Pub Date : 2026-01-07DOI: 10.1016/j.anucene.2026.112113
Yuan Xu , Yun Long , Long Cai , Zhe Jiao
We investigate unsteady hydrodynamics of a shaft-sealed reactor coolant pump (RCP) across cold/hot states (25 °C/292 °C; 1/15.9 MPa) and tip-clearance variations from the design tip clearance of 0.8 mm (0.5 mm smaller and 1.0 mm and 2.0 mm larger than the design value). Using SST k–ω CFD with rotor–stator coupling, we quantify performance, pressure-pulsation spectra, and radial forces. Dominant components occur at the shaft frequency (1fn≈24.75 Hz) and diffuser blade-passing (5fn≈123.75 Hz), with a leading-peak shift to 5fn near the impeller outlet. Hot conditions intensify pulsations and radial loading and smooth the performance curve; at ∼ 1.2Q the hot-state head is ∼ 5 % higher. The radial force shows periodic modulation (≈3.22–3.42 kN) and a five-lobe pattern. Clearance changes alter head and spectra: +2 mm reduces head and elevates 5fn, whereas − 0.5 mm improves uniformity and still lowers head. These results provide a spectral-shift–load-coupled basis for clearance tolerance and operating-window selection to enhance RCP stability and safety.
{"title":"Unsteady hydrodynamics of an RCP impeller across clearances and hot conditions pressure pulsation, spectral shift, and radial force","authors":"Yuan Xu , Yun Long , Long Cai , Zhe Jiao","doi":"10.1016/j.anucene.2026.112113","DOIUrl":"10.1016/j.anucene.2026.112113","url":null,"abstract":"<div><div>We investigate unsteady hydrodynamics of a shaft-sealed reactor coolant pump (RCP) across cold/hot states (25 °C/292 °C; 1/15.9 MPa) and tip-clearance variations from the design tip clearance of 0.8 mm (0.5 mm smaller and 1.0 mm and 2.0 mm larger than the design value). Using SST k–ω CFD with rotor–stator coupling, we quantify performance, pressure-pulsation spectra, and radial forces. Dominant components occur at the shaft frequency (1fn≈24.75 Hz) and diffuser blade-passing (5fn≈123.75 Hz), with a leading-peak shift to 5fn near the impeller outlet. Hot conditions intensify pulsations and radial loading and smooth the performance curve; at ∼ 1.2Q the hot-state head is ∼ 5 % higher. The radial force shows periodic modulation (≈3.22–3.42 kN) and a five-lobe pattern. Clearance changes alter head and spectra: +2 mm reduces head and elevates 5fn, whereas − 0.5 mm improves uniformity and still lowers head. These results provide a spectral-shift–load-coupled basis for clearance tolerance and operating-window selection to enhance RCP stability and safety.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112113"},"PeriodicalIF":2.3,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922129","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}
Pub Date : 2026-01-06DOI: 10.1016/j.anucene.2025.112112
Shihao Dong , Junjie Deng , Pengcheng Zhao , Zijing Liu , Wei Li
Current research on the multi-scale coupling of reactors primarily focuses on the development of coupled simulation programs, which suffer from numerous uncertainties. This work establishes an uncertainty quantification (UQ) framework for multi-scale thermal–hydraulic (TH) coupling, which leverages the preCICE open-source platform to integrate the high-fidelity CFD code FLUENT, subchannel code SUBCHANFLOW, and UQ code DAKOTA. A 3 × 3 rod bundle configuration is used as a benchmark to validate the coupled framework under steady-state and transient conditions. Under steady-state conditions, the coupled model consistently predict axial temperature distributions when benchmarked against solvers (FLUENT and SUBCHANFLOW), validating the computational accuracy of multi-scale TH coupling. Under transient conditions with sinusoidal inlet flow variations, the outlet flow response synchronizes the period and phase with input perturbations, confirming the dynamic simulation capability of coupled system. Uncertainty quantification suggests that key parameters, including coolant temperature and peak cladding temperature, exhibit a normal distribution approximately. Sensitivity analysis reveals that inlet mass flow rate, outlet pressure, inlet temperature, and fuel rod heat flux are the dominant parameters influencing the system response. Overall, the proposed system exhibits reliable response characteristics under dynamic conditions.
