Nuclear Engineering and Design最新文献

{"title":"Research status in safety analysis of steam generator tube rupture accident in lead-based fast reactors – A review","authors":"Yutong Chen ,&nbsp;Dalin Zhang ,&nbsp;Yue Lin ,&nbsp;Di Wang ,&nbsp;Zhenyu Feng ,&nbsp;Wenxi Tian ,&nbsp;S.Z. Qiu ,&nbsp;G.H. Su","doi":"10.1016/j.nucengdes.2025.113904","DOIUrl":"10.1016/j.nucengdes.2025.113904","url":null,"abstract":"<div><div>Apart from the inherent advantages including high thermal efficiency, low operating pressure, stable coolant chemical properties, large heat capacity and easy modularization, Lead-based Fast Reactors (LFRs) are capable of transmuting long-live nuclear wastes while breeding fissile nuclides, therefore it is recognized as one of the most promising Gen-IV reactor concepts. In most existing LFR design schemes, the intermedia loop is not utilized, making the reactor more vulnerable to the risk of Steam Generator Tube Rupture (SGTR) accident. As a result, safety analysis of SGTR accident of LFR has become a major concern over the last decades. In this paper, the key phenomena at different stages of SGTR accident of LFR are categorized, the theoretical and experimental research status are reviewed, and the corresponding countermeasures are suggested. Focused on the four typical development stages of SGTR accident of LFR, namely the pressure wave propagating stage, the multiphase mixture expanding stage, the primary coolant (molten lead) and secondary coolant (usually pressurized water) interacting stage and the steam bubble migration stage, the research methods and recent progress are summarized. Besides, investigations on phenomena like rapid depressurization and two-phase critical flow that simultaneously occur in the secondary side are discussed subsequently. For those issues, the latest research activities, existing problems and future outlooks are demonstrated. This paper could provide useful reference for design and safety analysis issues of LFR SGTR accidents.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113904"},"PeriodicalIF":1.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394246","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":"Regression algorithm-based prediction of burnup history in pebble-bed high-temperature reactors","authors":"Hongjian Zhang,&nbsp;Qing Zhu,&nbsp;Liguo Zhang,&nbsp;Tao Ma","doi":"10.1016/j.nucengdes.2025.113907","DOIUrl":"10.1016/j.nucengdes.2025.113907","url":null,"abstract":"<div><div>The pebble-bed high-temperature reactor operates with continuous refueling, featuring a vast number of fuel spheres within the core that are challenging to locate and track, leading to an unknown burnup history of the nuclear fuel. This poses difficulties for nuclear material accounting, source term analysis, and the establishment of experimental benchmarks in pebble-bed high-temperature reactors. Currently, the online burnup measurement system in HTR-PM can measure the activity of radioactive nuclides, which are highly correlated with the burnup history and can be utilized to construct the loss function in burnup history inversion.</div><div>To reliably provide anticipated optimal solutions, this paper conducts an in-depth study on the construction of the above loss function through regression on a large dataset for burnup history prediction. The following three aspects of work are undertaken: 1) Simulating the core pebble flow using a discrete element model, simplifying the burnup history into an irradiation history sequence that includes neutron flux rates and irradiation durations, and demonstrating the rationality of this simplification; 2) Utilizing the above irradiation history sequence as input into a nuclear inventory software to generate a substantial dataset of known burnup histories and nuclide activities. Constructing weighted regression and deep neural network models, with online measurable nuclides as input data and fuel sphere burnup history as output data, to quantify the data potential of solving the burnup history from online measurable nuclides and to evaluate the contribution of different nuclides to the solution; 3) Analyzing the contribution to the solution of online measurable nuclides from the perspectives of burnup chains and nuclide characteristics, and establishing criteria for selecting input data for the burnup history prediction model.</div><div>The research outcomes of this paper represent a crucial step in predicting the burnup history of pebble-bed high-temperature reactors, achieving a mathematical description of the high-amplitude, high-frequency variations in fuel sphere burnup history. This paper also provides the computational limits of regression models for burnup history based on online measurable nuclides and conducts a detailed analysis of the contribution of input data to the solution, breaking through the bottleneck of unknown burnup history of fuel spheres in pebble-bed high-temperature reactors.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113907"},"PeriodicalIF":1.