Abstract

This paper deals with a general methodology to evaluate the Source Term (ST) and the Radiological Consequences (RC) of a hypothetical Severe Accident (SA) at a Fukushima-like Spent Fuel Pool (SFP) by coupling ASTEC 2.1 and RASCAL 4.3 SA and consequence projections (CP) codes, respectively. The methodology consists of the following sequential steps: the ST provided by a prior simulation performed by ASTEC V2.1 code was used as input to RASCAL 4.3 code to make a RC analysis. This approach was developed as a preparatory study for the Management and Uncertainties in Severe Accident (MUSA) H2020 European Project, coordinated by CIEMAT, where the ENEA's Nuclear Installations safety laboratory is committed to performing an analysis on a Fukushima-like SFP with the aim to apply innovative management of SFP accidents (WP6) to mitigate the RC of the accident itself. To perform the RC studies that could have an impact on Italy, a Fukushima-like SFP was assumed located in one of the Italian cross-border NPP sites. The weather data adopted are both standard and real hourly meteorological data taken from more than one geographical location. The results of the RC for 96 h of ST release in a range of 160 km from the emission point are reported in terms of Total Effective Dose Equivalent (TEDE), Thyroid dose, and Cs-137 total ground deposition. The mitigating effect on ST and on RC of the cooling spray system (CSS) actuated with several pH values (i.e., 4,7,10) was also investigated.

1 Introduction

In the last ten years, following the Fukushima Daiichi Nuclear Power Plant (NPP) accident, there was an increase in the research activities devoted to exploring and update the codes capability to calculate the Source Term (ST) [1,2] and the Radiological Consequences (RC) [3,4] of Beyond Design Basis Accidents (BDBA) at Spent Fuel Pool (SFP). The increased attention in assessing the code capability to perform a Severe Accident (SA) progression in a NPP and a SFP resulted in the realization of the still in progress Management and Uncertainties of Severe Accidents (MUSA) European H2020 project in which the authors of this work are involved as official partners. MUSA overall objective is to evaluate the prediction capability of SA codes to modeling reactor and SFP accident scenarios with the quantification of the associated codes uncertainties and the effect of both existing and innovative mitigation strategies on the RC2. In this research framework, several studies were also performed for coupling ST and RC codes with the aim to create a comprehensive system capable to make evaluations of all physical quantities involved in the several phases of a SA event: fuel inventory released, time-dependent ST, and dose/activity distribution on the surrounding territory. The state of the art of this kind of study ranges from a simplified approach that involves the use of fast running codes/technics to evaluate the ST and the RC, to an intermediate approach that involves the use of a fast-running code/technique coupled with a dedicate ST or RC code, to a complex approach that includes the use of specifically designed codes both for ST and RC evaluation. In the field of simplified approach, analysis has already been carried out using reactor core inventory as ST and a short-term, short-range, near-surface release Gaussian atmospheric dispersion code to evaluate the RC [5]. In the area of intermediate approach, analysis that involves the use of analytic techniques (i.e., technical documents, look up tables, etc.) to evaluate the ST and a more comprehensive Lagrangian atmospheric dispersion code to evaluate the RC was performed [6,7]. In the field of complex approach, dedicate SA codes to evaluate an accident-related ST and a long-range Lagrangian atmospheric dispersion code was used [8]. This study can be considered a contribution in the context of the intermediate approach because involves the use of a specially designed code to model SA phenomena (i.e., ASTEC V2) with a fast-running code (i.e., RASCAL 4.3) that makes the RC consequence by means of a Gaussian puff atmospheric dispersion model. This type of coupling has not yet been tested in the scientific research context of coupled ST and RC evaluation systems and it could represent a good compromise between fast and accurate methodologies that could be validated in the next future with benchmarks studies with other types of ST and RC code coupling for furthering check its reliability. Specifically, ASTEC code has progressively become the European reference code for SA analyses for water-cooled reactors [9,10]. ASTEC V2 was developed and extensively validated within the Severe Accident Research NETwork of excellence (SARNET) from 2004 to 2013 within which innovative major improvements such as new core degradation and an in-core two-dimensional (2D) magma/debris relocation models were implemented [2]. ASTEC V2.1 also arises from the efforts performed in the Code for European Severe Accident Management (CESAM) European project within which a further improvement of physical modeling (i.e., new core degradation models, Melting Core Concrete Interaction (MCCI) coilability, new reflooding of degrade core model, improving the oxidation of Zircaloy cladding model, new ST evaluation capabilities in both RCS and containment, improving iodine chemistry modeling) and validation work was achieved to verify the general capability of ASTEC V2.1 to simulate the state-of-art of the most important SA phenomena particularly relevant in the progression of a SFP and a NPP SA scenario [2]. RASCAL 4 is the official code currently used by United States Nuclear Regulatory Commission (U.S.NRC) emergency operation center for making dose projections for atmospheric releases during radiological emergencies [11]. RASCAL is included in the Radiation Protection Computer Code Analysis and Maintenance Program (RAMP)—supported by the U.S.NRC—within the RAMP emergency response category as a stand-alone tool for making independent dose and consequences projections during radiological incidents and emergencies3. In this work, ldX Eulerian atmospheric dispersion code was also employed to make a preliminary conservative meteo data analysis. ldX is a code specifically developed by the French Institute De Radioprotection et De Sûreté Nucléaire (IRSN) to perform far range radionuclides dispersion analysis into the atmosphere. The model implemented in ldX is like that of Polair3D of the Polyphemus platform and has been validated against the European Tracer Experiment (ETEX), the Algeciras accident, and the Chernobyl accident [12]. The meteo dataset used in this study are all based on the latest fifth major global reanalysis data (ERA5) produced by the European Center for Medium Weather Forecast (ECMWF). The data are stored in ECMWF Meteorological Archival and Retrieval System (MARS) and a pertinent subset of the data, interpolated to a regular latitude/longitude grid, is available on the Copernicus Climate Change Service (C3S)4. ECMWF operates the C3S on behalf of the European Union (EU) and will bring together expertise from across Europe to deliver the service5.