{"title":"Uncertainty analysis method for the multi-scale coupling program based on preCICE","authors":"Shihao Dong , Junjie Deng , Pengcheng Zhao , Zijing Liu , Wei Li","doi":"10.1016/j.anucene.2025.112112","DOIUrl":"10.1016/j.anucene.2025.112112","url":null,"abstract":"<div><div>Current research on the multi-scale coupling of reactors primarily focuses on the development of coupled simulation programs, which suffer from numerous uncertainties. This work establishes an uncertainty quantification (UQ) framework for multi-scale thermal–hydraulic (TH) coupling, which leverages the preCICE open-source platform to integrate the high-fidelity CFD code FLUENT, subchannel code SUBCHANFLOW, and UQ code DAKOTA. A 3 × 3 rod bundle configuration is used as a benchmark to validate the coupled framework under steady-state and transient conditions. Under steady-state conditions, the coupled model consistently predict axial temperature distributions when benchmarked against solvers (FLUENT and SUBCHANFLOW), validating the computational accuracy of multi-scale TH coupling. Under transient conditions with sinusoidal inlet flow variations, the outlet flow response synchronizes the period and phase with input perturbations, confirming the dynamic simulation capability of coupled system. Uncertainty quantification suggests that key parameters, including coolant temperature and peak cladding temperature, exhibit a normal distribution approximately. Sensitivity analysis reveals that inlet mass flow rate, outlet pressure, inlet temperature, and fuel rod heat flux are the dominant parameters influencing the system response. Overall, the proposed system exhibits reliable response characteristics under dynamic conditions.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112112"},"PeriodicalIF":2.3,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922118","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}
Pub Date : 2026-01-06DOI: 10.1016/j.anucene.2026.112118
Wenming Yi , Feng Shen , GuoPing Quan , Xubo Ma , Guang Zhao
Accurate and efficient parameterization of assembly homogenized few-group constants is a critical challenge in reactor physics. Traditional methods are either too computationally expensive, like Monte Carlo codes, or struggle with the high-dimensional, non-linear relationships found in reactor data, like interpolation methods, especially when sample sizes are small. To address this, we propose a novel machine learning ensemble method, the Deep Neural Network with Gaussian Process Residual Correction (DNN-GPRC). This hybrid model uses a DNN to capture the primary data trends and a GPR to model and correct the DNN’s prediction residuals, leveraging GPR’s robustness on small datasets. Furthermore, we employ a Yeo–Johnson transformation in feature engineering to effectively mitigate the long-tail data distribution inherent in burnup calculations, significantly enhancing model performance. Tested on a small dataset of 2874 samples, the DNN-GPRC model consistently outperforms both standalone DNN and traditional linear interpolation methods. Crucially, on the test set, our model achieves a Root Mean Square Error of just 128 pcm for the infinite multiplication factor (), a result markedly superior to linear interpolation. This work demonstrates that the DNN-GPRC framework provides a high-accuracy, computationally efficient, and robust tool for few-group constant parameterization. It moves the field forward by enabling rapid and accurate analysis even in low-sample scenarios, which is vital for accelerating new reactor design cycles and improving simulation fidelity.
