Journal of Nuclear Engineering

Burnable poisoning and fuel enrichment zoning are two techniques often combined in order to optimize the fuel assembly behavior during the burnup cycle. In the present work, these two techniques will be applied to the 2D optimization of the fuel assembly conceptual design for the supercritical water-cooled reactor developed in the framework of the Joint European Canadian Chinese development of Small Modular Reactor Technology project, funded within the Euratom Research and Training programme 2019–2020. The initial configuration of the fuel assembly does not include any burnable absorbers and uses a homogeneous fuel enrichment of 7.5% in ²³⁵U. The infinite multiplication factor, $k_{\infty }$, starts from approximately 1.32 and drops, almost linearly, to 1.0 after a burnup of 40.0 MWd·kg⁻¹. The uniform enrichment is, however, responsible for a pin-power peaking factor that with fresh fuel starts from 1.32 and reduces to 1.08 at the end of the burnup cycle. A simplified analytical model is developed to assess the effect of different lumped burnable absorbers on the time dependence of the assembly $k_{\infty }$. It is shown that using an adequate number of B₄C rods, positioned in the outer wall of the fuel assembly, together with a suitable distribution of six different ²³⁵U enrichments, it allows for obtaining an assembly $k_{\infty }$ factor that starts from 1.11 at the beginning of the cycle and remains quite constant over a large fraction of the burnup cycle. Moreover, the pin-power peaking factor is reduced to 1.03 at the beginning of the cycle and remains almost unchanged until the end of the burnup cycle. Full article

Powder injection molding (PIM) has been used to produce nearly net-shaped samples of tungsten-based alloys. These alloys have been previously shown to have favorable characteristics when compared with standard ITER-grade tungsten. Six different alloys were produced with this method: W-1TiC, W-2Y₂O₃, W-3Re-1TiC, W-3Re-2Y₂O₃, W-1HfC and W-1La₂O₃-1TiC. These were tested alongside ITER-grade tungsten in the PSI-2 linear plasma device under ITER-relevant plasma and heat loads to assess their suitability for use in a fusion reactor. All materials showed good behavior when exposed to the lower pulse number tests (≤1000 ELM-like pulses), although standard tungsten performed slightly better, with no observable difference in surface roughness. High-power shots, namely one laser pulse of 1.6 GWm⁻², revealed that samples containing yttria are more prone to melting and droplet ejection. After high pulse number tests (10,000 and 100,000 pulses), with and without plasma, the reference tungsten showed the most cracking and highest surface roughness of all materials, while the PIM samples seemed to have a higher resistance to cracking. This can be attributed to the higher ductility of these alloys, particularly those containing rhenium. This means that tungsten-based alloys, whether produced via PIM or other methods, could potentially be used in certain areas of a fusion reactor. Full article

This work presents the mathematical frameworks of the “First-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integro-Differential Equations of Volterra-Type” (1st-FASAM-NIDE-V) and the “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integro-Differential Equations of Volterra-Type” (2nd-FASAM-NIDE-V). It is shown that the 1st-FASAM-NIDE-V methodology enables the efficient computation of exactly-determined first-order sensitivities of the decoder response with respect to the optimized NIDE-V parameters, requiring a single “large-scale” computation for solving the 1st-Level Adjoint Sensitivity System (1st-LASS), regardless of the number of weights/parameters underlying the NIE-net. The 2nd-FASAM-NIDE-V methodology enables the computation, with unparalleled efficiency, of the second-order sensitivities of decoder responses with respect to the optimized/trained weights involved in the NIDE-V’s decoder, hidden layers, and encoder, requiring only as many “large-scale” computations as there are non-zero first-order sensitivities with respect to the feature functions. These characteristics of the 1st-FASAM-NIDE-V and 2nd-FASAM-NIDE-V are illustrated by considering a nonlinear heat conduction model that admits analytical solutions, enabling the exact verification of the expressions obtained for the first- and second-order sensitivities of NIDE-V decoder responses with respect to the model’s functions of parameters (weights) that characterize the heat conduction model. Full article

