Progress in Nuclear Energy最新文献

{"title":"Modification of the turbulent model for flow in bare rod bundle based on data assimilation technology","authors":"Zhenyang Sun ,&nbsp;Hongyang Wei ,&nbsp;Yiwei Wang ,&nbsp;Sichao Tan ,&nbsp;Yitung Chen","doi":"10.1016/j.pnucene.2025.105955","DOIUrl":"10.1016/j.pnucene.2025.105955","url":null,"abstract":"<div><div>Conventional simulation approaches of the flow and heat transfer characteristics of the coolant in fuel rod bundle suffer from either excessive computational expenses or insufficient predictive precision. In this study, a method to improve the prediction accuracy of turbulent flow simulation in bare rod bundles is used. The ensemble Kalman filter algorithm in the data assimilation algorithm is used, and the existing dimensionless turbulent kinetic energy experimental data is used as the experimental observation value. The <span><math><mrow><mi>k</mi><mo>‐</mo><mi>ω</mi></mrow></math></span> SST turbulence model is studied for constant optimization and the influence of single-point data location changes on model prediction results is explored. The results show that compared with the default turbulence model, the modified turbulence model has better prediction accuracy. This work could bring reference for the further investigation of turbulent flow behavior in fuel assembly.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105955"},"PeriodicalIF":3.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expanded transfer functions – A method to correlate multigroup macroscopic cross sections to non-local operational parameters","authors":"Bailey Painter,&nbsp;Dan Kotlyar","doi":"10.1016/j.pnucene.2025.105914","DOIUrl":"10.1016/j.pnucene.2025.105914","url":null,"abstract":"","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105914"},"PeriodicalIF":3.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized fuel cycle and burnup analysis for pebble-bed reactors","authors":"Sefa Bektaş ,&nbsp;Volkan Seker ,&nbsp;Üner Çolak ,&nbsp;Thomas Downar","doi":"10.1016/j.pnucene.2025.105937","DOIUrl":"10.1016/j.pnucene.2025.105937","url":null,"abstract":"<div><div>In a pebble-bed reactor (PBR) core, hundreds of thousands of densely packed fuel pebbles flow slowly downward. This complicates fuel movement and extends computational time for fuel cycle analysis. To overcome this problem, a quasi-static pebble flow is combined with batch-wise refueling. Achieving an equilibrium core state requires a burnup sensitivity analysis to assess how methods for coupling neutronics with depletion impact the accuracy of burnup calculations. Numerical burnup calculations face a fundamental challenge of nonlinearity: the burnup matrix, which determines fuel depletion, varies over time due to its dependence on the neutron flux, which itself is influenced by the evolving nuclide density distributions. While the explicit Euler method is commonly used for coupling neutronics with fuel depletion, its low accuracy can be problematic in PBR applications. In contrast, the predictor–corrector method enhances accuracy but requires twice as many transport calculations, increasing computational demands. To address these challenges, this study performed a time-step optimization using the SERPENT Monte Carlo code on the HTR200 design under the once-through-then-out (OTTO) scheme. The study highlighted significant runtime reductions, from approximately 10 h to about 4 h, while analyzing the effective multiplication factor (k-eff) and key isotopes, such as Xe-135, U-235, and Pu-239.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105937"},"PeriodicalIF":3.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable machine learning for quantitative parameter importance and operational thresholds in PWR accident prediction","authors":"Jinqi Zheng,&nbsp;Yichun Wu,&nbsp;Qing Liang,&nbsp;Jiale Ling,&nbsp;Jiayan Fang","doi":"10.1016/j.pnucene.2025.105948","DOIUrl":"10.1016/j.pnucene.2025.105948","url":null,"abstract":"<div><div>The \"black box\" nature of machine learning models hinders trust and transparency in nuclear safety systems, where interpretability is critical. This study introduces an explainable CatBoost-SHAP framework for accident prediction in pressurized water reactors (PWRs). Leveraging CPR1000 reactor simulator and Optuna-optimized CatBoost, the model achieved high accuracy (R² &gt; 