{"title":"Prediction of homogenized few-group constants for pressurized water reactor assembly using a Deep Neural Network with Gaussian Process Residual Correction","authors":"Wenming Yi , Feng Shen , GuoPing Quan , Xubo Ma , Guang Zhao","doi":"10.1016/j.anucene.2026.112118","DOIUrl":"10.1016/j.anucene.2026.112118","url":null,"abstract":"<div><div>Accurate and efficient parameterization of assembly homogenized few-group constants is a critical challenge in reactor physics. Traditional methods are either too computationally expensive, like Monte Carlo codes, or struggle with the high-dimensional, non-linear relationships found in reactor data, like interpolation methods, especially when sample sizes are small. To address this, we propose a novel machine learning ensemble method, the Deep Neural Network with Gaussian Process Residual Correction (DNN-GPRC). This hybrid model uses a DNN to capture the primary data trends and a GPR to model and correct the DNN’s prediction residuals, leveraging GPR’s robustness on small datasets. Furthermore, we employ a Yeo–Johnson transformation in feature engineering to effectively mitigate the long-tail data distribution inherent in burnup calculations, significantly enhancing model performance. Tested on a small dataset of 2874 samples, the DNN-GPRC model consistently outperforms both standalone DNN and traditional linear interpolation methods. Crucially, on the test set, our model achieves a Root Mean Square Error of just 128 pcm for the infinite multiplication factor (<span><math><msub><mrow><mi>k</mi></mrow><mrow><mi>i</mi><mi>n</mi><mi>f</mi></mrow></msub></math></span>), a result markedly superior to linear interpolation. This work demonstrates that the DNN-GPRC framework provides a high-accuracy, computationally efficient, and robust tool for few-group constant parameterization. It moves the field forward by enabling rapid and accurate analysis even in low-sample scenarios, which is vital for accelerating new reactor design cycles and improving simulation fidelity.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112118"},"PeriodicalIF":2.3,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922126","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}
Pub Date : 2026-01-06DOI: 10.1016/j.anucene.2025.112060
Peter J. Kriemadis, Adriaan Buijs
The Zero Energy Deuterium (ZED-2) reactor is a zero-power research reactor located at the Chalk River site of Canadian Nuclear Laboratories (CNL). The reactor was built to assist in neutronics code validation efforts for CANadian Deuterium Uranium (CANDU) reactors, but may find further use in the validation of computer codes used in the design of Small Modular Reactors (SMRs). This paper describes the application of the OpenMC and SERPENT 2 codes to two published benchmarks for ZED-2 neutronics experiments. The results were then compared to MCNP and MONK code results on file. Experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook were reviewed to establish the differences one might expect from Monte Carlo code-to-code comparisons. The completed benchmarks were assessed against this review. In this manner, the OpenMC code is validated both against an experiment and against other validated codes.
{"title":"ZED-2 benchmarks performed in OpenMC and Serpent 2: A validation exercise for OpenMC applications","authors":"Peter J. Kriemadis, Adriaan Buijs","doi":"10.1016/j.anucene.2025.112060","DOIUrl":"10.1016/j.anucene.2025.112060","url":null,"abstract":"<div><div>The Zero Energy Deuterium (ZED-2) reactor is a zero-power research reactor located at the Chalk River site of Canadian Nuclear Laboratories (CNL). The reactor was built to assist in neutronics code validation efforts for CANadian Deuterium Uranium (CANDU) reactors, but may find further use in the validation of computer codes used in the design of Small Modular Reactors (SMRs). This paper describes the application of the OpenMC and SERPENT<!--> <!-->2 codes to two published benchmarks for ZED-2 neutronics experiments. The results were then compared to MCNP and MONK code results on file. Experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook were reviewed to establish the differences one might expect from Monte Carlo code-to-code comparisons. The completed benchmarks were assessed against this review. In this manner, the OpenMC code is validated both against an experiment and against other validated codes.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112060"},"PeriodicalIF":2.3,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145922117","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}
Pub Date : 2026-01-03DOI: 10.1016/j.anucene.2025.112104
Jing Zhang, Shurong Ding
FCM fuel, composed of TRISO particles and SiC matrix, is a typical accident tolerant fuel that holds a promising application prospect in various advanced nuclear reactors. Optimization of the microstructure of TRISO (Tri-Structural Isotropic) particles is crucial for enhancing both the safety and economy of nuclear fuel systems. In this study, the recently published novel fission gas swelling model or volume-growth strain models for the fuel kernel and the buffer layer are involved, enabling more accurate simulation of the irradiation thermo-mechanical coupling behaviors of FCM fuel. The three-dimensional mechanical constitutive relations, stress update algorithms and consistent stiffness moduli for the points within the buffer layer and PyC layer are newly formulated, and the corresponding procedures are developed. With the fuel kernel volume fraction and SiC layer dimensions kept constant, the effects of the thicknesses of the buffer layer, IPyC layer, and OPyC layer on the safety of FCM fuel are investigated. The research findings indicate that: (1) Increasing the buffer layer thickness can effectively improve its ability to accommodate kernel swelling, thereby markedly weakening the mechanical interactions between different parts; (2) With an increase of the buffer layer thickness from 50 µm to 80 µm, the peak first principal stresses in the SiC layer and the matrix decrease by 51 % and 79 %, respectively, leading to a significantly reduced failure risk; (3) A strategic redistribution of layer thicknesses can significantly strengthen the TRISO fuel safety, particularly by increasing the buffer layer thickness while decreasing both inner and outer dense PyC layer thicknesses, without altering other microstructural parameters. This study can provide theoretical guidance and analytical tools for the advanced manufacturing and optimization design of FCM fuel.