Recent advances in high-fidelity modeling, numerical computing, and data science have spurred interest in model-data integration for nuclear reactor applications. While machine learning often prioritizes data-driven predictions, this study focuses on data assimilation (DA) to synergize physical models with measured data, aiming to enhance predictive accuracy and reduce uncertainties. We implemented deterministic DA methods—Kalman filter (KF) and three-dimensional variational (3D-VAR)—in a one-dimensional single-phase natural circulation loop and extended 3D-VAR to RELAP5, a system code for two-phase loop analysis. Unlike surrogate-based or model-reduction strategies, our approach leverages full-model propagation without relying on computationally intensive sampling. The results demonstrate that KF and 3D-VAR exhibit robustness against varied noise types, intensities, and distributions, achieving significant uncertainty reduction in state variables and parameter estimation. The framework’s adaptability is further validated under oceanic conditions, suggesting its potential to augment baseline models beyond conventional extrapolation boundaries. These findings highlight DA’s capacity to improve model calibration, safety margin quantification, and reactor field reconstruction. By integrating high-fidelity simulations with real-world data corrections, the study establishes a scalable pathway to enhance the reliability of nuclear system predictions, emphasizing DA’s role in bridging theoretical models and operational demands without compromising computational efficiency. Full article

In current and future fusion devices, detecting hydrogen isotopes, particularly tritium and deuterium, implanted or redeposited on the surface of Plasma-Facing Components (PFCs) will be increasingly important to ensure safe machine operations. The Laser-Induced Breakdown Spectroscopy (LIBS) technique has proven capable of performing this task directly in situ, without handling or removing PFCs, thus limiting analysis times and increasing the machine’s duty cycle. To increase sensitivity and the ability to discriminate between isotopes, LIBS analysis can be performed under different background gases at atmospheric pressure, such as air, He, and Ar. In this work, we present the results obtained on tungsten coatings enriched with deuterium and/or hydrogen as a deuterium–tritium nuclear fuel simulant, measured with the LIBS technique in air, He, and Ar at atmospheric pressure, and discuss the pros and cons of their use. The results obtained demonstrate that both He and Ar can improve the LIBS signal resolution of the hydrogen isotopes compared to air. However, using Ar has the additional advantage that the same procedure can also be used to detect He implanted in PFCs as a product of fusion reactions without any interference. Finally, the LIBS signal in an Ar atmosphere increases in terms of the signal-to-noise ratio (SNR), enabling the use of less energetic laser pulses to improve performance in depth profiling analyses. Full article

While traditional risk importance measures in probabilistic risk assessment are effective for ranking safety-significant components, they often overlook critical aspects such as the timing of accident progression and consequences. Dynamic probabilistic risk assessment offers a framework to quantify such risk information, but standardized approaches for estimating risk importance measures remain underdeveloped. This study addresses this gap by: (1) reviewing traditional risk importance measures and their regulatory applications, highlighting their limitations, and introducing newly proposed risk-triplet-based risk importance measures, consisting of timing-based worth, frequency-based worth, and consequence-based worth; (2) conducting a case study of Level 2 dynamic probabilistic risk assessment using the Japan Atomic Energy Agency’s RAPID tool coupled with the severe accident code of MELCOR 2.2 to simulate a station blackout scenario in a boiling water reactor, generating probabilistically sampled sequences with quantified timing, frequency, and consequence of source term release; (3) demonstrating that the new risk importance measures provide differentiated insights into risk significance, enabling multidimensional prioritization of systems and mitigation strategies; for example, the timing-based worth quantifies the delay effect of mitigation systems, and the consequence-based worth evaluates consequence-mitigating potential. This study underscores the potential of dynamic probabilistic risk assessment and risk-triplet-based risk importance measures to support risk-informed and performance-based regulatory decision-making, particularly in contexts where the timing and severity of accident consequences are critical. Full article

The study of scalar field theories like the chameleon field model is of increasing interest due to the Universe’s accelerated expansion, which is believed to be caused in part by dark energy. These fields can elude experimental bounds set on them in high-density environments since they interact with matter in a density-dependent way. This paper analyzes the effect of chameleon fields on the quantum gravitational states of ultra-cold neutrons (UCNs) in qBounce experiments with mirrors. We discuss the deformation of the neutron wave function due to chameleon interactions and quantum systems in potential wells from gravitational forces and chameleon fields. Unlike other works that aim to put bounds on the chameleon field parameters, this work focuses on the quantum mechanics of the chameleonic neutron. The results deepen our understanding of the interplay between quantum states and modified gravity, as well as fundamental physics experiments carried out in the laboratory. Full article

