PoL Badge: Detecting Insider Threat Activities as well as Deviation from Workplace Patterns-of-Life (PoL) in Nuclear Reactor Facilities using Affordable Privacy-preserving Smart Badging
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Nuclear reactor digital twins (DTs) have been proposed for use as a safeguards technology to efficiently monitor new and novel reactors as they come online. A safeguards DT needs to be capable of detecting misuse and diversion as they occur, requiring physics models to be accurate and efficient. Mathematical surrogate models are capable of achieving the necessary efficiency and can largely maintain the accuracy of higher-order models given a quality training sample. The Multiphysics Object-Oriented Simulation Environment (MOOSE) code framework is specifically equipped to generate training samples and create surrogate models using full-order reactor physics models. Utilizing an operational AGN-201M reactor’s specifications, two surrogate types were trained on samples of variable size, and using Cartesian products, Latin hypercube sampling, and quadrature sampling, each was compared and evaluated on accuracy when compared to a full-order Monte Carlo model. Both surrogate types were able to capture reactivity changes within 0.05 $ of the Monte Carlo model while reducing the computation costs by eight orders of magnitude.
Nuclear light bulb reactor propellant duct absorption of thermal radiation and simulation experiments
Nuclear fission power offers an attractive alternative to solar electric or radioisotope power systems for certain applications on the Moon, Mars, and deep space science missions. The advantages of independence from solar irradiance, high energy density, and abundance of fuel allow fission power systems to enable novel, high power mission architectures. While NASA has had numerous fission power programs throughout its history, few have gone far beyond the design phase. The recent test campaign called the Kilopower Reactor Using Stirling Technology project (KRUSTY) focused on a low power, kilowatt-scale design for simplicity and reduced cost, with the driving motivation to perform a full nuclear hardware prototype test. Following the successful completion of the KRUSTY nuclear hardware test in March of 2018, NASA has begun the formulation process for a Technology Demonstration Mission (TDM) using the Kilopower reactor technology. In support of NASA's lunar surface initiatives, the Kilopower TDM will target a 1-3 kW fission electric power system that can survive the lunar night and operate for one year. The system will be heavily influenced by the KRUSTY reactor design, using a solid Uranium metal core with high temperature heat pipes and Stirling engine power conversion. During this formulation phase, continued engineering efforts are ongoing to improve heat transfer efficiency in the system, examine fission radiation damage effects, and begin to address the thermal and structural requirements of a Kilopower flight system.
High temperature liquid metal cooled nuclear reactor for military aircraft with long flight endurance and range
To improve the economics of commercial nuclear reactors, nuclear vendors and utilities are seeking approval for increased burnup usage of the existing nuclear fleet. This is especially critical for meeting the clean energy initiative by the United States Government, Department of Energy (DOE). However, one of the key challenges the nuclear industry faces in this regard is that the regions exposed to high burnup and low temperatures exhibit a fine-grained microstructure with large bubbles known as high-burnup structure (HBS) [1]. The formation of HBS has been correlated to the diminished performance of the reactor, as well as fuel fragmentation and pulverization during transient and accidental conditions [2]. Therefore, it is paramount to understand the mechanisms for HBS formation along with its impact on the properties and performance of nuclear fuels. While existing programs, such as Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuel Campaign (AFC) are focusing on evaluating the performance impact of HBS, the physical mechanisms contributing to HBS formation are still not fully understood. In addition, having predictive capabilities and sound understanding of the microstructural evolution of nuclear fuel is essential for accelerated development, qualification, and deployment of new nuclear materials and novel reactor designs for advanced nuclear reactors. There is a lack of consensus among researchers regarding the mechanisms leading to such restructuring observed in HBS. Grain subdivision due to polygonization versus recrystallization, continuous versus discrete recrystallization occurring in tandem or conjunction, etc., have been proposed and debated. In general, it is hypothesized that defect accumulation and dislocation interaction within the grains cause the realignment of dislocations into grain boundaries, leading to the new subgrain formation, which over time transforms into new grains. However, due to the lack of transient data, the importance of fission rate, irradiation, thermal, and stress history of the fuel on the restructuring could not be assessed. In situ microstructural evolution under various irradiation conditions is desired to bridge this gap. Alternatively, phase-field-based models have been developed to capture HBS formation via discrete recrystallization utilizing the classical nucleation approach [3–5]. However, in these models, the grain nucleation criteria are often defined based on empirical relations for burnup and fission gas density leading to dislocation density change. A mechanistic approach to capture the dislocation interaction with the microstructural features leading to grain subdivision is lacking.
