Large-eddy simulation analysis of turbulence characteristics of atmospheric boundary layers during a diurnal cycle

Hiromasa Nakayama · Takuto Sato · Tetsuya Takemi

In the safety assessment for the construction of nuclear facilities in Japan, wind tunnel experiments or computational fluid dynamics (CFD) are required to estimate spatial distribution of air concentrations of a plume emitted from a stack (Nuclear Safety Commission of Japan, 1982). The experimental or CFD results are used to derive effective stack height, which is applied for long-term assessment using a Gaussian plume model. The effective stack height is often found to be lower than the actual height of the stack, considering terrain and building effects in a way that provides a conservative evaluation. Although reliable data on wind velocity and material concentrations are obtained, the effective stack height is estimated under the assumption of neutral stability.In the atmosphere, heating and cooling within a boundary layer due to solar cycle during a day result in temperature differences, which introduce buoyancy forcing. Plume dispersion within the atmospheric boundary layer is also influenced by roughness elements, terrain, and thermal stability. In terms of thermal stability, atmospheric boundary layers are in general classified into three types; neutral boundary layer (NBL), stable boundary layer (SBL), and convective boundary layer (CBL). In an NBL, turbulence is generated and maintained by wind shear, while in an SBL turbulence is not only maintained by wind shear but also constrained by negative buoyancy. In a CBL, turbulence is mainly produced by shear and/or buoyancy. The most common stability classification scheme is the Pasquill-Gifford (P-G) (Turner, 1970), which defines six stability classes namely A (highly unstable), B (moderately unstable), C (slightly unstable), D (neutral), E (moderately stable), and F (extremely stable). The plume spreads over a flat ground surface in the typical meteorological conditions are determined by the P-G chart. Since atmospheric dispersion behaviors of a plume released from a tall stack are sensitively influenced by atmospheric stability, thermal effects should be incorporated into the effective stack height.In this study, we perform LESs of a diurnal cycle of atmospheric boundary layer (ABL) flows based on the similar computational conditions to Kumar et al. (2006). As a first step, our objective is to investigate the turbulence characteristics of various thermal-stratified ABL flows and classify them based on the P-G chart.

Multi-model ensemble analysis of JRODOS atmospheric dispersion models for nuclear emergency planning

Ramy-Badr Ahmed · Thomas Schichtel · Dmytro Trybushnyi · W. Raskob · Sadeeb Simon Ottenburger

The Real-Time On-Line Decision Support System (JRODOS) is operationally used worldwide to support off-site nuclear emergency management. This study presents a new JRODOS module for emergency planning that combines the JRODOS statistical module, which samples meteorological conditions over extended periods for a given site, with a dedicated post-processing workflow to analyze the outputs of the multiple atmospheric dispersion models integrated in JRODOS. Using the full emergency calculation chain, it derives early-phase protective action areas and applies user-defined thresholds to identify higher-probability zones. The approach is demonstrated for three representative nuclear power plant sites with contrasting terrain, and the resulting site- and model-dependent action areas are compared to assess the influence of model choice on planning outcomes.

Implementation of a GPU-Accelerated Lagrangian Particle Dispersion Model for Atmospheric Transport of Radioactive Nuclides

Qingyun Li · Tao He · Mingye Li · Junfang Zhang · Bing Lian · Liye Liu · et al.

Large-scale atmospheric dispersion model for emergency response to nuclear accidents requires high computational efficiency and numerical reliability. A GPU-oriented Lagrangian particle dispersion model was developed within FLEXPART framework to address these demands. Core transport processes—including advection, turbulent diffusion, convective mixing, and dry/wet deposition—were restructured for GPU parallel execution. Further incorporation of fast arithmetic operators and multi-level parallelization strategies substantially improved overall computational performance while preserving physical accuracy. Additional MPI-based parallel meteorological data decoupling and preprocessing tool has been developed, which alleviates data-handling bottlenecks. Meanwhile, multi-GPU execution and a load-balancing strategy enable efficient scaling in heterogeneous computing environments. Using the first release of European Tracer Experiment (ETEX-I) as a benchmark, the GPU program’s accuracy and acceleration were rigorously evaluated. Results show that, while maintaining nearly comparable accuracy (with relative errors on the order of 10−2), the program achieves an overall speedup of approximately 40.45 on a single-GPU platform, which can be further increased to about 52.05 in high-performance application scenarios where meteorological background fields are reusable. Moreover, multi-GPU experiments reveal favorable parallel scalability across configurations ranging from one to four GPUs, and confirm that the proposed load-balancing strategy effectively enhances computational efficiency in heterogeneous GPU environments.