The subject of the effect of pipeline layout on wall thinning in Mihama nuclear power plants was reviewed in relation to flow-accelerated corrosion (FAC). The pipeline consists of a complex layout with a straight pipe, elbow, curved pipe, orifice, and T-junction. To understand the mechanism of wall thinning in the pipeline, the basics of FAC, experimental and numerical approaches, and flow and mass transfer studies of the pipeline were reviewed and compared with actual Mihama pipeline data. The results indicate that the wall thinning in the Mihama pipeline was caused by the asymmetric mass transfer phenomenon arising from the pipeline layout effect induced by the swirl flow, resulting in the generation of a spiral flow downstream of the elbow and an increased mass transfer coefficient downstream of the orifice. Swirl flow can be generated by the coupled T-junction and elbow in the upstream pipeline. Furthermore, related topics in flow and mass transfer studies on short elbows and dual and triple elbows were reviewed in relation to wall thinning, which could depend on the elbow curvature, Reynolds number, and surface roughness. The low-frequency flow oscillation in a short elbow, the swirl flow generation in dual and triple elbows, and the influence of wall roughness could be other sources of the increased mass transfer coefficient in the pipeline. Full article

This research explores Dynamic Probabilistic Risk Assessment (DPRA) using EMRALD to evaluate the reliability and safety of passive safety systems in nuclear reactors, with a focus on mitigating Loss of Coolant Accidents (LOCAs). The BWRX-300 Small Modular Reactor (SMR) is used as an example to illustrate the proposed DPRA methodology, which is broadly applicable for enhancing traditional Probabilistic Safety Assessment (PSA). Unlike static PSA, DPRA incorporates time-dependent interactions and system dynamics, allowing for a more realistic assessment of accident progression. EMRALD enables the modelling of system failures and interactions in real time using dynamic event trees and Monte Carlo simulations. This study identifies critical vulnerabilities in passive safety systems and quantifies the Core Damage Frequency (CDF) under LOCA scenarios. The findings demonstrate the advantages of DPRA over traditional PSA in capturing complex failure mechanisms and providing a more comprehensive and accurate risk assessment. The insights gained from this research contribute to improving passive safety system designs and enhancing nuclear reactor safety strategies for next-generation reactors. Full article

(1) Background: Generation IV supercritical water-cooled reactors (SCWRs), including small modular reactor (SCW-SMR) variants, are pivotal in nuclear technology. Operating at 300–500 °C and 25 MPa, these reactors require detailed understanding of radiation chemistry and transient species to optimize water chemistry, reduce corrosion, and enhance safety. Boron, widely used as a neutron absorber, plays a significant role in reactor performance and safety. This study focuses on the yields of radiolytic species in subcritical and supercritical water exposed to ⁴He and ⁷Li recoil ions from the ¹⁰B(n,α)⁷Li fission reaction in SCWR/SCW-SMR environments. (2) Methods: We use Monte Carlo track chemistry simulations to calculate yields (G values) of primary radicals (e⁻_aq, H^•, and ^•OH) and molecular species (H₂ and H₂O₂) from water radiolysis by α-particles and Li³⁺ recoils across 1 picosecond to 0.1 millisecond timescales. (3) Results: Simulations show substantially lower radical yields, notably e⁻_aq and ^•OH, alongside higher molecular product yields compared to low linear energy transfer (LET) radiation, underscoring the high-LET nature of ¹⁰B(n,α)⁷Li recoil nuclei. Key changes include elevated G(^•OH) and G(H₂), and a decrease in G(H^•), primarily driven during the homogeneous chemical stage of radiolysis by the reaction H^• + H₂O → ^•OH + H₂. This reaction significantly contributes to H₂ production, potentially reducing the need for added hydrogen in coolant water to mitigate oxidizing species. In supercritical conditions, low G(H₂O₂) suggests that H₂O₂ is unlikely to be a major contributor to material oxidation. (4) Conclusions: The ¹⁰B(n,α)⁷Li reaction’s yield estimates could significantly impact coolant chemistry strategies in SCWRs and SCW-SMRs. Understanding radiolytic behavior in these conditions aids in refining reactor models and coolant chemistry to minimize corrosion and radiolytic damage. Future experiments are needed to validate these predictions. Full article

Supplementary cementitious materials (SCMs) may be prepared using industrial byproduct streams, aiding in the development of a more environmentally sustainable circular economy. However, these byproducts may carry a risk of exhibiting elevated levels of radioactivity because of the preceding processing that may have concentrated the radionuclides naturally occurring in the raw material. This processing causes the byproducts to be considered technologically enhanced naturally occurring radioactive material (NORM). Thus, the safe use of such SCMs requires robust data on the activity concentrations of three main radionuclides (²²⁶Ra, ²³²Th, ⁴⁰K) represented by the activity concentration index (ACI) used as a radiological suitability indicator. In this work, candidate SCMs derived from the alumina industry byproduct processed bauxite (PB), also referred to as bauxite residue, were assessed by measuring the activity of all available samples, including input raw materials and intermediate substances, through gamma spectrometry. PB was found to significantly impact the final ACI value of the building material. As a key analysis outcome applicable to the substances assessed in this work, no additional dose assessment is required, given the low ACI value of the building materials. This result indicates that, from a radiological perspective, the PB samples studied are suitable precursors for SCMs. In addition, a generalized approach was found to provide good estimations of the ACI value of building materials, which is useful to screen materials for regulatory compliance, without needing to prepare samples of the materials in question. Full article

