure increase In major Loss of Coolant Accidents (LOCAs) and Steam Line Breaks (SLBs), the containment spray system in the upper containment dome is also activated For effective coolant recirculation mode, the spray water will return to the lower compartment via the reactor hall floor and the segment area There are specific flow paths including flap check valves embedded in the wall between the UC segment area and the lower compartment Over the years, Fortum has separately built and maintained detailed safety analysis models and containment models in the Apros simulation environment for Loviisa NPP The highly detailed safety analysis models with primary and secondary side representations are completely built with six-equation components including the safety classified intermediate cooling circuit and other parts of the decay heat removal chain to the ultimate heat sink The reactor core model inside the pressure vessel can further be selected from three different options (1D/3-D/multi-channel LOCA) depending on the specific analysis case During recent years, special focus has been on connecting the highly detailed primary and secondary loop models to the detailed lumped parameter containment model The most important boundaries and connection points between six-equation thermal-hydraulics and lumped parameter containment models are the following: Fig 16 Schematic of the VICTORIA facility (Hongisto, 1995; Salminen et al., 2006) by four nodes The free flow area in the ice bed is calculated as a function of ice melting, i.e as the ice melts, the free flow area increases 3.5.5.3 Calculation results A global natural circulation flow upwards in one ice condenser and downwards in the other one was developed in the test (Fig 18) The main flow direction was upwards from the lower compartment through one ice condenser section to the dome region, and correspondingly downwards in the other IC section The calculated velocity above the IC-section was in good agreement with the measurements in the early phase of the experiment, but the velocity in the experiment decreased faster than in the calculation (Fig 19) The variation of measured velocities above one ice condenser section was significant Two Apros calculations were made by varying the ratio of axial and radial melting rates Beyond t = h, the calculated velocity followed closely the highest measured value The pressure increased rapidly in the beginning of the experiment when steam flowed from the lower into the upper compartment through the empty IC section (Fig 20) Later on, pressure increased only slightly as long as there was ice left in the full IC-section The early phase pressure was well predicted with Apros Later on, the pressure was slightly overestimated The gas temperature in the dome was slightly underestimated during the ice melting process, after which the agreement was good Conclusions of the validation case were that Apros was able to calculate the dome pressure and gas temperature in the ice condenser • Break flow modeling from the six-equation model to containment • ECCS and containment spray suction from the LC floor sump 40 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig 17 Apros nodalization concept for VICTORIA experiment no 42 • Heat losses from pipe walls to the containment atmosphere droplet diameter, the higher the energy transfer from the lower compartment atmosphere to the drain droplets and thus, the higher the sump water temperature The drain droplet diameter is one of the key initial parameters for the deterministic safety analysis The selected diameter value depends on whether limiting containment atmosphere conditions or sump water temperature and intermediate cooling circuit conditions are analyzed The design basis of any nuclear power plant is the collection of postulated initiating events From the containment design and analysis point of view the relevant scenarios are typically different leaks or breaks from the primary or secondary circuit to the containment atmosphere The goal of the deterministic containment safety analyses is to show that even in the most severe design basis conditions the emergency safety features and corresponding safety systems successfully limit the accident consequences to an acceptable level Critical acceptance criteria are related to the following physical parameters: Having the connection between the primary and secondary circuit models with the containment model gives some obvious advantages from the safety analysis point of view, such as: • Realistic containment back pressure calculation during an accident • Realistic sump water temperature calculation during ECCS and containment spray recirculation mode • Easier determination of possible break flow submergence under LC sump water surface An illustrative and simplified nodal structure of the Loviisa containment model is presented in Fig 23 The real nodal model is more complex and is based on the validation experiments presented