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387160","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":"Study on the removal behavior of corrosion products by mixed-bed ion exchange column in PWR","authors":"Shiyu Tan ,&nbsp;Haiyan Xie ,&nbsp;Shuang Chen ,&nbsp;Ke Wang ,&nbsp;Shitao Liu ,&nbsp;Dongyun Li ,&nbsp;Jing Li ,&nbsp;Yang Gao ,&nbsp;Hongguo Hou ,&nbsp;Caishan Jiao ,&nbsp;Nan Chao ,&nbsp;Tingting Liu ,&nbsp;Yu Zhou","doi":"10.1016/j.nucengdes.2025.113903","DOIUrl":"10.1016/j.nucengdes.2025.113903","url":null,"abstract":"<div><div>Accurate analysis and prediction of the removal behaviors of the ionic corrosion products in the mixed-bed ion exchange (MBIE) column in the chemical and volume control system in PWR is significantly necessary for judgement of the coolant quality and the resin bed replacement. In this paper, a film-controlled multicomponent MBIE column model is adopted to investigate the removal behaviors of various cationic and anionic corrosion products. The results suggest that this model can effectively predict the effluent concentration, the saturation adsorption time, and the resin loading. The mass transfer coefficient and ratio of the anionic and cationic resin can impose obvious influence on the estimation of the resin utilization. The larger the mass transfer coefficient is, the shorter the saturation adsorption time, and the lower of the initial effluent concentration. The resin can achieve the maximum utilization when the cationic and anionic reins fails simultaneously.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113903"},"PeriodicalIF":1.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387051","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":"Hybrid neural network and statistical forecasting methodology for predictive monitoring and residual useful life estimation in nuclear power plant components","authors":"S.A. Cancemi,&nbsp;M. Angelucci,&nbsp;A. Chierici,&nbsp;S. Paci,&nbsp;R. Lo Frano","doi":"10.1016/j.nucengdes.2025.113900","DOIUrl":"10.1016/j.nucengdes.2025.113900","url":null,"abstract":"<div><div>Lifetime extension of key components of Nuclear Power Plants (NPPs) is of great importance for reliable and continuous energy production. In this regard, the present paper proposes a novel Neural Network (NN) and time-series forecasting-based approach for the prediction of the health condition of nuclear components and the estimation of Remaining Useful Life (RUL) regarding Class II components, focusing on critical piping systems that may be subject to Flow- Accelerated Corrosion (FAC). A digital replica of a Class II piping was implemented in a finite element code to simulate the progressive thinning it suffers because of operational and environmental conditions. To the aim of the present study, generated synthetic data have been employed in the training phase of the NN model. Autoencoder, which is a special type of NN, that compresses input data into one major holistic signal representing the component’s health status, is used. The component RUL is computed in this study by the ARIMA algorithm. Results showed that the adopted hybrid methodology is capable of forecasting accurately the piping plastic deformation 6 to 14 months in advance, thus allowing for better and more efficient NPP maintenance and management.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113900"},"PeriodicalIF":1.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental study on sedimentary radioactive source-tems distribution characteristics of in-service nuclear power plants","authors":"Guoqing Xu ,&nbsp;Weizhong Sun ,&nbsp;Zhihua Li ,&nbsp;Yao Wu ,&nbsp;Weiqi Li ,&nbsp;Yushou Song ,&nbsp;Guobao Wang","doi":"10.1016/j.nucengdes.2025.113906","DOIUrl":"10.1016/j.nucengdes.2025.113906","url":null,"abstract":"<div><div>The number of investigation objects of sedimentary radioactive source-tems of in-service nuclear power plants is huge, so we can only select a few objects for investigation. Mastering the distribution characteristics of sedimentary radioactive source-tems can improve the representativeness and rationality of the selection of investigation objects, and it can also effectively reduce the cost. Based on four pressurized water reactor units, the scope of preliminary sedimentary radioactive source-tems investigation was determined according to the design principles of each system and the generation mechanism. The investigation objects were selected in a step-by-step manner, then HPGe, CZT and γ dose rate meter were used to measure the selected objects, and the experimental data were visualized by statistical methods. The experimental results were analyzed from three aspects: nuclide level, system level and unit level. The analysis results show that the distribution of ⁶⁰Co and ⁵⁸Co in the sedimentary radioactive source-tems is the most widespread and the highest in proportion, with a combined proportion of over 80%. The surface activity of the sedimentary radioactive source-tems in RCP, RCV, and RRA is the highest, and the types of sedimentary radioactive source-tems in the same system among the four units are basically the same. The distribution of the ambient dose equivalent rate and the surface activity of the sedimentary radioactive source-tems in each unit is roughly equivalent. The results of this experimental study can provide important reference value for the subsequent sedimentary radioactive source-tems investigation of the same type of nuclear power plant.