We present the performance and application of a commercial off-the-shelf Si PIN diode (Hamamatsu S14605) as a charged particle detector in a compact ion beam system (IBS) capable of generating D–D and p–B fusion charged particles. This detector is inexpensive, widely available, and operates in photoconductive mode under a reverse bias voltage of 12 V, supplied by an A23 battery. A charge-sensitive preamplifier (CSP) is mounted on the backside of the detector’s four-layer PCB and powered by two ±3 V lithium batteries (A123). Both the detector and CSP are housed together on the vacuum side of the IBS, facing the fusion target. The system employs a CF-2.75-flanged DB-9 connector feedthrough to supply the signal, bias voltage, and rail voltages. To mitigate the high sensitivity of the detector to optical light, a thin aluminum foil assembly is used to block optical emissions from the ion beam and target. Charged particles generate step responses at the preamplifier output, with pulse rise times in the order of 0.2 to 0.3 µs. These signals are recorded using a custom-built data acquisition unit, which features an optical fiber data link to ensure the electrical isolation of the detector electronics. Subsequent digital signal processing is employed to optimally shape the pulses using a CR-RCⁿ filter to produce Gaussian-shaped signals, enabling the accurate extraction of energy information. Performance results indicate that the detector’s baseline RMS ripple noise can be as low as 0.24 mV. Under actual laboratory conditions, the estimated signal-to-noise ratios (S/N) for charged particles from D–D fusion—protons, tritons, and helions—are approximately 225, 75, and 41, respectively. Full article

The need to model the effect of the assembly environment on the neutronic data has been felt since Smith’s topical article on assembly homogenization techniques. Indeed, simply homogenizing the cross sections using the spatial distribution and energy spectrum of the neutron flux calculated in a single assembly with reflective boundary conditions, neglecting the effect of the proximity of other types of assemblies, can induce inaccuracies affecting the results of core calculations. Many approaches have been proposed to take into account the real environment of the assembly. The purpose of this article is to review these methods to allow the reader to compare them. Full article

The exploitation of fusion energy in tokamak reactors relies on efficient and reliable tritium management. The tritium needed to sustain the deuterium–tritium fusion reaction is produced in the Li-based blanket surrounding the plasma chamber, and, therefore, the effective extraction and purification of the tritium bred in the Li-blankets is needed to guarantee the tritium self-sufficiency of future fusion plants. This work introduces a new technology for the extraction of tritium from the Pb–Li eutectic alloy used in liquid blankets. Process units based on the concept of Membrane Gas–Liquid Contactor (MGLC) have been studied for the extraction of tritium from the Pb–Li in the Water Cooled Lithium Lead blankets of the DEMO reactor. MGLC units have been preliminarily designed and then compared in terms of the permeation areas and sizes with the tritium extraction technologies presently under study, namely the Permeator Against Vacuum (PAV) and the Gas–Liquid Contactors (GLCs). The results of this study show that the DEMO WCLL tritium extraction systems using MGLC require smaller permeation areas and quicker permeation kinetics than those based on PAV (Permeator Against Vacuum) devices. Accordingly, the MGLC extraction unit exhibits volumes smaller than those of both PAV and GLC. Full article

This study presents a comprehensive analysis of the microstructural characteristics and chemical composition of base and weld materials from reactor pressure vessels in the first (units 1 and 2) and second (unit 8) generations of Russian VVER 440 reactors at the Greifswald nuclear power plant. We measured the specific activities of ⁶⁰Co and ¹⁴C in activated samples from units 1 and 2. ⁶⁰Co, with its shorter half-life (t_1/2 = 5.27 a), is a key dose-contributing radionuclide during decommissioning, while ¹⁴C (t_1/2 = 5700 a) plays an important role in a geological repository for low- and intermediate-level radioactive waste. Our findings reveal differences in the proportions of trace elements between the base and weld materials as well as between the two reactor generations. Microstructural analysis identified Mo-rich precipitates and (Mn, S)-rich inclusions containing secondary micro-inclusions in the unit 1 and 2 samples. Raman spectroscopy confirmed iron oxides (γ-Fe₂O₃, Fe₃O₄), silicates (Mn-SiO₃), and Cr₂O₃/NiCr₂O₄ in the base metal as well as MnFe₂O₃ in the weld metal. X-ray photoelectron spectroscopy identified Mn inclusions as MnS, MnS₂, or mixed Mn, Fe sulfides, and the Mo precipitates as MoSi₂. These findings offer valuable insights into the speciation of elements and the potential release of radionuclides through corrosion processes under repository conditions. Full article