The coupling between ASTEC and RASCAL codes was implemented in a serial manner: the ST provided by ASTEC at the end of a simulation was modified in a several parts (i.e., syntax, style, and time-step) to be accepted by RASCAL code by means of a python script specifically prepared for this purpose. Subsequently, RASCAL 4.3 was run to perform a RC analysis using as input the ASTEC reworked ST. Therefore, the information between ASTEC and RASCAL was exchanged only at the end of the ASTEC simulation, and no feedback control was implemented. At the same time, no code coupling was implemented because RASCAL 4.3 can only be used by means of a GUI based interface.

The following section presents the methodology used in this study. In the third section, the codes used in this work are discussed with the specific parameters and modules used to perform the analyses. In the fourth section, the results of the application of the ASTEC/RASCAL coupling methodology to a Fukushima-like SFP hypothetically located on one of the Italian cross-border sites are presented. In the last section, some considerations on the results and the planned future work are reported.

2 Methodology and Calculation Tools

The methodology presented in this study is in principle capable to perform a RC analysis on any nuclear facility; it consists of two steps: ST evaluation with the ASTEC V2.1 code (Study carried out with ASTEC V2, IRSN all rights reserved, [2020]) [13] and RC assessment with the RASCAL 4.3 code [11]. For the present study, ASTEC V2.1 is used to calculate and export a ST resulting from a Loss-of-Cooling SA scenario at a Fukushima-like SFP. Then, the ST file is imported into the RASCAL 4.3 code and the RC consequences are evaluated by means of the Atmospheric Transport module of RASCAL 4.3, according to the user-imposed meteorological conditions. The Fukushima-like SFP model, chosen to perform the ASTEC V2.1 analysis, is an upgraded version of that adopted in the NUGENIA-PLUS AIR-SFP European Project [14] and it will be further developed by ENEA to be used within the MUSA project activities [15]. This activity is developed within the WP6 task of the MUSA project, coordinated by IRSN.

Three meteorological conditions were investigated: RASCAL 4.3 predefined “standard” meteorological data; one point of real 3.456 × 10+5 s meteorological data located at a specific geographical point where one of the Italian cross-border NPP is located; three additional points of real 3.456 × 10+5 s meteorological data located far away from the chosen cross-border NPP site. The one point of hourly meteo data located at one of the Italian cross-border NPP was extracted from the history+ Meteoblue online hourly meteo data paid service6. The Meteoblue service datasets are based on ERA5 meteorological hourly reanalysis data with a spatial resolution of 3.0 × 10+4 m and are produced by combining measurement, observation and simulation data and applying data assimilation techniques to achieve the most realistic description of the weather occurrences7. The results may be validated and corrected through measurements and observation data, using different postprocessing techniques like downscaling, statistic, machine learning, and nowcasting8. The additional three points of hourly meteo data located at about 7.0 × 10+4 m away from the NPP were extracted from the ERA5 reanalysis database of the Copernicus online service9. ERA5 reanalysis method uses the data assimilation principle which combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. The ERA5 data used in this study are hourly data on a single pressure level with a resolution of 2.5 × 10+4 m10. Figure 1 presents the flowchart of the proposed methodology. All the analyses were performed on a Windows 10 64-bit desktop equipped with an Intel Core i7-4710HQ 2.50 GHz and 16 Gb of RAM.

Fig. 1
Flow chart of the methodology to evaluate the RC from ASTEC-RASCAL coupling
Fig. 1
Flow chart of the methodology to evaluate the RC from ASTEC-RASCAL coupling
Close modal

The next two subsections describe the calculation tools (i.e., ASTEC and RASCAL codes) used to evaluate the ST emitted and the RC on the population of the proposed Fukushima-like SFP SA scenario. In detail, the modules and the values of the main parameters assumed in the two codes will be briefly described.

2.1 Astec V2.1 Code.

The Accident Source Term Evaluation Code (study carried out with ASTEC V2, IRSN all rights reserved, [2020]) [2], jointly developed until 2015 by the French “Institut De Radioprotection et De Sûreté Nucléaire” (IRSN) and the German “Gesellschaft für Anlagen und Reaktorsicherheit gGmbH” (GRS), and developed now only by IRSN, aims at simulating an entire SA sequence in nuclear water-cooled reactors from the initiating event through the release of radioactive elements out of the containment. The main uses of ASTEC V2.1 are ST evaluations, accident management studies, and level-2 probabilistic safety assessment (PSA). It features a modular structure where each module is devoted to simulating a specific set of physical phenomena or a specific zone of the NPP. The modelization of the SFP has involved the following modules: CESAR, CPA, ICARE, ISODOP, and SOPHAEROS.

CESAR is dedicated to the thermal-hydraulic simulation in the primary cooling system (including the vessel) and in the secondary cooling system. It is a system code characterized by a two-phase flow model based on a default five equations approach and, to address the non-equilibrium mechanicals between the liquid and the gas phase, a phase slip model is considered (a six equations model is available in the current version of the code but has not been used in this study). The code adopts a finite volume discretization approach, which solves the energy and mass conservation equations on the control volume. The time integration is performed using Newton's method based on a fully implicit scheme [16,17].

ICARE is used to simulate the in-vessel core degradation phenomena. It implements mechanical models, processes several chemical reactions, incorporates FPs release, and describes core thermal behavior, degradation, and relocation in the Lower Plenum (LP), until the rupture of the Lower Head (LH) wall. The code uses basic 2D geometrical objects able to reproduce most of the internals of the core and the related exchange with the coolant fluid, managed by CESAR module. The core radial meshing is based on a multichannels approach enabling to model, by means of cylindrical concentric fluid channels, the axisymmetric core of a pressurized water reactor (PWR) but also to consider the specific core features of boiling water reactors (BWRs) and pressurized heavy-water reactors (PHWR). The multichannels approach, allowing the definition of several subchannels within concentric fluid channels, is also useful to model SFPs [13].