{"title":"Effects of coating layer thicknesses on the thermo-mechanical coupling behaviors of FCM fuels","authors":"Jing Zhang, Shurong Ding","doi":"10.1016/j.anucene.2025.112104","DOIUrl":"10.1016/j.anucene.2025.112104","url":null,"abstract":"<div><div>FCM fuel, composed of TRISO particles and SiC matrix, is a typical accident tolerant fuel that holds a promising application prospect in various advanced nuclear reactors. Optimization of the microstructure of TRISO (Tri-Structural Isotropic) particles is crucial for enhancing both the safety and economy of nuclear fuel systems. In this study, the recently published novel fission gas swelling model or volume-growth strain models for the fuel kernel and the buffer layer are involved, enabling more accurate simulation of the irradiation thermo-mechanical coupling behaviors of FCM fuel. The three-dimensional mechanical constitutive relations, stress update algorithms and consistent stiffness moduli for the points within the buffer layer and PyC layer are newly formulated, and the corresponding procedures are developed. With the fuel kernel volume fraction and SiC layer dimensions kept constant, the effects of the thicknesses of the buffer layer, IPyC layer, and OPyC layer on the safety of FCM fuel are investigated. The research findings indicate that: (1) Increasing the buffer layer thickness can effectively improve its ability to accommodate kernel swelling, thereby markedly weakening the mechanical interactions between different parts; (2) With an increase of the buffer layer thickness from 50 µm to 80 µm, the peak first principal stresses in the SiC layer and the matrix decrease by 51 % and 79 %, respectively, leading to a significantly reduced failure risk; (3) A strategic redistribution of layer thicknesses can significantly strengthen the TRISO fuel safety, particularly by increasing the buffer layer thickness while decreasing both inner and outer dense PyC layer thicknesses, without altering other microstructural parameters. This study can provide theoretical guidance and analytical tools for the advanced manufacturing and optimization design of FCM fuel.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112104"},"PeriodicalIF":2.3,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881360","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}
Pub Date : 2026-01-03DOI: 10.1016/j.anucene.2025.112101
Jiaxing Ren , Quanbo Li , Gongyao Liu , Weiqiang Xu , Ruifeng Tian , Puzhen Gao , Shouxu Qiao , Sichao Tan
Due to the complex effects of advection, pressure drop, and bubble interactions, the two-phase flow parameters change dynamically with flow development. This paper conducted an experimental study on air–water two-phase flow in a 5 × 5 rod bundle using a four-sensor conductivity probe and differential pressure transducers. An interfacial area parameter database containing over 5000 measurement points is established from the entire cross-sectional measurement at five axial positions. The enhanced bubble coalescence efficiency due to the geometry of subchannels results in an increasing trend of bubble velocity and a decreasing trend of interfacial area concentration. Cap-bubbly flows are found to have larger relative velocities than bubbly flows through the one-dimensional drift-flux analysis. The two-phase frictional pressure drop is calculated by the measured void fraction with the probe and used to evaluate the existing prediction models. The coupling relationship between the void fraction and pressure drop is also analyzed through operating flow parameters.