In this study, a 56-group covariance library was generated based on the recently released JENDL-5 covariance data, which cover 105 isotopes. The AMPX-6 code system facilitated the generation of this library. Subsequently, the TSUNAMI-IP code was employed to estimate the uncertainty in the effective neutron multiplication factor (keff) for the critical experiment conducted in the Japanese High-Temperature Test Reactor (HTTR). Our analysis involved comparing results obtained from three nuclear data libraries: JENDL-5, ENDF/B-VIII.0, and ENDF/B-VII.1. The keff uncertainty originated from the nuclear data of JENDL-5, ENDF/B-VIII.0, and ENDF/B-VII.1 and were estimated to be 0.387%, 0.581%, and 0.556%, respectively. Interestingly, when the JENDL-5 covariance library was combined with ENDF/B-VIII.0 for JENDL-5 nuclides lacking covariance data, the keff uncertainty increased to 0.464%. The primary contributors to the keff uncertainty, ranked in decreasing order, were U-235 (nubar), C-12 (n,gamma), U-235 (fission), C-12 (elastic), and U-238 (n,gamma). Notably, significant differences in the keff uncertainty were observed between JENDL-5 and ENDF/B-VIII.0, particularly for U-235 (nubar) and C-12 (elastic). Additionally, the sensitivity coefficients, similarity, and kinetics parameters were evaluated across the three libraries, leading to insightful inter-library comparison results. Full article

Safer and more efficient characterization of radioactive environments requires exploring intelligently, utilizing robotic systems which use smart strategies and physics-based statistical models. Bayesian Optimization (BO) provides one such statistical framework to explainably find the global maximum within noisy contexts while also minimizing the number of trials. For radiation survey and source location, the aid of such a machine learning algorithm could significantly cut down on time and health risks required for maintenance and emergency response scenarios. Maintaining the explainability while increasing the efficiency of the search has been found possible by including the high uncertainty data that is picked up while the agent is in transit. Now that the paths of transit matter to data acquisition they could be optimized as well. This paper introduces reinforcement learning (RL) to the BO search framework. The behavior of this RL additive is observed in simulation over three different datasets of real radiation data. It is shown that the RL additive can cause significant increases to the score of the maximum point discovered, but the computational time cost is increased by nearly 100% while the reconstructed radiation field root mean square error (RMSE) of the BO+RL algorithm matches BO performance within 1%. Full article

An experimental study was conducted on the feasibility of using frozen beads with the properties of Rupert’s drops—solid frozen beads with enhanced strength made from a mixture of aromatic hydrocarbons—in cryogenic neutron moderators utilizing bead technology. It is demonstrated that the use of a new modification of the dosing device with a high discharge rate (approximately 6 units/s) significantly improves process efficiency. With standard pneumatic transport parameters maintained, it was possible to load solid frozen beads made from a mixture of mesitylene and meta-xylene into the cryogenic moderator chamber. The loading speed increased five-fold, while the beads remained intact during pneumatic transport. Full article

This work presents the general mathematical frameworks of the “First and Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Integral Equations of Volterra Type” designated as the 1st-FASAM-NIE-V and the 2nd-FASAM-NIE-V methodologies, respectively. Using a single large-scale (adjoint) computation, the 1st-FASAM-NIE-V enables the most efficient computation of the exact expressions of all first-order sensitivities of the decoder response to the feature functions and also with respect to the optimal values of the NIE-net’s parameters/weights after the respective NIE-Volterra-net was optimized to represent the underlying physical system. The computation of all second-order sensitivities with respect to the feature functions using the 2nd-FASAM-NIE-V requires as many large-scale computations as there are first-order sensitivities of the decoder response with respect to the feature functions. Subsequently, the second-order sensitivities of the decoder response with respect to the primary model parameters are obtained trivially by applying the “chain-rule of differentiation” to the second-order sensitivities with respect to the feature functions. The application of the 1st-FASAM-NIE-V and the 2nd-FASAM-NIE-V methodologies is illustrated by using a well-known model for neutron slowing down in a homogeneous hydrogenous medium, which yields tractable closed-form exact explicit expressions for all quantities of interest, including the various adjoint sensitivity functions and first- and second-order sensitivities of the decoder response with respect to all feature functions and also primary model parameters. Full article