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DOE OSTI2023

Preliminary Neutronics Design and Analysis of the Fast Modular Reactor

General Atomics is developing a new 100-MW(thermal) fast modular reactor (FMR) that provides safe, carbon-free electricity and is capable of incremental capacity additions. The modular design allows it to be factory built and assembled onsite to keep the capital cost low, while the use of dry cooling facilitates siting to complement renewables in nearly any location. The FMR uses high-assay low-enriched uranium-dioxide fuel encapsulated by recognized irradiationresistant silicon carbide composite (SiGA®) cladding that is derisked in the current accident-tolerant fuel program. The FMR fuel assembly is a hexagonal fuel bundle of 120 fuel rods. The total length of the fuel assembly is less than 4 m, with an active fuel length of 1.8 m. The fuel assemblies are configured in an annular core that is located and supported by the reactor internals. The coolant material is helium at a normal operating pressure of 7 MPa. The core is surrounded by zirconium silicide (Zr 3 Si 2 ) and graphite reflector blocks. The fuel, coolant, internals, and reflectors are contained within a reactor pressure vessel. Here, the preliminary nuclear design and analysis established the arrangement of the active core and reflector blocks. The nuclear design analyses of the FMR defined the design parameters, such as fuel enrichments, excess reactivity, fueling scheme, fuel cycle, power distribution, and control rod worth. The preliminary conceptual design determined the three-batch fueling scheme with the allowable total power peaking factor of 1.5. The average discharge burnup is 100 GW days per ton of uranium.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Morphological Characterization of Uranyl Fluoride Particles via Atomic Force Microscopy

Uranium hexafluoride (UF 6 ) undergoes a rapid hydrolysis reaction when exposed to atmospheric water. In addition to producing hazardous HF gas, the hydrolysis reaction produces uranyl fluoride (UO 2 F 2 ), a radioactive solid phase particulate material. Because of the technological utility of UF 6 in the nuclear fuel cycle, understanding the transport properties of UO 2 F 2 aerosol produced via UF 6 hydrolysis is important for accident scenarios. Moreover, the fundamental chemical and physical properties of the UF 6 hydrolysis reaction are not completely understood. Recently, several experiments on the aerosol phase properties of UO 2 F 2 produced in this way have shown that under most relevant conditions, the particle size distribution (PSD) of UO 2 F 2 can be extremely small, approximately 3 to 5 nm, which is well below the threshold that can be routinely observed via scanning electron microscopy (SEM). Although readily observable in the aerosol phase, observation of nanometer-sized particles in the condensed phase (i.e. deposited on surfaces) remains a challenge. Here, in this study, we have used atomic force microscopy (AFM) to study the PSD and morphological characteristics of UO 2 F 2 deposited at low and high concentrations under different humidity conditions, a primary variable in the hydrolysis reaction. Here, we find strong agreement between PSD measured in the aerosol phase via scanning mobility particle sizing and PSD measured via AFM, with particle sizes peaked below 4 nm for low-humidity conditions. At higher humidity, the distribution is centered around 5 to 10 nm but extends up to 20 nm. These results are in stark contrast to previous measurements using SEM that show PSD on the order of 300- to 1000-nm particle sizes; moreover, these are the first direct measurements of individual particles of UO 2 F 2 having been produced via UF 6 hydrolysis deposited on surfaces. These measurements, therefore, open a new avenue for collecting and detecting UO 2 F 2 in the condensed phase and further refine the PSD, which is critical for environmental transport determinations.

Uranium hexafluoride↗

DOE OSTI2025

Introduction, Investigation, and Experimental Validation of a Novel Passive Neutron Spectrometer

Unfolding neutron energy spectra are instrumental for determining personal health effects and calculating dose received. This area of study is heavily researched, and Lawrence Livermore National Laboratory (LLNL) is investigating a passive neutron spectrometer for the purpose of acquiring the information needed to determine personnel dose in the event of a criticality accident. A part of this investigation is presented in this article through the examination of four experimental detector responses (DRs). These four DRs were acquired in the presence of 252 Cf, AmBe, GODIVA, and National Ignition Facility (NIF) neutron sources. An algorithm developed at LLNL was used to unfold the neutron fluence from each of the four DRs, and subsequently, fluence-to-dose conversion factors provided by the American National Standards Institute were used to calculate dose. Additionally, a multistep unfolding process was developed and employed to calculate the effects of both direct (from the source) and indirect (from room return) neutrons. The average error when unfolding the direct DR was less than 8%. The dose from 252 Cf was predicted with only 8% error. The multistep approach allowed for the identification of the low-energy neutrons in the 252 Cf, AmBe, and NIF DRs.