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113906"},"PeriodicalIF":1.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387050","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 and application of two-step uncertainty propagation and sensitivity analysis methodology for fast reactor safety analysis","authors":"I. Trivedi ,&nbsp;G. Delipei ,&nbsp;J. Hou ,&nbsp;G. Grasso ,&nbsp;K. Ivanov","doi":"10.1016/j.nucengdes.2025.113882","DOIUrl":"10.1016/j.nucengdes.2025.113882","url":null,"abstract":"<div><div>Uncertainty quantification (UQ) in nuclear reactors for transients is directly linked with safety assessment through the cross-sections uncertainties, provided as a covariance matrix, which are propagated through the reactor system to output of interest pertaining to reactor safety, such as peak temperatures in fuel/clad/coolant. Using a two-step approach, uncertainties are first quantified and propagated from basic input variables (such as reaction cross-sections) to intermediate quantities (such as reactivity feedback coefficients) through lattice level calculations. Uncertainties of intermediate quantities (from the first step) are then propagated through the system transient calculations, in the second step, to obtain uncertainties on reactor safety output parameters of interest. The scope of this work consists of Uncertainty Quantification &amp; Propagation of nuclear data uncertainties that are highly correlated through unprotected transient overpower and unprotected loss of flow to assess their impact on core safety parameters. This two-step approach in the presence of covariance renders the sensitivity analysis very challenging. In fact, usually the sensitivity analysis is restricted to each step, which limits its application since the sensitivities between the system output quantities and the basic input variables are difficult to obtain. In this work, we address this issue by proposing a simple, general methodology to combine the sensitivity indices obtained in each step by assuming the model behavior being linear. For the first step Generalized Perturbation theory based indices are used while in the second step the recently studied Johnson indices.</div><div>The uncertainty quantification and sensitivity methodologies discussed here are demonstrated on a generic LFR design which is based on the 500 MW_th demonstration Lead-cooled fast reactor (DLFR) using oxide fuel, developed by Westinghouse Electric Company (WEC).</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113882"},"PeriodicalIF":1.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387049","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":"Research on the intelligent control strategy of pressurizer pressure in PWRs based on a fuzzy neural network PID controller","authors":"Hongyang Wei,&nbsp;Ning Zhu,&nbsp;Zhenyang Sun,&nbsp;Sichao Tan,&nbsp;Ruifeng Tian","doi":"10.1016/j.nucengdes.2025.113875","DOIUrl":"10.1016/j.nucengdes.2025.113875","url":null,"abstract":"<div><div>For pressurized water reactors (PWRs), it is traditional method to use proportional-integral-derivative (PID) controllers to adjust the pressure and liquid level of the pressurizer. Traditional PID controllers have limitations, such as fixed parameters and an inability to adapt to changes in operating conditions. To address this issue, this paper proposes an intelligent control method based on a fuzzy neural network (FNN) PID approach for the pressurizer pressure control. To assess the control performance of this proposed method, a simulation code was developed. This code incorporated a two-region non-equilibrium model of the pressurizer, coupling with simulation of PID control, fuzzy PID control, and FNN-PID control. The typical PWRs pressurizer is simulated in the typical variable load transient process. The pressure simulation results under the control of these three controllers are compared, and the effectiveness of the FNN-PID controller proposed in this paper is also verified.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113875"},"PeriodicalIF":1.9,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387048","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":"Multi-scale modeling of creep behavior in U3Si2-Al composites and the impact on curved fuel elements’ irradiation performance","authors":"Yue Song ,&nbsp;Meng Lv ,&nbsp;Heng Xie","doi":"10.1016/j.nucengdes.2025.113902","DOIUrl":"10.1016/j.nucengdes.2025.113902","url":null,"abstract":"<div><div>U₃Si₂-Al dispersion fuel is a promising candidate for the conversion of high-performance research reactors due to its high burnup characteristics. As irradiation time increases, the in-pile creep performance of the composite fuel plays a crucial role in determining the mechanical integrity and safety of the fuel elements. To