{"title":"Research on the characteristics of interfacial area transport and flow resistance for upward two-phase flow in a 5 × 5 rod bundle","authors":"Jiaxing Ren , Quanbo Li , Gongyao Liu , Weiqiang Xu , Ruifeng Tian , Puzhen Gao , Shouxu Qiao , Sichao Tan","doi":"10.1016/j.anucene.2025.112101","DOIUrl":"10.1016/j.anucene.2025.112101","url":null,"abstract":"<div><div>Due to the complex effects of advection, pressure drop, and bubble interactions, the two-phase flow parameters change dynamically with flow development. This paper conducted an experimental study on air–water two-phase flow in a 5 × 5 rod bundle using a four-sensor conductivity probe and differential pressure transducers. An interfacial area parameter database containing over 5000 measurement points is established from the entire cross-sectional measurement at five axial positions. The enhanced bubble coalescence efficiency due to the geometry of subchannels results in an increasing trend of bubble velocity and a decreasing trend of interfacial area concentration. Cap-bubbly flows are found to have larger relative velocities than bubbly flows through the one-dimensional drift-flux analysis. The two-phase frictional pressure drop is calculated by the measured void fraction with the probe and used to evaluate the existing prediction models. The coupling relationship between the void fraction and pressure drop is also analyzed through operating flow parameters.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112101"},"PeriodicalIF":2.3,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881355","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}
Pub Date : 2026-01-02DOI: 10.1016/j.anucene.2025.112100
Ying Guan , Yang Li , Hualei Jiang , Daqing Wang , Daochuan Ge , Huaping Mei , Gui Fang , Lifu Gao , Haixia Wang
Bubble migration during a steam generator tube rupture (SGTR) accident in lead-cooled fast reactor (LFR) has garnered significant attention. This phenomenon can cause localized heat transfer deterioration and power fluctuations, posing substantial safety risks to the reactor. This paper presents a novel detection approach integrated with dynamic tracking for multiple micro bubbles, specifically designed for transparent liquid similarity experiments in SGTR research. The proposed method, named DAM-YOLO, incorporates dual attention mechanisms, a lightweight upsampling operator, and content-aware reassembly of features to enhance feature extraction capability and feature fusion performance for micro bubbles. Furthermore, by adopting the DeepSORT algorithm combined with the complete intersection over union (CIoU) matching metric, the issue of multiple target loss during tracking process is effectively addressed. In this study, bubble datasets were acquired from a self-developed similarity experimental facility. The results demonstrate that the precision (P), mean average precision (mAP), multiple object tracking accuracy (MOTA), multiple object tracking precision (MOTP), and id f1 score (IDF1) of the proposed model reach 96.4%, 95.6%, 85.27%, 86.99%, and 92.63%, respectively. This research can provide efficient intelligent technical support for analyzing the migration process of multiple micro bubbles in fluid dynamics studies.
{"title":"Computer vision-based detection and dynamic tracking of multiple micro bubbles in transparent liquid similarity experiments for SGTR in lead-cooled fast reactor","authors":"Ying Guan , Yang Li , Hualei Jiang , Daqing Wang , Daochuan Ge , Huaping Mei , Gui Fang , Lifu Gao , Haixia Wang","doi":"10.1016/j.anucene.2025.112100","DOIUrl":"10.1016/j.anucene.2025.112100","url":null,"abstract":"<div><div>Bubble migration during a steam generator tube rupture (SGTR) accident in lead-cooled fast reactor (LFR) has garnered significant attention. This phenomenon can cause localized heat transfer deterioration and power fluctuations, posing substantial safety risks to the reactor. This paper presents<!--> <!-->a novel detection approach integrated with dynamic tracking for multiple micro bubbles, specifically designed for transparent liquid similarity experiments in SGTR research. The proposed method, named <span>DAM</span>-YOLO, incorporates dual attention mechanisms, a lightweight upsampling operator, and content-aware reassembly of features to enhance feature extraction capability and feature fusion performance for micro bubbles. <span>Furthermore</span>, by adopting the DeepSORT algorithm combined with the complete intersection over union (CIoU) matching metric, the issue of multiple target loss during tracking process is effectively addressed. In this study, bubble datasets were acquired<!--> <!-->from a self-developed similarity experimental facility. The results demonstrate that the precision (P), mean average precision (mAP), multiple object tracking accuracy (MOTA), multiple object tracking precision (MOTP), and id f1 score (IDF1) of the proposed model reach 96.4%, 95.6%, 85.27%, 86.99%, and 92.63%, respectively. This research can provide efficient intelligent technical support for analyzing the migration process of multiple micro bubbles in fluid dynamics studies.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112100"},"PeriodicalIF":2.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881354","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}
Pub Date : 2026-01-02DOI: 10.1016/j.anucene.2025.112106
Tomáš Peltan , Tomáš Czakoj , Vlastimil Juříček , Jan Šimon , Michal Košťál
This study of a slightly moderated neutron reference field shaped by graphite has been established at the LR-0 reactor. This experimental configuration modifies the reference neutron spectrum toward lower energies while preserving spatial homogeneity using graphite. This core configuration was characterized through an extensive neutron flux mapping by four independent irradiation campaigns utilizing activation foil detectors. High-purity and well-known dosimetry reactions using activation foils of Au, Cu, Mn, Ta, and Ni were strategically positioned throughout the graphite insertion for neutron shape mapping. The resulting reaction rates were derived from gamma spectrometry using a well-defined HPGe detector. The measured data provide detailed spatial and spectral information on the neutron flux distribution and confirm the reproducibility and stability of the investigated volume in the graphite field, which can be validated as a new neutron reference field. This field can be used to research in advanced reactor systems and IV. gen reactors.
