Advanced technology fuels (ATF) with improved oxidation resistance are under development to enhance the safety of light water reactors. Cr-coated Zr alloy cladding, a promising near-term ATF, exhibits excellent oxidation resistance below the Cr-Zr eutectic temperature. However, its gradual loss of protective effect over time, even without mechanical damage, indicates the need to understand its degradation mechanisms. This article presents a phenomenological model describing degradation due to high-temperature oxidation, focusing on Zr ingress into the Cr coating and the formation of oxygen pathways that accelerate oxygen uptake into the Zr matrix. The model was validated against experimental data at 1200°C and 1300°C, reproducing key trends such as oxide growth, weight gain, and oxygen concentration profiles. Applying the same parameters to a different PVD-coated cladding test gave reasonable agreement at 1200°C, while discrepancies at 1300°C suggest Cr-Zr eutectic reactions from local temperature variations, highlighting the model’s sensitivity near the eutectic point.
{"title":"Development of phenomenological degradation models for Cr-Coated Zr alloy cladding under high-temperature oxidation conditions","authors":"Yoshinori Taniguchi, Vu-Nhut Luu, Yudai Tasaki, Yutaka Udagawa, Jinya Katsuyama","doi":"10.1016/j.anucene.2026.112177","DOIUrl":"10.1016/j.anucene.2026.112177","url":null,"abstract":"<div><div>Advanced technology fuels (ATF) with improved oxidation resistance are under development to enhance the safety of light water reactors. Cr-coated Zr alloy cladding, a promising near-term ATF, exhibits excellent oxidation resistance below the Cr-Zr eutectic temperature. However, its gradual loss of protective effect over time, even without mechanical damage, indicates the need to understand its degradation mechanisms. This article presents a phenomenological model describing degradation due to high-temperature oxidation, focusing on Zr ingress into the Cr coating and the formation of oxygen pathways that accelerate oxygen uptake into the Zr matrix. The model was validated against experimental data at 1200°C and 1300°C, reproducing key trends such as oxide growth, weight gain, and oxygen concentration profiles. Applying the same parameters to a different PVD-coated cladding test gave reasonable agreement at 1200°C, while discrepancies at 1300°C suggest Cr-Zr eutectic reactions from local temperature variations, highlighting the model’s sensitivity near the eutectic point.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"231 ","pages":"Article 112177"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186620","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 : 2026-06-01Epub Date: 2026-02-12DOI: 10.1016/j.anucene.2026.112197
Hailiang Shi, Mingtao He, Xinxin Wang, Jie Huang, Tingting Zou, Fanchao Chai, Changyou Zhao, Zhijun Li
To enhance the stability of axial power distribution during power transients in pressurized water reactors, a time-series neural network driven axial power control framework was proposed and applied in HPR1000 and CPR1000 reactors. As the first step, a long short-term memory surrogate model is trained to predict axial offset within < 1% mean relative error and submillisecond inference time. Then, an improved elitist genetic algorithm is adopted to optimize the control rod sequences. A full factorial sensitivity study of the genetic algorithm based on analysis of variance is also carried out. In the HPR1000 case, the minimal operation margin is optimized from 0.05% to 1.77%. Moreover, the required recovery time is also reduced from 40 h to 27 h. In the CPR1000 case, the optimized strategy confines axial power deviation within ± 0.5% of the reference value. The results demonstrate the extensibility of the approach to other pressurized water reactors for axial power control.