Analysis of the radiological impact on the Gulf region from an unexpected incident at the Bushehr nuclear power plant

Akbar Abbasi · Mayeen Uddin Khandaker · Fatemeh Mirekhtiary

Atmospheric dispersion and dose assessment of key radionuclides from a hypothetical VVER-1000 accident

Kambiz Kangarlou · Bahman Jalali Kondori · M T Holisaz · Armin Mosayebi · Behshad Valizadeh · Seyed Pezhman Shirmardi · et al.

Abstract In this study, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was utilized to simulate the atmospheric dispersion of major radionuclides including elements of Iodine ( 131 I, 132 I, 133 I, 134 I, 135 I), Cesium ( 134 Cs, 137 Cs), Strontium-90 ( 90 Sr), and Plutonium-239( 239 Pu) following a hypothetical accident at the VVER-1000 reactor (28.82°N, 50.88°E). Meteorological datasets from February, April, August, and October 2023 were incorporated into the model, and the corresponding inhalation and external radiation doses were evaluated using standard dose conversion factors. The simulation results demonstrated that both dispersion behavior and dose magnitude are highly influenced by meteorological parameters and the inherent physical–chemical characteristics of each radionuclide. Among the analyzed elements, 134 Cs exhibited the widest dispersion range, over a 24 h exposure period, the maximum inhalation dose (9.24 Sv) from 134 Cs and the maximum external dose from 131 I (1.28 Sv) were recorded in February. Furthermore, the maximum external dose from 134 Cs (0.22 Sv) was observed in August, and the maximum external dose from 133 I (0.04 Sv) was recorded in April. Incorporating seasonal variability and radionuclide-specific behavior into radiological impact assessments is significant. The results provide a robust scientific foundation for enhancing nuclear safety strategies, developing effective early warning systems, and optimizing emergency response and evacuation planning around nuclear power facilities.

An Integrated Tool Set for Spent Nuclear Fuel Pool Sabotage Assessment: Coupling DEPO-Based Physical Protection Effectiveness with WSPEEDI Consequence Modeling

Hamza El-Asaad

This study presents an integrated methodological framework that couples a physical protection system (PPS) performance assessment with atmospheric dispersion consequence modeling for a hypothetical sabotage scenario involving a spent nuclear fuel pool. The framework has two objectives: (1) to estimate the probability of adversary success using the design and evaluation process outline (DEPO) methodology and (2) to quantify off-site external dose consequences using the worldwide version of the system for prediction of environmental emergency dose information (WSPEEDI). Two U.S. nuclear power plants (South Texas Project and Comanche Peak) are examined as comparative case studies. A one-year meteorological and dispersion database (8760 simulations per site) is used to characterize the variability in the plume transport and deposition and to identify high-consequence scenarios.The results indicate that plausible variations in the PPS response parameters yield adversary success probabilities on the order of 10−1, while meteorological variability produces order-of-magnitude differences in the 4-day integrated external dose, as illustrated by the selected high-consequence realizations. These findings demonstrate that integrating protection effectiveness with consequence modeling provides a structured basis for comparative risk-informed assessments of spent fuel pool security vulnerabilities.

Particulate dispersion characteristics in the atmospheric boundary layer: Unraveling the effects of wind velocity profile and thermal stability

Deyi Chen · Baojie Nie · D Z Wang

Artificial Intelligence for the Determination of Factors Affecting Atmospheric Dispersion of Radionuclides, the Potential Concentration of Pollutants Downwind of a Source, to Study the Risk for Any Nuclear Facility

O.S. Ahmed · Hekmat Elbegawy · Khaled A Salman

Objectives The study’s primary goal is to use artificial intelligence programs to determine the factors influencing radionuclide atmospheric dispersion and the potential concentration of a pollutant downwind of a source.. Material and Methods These programs can provide information about atmospheric dispersion and determine the potential concentration of a pollutant downwind of a source, which is typically used to study risk analysis, emergency planning, and comprehension of the pertinent atmospheric dispersion in the study of radiological impact on man and his environment. Results The analysis demonstrated that the results of the artificial intelligence program’s atmospheric stability class correspond with the Pasquill-Guifford scheme and that the concentration of pollutants in the atmosphere is directly related to air quality, Our results for this work are shown with application. Conclusion As demonstrated by the application of artificial intelligence software tools, the concentration of pollutants decreases as the distance above ground increases at constant parameters like emission rate and height above ground. Finally, from the author’s point of view, recommended this work is used as training.