CPA provides a tool based on mechanistic models with the purpose of simulating all the relevant thermal-hydraulic processes and plant states taking place in the containment compartments of a Light Water Reactor (i.e., gas distribution, pressure build-up, condensation, hydrogen combustion, etc.). The discretization model adopted is a lumped-parameter one, where the compartments are divided into control volumes whose status is defined by the temperature and masses of each component [18].

SOPHAEROS deals with the chemistry and the transport phenomena of the FPs both in the reactor circuits and in the containment. The code divides the main physical and chemical phenomena into two parts: vapor and aerosol phase phenomena. The mass balance equation resulting from the intravolume phenomena combined with intervolume transport produce a nonlinear system of equations solved by the Newton Raphson method [19].

ISODOP is in charge of calculating FPs decay heat and the isotopes transmutation along the SA sequence [18].

ASTEC V2.1 Model of the Spent Fuel Pool.

Figure 2 describes the ASTEC V2.1 model of the SFP: it is an extension of the model developed by ENEA in the frame of NUGENIA-PLUS AIR-SFP project [14] which was limited to the simulation of thermal-hydraulic and core degradation in a Fukushima-like SFP, accommodating 1525 fuel assemblies (FAs) of different cooling time and burnup. In the developed ASTEC V2.1 model, the 1535 FAs with their racks are divided into 2 groups: the “Hot FAs” which include 548 FAs (21 GWd/MTU) for recently unloaded fuel (i.e., 3.7 months of cooling); and the “Cold FAs” which include 783 FAs (42 GWd/MTU) for the longer stored fuel (i.e., 3.15 years of cooling) plus 204 FAs of fresh fuel (for a total of 987 FAs).

Fig. 2
Axial view of the Fukushima-like SFP model—ASTEC code
Fig. 2
Axial view of the Fukushima-like SFP model—ASTEC code
Close modal

The FAs and racks of the 2 groups are described by ICARE macrocomponents. The 72 fuel rods of each FA are modeled with a representative cylindrical fuel rod enclosed by the Zr cladding. The Zr water rod, the Zr canister, the steel rack, and the concrete wall of the SFP, are also modeled as ICARE cylindrical structures. Specific ICARE components are dedicated to the simulation of the steel spacer grids. The floor of the pool was modeled with the ICARE structure dedicated to the LH of the reactor.

The evolution of decay power during the simulated accident transient was computed by ISODOP module and the initial total mass of FPs, assumed in the simulation, is based on the ORIGEN-ARP code [20] calculation of the FPs inventory of recently unloaded and longer stored fuel. The FPs mass was distributed in the “Hot” and “Cold” FAs by means of numerical factors, estimated as a function of decay heat computed by ORIGEN-ARP code, for recently unloaded and longer stored fuel and adjusted to consider the presence of the 204 fresh FAs in the Cold FAs group. In such a way, it has been possible to distinguish the thermal behavior of the two groups of FAs during the simulated accident transient.

The SFP was radially divided into two concentric main fluid channels: “Pool inner channel” and “Pool outer channel” (Fig. 2). The pool inner channel contains 4 additional fluid subchannels, housing the 2 groups of FAs with their racks. The two concentric subchannels indicated as “Hot fuel channel” and “Hot bypass channel” (Fig. 2), deal with the Hot FAs. The first one simulates the fluid in the rods bundle and the second the fluid in the gap between the canister and the rack. The same approach is used for the “Cold fuel channel” and “Cold bypass channel” (Fig. 2), dealing with the Cold FAs. The weight of the described channels is based on the number of related assemblies: 548 for the hot channels and 987 for the cold channels.

The 6 SFP fluid channels are connected at the top end with a small CESAR volume, which is used to connect the top part of the pool, with a CPA zone modeling the SFP building. The SFP building zone is connected to an environment zone, imposing atmospheric temperature and pressure. The CPA SFP building model includes lateral, ceiling, and bottom walls of the containment, to consider a series of physical phenomena such as steam condensation and aerosol deposition.

The Zircaloy oxidation by means of steam and air, the creep and burst of the claddings, the dissolution of UO2 and ZrO2 by liquid Zirconium as well as the material melting, and relocation were modeled. The melting temperature of both UO2 and ZrO2 was set between 2550 K (solid) and 2600 K (liquid). Oxidation of U-Zr-O in the relocated materials mixture (i.e., MAGMA) is also activated.

The studied accident is a Loss of Cooling without mitigation measures. The simulation starts with a water level which is just at the top of racks, to reduce the computation time.

A Cooling Spray System (CSS) was subsequently added to investigate the mitigation effect of the water on ST emission. The CSS was designed to pump the condensed water located at the bottom of the SFP building in recirculation mode. It was hypothesized that the SFP has connected to a chemical control system thanks to which the pH of the sprayed water can be set by the user. In the calculations, the CSS was activated by a water level setpoint, at about 1.656 × 10+5 s after the start of the transient and kept working until the end of the calculation.

2.2 Rascal 4.3 Code.

The Radiological Assessment System Consequences AnaLysis (RASCAL) [4] code was developed by U.S. Nuclear Regulatory Commission to provide a tool for the rapid assessment of an incident or accident at any nuclear facility and aid decision making such as whether the public should evacuate or shelter in place. RASCAL evaluates time-dependent atmospheric releases (i.e., ST) and dose projection (i.e., RC) from any nuclear facilities that handle nuclear material. The 4.3 version contains new features and revision of several old features (i.e., extension of the domain up to 1.6 × 10+5 m, increase of the transport time to 3.456 × 10+5 s, capability to both import and/or merge ST, and to evaluate the child thyroid dose) in response to the lessons learned by the U.S. NRC staff after the events at the Fukushima Daiichi NPP. The main new and revised features are consistent with the possibility to evaluate the RC on the Italian territory of a hypothetical SA at one of the nearest SFPs. The “Source Term to Dose” (STDose) primary tool was used to evaluate the RC due to a SA scenario by means of some parameter's specifications given as input to a series of subtools that allow to define the source and location of the radioactive emission, the time-dependent ST, the release conditions, and the meteorological model [11].