{"title":"Axial power control strategy for pressurized water reactors based on time-series neural network and improved genetic algorithm","authors":"Hailiang Shi, Mingtao He, Xinxin Wang, Jie Huang, Tingting Zou, Fanchao Chai, Changyou Zhao, Zhijun Li","doi":"10.1016/j.anucene.2026.112197","DOIUrl":"10.1016/j.anucene.2026.112197","url":null,"abstract":"<div><div>To enhance the stability of axial power distribution during power transients in pressurized water reactors, a time-series neural network driven axial power control framework was proposed and applied in HPR1000 and CPR1000 reactors. As the first step, a long short-term memory surrogate model is trained to predict axial offset within < 1% mean relative error and submillisecond inference time. Then, an improved elitist genetic algorithm is adopted to optimize the control rod sequences. A full factorial sensitivity study of the genetic algorithm based on analysis of variance is also carried out. In the HPR1000 case, the minimal operation margin is optimized from 0.05% to 1.77%. Moreover, the required recovery time is also reduced from 40 h to 27 h. In the CPR1000 case, the optimized strategy confines axial power deviation within ± 0.5% of the reference value. The results demonstrate the extensibility of the approach to other pressurized water reactors for axial power control.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"231 ","pages":"Article 112197"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186630","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 : 2026-06-01Epub Date: 2026-02-11DOI: 10.1016/j.anucene.2026.112192
Shaojie Tan , Songbai Cheng , Yanan Zhao
To investigate fuel–coolant interactions in light water reactor severe accident, we developed VTMCI experimental facility. We performed multiple series of visual fragmentation experiments by releasing various fused low-melting-point metals into a water tank. This paper integrates experimental data from our previous VTMCI experiments to systematically analyze the influences of multiple key parameters on agglomerated debris formation and characteristics. The results show that the melt superheat and water subcooling significantly affect the mass fraction of agglomerated debris. When the melt inlet velocity or water depth increases, the mass fraction of agglomerated debris decreases. As the superheat of molten material increases or the subcooling of coolant decreases, the porosities of agglomerated and fragmented debris bed decrease. When the melt inlet velocity or water depth changes significantly, the porosity changes of agglomerated and fragmented debris bed are negligible. Nozzle diameter has negligible influence on debris bed formation.
{"title":"Investigation on agglomerated debris formation during fuel–coolant interactions with multiple series of experiments","authors":"Shaojie Tan , Songbai Cheng , Yanan Zhao","doi":"10.1016/j.anucene.2026.112192","DOIUrl":"10.1016/j.anucene.2026.112192","url":null,"abstract":"<div><div>To investigate fuel–coolant interactions in light water reactor severe accident, we developed VTMCI experimental facility. We performed multiple series of visual fragmentation experiments by releasing various fused low-melting-point metals into a water tank. This paper integrates experimental data from our previous VTMCI experiments to systematically analyze the influences of multiple key parameters on agglomerated debris formation and characteristics. The results show that the melt superheat and water subcooling significantly affect the mass fraction of agglomerated debris. When the melt inlet velocity or water depth increases, the mass fraction of agglomerated debris decreases. As the superheat of molten material increases or the subcooling of coolant decreases, the porosities of agglomerated and fragmented debris bed decrease. When the melt inlet velocity or water depth changes significantly, the porosity changes of agglomerated and fragmented debris bed are negligible. Nozzle diameter has negligible influence on debris bed formation.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"231 ","pages":"Article 112192"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186632","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 : 2026-05-01Epub Date: 2025-12-22DOI: 10.1016/j.anucene.2025.112078
Huanjun Kong, Ya Li, Jianqiang Shan, Miao Gui
This study presents an experimental investigation on the characteristics of critical heat flux (CHF) in inclined circular tube. The test section comprised a circular tube with an inner diameter of 8 mm and a maximum effective heating length of 1600 mm. Using R134a as the working fluid, experiments were performed over a pressure range of 1.6–2.7 MPa, mass fluxes of 1000–3000 kg/m2/s, and inclination angles of 0°–25°. The results demonstrate that inclination generally degrades CHF at low outlet quality, with the deterioration effect enhanced by reduced mass flux and increased inclination angle. CHF has deteriorated by approximately 46 % at most. In contrast, CHF remains largely insensitive to inclination under high quality conditions. The refined subchannel analysis provides more localized void fraction data, yielding a more accurate understanding of the influencing mechanisms. It indicates that when CHF occurs at a uniform heat flux, the void fraction in the upper region of the channel remains consistent across different inclination angles. The influence of inclination on CHF is intrinsically linked to flow patterns: under bubbly flow conditions, the void fraction at the top of the inclined tube is lower than that in vertical configurations; however, when the flow pattern transitions to slug flow, the void fraction in the inclined tube aligns with that observed in vertical tubes.