{"title":"A development of a new slightly moderated reference field in graphite insertion in the LR-0 reactor","authors":"Tomáš Peltan , Tomáš Czakoj , Vlastimil Juříček , Jan Šimon , Michal Košťál","doi":"10.1016/j.anucene.2025.112106","DOIUrl":"10.1016/j.anucene.2025.112106","url":null,"abstract":"<div><div>This study of a slightly moderated neutron reference field shaped by graphite has been established at the LR-0 reactor. This experimental configuration modifies the reference neutron spectrum toward lower energies while preserving spatial homogeneity using graphite. This core configuration was characterized through an extensive neutron flux mapping by four independent irradiation campaigns utilizing activation foil detectors. High-purity and well-known dosimetry reactions using activation foils of Au, Cu, Mn, Ta, and Ni were strategically positioned throughout the graphite insertion for neutron shape mapping. The resulting reaction rates were derived from gamma spectrometry using a well-defined HPGe detector. The measured data provide detailed spatial and spectral information on the neutron flux distribution and confirm the reproducibility and stability of the investigated volume in the graphite field, which can be validated as a new neutron reference field. This field can be used to research in advanced reactor systems and IV. gen reactors.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112106"},"PeriodicalIF":2.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881356","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}
Pub Date : 2025-12-31DOI: 10.1016/j.anucene.2025.112109
Ji Liu , Yongkuo Liu , Zhouxin Shi , Jiarong Gao , Yukun Liu , Zhen Wang , Guohua Wu
Due to the unique nature of nuclear power plants, highly reliable fault diagnosis methods are required to ensure operational safety and stability. To fully capture the spatiotemporal dependencies in multivariate time series (MTS) data and improve the accuracy of fault diagnosis in nuclear power plant systems, this paper proposes a hybrid diagnostic framework integrating Crossformer and Support Vector Machine (SVM), referred to as the Crossformer-SVM model. First, using the PCTRAN simulation platform and the Fuqing simulation machine as data sources, fault datasets with noise and without noise are constructed. Then, the Crossformer model is employed to hierarchically extract the spatiotemporal features of the system fault data, which are used as inputs for the SVM classifier. Finally, the SVM classifier is used to identify the fault modes of the system. In addition, a comparative experiment is conducted between the proposed Crossformer-SVM model and other deep learning models, such as CNN-LSTM. The experimental results show that, compared to other deep learning fault diagnosis models, the proposed method achieves the highest accuracy, with a minimum accuracy of 99.20% for the two types of noise-free datasets. It also maintains excellent diagnostic performance under noise, with diagnostic accuracies of 98.92% and 98.88% for the Fuqing simulator and PCTRAN data, respectively. This provides a reliable fault diagnosis method for nuclear power plant systems.