Identification and verification of worst-case radiological transport scenarios for Ireland: A simulation-based approach to nuclear emergency preparedness (2011–2024)

Marc Sturrock · Robert Ryan · Kevin Kelleher

This study presents a comprehensive simulation-based assessment of potential transboundary radiological transport to Ireland from six nuclear facilities in the United Kingdom and France, utilising weather data over a fourteen-year period (2011-2024). Systematic screening of 2.2 million HYSPLIT atmospheric dispersion simulations identified eighteen worst-case scenarios representing maximum ground deposition, maximum air concentration, and minimum warning time. Independent verification using FLEXPART and HYSPLIT demonstrated expected inter-model variability (factor of 1-10), with both Lagrangian models providing consistent risk assessment brackets. Heysham, despite its complex 19-isotope AGR source term, produced negligible radiological doses to Ireland (<0.01 mSv), substantially below intervention thresholds. More distant continental facilities (Flamanville, Paluel, Sizewell B) showed low but measurable doses (0.1-4.6 mSv), remaining well below the 50 mSv sheltering threshold. This study addresses urgent-phase protective actions only; transitional-phase food chain countermeasures are beyond scope. Hinkley Point C (under construction) showed elevated but sub-threshold doses (0.3-8.5 mSv). However, the cancelled Wylfa Newydd gigawatt-scale project (the site is now proposed for small modular reactors), owing to its extreme proximity to Ireland, exhibited concerning dose predictions: FLEXPART calculated 19.6 mSv under maximum deposition conditions (May 2024 scenario), approaching the 50 mSv sheltering threshold, whilst HYSPLIT predicted 4.5 mSv. This inter-model variability (factor of ∼5) highlights genuine uncertainty for near-source impacts but converges on a critical finding: were a gigawatt-scale reactor constructed at the Wylfa site, severe accidents during specific meteorological patterns could require protective actions in Ireland. Machine learning models (XGBoost) achieved validation accuracies of 85-93% for rapid impact prediction, whilst global sensitivity analysis revealed that meteorological conditions, rather than release parameters, dominate consequence severity. These findings provide quantitative assurance that existing nuclear infrastructure poses low transboundary risk to Ireland well below urgent-phase intervention thresholds (sheltering and evacuation), whilst demonstrating that facility proximity constitutes the dominant factor determining potential radiological impact.

Post-accident radiological impact evaluation for small modular reactor and commercial nuclear power plants in Estonia

Krislin Sartakov · Siiri Salupere · Marti Jeltsov

Off-site risk area delineation under severe nuclear accident conditions: A deterministic-probabilistic coupled consequence analysis

Shengyu Liu · Hongchun Ding · Alice Hu · Guohua Wu · Sheng Fang · wei wang

Uncovering hidden dispersion patterns of radioactive cesium-rich microparticles from Fukushima Daiichi

Kanako Miyazaki · Kazuki Fueda · Masanao Kadowaki · Hiroaki Terada · Naofumi Kozai · Hajime Iwata · et al.

Plume modelling and estimation dose of airborne radioactivity at nuclear facility

Rizky Ilham Fadzillah · Eka Karunia Putri · Gadis Ananda Dinanti Handoko · Hilya Milatul Rosyidah · Suryo Wiroyudho Wibowo · Nanda Fista Elasari · et al.

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Courtney Otani · Robby Christian · Wen-Chi Cheng · Kurt Vedros