{"title":"Experimental and mechanistic study on critical heat flux of R134a in tube under inclined conditions","authors":"Huanjun Kong, Ya Li, Jianqiang Shan, Miao Gui","doi":"10.1016/j.anucene.2025.112078","DOIUrl":"10.1016/j.anucene.2025.112078","url":null,"abstract":"<div><div>This study presents an experimental investigation on the characteristics of critical heat flux (CHF) in inclined circular tube. The test section comprised a circular tube with an inner diameter of 8 mm and a maximum effective heating length of 1600 mm. Using R134a as the working fluid, experiments were performed over a pressure range of 1.6–2.7 MPa, mass fluxes of 1000–3000 kg/m<sup>2</sup><sup>/</sup>s, and inclination angles of 0°–25°. The results demonstrate that inclination generally degrades CHF at low outlet quality, with the deterioration effect enhanced by reduced mass flux and increased inclination angle. CHF has deteriorated by approximately 46 % at most. In contrast, CHF remains largely insensitive to inclination under high quality conditions. The refined subchannel analysis provides more localized void fraction data, yielding a more accurate understanding of the influencing mechanisms. It indicates that when CHF occurs at a uniform heat flux, the void fraction in the upper region of the channel remains consistent across different inclination angles. The influence of inclination on CHF is intrinsically linked to flow patterns: under bubbly flow conditions, the void fraction at the top of the inclined tube is lower than that in vertical configurations; however, when the flow pattern transitions to slug flow, the void fraction in the inclined tube aligns with that observed in vertical tubes.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112078"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838561","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 : 2026-05-01Epub Date: 2025-12-20DOI: 10.1016/j.anucene.2025.112077
Dong Wang , Shihao Wu , Kai Lu , Yapei Zhang , Xi Liu , Jiaxin Zhang , Kui Ge
Cr-coated Zr alloy cladding stands as the near-term research and development focus for accident tolerant fuel. Accurately evaluating the survival time of Cr coatings under high-temperature conditions holds significant importance for reactor safety analysis. This evaluation must consider Cr-Zr interactions (including ZrCr2 growth and Cr dissolution within the Zr substrate), as their contribution to coating consumption is comparable to that of oxidation. We have modified the previously developed Fick’s-law-based SICO code to adapt to the simulation of Cr coating diffusion loss. Here, the Cr diffusion coefficients of Zr and ZrCr2 are key parameters influencing the simulation accuracy. In this study, a multi-objective optimization method was employed to obtain the Cr diffusion coefficients for achieving best match between simulation results and experimental data. Sensitivity tests on Cr diffusion coefficients were carried out using the adapted SICO code. The Residual Sum of Squares (RSS) between simulation results and experimental data was calculated, and response surfaces of RSS with respect to Cr diffusion coefficients were constructed. The NSGA-Ⅱ algorithm and TOPSIS method were applied to obtain the optimal combination of diffusion coefficients for each case. Ultimately, the optimal temperature-dependent correlations for the Cr diffusion coefficients were obtained by fitting the optimal diffusion coefficients with Arrhenius equation. Compared with applying literature-reported correlations, applying our optimized correlations significantly improves the prediction accuracy of Cr and ZrCr2 thicknesses. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Error (MRE) between simulation results and experimental data are reduced by over 20 %, with a maximum reduction exceeding 50 %.