The source of the radioactive emission was placed at a SFP according to the case under investigation: a SA event from a Fukushima-like SFP.

In order to locate in space, the user-defined weather data, the position of the SFP was estimated according to a procedure that involves the use of the s.c. surrogate NPP (i.e., plant already available in RASCAL 4.3 database of U.S. plants and which differs from the real plant only in terms of actual power and actual core average burnup) [3,21]. In practice, this means to find among the RASCAL U.S. fleet a BWR-4 Mark-1 plant, which could be used to mockup the Fukushima-Daiichi NPP unit 4 containing the SFP under SA conditions. The plant chosen for the analysis is Cooper NPP, a U.S. BWR-4 Mark-1 NPP currently in operation.

The time-dependent ST was imported from ASTEC V2.1 calculation results. The ST time-resolution from ASTEC V2.1 output was setup on a radionuclide emission value every 900 s. RASCAL 4.3 allows to use only a subset of the radionuclides evaluated with ASTEC V2.1 code, therefore only the radiological relevant nuclides were imported into RASCAL 4.3 from the ST obtained with ASTEC V2.1.

The dispersion of the radionuclides in the atmosphere during the SA event was evaluated by means of RASCAL 4.3 2-D Gaussian puff model (i.e., TADPUFF) for a distance up to 1.6 × 10+5 m from the release point for which temporal and spatial variations in meteorological condition are not negligible; the model domain consists of a Cartesian square grid with 41 × 41 receptor nodes uniformly distributed through the domain itself [22]. The radionuclide atmospheric transport time on the environment was set to 3.456 × 10+5 s.

RASCAL 4.3 considers the horizontal and vertical radionuclide spread distance-dependent on the emission point by means of dispersion parameters (i.e., σy, σz) which are a function of the following variables: friction velocity, mixing layer height, plume height, Monin-Obukhov length and Coriolis factor. These variables exhibit a functional relationship with the dispersion parameters according to the stability class [23,24].

RASCAL includes the two types of radionuclides deposition mechanisms: dry deposition (i.e., the uptake at the earth's surface) and wet deposition (i.e., absorption into droplet followed by droplet precipitation or impaction on the earth's surface [25]. Dry deposition is evaluated as the product of a deposition velocity and radionuclide concentration; the deposition velocity is in turn evaluated based on meteo conditions (i.e., stability class), surface roughness (i.e., friction velocity), and wind speed. Typical values of deposition velocity are between 0.0021 and 0.016 m/s for reactive gases, between 0.0031 and 0.0090 m/s for particles and between 0.0014 and 0.0072 m/s for vapor (i.e., I2) [26].

Wet deposition is assessed using different models for particles and gases. In particular, for particles, the wet deposition rate is calculated as the product of a washout coefficient and the overall particles deposition as precipitation falls through the full extent of the plume. The washout coefficient is a function of precipitation type, intensity and, to a limited extent, temperature; typical washout coefficient values are between 0.25 (light rain) and 0.3 (moderate snow). Wet deposition rate for gases is instead evaluated as a product of a solubility coefficient and the rain/snow precipitation rate, assuming that the concentration of gases in the air and in the precipitation is in equilibrium; typical wet deposition velocity is between 2.8 × 10−5 m/s (light rain) and 4.2 × 10−4 m/s (moderate snow) [24].

RASCAL 4.3 assumes null dry and wet deposition for nonreactive (CH3I) and noble gases (Krypton). It also assumes that the atmospheric iodine is made up of 25% particles, 30% vapor (i.e., I2), and 45% organic form (i.e., CH3I). This speciation contributes to the deposition of iodine and to the inhalation doses if ICRP 60/72 dose coefficients are selected, while it does not enter into inhalation doses if ICRP 26/30 dose factors are applied [24].

RASCAL 4.3 Model of the Meteorological Data.

In this study, the RC analysis was performed using three different meteorological datasets. The first includes standard time-independent meteorological data as defined within RASCAL 4.3 code. Table 1 reports the first set of RASCAL 4.3 constant “standard” meteorological data.

Table 1

Value of the standard weather parameters, code: RASCAL 4.3

Date (dd/mm/yyyy)Wind speed (m/s)Wind direction (degree)Precipitation (m/s)Surface temperature (K)Stability class
25–29/12/20021.890.00.0294.2D
Date (dd/mm/yyyy)Wind speed (m/s)Wind direction (degree)Precipitation (m/s)Surface temperature (K)Stability class
25–29/12/20021.890.00.0294.2D

The second dataset includes one point of actual hourly meteorological data in a time frame of 3.456 × 10+5 m/s from the start of the ST emission. The starting date of the ST emission was based on a preliminary conservative analysis of the radiological impact on Italian territory of a hypothetical SA at one of the cross-border NPPs using the French Eulerian atmospheric dispersion code ldX, owned by IRSN [12]. The analysis with ldX assumed a “puff” (i.e., 8.64 × 10+4 s of constant emission) release of I-131 (i.e., 1.0 × 10+17 Bq) for a transport time of 3.456 × 10+5 s using an operational meteorological dataset provided by Météo France and available in a range of ten years (i.e., 2002–2011) on the so-called ARPEGE domain (resolution 5.0 × 10+4 m). The most conservative start date obtained for one of the neighboring sites is: 2002-12-25 at 09:00 p.m. This dataset was located on the NPP site, and it was extracted from the on-line history+ Meteoblue paid service6. Table 2 reports some date-related values of the dataset of hourly meteo data.