<ns5:p>Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.</ns5:p>

Predicted DBA Doses Versus Fukushima Accident Doses: A Comparative Analysis

Igor Sarygin · Richard Brey

This study evaluates the conservatism inherent in U.S. Nuclear Regulatory Commission (NRC) design-basis accident (DBA) modeling by comparing predicted radiological dose consequences for a boiling water reactor loss-of-coolant accident with empirical dose measurements from the Fukushima Daiichi nuclear accident. Dose consequence estimates were generated using bounding source term assumptions and methodologies from NRC Regulatory Guide 1.183, combined with atmospheric dispersion factors calculated in accordance with NRC Regulatory Guide 1.145.Benchmarking was performed by comparing the modeled results against empirical dose estimates reported in the U.S. Department of Defense Defense Threat Reduction Agency (DTRA) Operation Tomodachi studies of military personnel exposures. Tables 2, 3, and 4 summarize the key data sets: Table 1 presents calculated Dose Assessment and Recording Working Group (DARWG) site-specific X/Q values, Table 2 lists the calculated DBA doses for external exposure and inhalation, and Table 3 provides corresponding empirical DARWG dose measurements.The results demonstrate a pronounced conservatism in NRC DBA predictions. For instance, at Sendai Airport (50 miles from the Fukushima Daiichi Nuclear Power Plant), the modeled DBA inhalation dose (275.14 mSv) was approximately 47 times greater than the measured value from DTRA assessments (5.9 mSv). This disparity underscores the value of integrating real-world accident data into regulatory modeling to maintain robust safety margins while improving realism, regulatory efficiency, and public confidence.

Global transport of 131I and 137Cs released into the atmosphere from the Fukushima nuclear accident

Kyung-Suk Suh · Kihyun Park · Byung-Il Min · Sora Kim · Yoomi Choi · Jiyoon Kim · et al.

An atmospheric dispersion model was used to assess the global transport and deposition of 131 I and 137 Cs released into the air during the Fukushima accident in 2011. Simulations results showed that the radionuclides traveled eastward across the Pacific by the westerlies. The radioactive plume estimated to reach the U.S. West Coast approximately 5 days after the accident, Europe after about 12 days, and Mongolia and China after around 16 days. It subsequently dispersed across the entire Northern Hemisphere approximately within 17 days. The calculated concentrations of radionuclides were generally consistent with observations, including monitoring data from CTBTO and Korea. A substantial portion of the released radionuclides was deposited into the Pacific Ocean, with about 54% of 131 I and 76% of 137 Cs settling on the sea surface. Further analysis confirmed that the 137 Cs detected in seawater samples from the central Pacific and U.S. West Coast in April and May 2011, originated from atmospheric deposition onto the ocean rather than direct release into the sea from the Fukushima accident.

Inverse estimation of size-distribution parameters of emitted aerosols following the Fukushima accident using FLEXPART simulations and measurements

Kyung Tae Jung · Jong-Hoon Kim · Ivan Kovalets

The size distribution (SZ) of radioactive aerosols emitted after nuclear accident at nuclear power plants plays a crucial role in assessment of the subsequent atmospheric transport and deposition. However, in reality this distribution in the source is usually unknown. The SZ of particles in the plume also changes with travel time of the plume, because the coarser particles fall out more rapidly than the finer particles. Hence when the measurements of SZ are undertaken at certain distances from the source the SZ could be already altered by plume travel time while it is SZ in the source which is required by atmospheric transport models (ATMs) for simulation of radionuclides atmospheric dispersion and deposition. Also, SZ measurements are usually not available in real time during the accident. More readily available measurements are airborne concentrations. Hence when concentration measurements are available, the SZ parameters of ATMs could be fitted to achieve better agreement between model and measurements. In this work, the inverse problem is stated to identify the optimal set of size distribution parameters of the Fukushima source term – activity-averaged mean aerodynamic diameter (d) and geometric standard deviation (σ) which best fit results of FLEXPART ATM to both, local and global measurements datasets. The problem is formulated as multi-objective optimization in which two objective functions. The first objective function J1 corresponds to model deviations from measurements in the territory of Japan, while the second objective function J2 corresponds to model deviations from the global observations of CTBTO measurement stations. The combined cost function J=J1J2 , characterizing model deviation against measurements in both datasets was also considered. In this way, the estimate of the unknown SZ parameters, which fits both local and global concentration observations is to be found. The method of finding Pareto solution of such multi-objective optimization problem was developed and preliminary results of comparisons of the estimated SZ parameters with SZ measurements, performed following Fukushima accident were obtained. The solution of the stated problem leads to reasonable results. The simulations with small values of 1≤σ≤2 led to excellent agreement of estimated mean aerodynamic diameter d of emitted particles between 2 and 3 μm with available measurements of SZ. At the same time if large values of σ were allowed the resulting estimated mean aerodynamic diameter could significantly deviate from the observed values. The use of the small values of mean aerodynamic diameter (d

Investigating nuclear events and vector borne disease risk through atmospheric dispersion modelling with HYSPLIT