in the previous sections In certain nodes, the blue color indicates the possible presence of liquid water surface due to floor sump structure Another important feature to note is the ice condenser drain sprays located in the bottom of the ice condenser floor The water formed by ice melting is led through gravity-driven drain valves and splashed, forming small droplets These droplets fall through the lower compartment atmosphere and have a significant effect on the lower compartment conditions and sump water temperatures The smaller the average drain 41 Containment pressure Containment temperature Containment inner wall steel liner temperature Average temperature of the lower compartment Sump water temperature Intermediate cooling circuit temperatures Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig 20 Overpressure (left) and gas temperature (right) in the dome Fig 18 Schematic of the natural circulation flow loop inside the VICTORIA facility (Hongisto, 1995) Fig 21 Colored side-cut view of the Loviisa Ice Condenser Containment lower compartment Criteria (5) and (6) are reliability and durability requirements for the intermediate cooling system and the decay heat removal chain from the containment to the ultimate heat sink For Loviisa NPP, the limiting design basis accidents of the containment are based on following events: Fig 19 Gas velocities above the ice condenser section • Hot- and cold leg 100% guillotine breaks of primary circuit pipes (HLLOCA & CLLOCA) • Smaller breaks of hot- and cold-legs (SBLOCAs) • Large Steam Line break (SLB) • Smaller 10% steam Line Break The criteria (1) through (3) are typical pressure and temperature limits for the containment integrity The limiting accidents challenging these parameters and acceptance criteria are usually the largest primary or secondary pipe breaks For the other criteria (4) through (6), the limiting initiating events are less obvious Criterion (4) is related to reliability and durability requirements regarding safety graded electricity and automation components inside the containment and the The event-specific analysis goals and initial assumptions are summarized in Table The goal of this section was to provide an overall introduction to the 42 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Fig 22 Side view of the containment sectors relative to ice condensers Fig 23 Illustrative nodal structure of the Loviisa 1&2 Apros containment model 43 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al Table Main limiting design Basis conditions Case Limiting parameters CLLOCA HLLOCA Containment pressure Containment temperature SBLOCAs Sump water temperature Intermediate cooling circuit temperatures SLB 100% Containment pressure Containment temperature Lower compartment temperature Lower compartment temperature SLB 10% Initial assumptions - Minimum ECCS capacity to maximize steam content of the leak - IC drain droplet size is maximized to minimize energy loss to droplets - ECCS capacity is to maximized to maximize the flow through core and also cause early break submergence - IC drain droplet size is minimized to maximize heat transfer to sump - Break size is largest possible without actuating the containment spray - RCP corresponding the damaged loop will run until SG empty (off-site power is not lost) - IC drain droplet size is maximized - RCP corresponding the damaged loop will run until SG empty (off-site power is not lost) - IC drain droplet size is maximized Fig 24 Some illustrative Apros results from five different loss of primary coolant test simulations package and was developed for modeling of containment/compartment phenomena during accidents The main features of ACON and the current validation process were summarized Severe accident phenomena were not considered in this paper The Apros validation calculations cover nearly 50 experiments and several code benchmark exercises in various single and multi-room geometries representative of BWR Mark II, PWR large dry and PWR ice condenser containments The validation work indicates that ACON is capable of calculating containment thermal-hydraulic behavior including related aspects of engineering safety systems reliably and ACON can be used for safety analyses of NPP containments/compartments It is recommended that the future validation work of ACON should be focused more on the separate effects than on the integral tests Some of the validation calculations performed with earlier code versions should be repeated using the latest version Most of the current validation calculations are performed as open exercises Additional blind calculations, without any knowledge about previous experimental results, would be useful in assessing the predictive capability of the code ACON has been applied in various analysis tasks within the nuclear industry, but also in non-nuclear design tasks most important Loviisa-related design basis events, taking into account article length limitations