Table 2

Value of the actual hourly weather parameters, location: SFP site

Wind speed (m/s)
Date (yyyy-mm-dd)Hour (hh:mm)Average (2700 s)Gust (900 s)Wind direction (degree)Precipitation (m/s)Surface temperature (K)Stability class
2002-12-2521:003.34.665.10265.2D
2002-12-2522:003.34.563.42.8 × 10−8264.2D
2002-12-2523:003.14.961.62.8 × 10−8264.2D
......
2002-12-2919:001.74.3170.10337.2E
2002-12-2920:001.75.1185.00296.2F
2002-12-2921:001.94.7187.00291.2E
Wind speed (m/s)
Date (yyyy-mm-dd)Hour (hh:mm)Average (2700 s)Gust (900 s)Wind direction (degree)Precipitation (m/s)Surface temperature (K)Stability class
2002-12-2521:003.34.665.10265.2D
2002-12-2522:003.34.563.42.8 × 10−8264.2D
2002-12-2523:003.14.961.62.8 × 10−8264.2D
......
2002-12-2919:001.74.3170.10337.2E
2002-12-2920:001.75.1185.00296.2F
2002-12-2921:001.94.7187.00291.2E

The stability class was evaluated using wind speed, solar radiation and cloud cover hourly data according to Pasquill-Gifford classification [23]. The wind speed for each hourly meteo data was set by means of two values: average wind for the first 2.7 × 10+3 s and gust wind for the second 9.0 × 10+2 s. Figures 3 and 4 report the wind rose and the wind velocity distribution within 3.456 × 10+5 s from the emission date (i.e., 25-12-2002) using the second meteo dataset.

Fig. 3
Wind rose on the SFP—Meteoblue data
Fig. 3
Wind rose on the SFP—Meteoblue data
Close modal
Fig. 4
Average and gust wind—Meteoblue data
Fig. 4
Average and gust wind—Meteoblue data
Close modal

According to the Meteoblue service definition for which the wind rose displays the direction in which the wind blows, the prevailing winds directions come from N, NNE, NE, and account for up to 70% of the total wind directions; the highest wind speed values come from NNE, NE, and WSW with an average value of 4.0 m/s. The difference between gust and average wind in the overall time frame is between a factor 1 and 10 (Fig. 4).

The second, third, and fourth datasets used in this study also include actual hourly meteorological data in a time frame of 5.76 × 10+3 s from the start of the hypothetical ST emission from NPP site. The three datasets are all located at about 7.0 × 10+3 m away from the NPP, but the second and the third ones—here referred as north and south dataset—are shifted of ±20 deg with respect to the geographical location of the fourth one, here referred as central dataset. This choice has allowed to define hourly meteo information in areas of the geographical domain that are at 2.5 computational cells from the location of the central dataset, being the RASCAL computational cells dimension equal to 8.0 × 10+3 m. The meteo dataset was extracted from ERA5 hourly data available for free within the Copernicus European service9. ERA5 is the fifth generation of European Center Medium Weather Forecast (ECMWF) meteo data reanalysis of the global climate and weather10. The meteo data were downloaded in a Network Common Data Form (i.e., *.nc file format) and the single hourly weather variables (i.e., wind velocity, wind speed, temperature, solar radiation, precipitation) were extracted for each of the three datasets (i.e., central, north, and south) by means of a python script specifically implemented for this work. The stability class was once again evaluated using wind speed, solar radiation and cloud cover hourly data according to Pasquil-Gifford classification [23]. The cloud cover hourly data was taken from a free online service11. Tables 35 report some date-related hourly parameters of the three datasets.

Table 3

Values of the hourly weather data—North point: 70 km away from NPP site, +20 deg from Central point

DateHourWind speedWind directionPrecipitationTemperature
(yyyy-mm-dd)(hh:mm)(m/s)(degree)(m/s)(K)Stability class
2002-12-2521:002.184.60.0298.2D
2002-12-2522:001.981.00.0301.2D
2002-12-2523:001.978.10.0301.2D
2002-12-2919:001.3225.00.0253.2D
2002-12-2920:001.4225.00.0262.2F
2002-12-2921:001.5233.10.0261.2D
DateHourWind speedWind directionPrecipitationTemperature
(yyyy-mm-dd)(hh:mm)(m/s)(degree)(m/s)(K)Stability class
2002-12-2521:002.184.60.0298.2D
2002-12-2522:001.981.00.0301.2D
2002-12-2523:001.978.10.0301.2D
2002-12-2919:001.3225.00.0253.2D
2002-12-2920:001.4225.00.0262.2F
2002-12-2921:001.5233.10.0261.2D

Source: ERA5 meteo data.

Table 4

Values of the hourly weather data—Central point: 70 km away from NPP site

DateHourWind speedWind directionPrecipitationTemperature
(yyyy-mm-dd)(hh:mm)(m/s)(degree)(m/s)(K)Stability class
2002-12-2521:002.276.60303.2D
2002-12-2522:002.176.00306.2D
2002-12-2523:002.173.30306.2D
2002-12-2919:001.4213.70260.2D
2002-12-2920:001.6217.60269.2F
2002-12-2921:001.8222.70267.2D
DateHourWind speedWind directionPrecipitationTemperature
(yyyy-mm-dd)(hh:mm)(m/s)(degree)(m/s)(K)Stability class
2002-12-2521:002.276.60303.2D
2002-12-2522:002.176.00306.2D
2002-12-2523:002.173.30306.2D
2002-12-2919:001.4213.70260.2D
2002-12-2920:001.6217.60269.2F
2002-12-2921:001.8222.70267.2D

Source: ERA5 meteo data.

Table 5

Values of the hourly weather data—South point: 70 km away from SFP site, −20 deg from Central point

DateHourWind speedWind directionPrecipitationTemperature
(yyyy-mm-dd)(hh:mm)(m/s)(degree)(m/s)(°C)Stability class
2002-12-2521:001.873.60.0309.2D
2002-12-2522:001.873.60.0310.2D
2002-12-2523:001.772.60.0310.2D
2002-12-2919:001.4219.30.0244.2D
2002-12-2920:001.7220.20.0257.2F
2002-12-2921:001.8222.70.0262.2D
DateHourWind speedWind directionPrecipitationTemperature
(yyyy-mm-dd)(hh:mm)(m/s)(degree)(m/s)(°C)Stability class
2002-12-2521:001.873.60.0309.2D
2002-12-2522:001.873.60.0310.2D
2002-12-2523:001.772.60.0310.2D
2002-12-2919:001.4219.30.0244.2D
2002-12-2920:001.7220.20.0257.2F
2002-12-2921:001.8222.70.0262.2D

Source: ERA5 meteo data.