assess the creep behavior, a multi-scale representative volume element (RVE) model of U₃Si₂-Al composite fuel was developed in this study and the influence factors were investigated. Meanwhile, the developed model was used in a three-dimensional finite element model to analyze the mechanical deformation of the composite fuel plates under irradiation. The obtained results show that: (1) the macroscopic creep rate of U₃Si₂-Al composites was influenced by factors such as U₃Si₂ volume fraction, tensile stress, temperature, and fission rate; (2) the aluminum matrix is the primary contributor to overall creep deformation, with its thermal creep contribution being the dominant factor, exhibiting substantially higher creep rates than U₃Si₂ particles; and (3) using the aluminum matrix creep model in place of the creep model with a coefficient of 50 × 10⁻²²mm³/fission/MPa resulted in greater thickness increases and modifications in Mises stress distribution in curved fuel plates under irradiation conditions. This research provides a critical theoretical framework for understanding the creep behavior of U₃Si₂-Al composites, facilitating future mechanical stress analysis of fuel elements.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113902"},"PeriodicalIF":1.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377021","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":"Optimizing the small modular reactor core loading with dual-cooled fuel via Henry gas solubility optimization algorithm","authors":"H. Zayermohammadi Rishehri,&nbsp;G.R. Ansarifar","doi":"10.1016/j.nucengdes.2025.113899","DOIUrl":"10.1016/j.nucengdes.2025.113899","url":null,"abstract":"<div><div>An investigation into the influence of innovative dual-cooled fuel geometric structural characteristics on critical reactor core parameters, such as temperature reactivity coefficients and convective heat transfer coefficient, is essential for accurately assessing its neutronic and thermohydraulic performance and estimating safety margins. This study calculated the fuel and coolant/moderator temperature reactivity coefficients in the NuScale-type reactor using WIMS-CITATION codes. Additionally, the impact of increasing the size of dual-cooled fuel rods on these coefficients was analyzed. The study also calculated the hot rod convective heat transfer coefficient for proposed fuel rods using a Computational Fluid Dynamics (CFD) and sub-channel model method. The results demonstrated that increasing the internal radius of the fuel decreases the temperature reactivity feedback coefficient of fuels, while the feedback coefficient of coolant exhibits a parabolic trend. All proposed fuel rods exhibited negative coolant and fuel temperature reactivity coefficients, and increasing the internal radius resulted in a reduction in the convective heat transfer coefficient. Furthermore, the study explored the use of Artificial Neural Network (ANN) and Gene Expression Programming (GEP) models to develop an optimal method with low computational cost. Based on statistical indicators, the ANN was found to outperform GEP. Finally, the designed ANN, coupled with the Henry Gas Solubility Optimization (HGSO) algorithm, was employed to determine the optimal dual-cooled fuel based on desired parameters.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113899"},"PeriodicalIF":1.9,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377022","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":"Adaptive learning observer and radial basis function neural networks based fixed-time fault-tolerant control of load following for a MHTGR with CRDM faults","authors":"Wangheng Liu ,&nbsp;Hongliang Liu ,&nbsp;Zigen Ouyang ,&nbsp;Wenjie Zeng ,&nbsp;Hua Liu","doi":"10.1016/j.nucengdes.2025.113872","DOIUrl":"10.1016/j.nucengdes.2025.113872","url":null,"abstract":"<div><div>Load following of the Modular High-Temperature Gas-Cooled Reactor (MHTGR) under Control Rod Drive Mechanism (CRDM) faults and disturbances remains a major challenge. This paper focuses on proposing a fixed-time fault-tolerant control method for this issue without considering the sensitivities associated with parameter setting. Firstly, to reconstruct some unmeasurable states of the MHTGR and the values of CRDM faults, an adaptive learning observer is established. Based on the learning characteristic of Radial Basis Function Neural Networks (RBFNN), the lumped uncertainties can be approximated. And then a fixed-time fault-tolerant controller is developed to ensure that the actual load output of the MHTGR actually tracks the expected output power within a fixed time, which can be determined through the system and controller parameters. Finally, simulations under two operational conditions demonstrate the control method is effective and feasible to the MHTGR system under disturbance and CRDM faults.</div></div>","PeriodicalId":19170,"journal":{"name":"Nuclear Engineering and Design","volume":"433 ","pages":"Article 113872"},"PeriodicalIF":1.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349963","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}