{"title":"Research on fault diagnosis method for nuclear power plants based on crossformer-SVM","authors":"Ji Liu , Yongkuo Liu , Zhouxin Shi , Jiarong Gao , Yukun Liu , Zhen Wang , Guohua Wu","doi":"10.1016/j.anucene.2025.112109","DOIUrl":"10.1016/j.anucene.2025.112109","url":null,"abstract":"<div><div>Due to the unique nature of nuclear power plants, highly reliable fault diagnosis methods are required to ensure operational safety and stability. To fully capture the spatiotemporal dependencies in multivariate time series (MTS) data and improve the accuracy of fault diagnosis in nuclear power plant systems, this paper proposes a hybrid diagnostic framework integrating Crossformer and Support Vector Machine (SVM), referred to as the Crossformer-SVM model. First, using the PCTRAN simulation platform and the Fuqing simulation machine as data sources, fault datasets with noise and without noise are constructed. Then, the Crossformer model is employed to hierarchically extract the spatiotemporal features of the system fault data, which are used as inputs for the SVM classifier. Finally, the SVM classifier is used to identify the fault modes of the system. In addition, a comparative experiment is conducted between the proposed Crossformer-SVM model and other deep learning models, such as CNN-LSTM. The experimental results show that, compared to other deep learning fault diagnosis models, the proposed method achieves the highest accuracy, with a minimum accuracy of 99.20% for the two types of noise-free datasets. It also maintains excellent diagnostic performance under noise, with diagnostic accuracies of 98.92% and 98.88% for the Fuqing simulator and PCTRAN data, respectively. This provides a reliable fault diagnosis method for nuclear power plant systems.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112109"},"PeriodicalIF":2.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881415","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}
Pub Date : 2025-12-31DOI: 10.1016/j.anucene.2025.112088
Siyuan Wu, Jinpeng He, Weiguo Gu, Deyi Chen, Baojie Nie, Dezhong Wang
The dispersion uplift of the aerosol plume due to the complex mountain subsurface and the residence of the plume in the clockwise turnaround flow behind the hill are still a major obstacle in accurately predicting the dispersion concentration distributions of aerosols in the atmospheric emissions from nuclear power plants, despite the use of complex numerical models. In particular, the effect of hill combination on dispersion trajectories and concentration distributions has not received widely attention in previous experimental studies. The focus of this study is on the effect of the distance between two identical parallel aligned hills on the dispersion trajectory and concentration distribution of the aerosol plume under neutral atmospheric conditions. A combination of planar particle laser concentration measurement method and CFD simulation was used to characterize the flow reattachment and plume trajectories as well as the dispersion distribution. The results show that when the interval between the two hills is less than , the total reattachment length remains at as in the case of a single hill, and the dispersion trajectory is basically consistent with that of a single hill. The concentration accumulates on the windward side of the second hill between valleys. When the distance between the two hills is greater than , the reattachment length of the first hill recovers to as in the case of a single hill, and the second hill begins to move away from the influence area of the first hill.
{"title":"Effects of two-dimensional hills combination with distance variation on the aerosols dispersion based on wind tunnel experiment","authors":"Siyuan Wu, Jinpeng He, Weiguo Gu, Deyi Chen, Baojie Nie, Dezhong Wang","doi":"10.1016/j.anucene.2025.112088","DOIUrl":"10.1016/j.anucene.2025.112088","url":null,"abstract":"<div><div>The dispersion uplift of the aerosol plume due to the complex mountain subsurface and the residence of the plume in the clockwise turnaround flow behind the hill are still a major obstacle in accurately predicting the dispersion concentration distributions of aerosols in the atmospheric emissions from nuclear power plants, despite the use of complex numerical models. In particular, the effect of hill combination on dispersion trajectories and concentration distributions has not received widely attention in previous experimental studies. The focus of this study is on the effect of the distance between two identical parallel aligned hills on the dispersion trajectory and concentration distribution of the aerosol plume under neutral atmospheric conditions. A combination of planar particle laser concentration measurement method and CFD simulation was used to characterize the flow reattachment and plume trajectories as well as the dispersion distribution. The results show that when the interval between the two hills is less than <span><math><mrow><mn>4</mn><mi>H</mi></mrow></math></span>, the total reattachment length remains at <span><math><mrow><mn>9</mn><mi>H</mi></mrow></math></span> as in the case of a single hill, and the dispersion trajectory is basically consistent with that of a single hill. The concentration accumulates on the windward side of the second hill between valleys. When the distance between the two hills is greater than <span><math><mrow><mn>12</mn><mi>H</mi></mrow></math></span>, the reattachment length of the first hill recovers to <span><math><mrow><mn>9</mn><mi>H</mi></mrow></math></span> as in the case of a single hill, and the second hill begins to move away from the influence area of the first hill.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112088"},"PeriodicalIF":2.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881358","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}
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