In order to evaluate if the three geographical points on which the meteo data were extracted are located quite far from each other to produce detectable differences on the meteo data field, the time-dependent trend of the wind speed and wind direction of the central, north, and south datasets were compared (Figs. 5 and 6). The convention adopted for the wind direction is equal to that used by RASCAL 4.3: clockwise with the zero set in the compass southern direction is the direction in which the wind—that comes from north—arrives.

Fig. 5
Comparison of the wind speed versus time of the three meteo dataset—ERA5 data
Fig. 5
Comparison of the wind speed versus time of the three meteo dataset—ERA5 data
Close modal
Fig. 6
Comparison of the wind direction versus time of the three meteo dataset—ERA5 data
Fig. 6
Comparison of the wind direction versus time of the three meteo dataset—ERA5 data
Close modal

The intercomparison of the three datasets of wind speed and direction showed in some time range not negligible relative difference, also more than ±10%, with respect to the central dataset. In detail, the relative differences of north wind direction data are more than ±10% for the following time frames: 2.16 × 10+4 s starting from 15:00 on 26/12/02, 3.96 × 10+4 s starting from 00:00 on 28/12/02, 2.16 × 10+4 s starting from 16:00 on 28/12/02, 2.88 × 10+4 s starting from 06:00 on 29/12/02. The relative differences of south wind direction are also more than ±10% for the following time frame: 4.34 × 10+4 s from 03:00 on 29/12/02. Moreover, the relative difference of north and south hourly wind direction data that overruns a relative difference of ±10% are 38.1% and 39.2%, respectively. The evaluation of the wind roses of the three locations where the hourly meteo data were located, also provided a qualitative estimation of the difference between each of the three meteo dataset (Figs. 79).

Fig. 7
Wind Rose of the North Point—ERA5 meteo data
Fig. 7
Wind Rose of the North Point—ERA5 meteo data
Close modal
Fig. 8
Wind Rose of the Central Point—ERA5 meteo data
Fig. 8
Wind Rose of the Central Point—ERA5 meteo data
Close modal
Fig. 9
Wind Rose of the South Point—ERA5 meteo data
Fig. 9
Wind Rose of the South Point—ERA5 meteo data
Close modal

3 Results and Discussions

The first set of results is the ST generated by ASTEC code. Figure 10 shows the time-dependent ST produced from a series of radionuclides (RNs) released from the SFP since the start of release in atmosphere (i.e., 4.32 × 10+5 s) for 3.456 × 10+5 s of emission time. The RNs list (i.e., Cs-134, Cs-136, Cs-137, I-131, Kr-85, Pu-238, Ru-106, Sr-90, Y-90) is the list of radionuclides with the greatest radiological impact potentially emitted from an SFP as assessed by IRSN and ENEA within the MUSA Project activities2. Figure 10 reports the contribution to the ST of all radionuclides included in the RNs list with the exclusion of Pu-238 for which ASTEC provides the first release in atmosphere only after 10 days from the start of the SA event at the SFP, time for which it is reasonable to assume that all the necessary emergency response countermeasures have already been implemented.

Fig. 10
ST emitted from SFP during a Loss-of-Coolant severe accident scenario—ASTEC code
Fig. 10
ST emitted from SFP during a Loss-of-Coolant severe accident scenario—ASTEC code
Close modal

Figure 10 also shows that the most important radionuclides release occurs between 2.628 × 10+5 and 2.988 × 10+5 s after the start of atmospheric emission and that all the radiologically important RNs reach a saturation value 3.6 × 10+4 s before the end of the RASCAL 4.3 calculation. However, Y-90 presents a residual activity of 4.4 × 10+16 Bq until the end of the imposed ASTEC simulation; this activity could be potentially released before the adoption of emergency countermeasures. Nevertheless, ENEA contribution on the RNs list assessment found that Y-90 is a contributor for groundshine exposition mode only with, in addition, a negligible weight (<1%) compared to the other radiological relevant radionuclides. Therefore, neglecting the residual 4.4 × 10+16 Bq activity not considered in the RASCAL calculation does not introduce an appreciable error in the RC assessment.

The second set of results is the evaluation of the mitigation effect of the CSS actuated with several pH values on the ST generated by each of radionuclides belonging to the RNs list. Figures 11 reports the reduction effect due to the activation of the CSS for several pH values on I-131, being in the ASTEC modeling the other radionuclides included in RN list are not affected by the pH of the water. Figure 11 also accounts for a decrease of the I-131 released activity as water pH increases; this phenomenon essentially depends on the pH-related behavior of two chemical reactions involved in the water phase chemistry: the increase of I2 hydrolysis and of the HOI disproportionation as the pH value increase [27,28].

Fig. 11
I-131 ST for several mitigation conditions (Spray: OFF/ON, pH: 4,7,10)
Fig. 11
I-131 ST for several mitigation conditions (Spray: OFF/ON, pH: 4,7,10)
Close modal

The third set of results is the RC due to the atmospheric transport of the evaluated ST with real, site-related hourly meteorological dataset located in one and four points of the geographical domain, respectively. The adoption of one-point hourly meteo data has allowed to evaluate the effect of time-dependent weather conditions on the final RC results (Figs. 14,17, and 20); the adoption of four-point hourly meteo dataset has allowed to assess the effect of time-dependent and space-dependent weather conditions on the RC results (Figs. 15,18,and 21) and to compare the four-point meteo data with the one-point meteo data RC results.

The intercomparison between one point and four-point meteo data fields (Figs. 12 and 13) on a fixed date emphasizes that the adoption of a more refined meteo field (Fig. 13) allows to perform RC analysis with RASCAL 4.3 in a more realistic situation with a nonuniform wind field and meteo parameters (i.e., stability, precipitation, mixing heights) on the 2D domain. The topography adopted in the simulation is related to the surrogate Cooper NPP plant.