0.999, MAPE &lt;1 %) on small break loss-of-coolant accident (SBLOCA) datasets for both hot-leg and cold-leg scenario, outperforming XGBoost and LightGBM. SHAP analysis identified key thermal-hydraulic drivers (e.g., steam generator (SG) pressure &lt;6.74 MPa, wide-range downcomer level &lt;−1.4 %) and uncovered nonlinear interactions among multi-loop variables, consistent with reactor physics. The framework's dual capability - high predictive precision and mechanistic interpretability - enables operators to validate decision pathways and prioritize safety thresholds. By bridging the gap between opaque AI and nuclear safety demands, this work provides practical guidelines for real-time diagnostics and proactive accident mitigation in PWRs.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105948"},"PeriodicalIF":3.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing radiation target level for the shielding design of a nuclear-powered container ship and its determination process using MCNP6 code","authors":"Hyoeun Lee,&nbsp;Jaehyun Cho","doi":"10.1016/j.pnucene.2025.105947","DOIUrl":"10.1016/j.pnucene.2025.105947","url":null,"abstract":"<div><div>As the International Maritime Organization strives for net-zero emissions in the maritime sector by 2050, nuclear-powered ships offer a viable solution due to their zero greenhouse gas emissions, long operational lifespan, and high energy density. However, the implementation of nuclear propulsion raises concerns regarding crew radiation exposure and national security, issues that necessitate optimal radiation shielding. This study proposes the concept of radiation target level (RTL) to inform the radiation shielding design of nuclear-powered ships. To maximize economic viability while ensuring safety, the reference ship, a 15,000 TEU container ship, is divided into a shielding zone, which encloses the reactor and the primary shielding, and a non-shielding zone, which includes crew living and work areas. Radiation exposure in the non-shielding zone is managed by controlling the time spent in different areas of this zone, referred to as stay time, adhering to the ALARA principle. Using MCNP6 code, radiation levels are analyzed at key locations and permissible stay times are evaluated against ICRP dose limits. As a result, this study determined an optimal RTL of 8.92 μSv/hr, ensuring compliance with an annual dose limit of 1 mSv for all personnel on board. This result provides a reference for shielding design, radiation zone classification, and crew exposure management, contributing to the safe and economically viable operation of nuclear-powered ships.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105947"},"PeriodicalIF":3.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-based noise diagnostics for water-cooled SMRs: proof of principle on 2-dimensional systems","authors":"Salma Magdi Hussein ,&nbsp;Christophe Demazière","doi":"10.1016/j.pnucene.2025.105950","DOIUrl":"10.1016/j.pnucene.2025.105950","url":null,"abstract":"<div><div>This study explores a core monitoring approach for two-dimensional Small Modular Reactors (SMRs) using neutron noise analysis and machine learning (ML) methods. Absorber of Variable Strength (AVS) perturbations are simulated in the frequency domain to analyze reactor noise behavior differences between large reactors and SMRs. It is demonstrated that SMRs exhibit stronger point-kinetic characteristics, complicating perturbation diagnosis. Thermal-group neutron noise is found to carry more diagnostic information than fast-group neutron noise. This makes thermal-group neutron noise more effective for localizing perturbations. A convolutional neural network (CNN) is trained on a dataset that contains only one or two AVS sources per sample. Despite this limited training dataset, the model can accurately localize up to 10 sources in a sample. The results demonstrate the model's strong generalization capability and high nodal accuracy. To address sparse detector scenarios, a two-stage pipeline is designed to reconstruct full reactor noise fields from limited data points prior to source localization. The pipeline demonstrates effective reconstruction and localization with 50 % detector coverage, accurately capturing both global and local noise components. For reduced instrumentation scenarios of 11 %, 6 %, and 3 % coverage, the model retains reasonable performance, with proximity-based metrics indicating robust localization capabilities. The results highlight the importance of strategic detector placement to balance global and local noise components for effective anomaly detection. The research demonstrates that ML techniques can enhance neutron noise analysis, even under limited data availability. This work contributes to enhancing the safety and operational reliability of SMRs, emphasizing the importance of advanced monitoring methods and data-informed instrumentation layouts to optimize performance, safety, and efficiency.