Journal of Nuclear Engineering

Nuclear power is typically deployed as a baseload generator. Increased penetration of variable renewables motivates combining nuclear and renewable technologies into Integrated Energy Systems (IES) to improve dispatchability, component synergies and, through cogeneration, address multiple markets. However, combining multiple energy resources heavily depends on the proper selection of each system’s location and design limitations. In this paper, co-siting options for IES that couple nuclear and concentrating solar power (CSP) with thermal desalination are investigated. A comprehensive siting analysis is performed that utilizes global information survey data to determine possible co-siting options for nuclear and solar thermal generation in the United States. Viable co-siting options are distributed across the Southwestern U.S., with the greatest concentration of siting options in the southern Great Plains, although siting with higher solar direct normal irradiance is possible in other states such as Arizona and New Mexico. Brackish water desalination is also attractive across the southwest U.S. due to high water stress, but for brackish water desalination reverse osmosis (an electricity driven process) is most cost- and energy-efficient, which does not require co-siting with the thermal generator. The most attractive state for nuclear and thermal desalination (which is more attractive when using seawater) is Texas, although other areas may become attractive as water stress increases over the coming decades. Co-siting of all CSP and thermal desalination is challenging as attractive CSP sites are not coastal. Full article

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the ¹³³Ba, ⁶⁰Co, ¹³⁷Cs, and ¹⁵²Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification. Full article

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (1st-CASAM-NODE) which yields exact expressions for the first-order sensitivities of NODE decoder responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim–Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, etc.). This work also lays the foundation for the ongoing work on conceiving the “Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (2nd-CASAM-NODE) which aims at yielding exact expressions for the second-order sensitivities of NODE decoder responses to the NODE parameters and initial conditions while enabling the most efficient computation of these sensitivities. Full article

Zirconium hydride is commonly used for next-generation reactor designs due to its excellent hydrogen retention capacity at temperatures below 1000 K. These types of reactors operate at thermal neutron energies and require accurate representation of thermal scattering laws (TSLs) to optimize moderator performance and evaluate the safety indicators for reactor design. In this work, we present an atomic-scale representation of sub-stoichiometric ZrH_2−x$(0.3\le x\le 0.6)$, which relies on ab initio molecular dynamics (AIMD) in tandem with velocity auto-correlation (VAC) analysis to generate phonon density of states (DOS) for TSL development. The novel NJOY+NCrystal tool, developed by the European Spallation Source community, was utilized to generate the TSL formulations in the A Compact ENDF (ACE) format for its utility in neutron transport software. First, stoichiometric zirconium hydride cross sections were benchmarked with experiments. Then sub-stoichiometric zirconium hydride TSLs were developed. Significant deviations were observed between the new $\delta$-phase ZrH_2−x TSLs and the TSLs in the current ENDF release. It was also observed that varying the hydrogen vacancy defect concentration and sites did not cause as significant a change in the TSLs (e.g., ZrH_1.4 vs. ZrH_1.7) as was caused by the lattice transformation from $ϵ$- to $\delta$-phase. Full article

A miniature nuclear reactor is desirable for deployment as a localized nuclear power station in support of a carbon-free power supply. Coupling aspects of proliferation-resistant fuel with natural burnable absorber loading are evaluated for once-through operation cycle performance to minimize the need for refueling and fuel shuffling operations. The incorporation of 0.075 wt.% ²³⁷Np provides favorable plutonium isotopic vectors throughout an operational lifetime of 5.5 years. providing 35 MWe. Core performance was assessed using a verification-by-comparison approach for core designs with or without ²³⁷Np and/or gadolinia burnable absorber. Burnup Monte Carlo calculations were performed via MCOS coupling of MCNP and ORIGEN to an achievable burnup of ~62.5 GWd/t. The results demonstrate a minimal penalty to reactor performance due to the addition of these materials as compared against the reference design. Coupling of a proliferation-resistant fuel concept with a uniform loading of natural gadolinia burnable absorber for LEU+ fuel (7.5 wt.% ²³⁵U/U UO₂) provides favorable excess reactivity considerations with minimized concerns for additional residual waste and more uniform distribution of un-depleted ²³⁵U in discharged fuel assemblies. Full article