Fig. 12
Meteorological data with one-point meteo data, 2002/12/26 08:45—RASCAL 4.3
Fig. 12
Meteorological data with one-point meteo data, 2002/12/26 08:45—RASCAL 4.3
Close modal
Fig. 13
Meteorological data with four-points meteo data, 2002/12/26 08:45—RASCAL 4.3
Fig. 13
Meteorological data with four-points meteo data, 2002/12/26 08:45—RASCAL 4.3
Close modal

Figures 1416 report both TEDE, thyroid dose, and Cs-137 total ground deposition distribution maps for the most conservative SA scenario (i.e., Sprays not activated). The inhalation dose factor used in the calculation is based on the recommendation of the International Commission on Radiological Protection (i.e., ICRP 60/72) [29]. An intercomparison with the distribution maps achieved with the RASCAL 4.3 standard Meteorology data is also reported. The maps reveal that the SE-SSE is the direction of the most impacted zone according to the direction from which the wind blow (i.e., 300–350 rad) in the timeframe (i.e., 2.628 × 10+5 – 3.132 × 10+5 s) of the maximum radiological emission (Fig. 3). In general, a significant impact of different meteorological conditions and ST emission time on both the distribution of the dose and the total ground deposition was noticed. For the Total Effective Dose Equivalent (TEDE) scenario and with respect to the application of the standard meteo dataset, the one point of actual meteo data reduces the radionuclides spread into the atmosphere from more than 1.6 × 10+5 m to about 1.0 × 10+5 m (Fig. 14), the adoption of four-point actual meteo data further reduce the radionuclides spread at about 8.0 × 10+4 m (Fig. 15). Figures 1419 report a legend with a dose range split according to early phase criteria of the Protection Action Guide (PAG) implemented by U.S. Emergency Protection Agency (EPA) [30]. For the specific SA scenario and meteo data implemented in this study, RASCAL 4.3 foresees the adoption of some early phase protective actions (i.e., sheltering-in-place or evacuation of the public) in the SE-SSE directions up to 1.1 × 10+5 m from the emission with a one-point hourly meteorology data (Fig. 14). The insertion of other three-point of actual meteo data in a time-frame of 3.456 × 10+5 s produced a reduction of the distance to which early protective action should be adopted up to 6.0 × 10+5 m (Fig. 15).

Fig. 14
TEDE, one actual 96 h meteo data points—RASCAL 4.3
Fig. 14
TEDE, one actual 96 h meteo data points—RASCAL 4.3
Close modal
Fig. 15
TEDE, four actuals 96 h meteo data points—RASCAL 4.3
Fig. 15
TEDE, four actuals 96 h meteo data points—RASCAL 4.3
Close modal
Fig. 16
TEDE, standard meteorology—RASCAL 4.3
Fig. 16
TEDE, standard meteorology—RASCAL 4.3
Close modal
Fig. 17
Thyroid dose maps with one point of actual 96 h meteo data—RASCAL 4.3
Fig. 17
Thyroid dose maps with one point of actual 96 h meteo data—RASCAL 4.3
Close modal
Fig. 18
Thyroid dose maps with four points of actual 96 h meteo data—RASCAL 4.3
Fig. 18
Thyroid dose maps with four points of actual 96 h meteo data—RASCAL 4.3
Close modal
Fig. 19
Thyroid dose maps with a standard meteorology—RASCAL 4.3
Fig. 19
Thyroid dose maps with a standard meteorology—RASCAL 4.3
Close modal

The second set of evaluated results are the thyroid dose distribution for adult population, being this radiological parameter one of the main indicators considered by stakeholders to evaluate the adoption of possible emergency countermeasure in an early phase of a SA scenario (Figs. 1719).

The evaluation of Cs-137 total ground deposition was also performed with the aim to have an assessment of the late consequences of the Fukushima-like SFP severe accident scenario (Figs. 2022). Figures 2022 highlight that—regardless of the meteo data scenario (i.e., standard, one point, four points meteo data) considered in this study—the Cs-137 total ground deposition alone involves the adoption of late countermeasures up to a distance greater than 1.6 × 10+5 m; in fact, the total ground deposition exceeds in all the involved cells the maximum level allowed by the European Union for leaf vegetables (i.e., 2500 Bq/m2) [31].

Fig. 20
Cs-137 Ground deposition map for one point of actual hourly meteo data—RASCAL 4.3
Fig. 20
Cs-137 Ground deposition map for one point of actual hourly meteo data—RASCAL 4.3
Close modal
Fig. 21
Cs-137 Ground deposition map for four points of actual hourly meteo data—RASCAL 4.3
Fig. 21
Cs-137 Ground deposition map for four points of actual hourly meteo data—RASCAL 4.3
Close modal
Fig. 22
Cs-137 Ground deposition maps for constant standard meteo data—RASCAL 4.3
Fig. 22
Cs-137 Ground deposition maps for constant standard meteo data—RASCAL 4.3
Close modal

The computational time required to perform a RC analysis with increasingly detailed meteo data was also evaluated (Table 6). The results showed that also the time required to perform an RC analysis with the more complex meteo dataset (i.e., four actuals meteo data points) is consistent with emergency preparedness activities for which it is crucial to realize a RC analyses in a fast-running mode. Table 7 summarizes the several ST and RC cases analyzed in this study with the associated main parameters options.