Nuclear Criticality Safety Program (NCSP)↗

DOE OSTI2025

Dynamic Modeling of a Fast Spectrum Molten Salt Reactor Integrated Energy System

Liquid-fueled molten salt fast reactors and nuclear-powered integrated energy systems (IESs) have the potential to play a pivotal role in the green energy transition. However, these systems have little to no operating experience. There is therefore increased interest and value in modeling and simulating these systems. The IES dynamic model developed in this work utilizes a lumped-parameter control volume methodology to investigate the behavior of the IES in a variety of accident scenarios. The results provide initial evidence for the potential inherent safety of the advanced reactor because of temperature-dependent reactivity feedback and the efficiency of hydrogen and electricity production at the high temperatures provided by the advanced reactor.

MCFR↗

DOE OSTI2025

Identification of Important Phenomena for Light Water Reactors During Heat Transport System Failure Events in Integrated Energy Systems

This work adapts historical literature and existing phenomena identification and ranking tables (PIRT) to be applicable to a novel nuclear power plant (NPP) and chemical or thermal process integrated energy system (IES), particularly focusing on the process heat and heat transport system failure events that are not a concern during normal NPP operation but become vital when an IES is considered. Nuclear energy has been suggested to go beyond base-load applications and be used for hydrogen co-generation systems, amongst other IESs. Prior to the implementation of nuclear IESs, sufficient analysis must be performed on accident events to ensure public safety. The events considered were deemed important because of their potential to damage systems, structures, and components (SSCs). Process thermal events of concern include loss of heat load and temperature transient events. Loss of heat load events were characterized as having high importance and being well understood. Temperature transient events may be further categorized by the cyclic loading and harmonics phenomena. Cyclic loading issues were classified as medium to high importance with knowledge gaps existing regarding fatigue and low power operation, while harmonics phenomena were classified as low importance and are well understood. Heat transport system failure events of concern include intermediate and process heat exchanger failures, mass addition to reactor coolant, ingress of material from thermal manifold/energy storage, and loss of intermediate fluid. Furthermore, these events tended to be of high or medium importance, with some knowledge gaps needing to be filled for individual reactor systems due to unique designs.

Integrated Energy System (IES)↗

DOE OSTI2025

An Evaluation and Qualification of U.S.-Based Research Reactors for Irradiation Capabilities Supporting Advanced Nuclear Systems

Irradiation experiments are a prerequisite for evaluating nuclear reactor system designs, analyzing the performance of these systems, and obtaining licenses. Likewise, irradiation facilities are necessary for producing the radioisotopes used in industrial and medical applications. Recent developments in modeling and simulation capabilities and advancements in computational resources have further enabled the design of irradiation experiments for evaluating radiation-induced phenomena and determining nuclear fuel, material, and system design and safety criteria pertaining to both normal and accident scenarios. These computational tools and models require comprehensive experimental datasets acquired under prototypic radiation conditions—for exploring material and system performance under the uniquely harsh environments found in nuclear reactors—to enable verification and validation for qualification and licensing purposes. However, qualification of irradiation experimental facilities, primarily research and test reactors (RTRs), necessitates that their performance be evaluated based on the irradiation environment (e.g. flux, power, testing capabilities) using an appropriate scoring matrix. Although many university campus RTRs are available for research and development (R&D) activities and initiatives, this study focuses on evaluating and qualifying the irradiation facilities (mostly RTRs) within the United States that are suitable for advanced nuclear fuel, material, and system irradiation experiments aimed at establishing operational-performance limits and informing component and fuel designs so as to improve operational efficiencies and mitigate proliferation vulnerabilities, as well as for radioisotope production aimed at multipurpose applications. As a result, the findings of the present study support the acceleration of nuclear fuel and material qualifications, thus hastening new and advanced nuclear energy system demonstrations and radioisotope production efforts by using extended R&D.

irradiation experiment↗

DOE OSTI2023

Coupling Shared E-scooters and Public Transit: A Spatial and Temporal Analysis

The integration of shared e-scooters with public transit is a promising solution for urban mobility's first/last-mile challenge. This study explores spatiotemporal factors influencing this integration, using 35-day e-scooter trip data from Chicago. Employing a random-effect negative binomial approach, we modeled the frequency of e-scooter trips to access/egress to/from bus stops and train stations. Results indicate that weather conditions, design features like intersection density, and multimodal network density significantly influence usage. The transit system characteristics such as service frequency have a positive effect on the integration of e-scooters and trains while a similar effect for bus and e-scooter integration was not significant. Furthermore, safety-related variables such as accident and crime rates as well as demographic characteristics were also revealed to be significant factors in our study. These findings offer vital insights to urban planners and policymakers for infrastructure, safety enhancements, and interventions to encourage efficient e-scooter-public transit integration.