Space nuclear propulsion systems are capable of enabling future crewed missions to Mars. Two primary options of these systems exist: nuclear thermal propulsion (NTP) and nuclear electric propulsion (NEP). NTP systems use a reactor as a heat exchanger to heat a hydrogen propellant to produce high specific impulse (≥ 900 s) and thrust (10 - 100 klbf). A NTP materials challenge is development of nuclear fuel capable of operating for short durations (hours) under high power densities (≥ 5 MW/L) and temperatures (> 2700 K) in a corrosive hydrogen environment. In NEP systems, the reactor heats a working fluid which transfers heat to a power conversion system to power electric thrusters. NEP is capable of higher specific impulse (≥ 2000 s) but limited to low thrust (10s lbf). Light weight vessel and in-core structural materials that are radiation-resistant, creep-resistant, and dimensionally stable while operating at ~1500 K over mission times up to several years are needed for NEP. Both systems can benefit from high temperature neutron moderators. Through the Space Nuclear Propulsion project, NASA, supported by the DOE, is developing NTP and NEP systems. Technology maturation planning and risk reduction activities related to fabrication and testing of reactor material candidates is ongoing. This presentation overviews NTP and NEP materials needs and current ceramic and composite development activities.
Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.
Scintillation-based fast-neutron detectors that are smaller and less power-hungry than mainstream scintillation-based fast-neutron detectors are undergoing development. There are numerous applications for such detectors in monitoring fast-neutron fluxes from nuclear reactors, nuclear materials, and natural sources, both on Earth and in outer space. A particularly important terrestrial application for small, low-power, portable fast-neutron detectors lies in the requirement to scan for nuclear materials in cargo and baggage arriving at international transportation facilities. The present development of miniature, low-power scintillation-based fast-neutron detectors exploits recent advances in the fabrication of avalanche photodiodes (APDs). Basically, such a detector includes a plastic scintillator, typically between 300 and 400 m thick with very thin silver mirror coating on all its faces except the one bonded to an APD. All photons generated from scintillation are thus internally reflected and eventually directed to the APD. This design affords not only compactness but also tight optical coupling for utilization of a relatively large proportion of the scintillation light. The combination of this tight coupling and the avalanche-multiplication gain (typically between 750 and 1,000) of the APD is expected to have enough sensitivity to enable monitoring of a fast-neutron flux as small as 1,000 cm(exp -2)s(exp -1). Moreover, pulse-height analysis can be expected to provide information on the kinetic energies of incident neutrons. It has been estimated that a complete, fully developed fast-neutron detector of this type, would be characterized by linear dimensions of the order of 10 cm or less, a mass of no more than about 0.5 kg, and a power demand of no more than a few watts.
Nuclear reactor design as heat source for electric power generation in space
Nuclear science plays a key role in non-proliferation activities supporting advanced reactor technologies. Nuclear data underpin predictions and interpretations of nuclear material behavior and signatures in reactor fuel production, use, transport, and storage. Advanced reactors provide new challenges compared to the current fleet of thermal fission reactors. This report consolidates reported nuclear data needs from representative workshops, conferences, and publications, identifying six themes for recommended future investments supporting non-proliferation and safeguards applications. While also identified as data needs, major fission product evaluations and (α,n) reactions were omitted as there are ongoing activities producing new data under NA22/Objective O. Each theme is summarized below with example data and association with the nonproliferation mission for advanced fuels and reactors.