Table 6

Time required to perform RC analysis with different set of meteo data

Set of meteorology data Computational time (s)
Standard meteorology (One point of time independent meteo data)2100
NPP site related meteorology (One point of actual 96 h meteo data)2880
NPP site related meteorology (Four points of actual 96 h meteo data)6180
Set of meteorology data Computational time (s)
Standard meteorology (One point of time independent meteo data)2100
NPP site related meteorology (One point of actual 96 h meteo data)2880
NPP site related meteorology (Four points of actual 96 h meteo data)6180
Table 7

Summary of ST and RC cases analyzed with the associate parameter's options

STRC
CaseNuclidesSprayTime frameMeteodataPhysical/dosimetric quantitiesTime frame
1Cs-134, Cs-136, Cs-137, I-131, Kr-85, Pu-238, Ru-106, Sr-90, Y-90No96 hours since the start of the atmospheric emissionStandardTEDE, Thyroid dose,
Cs-137 total ground deposition
96 hours of atmospheric transport
2NoHourly, one point
3NoHourly, four points
4I-131Yes
pH = 4
No RC evaluation
5I-131Yes
pH = 7
6I-131Yes
pH = 10
STRC
CaseNuclidesSprayTime frameMeteodataPhysical/dosimetric quantitiesTime frame
1Cs-134, Cs-136, Cs-137, I-131, Kr-85, Pu-238, Ru-106, Sr-90, Y-90No96 hours since the start of the atmospheric emissionStandardTEDE, Thyroid dose,
Cs-137 total ground deposition
96 hours of atmospheric transport
2NoHourly, one point
3NoHourly, four points
4I-131Yes
pH = 4
No RC evaluation
5I-131Yes
pH = 7
6I-131Yes
pH = 10

4 Conclusions

In this paper, a general methodology to evaluate the RC due to a hypothetical SA scenario at a Fukushima-like SFP was proposed. This methodology can be considered an additional contribution to the intermediate approach research field of the ST and RC codes coupling and it will allow future benchmark studies with the other types of ST and RC codes coupling systems. It also lets to make a more precise evaluation of the RC with respect to the use of a stand-alone radiological impact assessment code because it combines a code specifically designed to estimate the ST during a SA (i.e., ASTEC v2.1) with a validated and widely used fast-running code for RC analysis (i.e., RASCAL 4.3). The preliminary application of this methodology on an Italian cross-border site, where it is hypothesized that a Fukushima-like SFP is positioned, has highlighted the relevant impact of ST temporal dynamic on the final spatial dose distribution. The adoption of increasingly refined meteo datasets (i.e., from standard to four points of hourly meteo data) caused a reduction in the distance from the emission point at which nonnegligible radiological effects could occur. If countermeasures are activated and/or effective to stop the SFP release three days before the emission start, the adoption of a classical mitigation strategy (i.e., spray system) has revealed that a chemically basic environment seems capable of reducing the RC resulting from the major contributors to the dose (i.e., I-131), being I-131 the only radionuclide, among them, to be affected by water pH value in the ASTEC modelization. In the future, this methodology will be applied to a real European SFP placed in one of the Italian cross-border NPP sites, together with actual terrain roughness and morphology data of the site itself, and with time-dependent weather data on more than four points of the geographical domain.

Acknowledgment

The authors would like to thank Dr. Antonio Cervone ENEA researcher of the FSN-SICNUC-SIN laboratory for the support given in obtaining the ERA5 meteo data from the Copernicus online database service.

Funding Data

  • This project has received funding from the Euratom Research and training program 2014–2018 under grant agreement No. 847441 (Funder ID: 10.13039/100018708).

Disclaimer

Views and opinions expressed in this paper reflect only the author's view and the European Commission is not responsible for any use that may be made of the information it contains.

Nomenclature

     
  • ARPEGE =

    action de recherche petite echelle grande echelle

  •  
  • ASTEC =

    accident source term evaluation code

  •  
  • BDBA =

    beyond design basis accidents

  •  
  • BWR =

    boiling water reactor

  •  
  • CESAR =

    primary and secondary cooling system thermoydraulic module of ASTEC code

  •  
  • CP =

    consequence projections

  •  
  • CPA =

    containment thermoydraulic module of ASTEC code

  •  
  • CSS =

    cooling spray system

  •  
  • C3S =

    climate change service

  •  
  • ECMWF =

    European Center for Medium Weather Forecast

  •  
  • ENEA =

    Italian National Agency for New Technologies, Energy and Sustainable Economic Development

  •  
  • ERA5 =

    fifth major global reanalysis data produced by ECMWF

  •  
  • ETEX =

    European tracer experiment

  •  
  • EU =

    European Union

  •  
  • EPA =

    Emergency Protection Agency

  •  
  • FA =

    fuel assembly

  •  
  • FSN-SICNUC-SIN =

    Laboratory for the Safety of Nuclear Installations of ENEA Fusion and Nuclear Security Department

  •  
  • GRS =

    German Gesellschaft für Anlagen und ReaktorSicherheit

  •  
  • ICARE =

    in-vessel core degradation module of ASTEC code

  •  
  • ICRP =

    International Commission on Radiological Protection

  •  
  • IRSN =

    Institute De Radioprotection et De Sûreté Nucléaire

  •  
  • ISODOP =

    isotopes time-dependent activities and decay heat module of ASTEC code

  •  
  • ldX =

    long distance eulerian atmospheric dispersion code

  •  
  • LH =

    lower head

  •  
  • LP =

    lower plenum

  •  
  • MARS =

    Meteorological Archival and Retrieval System

  •  
  • MCCI =

    melting core concrete interaction

  •  
  • MUSA =

    management and uncertainties in severe accident

  •  
  • NPP =

    nuclear power plant

  •  
  • NUGENIA-PLUS A IR-SFP =

    Nuclear GENeration II & III Association: AIR-SFP project

  •  
  • ORIGEN-ARP =

    isotopic depletion and decay analysis code using problem-dependent cross sections generated by Automatic Rapid Processing module

  •  
  • PAG =

    Protection Action Guide

  •  
  • PSA =

    probabilistic safety assessment

  •  
  • PHWR =

    pressurized heavy water reactor

  •  
  • PWR =

    pressurized water reactor

  •  
  • RAMP =

    radiation protection computer code analysis and maintenance program

  •  
  • RASCAL =

    radiological assessment system consequences analysis

  •  
  • RC =

    radiological consequences

  •  
  • RN =

    radionuclide

  •  
  • SA =

    severe accident

  •  
  • SARNET =

    Severe Accident Research NETwork of excellence

  •  
  • SFP =

    spent fuel pool

  •  
  • SOPHAEROS =

    fission product transport module of ASTEC code

  •  
  • ST =

    source term

  •  
  • TEDE =

    total effective dose equivalent

  •  
  • U.S.NRC =

    United States Nuclear Regulatory Commission

Footnotes

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