Chicago↗

DOE OSTI2022

Urban working groups in the IAEA’s model testing programmes: overview from the MODARIA I and MODARIA II programmes

The IAEA’s model testing programmes have included a series of Working Groups concerned with modelling radioactive contamination in urban environments. These have included the Urban Working Group of Validation of Environmental Model Predictions (1988–1994), the Urban Remediation Working Group of Environmental Modelling for Radiation Safety (EMRAS) (2003–2007), the Urban Areas Working Group of EMRAS II (2009–2011), the Urban Environments Working Group of (Modelling and Data for Radiological Impact Assessments) MODARIA I (2013–2015), and most recently, the Urban Exposures Working Group of MODARIA II (2016–2019). The overarching objective of these Working Groups has been to test and improve the capabilities of computer models used to assess radioactive contamination in urban environments, including dispersion and deposition processes, short-term and long-term redistribution of contaminants following deposition events, and the effectiveness of various countermeasures and other protective actions, including remedial actions, in reducing contamination levels, human exposures, and doses to humans. This paper describes the exercises conducted during the MODARIA I and MODARIA II programmes. These exercises have included short-range and mid-range atmospheric dispersion exercises based on data from field tests or tracer studies, hypothetical urban dispersion exercises, and an exercise based on data collected after the Fukushima Daiichi accident. We report improvement of model capabilities will lead to improvements in assessing various contamination scenarios (real or hypothetical), and in turn, to improved decision-making and communication with the public following a nuclear or radiological emergency.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2022

Assessment of doses in contaminated urban areas: modelling exercise based on Fukushima data

State-of-the-art dose assessment models were applied to estimate doses to the population in urban areas contaminated by the Fukushima Daiichi Nuclear Power Plant accident. Assessment results were compared among five models, and comparisons of model predictions with actual measurements were also made. Assessments were performed using both probabilistic and deterministic approaches. Predicted dose distributions for indoor and outdoor workers from a probabilistic approach were in good agreement with the actual measurements. In addition, when the models were applied to assess the doses to the representative person, based on a concept recommended by the International Commission on Radiological Protection and in the International Atomic Energy Agency Safety Standards, it was evident that doses to the representative person obtained with a deterministic approach were always higher than those obtained with a probabilistic approach using the same model.

dose assessment↗

DOE OSTI2024

Transfer functions for Q A /Q B international regulatory limits for the safe transport of radioactive materials

This paper presents a proposed revision of the International Atomic Energy Agency transport regulations, related to the A 1 and A 2 limit values used to determine the radioactive transport classification. Based on the 'Q system', a novel methodology was introduced to derive Q A and Q B values related to scenarios involving external exposure from a distant source. These values are key parameters that respectively represent the total effective dose and total equivalent dose to the skin, from all primary and secondary particles contributing to radiation exposure. The International Working Group (WG A 1 /A 2 ) is established and associated with the TRANSSC Technical Expert Group on Radiation Protection. A review of the A 1 and A 2 values is performed in response to identified limitations within the existing Q system. The followed approach is based on Monte Carlo simulations that enabled the development of transfer functions aimed at reducing computational time and increasing the flexibility of dose evaluations for any radionuclide with known particle emission spectra. This method allows updating the Q A and Q B values to account for future data evolutions (decay data, fluence-to-dose conversion coefficients) and standardizing the calculation of regulation limits across all referenced radionuclides and scenarios related to external exposure. The transfer functions are established using three Monte Carlo simulation codes—FLUKA, Geant4, and MCNP—and address the previous limitations of the 'Q system', reflecting the latest International Commission for Radiation Protection recommendations and improvements in calculation techniques. The results of the WG show consistent agreement across the codes, with minor discrepancies observed at low primary energies due to statistical uncertainties and different handling of stopping power for electrons/positrons in the codes. This revised approach aligns with current standards and recommendations, ensuring that the radiological consequences of transport accidents are acceptable for the new A 1 and A 2 limits from a radiological protection perspective.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2025

Development of advanced vacuum technologies for extending plasma pulse duration on EAST