This paper focuses on the highly radioactive, long-lasting nuclear waste produced by the currently operating fission reactors and on the sensitive issue of spent fuel reprocessing. Also included is a short description of the fission process and a detailed analysis of the more hazardous radioisotopes produced either by secondary reactions occurring in the nuclear installations or by decay of the fission fragments. The review provides an overview of the strategies presently adopted to minimize the harmfulness of the nuclear waste to be disposed, with a focus on the development and implementation of methodologies for the spent fuel treatments. The partitioning-conditioning and partitioning-transmutation options are analyzed as possible solutions to decrease the presence of long-lived highly radioactive isotopes. Also discussed are the chemical/physical approaches proposed for the recycling of the spent fuel and for the reusing of some technologically relevant isotopes in industrial and pharmaceutical areas. A brief indication is given of the opportunities offered by innovative types of reactors and/or of new fuel cycles to solve the issues presently associated with radioactive waste. Full article

Modeling the response of gamma detectors has long been a challenge within the nuclear community. Significant research has been conducted to digitally replicate instruments that can cost over USD 100,000 and are difficult to operate outside of a laboratory setting. The large cost and availability prevent some from making use of such equipment. Subsequently, there have been multiple attempts to create cost-effective codes that replicate the response of sodium-iodide and high-purity germanium detectors for data derivation related to gamma-ray interaction with matter. While robust programs do exist, they are often subject to export controls and/or they are not intuitive to use. Through the use of hybrid Monte Carlo methods, MATLAB can be used to produce a fast first-order response of various gamma-ray detectors. The combination of a graphical user interface with a numerical-based script allows for open-source and intuitive code. When benchmarked with experimental data from Co-60, Cs-137, and Na-22, the code can numerically calculate a response comparable to experimental and industry-standard response codes. Evidence supports both savings in computational requirements and the inclusion of an intuitive user experience that does not heavily compromise data when compared to other standard codes, such as MCNP and GADRAS, or experimental results. When the application is installed on a Dell Intel i7 computer with 16 cores, the average time to simulate the benchmarked isotopes is 0.26 s. Installation on an HP Intel i7 four-core machine runs the same isotopes in 1.63 s. The results indicate that simple gamma detectors can be modeled in an open-source format. The anticipation for the MATLAB application is to be a tool that can be easily accessible and provide datasets for use in an academic setting requiring gamma-ray detectors. Ultimately, this article provides evidence that hybrid Monte Carlo codes in an open-source format can benefit the nuclear community in both computational time and up-front cost for access. Full article

The SCALE/Polaris–PARCS code procedure has been used in the confirmatory analysis for boiling water reactors by the US Nuclear Regulatory Commission. In this study, the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library was validated by comparing the simulated results with the measured data for operating boiling water reactors, including Peach Bottom Unit 2 cycles 1–3, Hatch Unit 1 cycles 1–3, and Quad Cities Unit 1 cycles 1–3. The uncertainties and biases of the SCALE/Polaris–PARCS code package for boiling water reactor physics analysis were evaluated in the validation for key nuclear parameters such as reactivity and traversing in-core probe data. Full article

This study was conducted to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library for pressurized water reactor (PWR) analysis, by comparing simulated results with measured data for critical experiments and operating PWRs. Uncertainties of the SCALE/Polaris–PARCS code procedure for PWR analysis were evaluated in the validation for the PWR key nuclear parameters such as critical boron concentrations, reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors. Full article

Simulation modeling is crucial in support of probabilistic risk assessment (PRA) for nuclear power plants (NPPs). There is a challenge, however, associated with simulation modeling that relates to the time and resources required for collecting data to determine the values of the input parameters. To alleviate this challenge, this article develops a formalized methodology to generate surrogate values of input parameters grounded on the decomposition of phenomenological nondimensional parameters (PNPs) while avoiding detailed data collection. While the fundamental principles of the proposed methodology can be applicable to various hazards, the developments in this article focus on fire PRA as an example application area for which resource intensiveness is recognized as a practical challenge. This article also develops a computational platform to automate the PNP decomposition and seamlessly integrates it with state-of-practice fire scenario analysis. The applicability of the computational platform is demonstrated through a multi-compartment fire case study at an NPP. The computational platform, with its embedded PNP decomposition methodology, can substantially reduce the effort required for input data collection and extraction, thereby facilitating the efficient use of simulation modeling in PRA and enhancing the fire scenario screening analysis. Full article