S. McKeague · Klara Finkele · Saji Varghese

As a part of the Agricultural Meteorology research unit at Met Éireann, atmospheric dispersion modelling (ADM) is used to investigate and provide forecast for emergency and risk awareness networks. ADM is performed computationally to create mathematical simulations of the transport and dispersion of particles in the atmosphere. At present, Met Éireann uses the HYSPLIT program in order to calculate and model the trajectory and concentrations of airborne pollutants. HYSPLIT allows for a high degree of customization of the pollutant source terms, which enables dispersion modelling estimations of emission from both man-made and natural sources of interest, including but not limited to nuclear release, smoke, small insects and pollen. This can be used to predict future concentrations, depositions and arrival times of particles under specific scenarios.Met Éireann currently acts in support of the EPA for nuclear dispersion modelling, in the event of an emergency. We provide daily meteorological forecast data to the EPA and, as a part of the Response and Assistance Network (RANET), can provide additional modelling during an event if requested. We participated with the EPA during the ConvEx-3 exercise in 2025, simulating a nuclear emergency in Romania, to test our communication and dispersion modelling capabilities. Our communications during the event were responsive and modelling results across multiple programs agreed. The experience of the exercise will be used in the development of ensemble dispersion modelling pipelines for future events.Met Éireann also runs an operational daily forecast of Bluetongue virus, which is based on dispersion modelling the possible transport of the insect that act as the vector. This is provided to relevant agricultural stakeholders, particularly in close collaboration with UCD and DAFM. As climate change continues, a range of pests and possible disease vectors that were either previously unknown to Ireland or inactive at certain times of the year could potentially harm native species of plants &amp; animals. This may necessitate further research and expansion of the current dispersion work on forecasting possible pest or disease vector risks.

Modeling of the Radiological Atmospheric Dispersion and Consequences of Hypothetical Nuclear Accident at an Coastal Site using MACCS2 Code

O.S. Ahmed · Hekmat Elbegawy · Gehan Y. Mohamed

Objectives In order to determine the atmospheric diffusion coefficient (χ/Q) and assess the radiation dosage resulting from a hypothetical release of iodine-131 under stable atmospheric conditions (stability class E), this study will model the atmospheric diffusion of radioactive contaminants using the MACCS2 tool. Material and Methods The MACCS2 code was used to perform atmospheric diffusion simulations under atmospheric stability class E, examining how wind speed and distance from the emission point affected the relative air concentration. The diffusion coefficient (χ/Q) reached its maximum value of 3.67E−03 s/m 3 at a wind speed of 0.5 m/s and a distance of 100 m. This value was entered into the Total Effective Dose Equivalent (TEDE) calculation. Four age groups were included in the study: adults who worked outside, adults who worked indoors or retired, children (10 years old), and (1 year old). Results The maximal effective dose (TEDE) of I-131 was found to be 9.38 E−07 TEDE for adults outside, 8.26 E−07 TEDE for adults indoors, 5.68 E−07 TEDE for children (10 years old), and 1.93 E−07 TEDE for newborns (1 year old) in stability class E at a wind speed of 0.5 m/s and a distance of 100 m. It was also demonstrated that as wind speed and distance increased, the concentration and dose levels decreased. The International Atomic Energy Agency’s recommended yearly occupational exposure limit of 2 E−02 TEDE was far below all computed values. Conclusion The results indicate that the hypothetical scenario for stable atmospheric condition (E) does not result in doses that are higher than those that are internationally permitted limits. The study underscores the importance of using the MACCS2 code in assessing radiological consequences and supporting control and safety decisions at nuclear facilities.

Study on flow and turbulence characteristics measured by an on-site meteorological station at a nuclear facility for a real-time atmospheric dispersion simulation

Hiromasa Nakayama · Takaaki Kono · Takuto Sato

We have been developing a practical and quick high-resolution atmospheric dispersion simulation model for radioactive plumes monitoring in the vicinity of nuclear facilities. This framework is composed of large-eddy simulation precalculated database of three-dimensional distributions of wind velocities and on-site meteorological observations at a stationary point. The LES-database was created under the assumption of a neutral atmospheric stability condition from a practical point of view. Since atmospheric dispersion behaviors of a plume released from a stack are sensitively influenced by atmospheric stability, the thermal effects should be incorporated into the LES-database. In this study, we first analyzed half-a-year meteorological data of turbulence intensity and atmospheric stability at the target nuclear facility, and then investigated the turbulence intensities under different atmospheric thermal stability conditions for improving the framework of the real-time high-resolution atmospheric dispersion simulation.