Advanced vacuum technologies, including pumping, fueling and wall conditioning, have been successfully developed or upgraded to efficiently control the fuel and impurity particles to extend the plasma pulse duration in the experimental advanced superconducting tokamak (EAST). To improve the particle exhaust rate cryopumps with a 60% increase in pumping speed and ∼2 times increase in saturation capacity have been developed, and molecular pumps with a ∼30% increase in pumping speed have been upgraded. In order to monitor the molecular pump status while avoiding bearing faults and overload accidents, a fault detection system has been built which can offer an early warning to avoid more losses within the fusion device. A series of fueling technologies have been developed including gas injection system, supersonic molecular beam injector, pellet injector (PI), massive gas injector and shattered pellet injector, installed at the midplane and divertor positions at different ports to improve fueling uniformity and efficiency. Meanwhile, routine wall conditioning such as electric and hot N 2 baking, ion cyclotron wall conditioning and glow discharge cleaning have been successfully developed to remove the impurity particles from the inner component and materials. The low Z material wall coating and real-time powder injection during plasma discharge are also designed and applied to further improve particle control capability. Finally, by using these advanced vacuum related technologies, good vacuum (<2 × 10 −6 Pa) and wall conditions are realized, and the fuel and impurity particles can be effectively and stably controlled, which promotes the achievement of the record plasma of ∼1056 s pulse duration with the line-averaged electron density of 1.8 × 10 19 m −3 on EAST. They provide a very important reference for vacuum system design and operation for future fusion devices.

EAST↗

DOE OSTI2025

Toward machine learning interatomic potentials for modeling uranium mononitride

Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale modeling of UN at finite temperatures. We constructed a training set using density functional theory (DFT) calculations that was enriched through an active learning procedure, and two neural network potentials were generated. Both potentials successfully reproduce key thermophysical properties of interest, such as temperature-dependent lattice parameter, specific heat capacity, and bulk modulus. We also evaluated the energy of stoichiometric defect reactions and defect migration barriers and found close agreement with DFT predictions, demonstrating that our potentials can be used for modeling defects in UN. Additional tests provide evidence that our potentials are reliable for simulating diffusion, noble gas impurities, and radiation damage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Spatiotemporal predictions of toxic urban plumes using deep learning

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic plumes by solving fluid dynamical equations. However, these models can be computationally expensive due to the need for many grid cells to simulate turbulent flow and resolve individual buildings and streets. In emergency response situations, alternative methods are needed that can run quickly and adequately capture important spatiotemporal features. Here, we present a novel deep learning model called ST-GasNet inspired by the mathematical equations that govern the behavior of plumes as they disperse through the atmosphere. ST-GasNet learns the spatiotemporal dependencies from a limited set of temporal sequences of ground-level toxic urban plumes generated by a high-resolution large eddy simulation model. On independent sequences, ST-GasNet accurately predicts the late-time spatiotemporal evolution, given the early-time behavior as an input, even when a building splits a large plume into smaller plumes. By incorporating large-scale wind boundary condition information, ST-GasNet achieves a prediction accuracy of at least 90% on test data for the entire prediction period.

Civil and Environmental Engineering↗

DOE OSTI2020

Chelation Modeling: The Use of Ad Hoc Models and Approaches to Overcome a Dose Assessment Challenge

Here, chelating agents are administered to treat significant intakes of radioactive elements such as plutonium, americium, and curium. These drugs may be used as a medical countermeasure after radiological accidents and terrorist acts. The administration of a chelating agent, such as Ca-DTPA or Zn-DTPA, affects the actinide's normal biokinetics. It enhances the actinide's rate of excretion, posing a dose assessment challenge. Thus, the standard biokinetic models cannot be directly applied to the chelation-affected bioassay data in order to assess the radiation dose. The present study reviews the scientific literature, from the early 1970s until the present, on the different studies that focused on developing new chelation models and/or modeling of bioassay data affected by chelation treatment. Although scientific progress has been achieved, there is currently no consensus chelation model available, even after almost 50 y of research. This review acknowledges the efforts made by different research groups, highlighting the different methodology used in some of these studies. Finally, this study puts into perspective where we were, where we are, and where we are heading in regards to chelation modeling.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Internal Radiation Dose Evaluation For An Unruptured Post Release Tristructural Istropic Fuel Particle for Advanced and Micro-reactor Applications