However, especially after the Fukushima accident, different Design Extension Conditions including common cause failures and complex failure combinations and their mitigation with the passive safety features have had an increasingly important role in the updated list of initiating events In addition to maintaining Loviisa FSAR analyses, Fortum has many customer projects with extensive PWR and BWR plant containment modeling tasks with, e.g passive safety systems (Apros, 2016) Some illustrative results from five different loss of primary coolant test simulations can be seen in Fig 24 A large × 100% cold-leg break accident DBALOCA will lead to strong non-condensable gas and steam flow through ice condensers into the upper compartment and the containment spray system will be actuated at an early stage during an accident This is the design basis initiating event from the containment pressure capacity point of view The smaller breaks not increase the upper compartment pressure level sufficiently to activate the containment spray system, and so the spray injection initiation is delayed until the ECCS tank is almost empty and the sump recirculation phase is initiated When the containment spray is not in operation, the ECCS tank water volume is injected into the primary circuit solely by the high- and low-safety injection pumps The majority of the injected water flows through the reactor core, leading to higher sump water temperatures and a higher heat transfer rate to the intermediate cooling circuit during the recirculation phase The higher intermediate cooling circuit temperature pulses can be seen on the right-hand side of Fig 24 The short-term upper compartment pressure and temperature behavior is clearly limited by maximum break sizes In the long-term analyses, the smaller breaks have a limiting role, especially when maximizing the intermediate cooling circuit temperatures Acknowledgements Most of the validation work was carried out within the Finnish National Research Program SAFIR The work was funded by the Finnish National Nuclear Waste Management Fund (VYR) and VTT Appendix A Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.pnucene.2019.03.031 Summary/conclusions The Apros Containment Code (ACON) is a part of the Apros Nuclear 44 Progress in Nuclear Energy 116 (2019) 28–45 A Silde, et al References Stratification and Lappeenranta University of Technology, Stratification and Mixing Lappeenranta University of Technology CONDEX 1/2008 Luukka, J., Silde, A., 2010 Validation of Apros Containment Model against PPOOLEX Experiments STR-1, STR-4 and WLL-5-2, Revision 1.0 Research Report No VTT-R00763-10, Rev 1.0 VTT Technical Research Centre of Finland ltd 15.5.2010 Malet, J., Vendel, J., 2009 SARNET-2: Droplet Heat and Mass Transfer Studies Specification Report SERAC/10.2.1.1.5 IRSN Malet, 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2014 Freitag, M., Schmidt, E., Gupta, S., Poss, G., 2016 Simulation benchmark based on Thaiexperiment on dissolution of a steam stratification by natural convection Nucl Eng Des 299 (2016), 37–45 Harti, M., 2005 Validation of the Apros 5.06 Containment Internal Spray System Models against International Standard Problem No 35 Fortum Report No THERMO-497 Fortum Nuclear Services ld Hongisto, O., Tuomisto, H., Lundströn, P., 1991 Hydrogen distribution experiments for Loviisa ice condenser containments In: Proceedings Workshop on Hydrogen Behaviour and Mitigation in Water-Cooled Nuclear Power Reactors March 4-8, 1991 Brussels, Belgium Hongisto, O., 1995 The Results of Test Phase of the VICTORIA Experiment Part A: Natural Circulation Experiment Imatran Voima Oy Research Report DLV1-G380-387 30.6.1995 Confidential Hänninen, M., 1989 A Solution of One-Dimensional Flow and Heat Transfer Processes with Difference Method Thesis for the Degree of Licenciate of Technology Lappeenranta university of technology Hänninen, M., Silde, A., Eerikäinen, L., 2003 Basic Validation of Containment and SixEquation Models Research Report PRO4/7831/03 VTT Technical Research Centre of Finland Ltd December 2003 Confidential Hänninen, M., 2003 Validation of Apros Containment Model against Marviken Test 18 Research Report No PRO5/7828/03 VTT Technical Research Centre of Finland Ltd December 2003 Confidential Laine, J., Puustinen, M., Räsänen, A., 2008 PPOOLEX Experiments on Thermal 45 ... using the heat and mass transfer analogy The Nusselt number for both natural and forced convection flow is calculated, and as a default the higher of the two values is used in the heat and mass transfer... the wall between the UC segment area and the lower compartment Over the years, Fortum has separately built and maintained detailed safety analysis models and containment models in the Apros simulation. .. vacuum breaker and a leakage hole in the intermediate deck door The liner of the wall, ceiling, floor, and flange, and the lumped mass of pipe connections and valves, etc., are modeled as heat