{"title":"Inverse determination of Cr diffusion coefficients in Zr alloys via Fick’s law and multi-objective optimization","authors":"Dong Wang , Shihao Wu , Kai Lu , Yapei Zhang , Xi Liu , Jiaxin Zhang , Kui Ge","doi":"10.1016/j.anucene.2025.112077","DOIUrl":"10.1016/j.anucene.2025.112077","url":null,"abstract":"<div><div>Cr-coated Zr alloy cladding stands as the near-term research and development focus for accident tolerant fuel. Accurately evaluating the survival time of Cr coatings under high-temperature conditions holds significant importance for reactor safety analysis. This evaluation must consider Cr-Zr interactions (including ZrCr<sub>2</sub> growth and Cr dissolution within the Zr substrate), as their contribution to coating consumption is comparable to that of oxidation. We have modified the previously developed Fick’s-law-based SICO code to adapt to the simulation of Cr coating diffusion loss. Here, the Cr diffusion coefficients of Zr and ZrCr<sub>2</sub> are key parameters influencing the simulation accuracy. In this study, a multi-objective optimization method was employed to obtain the Cr diffusion coefficients for achieving best match between simulation results and experimental data. Sensitivity tests on Cr diffusion coefficients were carried out using the adapted SICO code. The Residual Sum of Squares (RSS) between simulation results and experimental data was calculated, and response surfaces of RSS with respect to Cr diffusion coefficients were constructed. The NSGA-Ⅱ algorithm and TOPSIS method were applied to obtain the optimal combination of diffusion coefficients for each case. Ultimately, the optimal temperature-dependent correlations for the Cr diffusion coefficients were obtained by fitting the optimal diffusion coefficients with Arrhenius equation. Compared with applying literature-reported correlations, applying our optimized correlations significantly improves the prediction accuracy of Cr and ZrCr<sub>2</sub> thicknesses. The Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Error (MRE) between simulation results and experimental data are reduced by over 20 %, with a maximum reduction exceeding 50 %.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112077"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838562","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 : 2026-05-01Epub Date: 2025-12-23DOI: 10.1016/j.anucene.2025.112090
Xuewei Miao, Zhonghao Li, Qingyue You, Dingping Peng, Bo Cao
This study proposes a source term inversion method for nuclear accidents based on the Harris Hawks Optimization (HHO) algorithm and a Gaussian plume model, enabling accurate estimation of radionuclide release rates and the two-dimensional location of release points using off-site monitoring data under accident scenarios. To evaluate model performance, validation was conducted through simulated experiments under two accident scenarios with known and unknown release locations and tracer experiments involving seven different release scenarios. The simulation results demonstrate that, compared with two other swarm intelligence algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), the HHO-based inversion model achieves higher estimation accuracy, faster convergence speed, and greater stability during iterative inversion. The convergence rate and accuracy of the model are somewhat dependent on the initialization range of the population and the boundary constraints of the target parameters. The tracer experiment validation shows that the HHO model performs well in most cases, with an average relative error of 0.0341 in release rate inversion and an average positional deviation of 133 m across the seven experiments. Sensitivity analysis indicates that the HHO inversion model exhibits certain robustness in estimating release rates, while the two-dimensional location of the release point is more susceptible to interference from noise in off-site monitoring data.
{"title":"Source term inversion method for nuclear accidents based on Harris Hawks Optimization","authors":"Xuewei Miao, Zhonghao Li, Qingyue You, Dingping Peng, Bo Cao","doi":"10.1016/j.anucene.2025.112090","DOIUrl":"10.1016/j.anucene.2025.112090","url":null,"abstract":"<div><div>This study proposes a source term inversion method for nuclear accidents based on the Harris Hawks Optimization (HHO) algorithm and a Gaussian plume model, enabling accurate estimation of radionuclide release rates and the two-dimensional location of release points using off-site monitoring data under accident scenarios. To evaluate model performance, validation was conducted through simulated experiments under two accident scenarios with known and unknown release locations and tracer experiments involving seven different release scenarios. The simulation results demonstrate that, compared with two other swarm intelligence algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), the HHO-based inversion model achieves higher estimation accuracy, faster convergence speed, and greater stability during iterative inversion. The convergence rate and accuracy of the model are somewhat dependent on the initialization range of the population and the boundary constraints of the target parameters. The tracer experiment validation shows that the HHO model performs well in most cases, with an average relative error of 0.0341 in release rate inversion and an average positional deviation of 133 m across the seven experiments. Sensitivity analysis indicates that the HHO inversion model exhibits certain robustness in estimating release rates, while the two-dimensional location of the release point is more susceptible to interference from noise in off-site monitoring data.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112090"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838528","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}
The release of fission gas in nuclear fuel significantly impacts fuel performance. Currently, many engineering models for fission gas release (FGR) rely on empirical corrections of simplified processes, introducing considerable uncertainty. Therefore, implementing mechanism-based FGR models grounded in physical behavior is crucial for improving the reliability of fuel performance codes. In this study, an established mechanism-based FGR model (incorporating atomic diffusion, intra-granular bubble re-solution, grain-boundary sweeping, and inter-granular bubble dynamics) was integrated into the fuel performance analysis code FROBA, along with a non-thermal release model. The implementation couples grain-boundary gas release with swelling equations. Model validation against literature benchmarks under steady-state conditions demonstrates excellent agreement with experimental data and other codes for both FGR fraction and swelling rate. Uncertainty analysis confirms the model’s effectiveness within the implemented scope.