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105950"},"PeriodicalIF":3.2,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deterministic and probabilistic Deep Learning in predicting reactor physics of subcritical system driven by a pulsed source","authors":"Ronald Daryll E. Gatchalian ,&nbsp;Pavel V. Tsvetkov","doi":"10.1016/j.pnucene.2025.105949","DOIUrl":"10.1016/j.pnucene.2025.105949","url":null,"abstract":"<div><div>Widely reported are the non-ideal response of standard techniques in reactivity measurement when the Subcritical Assembly (SCA) is far from critical. This emanates from the loose applicability of fundamental mode assumption in Point Reactor Kinetics from which the analytical formulae relating detector response to reactivity were derived. This work evaluated the potential of Deep Learning (DL) in overcoming these biasing effects particularly in an SCA driven by a Pulsed Neutron Source (PNS). Deterministic DL models processing core map and detector temporal response were trained using data from neutronics calculations, and subsequently compared with Area-ratio, and Slope-fit methods in a simulated PNS experiment. Results show the robustness of DL against spatial effect that severely affected Area-ratio method leading to severe underestimation, a non-conservative scenario in criticality safety. As illustration, <span><math><mrow><msubsup><mi>k</mi><mrow><mi>e</mi><mi>f</mi><mi>f</mi></mrow><mrow><mi>D</mi><mi>L</mi></mrow></msubsup><mo>=</mo><mn>0.94158</mn></mrow></math></span> is approximately equal to <span><math><mrow><msubsup><mi>k</mi><mrow><mi>e</mi><mi>f</mi><mi>f</mi></mrow><mrow><mi>M</mi><mi>C</mi><mi>N</mi><mi>P</mi></mrow></msubsup><mo>=</mo><mn>0.94093</mn><mo>±</mo><mn>0.00034</mn></mrow></math></span>; meanwhile <span><math><mrow><msubsup><mi>k</mi><mrow><mi>e</mi><mi>f</mi><mi>f</mi></mrow><mrow><mi>A</mi><mi>r</mi><mi>e</mi><mi>a</mi><mo>−</mo><mi>r</mi><mi>a</mi><mi>t</mi><mi>i</mi><mi>o</mi></mrow></msubsup><mo>=</mo><mn>0.435</mn><mo>±</mo><mn>0.00900</mn><mo>≪</mo><msubsup><mi>k</mi><mrow><mi>e</mi><mi>f</mi><mi>f</mi></mrow><mrow><mi>M</mi><mi>C</mi><mi>N</mi><mi>P</mi></mrow></msubsup></mrow></math></span>. Furthermore, DL did not indicate increasing bias as system becomes deeply subcritical unlike Slope-fit method. These advantages also extended to probabilistic variants based on Bayesian Neural Networks, which were found to be well-calibrated due to matching predicted and observed confidence levels. These findings suggest the strong potential of deploying DL in an operational context, helping assure safety margins in SCAs and safe approach to criticality in research reactors.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105949"},"PeriodicalIF":3.3,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of surface condition, temperature and relative humidity on atmospheric chloride-induced stress corrosion cracking of stainless steel","authors":"Chun-Ping Yeh,&nbsp;Kun-Chao Tsai,&nbsp;Jiunn-Yuan Huang","doi":"10.1016/j.pnucene.2025.105926","DOIUrl":"10.1016/j.pnucene.2025.105926","url":null,"abstract":"<div><div>SS304L representative of dry storage canister material were subjected to chloride-induced stress corrosion cracking, which is a crucial safety concern when exposed to the marine environment. In addition, co-deposition of dust and salt on the canister surface can enhance the crevice corrosion susceptibility of 304L stainless steel. White emery was utilized in this study to simulate the dust accumulation on the surface of the as-machined sample. An investigation into the effect of surface condition, temperature, dust accumulation and relative humidity on crevice corrosion was employed on austenitic 304L stainless steel tested under 35 °C and 45 °C with 45 %, 55 % and 70 % relative humidity (RH). In order to assess the potential for atmospheric chloride-induced stress corrosion cracking (AISCC), the experimental results of SS304L are analyzed.