The last decade has seen the development and application of data-driven methods taking off in nuclear engineering research, aiming to improve the safety and reliability of nuclear power. This work focuses on developing a reinforcement learning-based control sequence optimization framework for advanced nuclear systems, which not only aims to enhance flexible operations, promoting the economics of advanced nuclear technology, but also prioritizing safety during normal operation. At its core, the framework allows the sequence of operational actions to be learned and optimized by an agent to facilitate smooth transitions between the modes of operations (i.e., load-following), while ensuring that all safety significant system parameters remain within their respective limits. To generate dynamic system responses, facilitate control strategy development, and demonstrate the effectiveness of the framework, a simulation environment of a pebble-bed high-temperature gas-cooled reactor was utilized. The soft actor-critic algorithm was adopted to train a reinforcement learning agent, which can generate control sequences to maneuver plant power output in the range between 100% and 50% of the nameplate power through sufficient training. It was shown in the performance validation that the agent successfully generated control actions that maintained electrical output within a tight tolerance of 0.5% from the demand while satisfying all safety constraints. During the mode transition, the agent can maintain the reactor outlet temperature within $\pm 1.5$ °C and steam pressure within 0.1 MPa of their setpoints, respectively, by dynamically adjusting control rod positions, control valve openings, and pump speeds. The results demonstrate the effectiveness of the optimization framework and the feasibility of reinforcement learning in designing control strategies for advanced reactor systems. Full article

Recent experimental investigations have demonstrated that a substantial amount of H⁻/D⁻ ions can be formed by thermal desorption processes. Based on these new findings, new mini axial and coaxial-type neutron tubes have been developed for the production of high or low-energy neutrons via the d-d, d-¹⁰B, d-⁷Li or p-⁷Li nuclear reactions. By operating these mini neutron tubes with a high frequency AC high-voltage supply, short pulses of high intensity neutron beams can be generated. Multiple applications, such as carbon and well logging, neutron imaging, cancer therapy, medical isotope production, fission reactor start-up, fusion reactor material evaluation, homeland security and space exploration can be performed with the subcompact neutron generator system. It is shown that the performance of these new mini neutron tubes can exceed those of the conventional plasma-based neutron sources. Full article

This study used an analytical computational model to evaluate safe zones in contaminated areas that may result from a hypothetical significant off-site release from a nuclear power plant. The model, considering local atmospheric stability, wind direction, and location, calculates the expected total effective dose equivalent (TEDE) and potential safety zones. This research, focused on an area near a nuclear facility affected by an accidental release, used SCALE and HotSpot Health Physics codes to simulate the reactor’s core inventory content and off-site release. This study’s findings underscore that the risk of developing solid cancer (testing morbidity) is influenced by both local atmospheric stability and the composition of the potentially affected population (primarily age and sex). These findings, backed by an analytical approach, can significantly influence logistical and operational planning. The utilization of computer simulations can also aid in creating flexible response scenarios to real events. Full article

The lifespan of core graphite under neutron irradiation in a commercial molten salt reactor (MSR) has an important influence on its economy. Flattening the fast neutron flux (≥0.05 MeV) distribution in the core is the main method to extend the graphite irradiation lifespan. In this paper, the effects of the key parameters of MSRs on fast neutron flux distribution, including volume fraction (VF) of fuel salt, pitch of hexagonal fuel assembly, core zoning, and layout of control rod assemblies, were studied. The fast neutron flux distribution in a regular hexagon fuel assembly was first analyzed by varying VF and pitch. It was demonstrated that changing VF is more effective in reducing the fast neutron flux in both global and local graphite blocks. Flattening the fast neutron flux distribution of a commercial MSR core was then carried out by zoning the core into two regions under different VFs. Considering both the fast neutron flux distribution and burnup depth, an optimized core was obtained. The fast neutron flux distribution of the optimized core was further flattened by the rational arrangement of control rod channels. The calculation results show that the final optimized core could reduce the maximum fast neutron flux of the graphite blocks by about 30% and result in a more negative temperature reactivity coefficient, while slightly decreasing the burnup and maintaining a fully acceptable core temperature distribution. Full article