There are unique benefits from advanced/micro reactor designs and fuel types that offer safety features in the case of an accident that may reduce environmental consequences compared to conventional reactors and fuels. Several micro reactor designs, for both civilian and military applications, are proposed using tristructural-isotropic (TRISO) fuel. TRISO particles are a robust advanced nuclear fuel type that leads to the unique question of how unruptured, activated TRISO particles will interact with humans. Human exposure to nuclear fuel, or radionuclides, includes all pathways of exposure. However, TRISO particles are 0.9 mm in size, and that particle size restricts internal dose assessment to the ingestion pathway; eliminating the inhalation and dermal absorption pathways. Furthermore, activity of the TRISO particle was established by High Temperature Engineering Test Reactor simulations assuming the TRISO particle was one day post-release from the reactor. International Commission of Radiological Protection publications 100 and 133 were used to develop the internal dosimetry model for an unruptured TRISO particle for the International Commission of Radiological Protection reference male and female dose assessment. The rectosigmoid colon had the highest internal organ dose for both reference male (2.1 Sv) and reference female (2.3 Sv). The internal dose from ingestion of the scenario-defined TRISO particle was 0.25 Sv for the reference male and 0.29 Sv for the refence female, which exceeds the annual occupational effective dose limit of 0.05 Sv in the code of federal regulations, 10.CFR.20 Subpart C.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2023

Examination of decay heat measurements and their relevance for understanding the origin of the reactor antineutrino anomaly

Measurements of the decay energy released as a function of time following the thermal neutron induced fission of 235 U and 239,241 Pu were performed in the 1970s at Oak Ridge National Laboratory with the purpose of quantifying possible loss of coolant accident scenarios. The derivative of this decay energy with respect to time, known in technical parlance as decay heat, is mainly composed of two terms, that of the electrons produced together with antineutrinos in the $β$-minus decay of the neutron-rich fission products, and that of the $γ$ rays produced in the subsequent decay of excited nuclear levels. In this work we study if this extensive set of decay energy measurements can be used to assess the reactor antineutrino anomaly, that is, the approximately 5% deficit of electron antineutrinos produced by nuclear reactors, first deduced by Mention and collaborators in 2011, and observed by the major reactor antineutrino experiments since. Furthermore, with the assistance of nuclear databases, we are able to obtain the ratio of electron spectra under equilibrium conditions for 235 U to 239 Pu, in better agreement with the lower trend recently reported by Kopeikin and collaborators, as well as those for 235 U to 241 Pu and 241 Pu to 239 Pu, which do not agree well with those measured at the Institut Laue-Langevin in the 1980s. We conclude that a new experimental campaign is needed to measure the electron spectra utilizing a high resolution and signal-to-noise-ratio electron spectrometer and a highly precise fission normalization procedure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Driver Distraction Behavior Detection using a Vision Transformer Model based on Transfer Learning Strategy

Driver distraction behavior is one of the critical factors in traffic accidents. Thus, advanced driver state detection system has become the focus in the field of intelligent vehicle. However, in practical applications, insufficient samples of driving distraction behaviors bring great challenges to training a personalized behavior distraction detection model for a specific driver. To this end, a novel transformer model based on a transfer learning strategy is proposed in this paper to accurately recognize driver distraction behavior. Inspired by the effect of the transformer network in visual recognition, we firstly present a transformer behavior distraction detection system to identify the behavior categories that cause driver distraction. Then, for the specific driving dataset in practical application scenarios, the transfer learning strategy is introduced into the driver distraction detection model to further train the general transformer network. The effectiveness of the transformer based on the transfer learning strategy is validated compared with other traditional deep learning methods. The results show that the proposed detection method has better generalization ability and higher accuracy.

Fang, Zhenwu↗

DOE OSTI2023

HCPerf: Driving Performance-Directed Hierarchical Coordination for Autonomous Vehicles

The rapid development of autonomous driving poses new research challenges to the on-vehicle computing system. In particular, the execution time of autonomous driving tasks highly depends on the specific driving environment. For instance, the execution time of configurable sensor fusion increases significantly as the scene becomes complex, which leads to end-to-end deadline misses from sensing to control and may cause accidents. Thus, a framework that can effectively utilize the system resources to guarantee the end-to-end deadlines of autonomous driving tasks as well as effectively prioritize the responsiveness and throughput of the control commands is crucial for autonomous driving. In this paper, we propose HCPerf, a performance-directed hierarchical coordination framework that intelligently coordinates the autonomous driving tasks with high execution time variation and complex dependencies according to the driving performance in real-time. Specifically, HCPerf mainly consists of two coordinators. The internal coordinator intelligently schedules the tasks according to the driving performance of the vehicle in order to help them meet the end-to-end deadlines while well prioritizing the responsiveness and throughput of the control commands. At the same time, the external coordinator dynamically tunes the rates of tasks according to the schedulability in order to efficiently utilize the system resource. We conduct extensive experiments on both simulation and hardware testbeds with the representative autonomous driving application. The results show that HCPerf can effectively improve the driving performance by 7.69%-45.94% in different driving scenarios.

Ma, Jialiang↗