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105926"},"PeriodicalIF":3.2,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust state estimation from partial out-core measurements with Shallow Recurrent Decoder for nuclear reactors","authors":"Stefano Riva ,&nbsp;Carolina Introini ,&nbsp;Antonio Cammi ,&nbsp;J. Nathan Kutz","doi":"10.1016/j.pnucene.2025.105928","DOIUrl":"10.1016/j.pnucene.2025.105928","url":null,"abstract":"<div><div>Reliable, real-time state estimation in nuclear reactors is of critical importance for monitoring, control and safety. It further empowers the development of digital twins that are sufficiently accurate for real-world deployment. As nuclear engineering systems are typically characterised by extreme environments, their in-core sensing is a challenging task, even more so in Generation-IV reactor concepts, which feature molten salt or liquid metals as thermal carriers. The emergence of data-driven methods allows for new techniques for accurate and robust estimation of the full state space vector characterising the reactor (mainly composed by neutron fluxes and the thermal-hydraulics fields). These techniques can combine different sources of information, including computational proxy models and local noisy measurements on the system, in order to robustly estimate the state. This work leverages the <em>Shallow Recurrent Decoder</em> (SHRED) architecture to estimate the entire state vector of a reactor from three, out-of-core time-series neutron flux measurements alone. Specifically, the Molten Salt Fast Reactor, in the geometry of the EVOL (Evaluation and Viability of Liquid Fuel Fast Reactor System) project, is demonstrated as a test case, with neutron flux measurements alone allowing for reconstruction of the 20 coupled field variables of the dynamics. This approach can further quantify the uncertainty associated with the state estimation due to its considerably low training cost on compressed data. The accurate reconstruction of every characteristic field in real-time makes this approach suitable for monitoring and control purposes in the framework of a reactor digital twin.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105928"},"PeriodicalIF":3.3,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of cross-section model of two-step code system considering control rod depletion for soluble boron free operation of SMR","authors":"Jinsu Park ,&nbsp;Wonkyeong Kim ,&nbsp;Yeongseok Kang ,&nbsp;Wisoo Jeong ,&nbsp;Changhyun Lim ,&nbsp;Jooil Yoon ,&nbsp;Deokjung Lee","doi":"10.1016/j.pnucene.2025.105951","DOIUrl":"10.1016/j.pnucene.2025.105951","url":null,"abstract":"<div><div>This paper demonstrates an advanced cross-section model including a control rod depletion for the soluble boron-free operation of small modular reactors (SMRs), specifically utilizing the STREAM/RAST-K two-step code system. With the growing demand for SMRs and the shift toward boron-free operations, control rods are essential for controlling excess reactivity. However, the insertion of control rods changes the neutron spectrum and depletes both the fuel and control rod material, necessitating a more accurate modeling approach. It is impossible to adequately address the effects of control rod insertion during fuel depletion using traditional cross-section model from two-step code system. In advanced cross-section model, the microscopic cross-section and number density changes caused by fuel and control rod depletion is possible to track. Also, this approach combines cross-section set from both rodded and unrodded fuel depletion using a history index variable. The new method is verified against whole core transport code (STREAM3D) using multi-cycle depletion calculations of SMRs, showing improved accuracy in control rod worth and power distribution predictions. Although reactivity predictions showed similar accuracy due to error cancellation, the overall method enhances precision in reactor physics calculations.</div></div>","PeriodicalId":20617,"journal":{"name":"Progress in Nuclear Energy","volume":"189 ","pages":"Article 105951"},"PeriodicalIF":3.3,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}