Properties of high temperature materials for nuclear rocket reactor application - reactor concepts for low power lightweight nuclear power plant
Next-generation nuclear reactors demand structural materials capable of withstanding extreme conditions, including high temperatures, intense neutron flux, and corrosive environments. Multi-Principal Element Alloys (MPEAs) have emerged as promising candidates due to their exceptional radiation tolerance, thermal stability, and compositional flexibility. This study introduces a versatile and customizable Robust Alloy Design (RAD) strategy for systematically designing MPEAs for GEN-IV reactor fuel cladding. The RAD framework integrates nuclear-relevant selection criteria, empirical parameter assessments, and high-throughput CALPHAD simulations to efficiently narrow compositional space and identify stable alloys. A unified RAD score developed for the first time, combines key performance metrics, including fuel-clad chemical interaction (FCCI), neutron absorption cross-section (NAC), valence electron configuration (VEC), and melting point factor (MPF), into a flexible ranking system adaptable to reactor-specific priorities. Among 724 candidates, V555(5Al–5Cr–5Fe–85V) emerged as the top alloy, validated experimentally with a homogeneous single-phase BCC microstructure and superior mechanical properties (nano-indentation: 3.389 ± 0.258 GPa; Vickers hardness: 240 ± 6.7 HV), significantly outperforming Zircaloy-4 and V-4Cr-4Ti. Importantly, the RAD strategy is not limited to nuclear applications; its customizable weighting system enables scalability to other extreme environments. This adaptability positions RAD strategy as a versatile tool for advanced materials design across multiple industries.
The pellet bed reactor (PBR) for nuclear propelled vehicles is briefly discussed. Much of the information is given in viewgraph form. Viewgraphs include information on the layout for a Mars mission using a PBR nuclear thermal rocket, the rocket reactor layout, the fuel pellet design, materials compatibility, fuel microspheres, microsphere coating, melting points in quasibinary systems, stress analysis of microspheres, safety features, and advantages of the PBR concept.
The paper analyzes the consequences of heat pipe failures, that resulted in modifications to the basic design of a heat-pipe cooled, fast spectrum nuclear reactor and led to consideration of an entirely different core design. The new design features an integral laminated core configuration consisting of alternating layers of UO2 and molybdenum sheets that span the diameter of the core. Design characteristics are presented and compared for two reactors. A conceptual design for a heat exchanger between the core and the thermionic converter assembly is described. This heat exchanger would provide design and fabrication decoupling of these two assemblies.
Nuclear reactor system could provide power to support a long term human exploration to the moon. Such a system would require shielding to protect astronauts from its emitted radiations. Shielding studies have been performed for a Gas Cooled Reactor (GCR) system because it is considered to be the most suitable nuclear reactor system available for lunar exploration, based on its tolerance of oxidizing lunar regolith and its good conversion efficiency (Wright, 2003). The goals of the shielding studies were to provide optimal material shielding configuration that reduces the dose (rem) to the required level in order to protect astronauts, and to estimate the mass of regolith that would provide an equivalent protective effect if it were used as the shielding material. All calculations were performed using MCNPX code, a Monte Carlo transport code.
Probabilistic safety requirements currently formulated or proposed for space systems, nuclear reactor systems, nuclear weapon systems, and other types of systems that have a low-probability potential for high-consequence accidents depend on showing that the probability of such accidents is below a specified safety threshold or goal. Verification of compliance depends heavily upon synthetic modeling techniques such as PRA. To determine whether or not a system meets its probabilistic requirements, it is necessary to consider whether there are significant risks that are not fully considered in the PRA either because they are not known at the time or because their importance is not fully understood. The ultimate objective is to establish a reasonable margin to account for the difference between known risks and actual risks in attempting to validate compliance with a probabilistic safety threshold or goal. In this paper, we examine data accumulated over the past 60 years from the space program, from nuclear reactor experience, from aircraft systems, and from human reliability experience to formulate guidelines for estimating probabilistic margins to account for risks that are initially unknown or underappreciated. The formulation includes a review of the safety literature to identify the principal causes of such risks.