When studying hazardous materials such as spent nuclear fuel (SNF), the minimisation of sample volumes is essential, together with the use of chemically-similar surrogates where possible. For example, the bulk behaviour of urania (UO₂) can be mimicked by appropriately-engineered thin films of sufficient thickness, and inactive materials such as ceria (CeO₂) can be used to study the effects within radioactive systems used to fuel nuclear fission. However, thin film properties are sensitive to the preparative method, many of which require the use of highly toxic precursors and specialised apparatus (e.g., chemical vapour deposition). To address this, we present the development of a flexible, tuneable, scalable method for the preparation of thin-film CeO₂ SIMFUEL models with a thickness of ≈5 μm. The effects of γ irradiation (up to 100 kGy) and dopants including trivalent lanthanides (Ln³⁺) and simulant ε-particles on the structure and long-term leaching of these systems under SNF storage conditions were explored, alongside the context of this within further work. It was found that the sensitivity of CeO₂ films to reduction upon irradiation, particularly in the presence of simulant ε-particles, resulted in increased leaching of Ce (as Ce^III), while trivalent lanthanides (Nd³⁺ and Eu³⁺) had a minimal effect on Ce leaching. Full article

Reliability and efficiency of valves are necessary for precise control and sufficient heat-flow to heat application plants for the integrated energy systems of nuclear power plants (NPPs). Strategic Management Analysis Requirement and Technology (SMART) valves’ ability to control flow and assess environmental parameters stands out for these requirements. Their ability to sustain the downstream flow rate, prevent reverse flow, and maintain pressure in the heat transport loop is much more efficient with the integration of sensors and intelligent algorithms. For assessing valve performance and monitoring, mechanical design and operating conditions are two important parameters. In this study, the butterfly valves of three different sizes are simulated with water and steam using STAR-CCM+ in various flow regimes and positions to analyze performance parameters to strategize an automated control system for efficiently balancing the heat–transport network. Also, flow behavior is studied using velocity and pressure fields for valve–body geometry optimization. It can be observed, through performance parameters, that the valves are suitable for operation between 30° and 90° positions with significantly low loss coefficients and high flow coefficients, and the performance parameters follow a certain pattern in both water and steam flow in each scenario. Full article

The development of compact neutron sources for applications is extensive and features many approaches. For ion-based approaches, several projects with different parameters exist. This article focuses on ion-based neutron production below the spallation barrier for proton and deuteron beams with arbitrary energy distributions with kinetic energies from 3 $\mathrm{M}$$\mathrm{e}\mathrm{V}$ to 97 $\mathrm{M}$$\mathrm{e}\mathrm{V}$. This model makes it possible to compare different ion-based neutron source concepts against each other quickly. This contribution derives a predictive model using Monte Carlo simulations (an order of 50,000 simulations) and deep neural networks. It is the first time a model of this kind has been developed. With this model, lengthy Monte Carlo simulations, which individually take a long time to complete, can be circumvented. A prediction of neutron spectra then takes some milliseconds, which enables fast optimization and comparison. The models’ shortcomings for low-energy neutrons (<$0.1 \mathrm{M}\mathrm{e}\mathrm{V}$) and the cut-off prediction uncertainty ($\pm 3 \mathrm{M}\mathrm{e}\mathrm{V}$) are addressed, and mitigation strategies are proposed. Full article

In this paper, the interactions of low-energy muons (E < 10 MeV) with natural silicon, the basic material of microelectronics, are studied by Geant4 and SRIM simulation. The study is circumscribed to muons susceptible to slowdown/stop in the target and able to transfer sufficient energy to the semiconductor to create single events in silicon devices or related circuits. The capture of negative muons by silicon atoms is of particular interest, as the resulting nucleus evaporation and its effects can be catastrophic in terms of the emission of secondary ionizing particles ranging from protons to aluminum ions. We investigate in detail these different nuclear capture reactions in silicon and quantitatively evaluate their relative importance in terms of number of products, energy, linear energy transfer, and range distributions, as well as in terms of charge creation in silicon. Finally, consequences in the domain of soft errors in microelectronics are discussed. Full article