{"title":"Development and application of a mechanism-based fission gas release model in FROBA fuel performance code","authors":"Kou Minghai , Xiao Xinkun , Yu Songjiao , Chen Ronghua , Jiang Pinting , Dai Mingliang , Zhang Kui , Wu Yingwei , Tian Wenxi , Qiu Suizheng","doi":"10.1016/j.anucene.2025.112094","DOIUrl":"10.1016/j.anucene.2025.112094","url":null,"abstract":"<div><div>The release of fission gas in nuclear fuel significantly impacts fuel performance. Currently, many engineering models for fission gas release (FGR) rely on empirical corrections of simplified processes, introducing considerable uncertainty. Therefore, implementing mechanism-based FGR models grounded in physical behavior is crucial for improving the reliability of fuel performance codes. In this study, an established mechanism-based FGR model (incorporating atomic diffusion, intra-granular bubble re-solution, grain-boundary sweeping, and inter-granular bubble dynamics) was integrated into the fuel performance analysis code FROBA, along with a non-thermal release model. The implementation couples grain-boundary gas release with swelling equations. Model validation against literature benchmarks under steady-state conditions demonstrates excellent agreement with experimental data and other codes for both FGR fraction and swelling rate. Uncertainty analysis confirms the model’s effectiveness within the implemented scope.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112094"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838533","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 : 2026-05-01Epub Date: 2025-12-23DOI: 10.1016/j.anucene.2025.112066
Yunxiang Li , Runsheng Yang , Yuefeng Guo , Xingkang Su , Yuping Zhou , Jian Hong , Yuxing Liu , Zinan Huang , Xin Su , Youpeng Zhang , WenJun Hu , Long Gu
The thermal–hydraulic behavior of liquid lead–bismuth eutectic in wire-wrapped fuel assemblies plays a crucial role in the safety design of the CiADS sub-critical reactor. A four-equation model, which incorporates both dynamic and thermal time scales to transport the turbulent Prandtl number, may enhance the predictive accuracy of heat transfer in LBE. In this work, an in-house solver, LBE4EqnFoam, was developed on the open-source CFD platform OpenFOAM and applied to the simulation of the CiADS wire-wrapped fuel assembly. High-fidelity calculations of the bundle section suggest that the pressure field exhibits non-uniform “high-pressure” and “low-pressure” regions along the wire-winding direction. The predicted pressure drop shows good agreement with the Cheng and Todreas correlation, with a maximum relative deviation of less than 9 %. The coolant velocity distribution was found to be opposite to the pressure field, with lower velocities inside the “high-pressure” regions. Strong fluctuations of transverse secondary flows were observed among different subchannels, and their intensity increased near the spacers, reaching a maximum of 0.33. The average coolant temperature in the edge and corner channels tended to be lower than the bulk average, while the highest coolant temperature, up to 684 K, occurred within the internal subchannels. The Nusselt number distribution indicates that heat transfer becomes nearly fully developed between the 5th and 6th pitches. The wall hot-spot factor was larger in the internal channels, reflecting a less uniform wall temperature compared with the cross-sectional average. Furthermore, the strongest coolant temperature fluctuations were located between the edge and outer internal channels, whereas the maximum turbulent Prandtl number appeared in the internal subchannels.
{"title":"Numerical study on the turbulent heat transfer behaviors of the fuel assembly with spacer wires in lead-based fast reactors based on four-equation model","authors":"Yunxiang Li , Runsheng Yang , Yuefeng Guo , Xingkang Su , Yuping Zhou , Jian Hong , Yuxing Liu , Zinan Huang , Xin Su , Youpeng Zhang , WenJun Hu , Long Gu","doi":"10.1016/j.anucene.2025.112066","DOIUrl":"10.1016/j.anucene.2025.112066","url":null,"abstract":"<div><div>The thermal–hydraulic behavior of liquid lead–bismuth eutectic in wire-wrapped fuel assemblies plays a crucial role in the safety design of the CiADS sub-critical reactor. A four-equation model, which incorporates both dynamic and thermal time scales to transport the turbulent Prandtl number, may enhance the predictive accuracy of heat transfer in LBE. In this work, an in-house solver, LBE4EqnFoam, was developed on the open-source CFD platform OpenFOAM and applied to the simulation of the CiADS wire-wrapped fuel assembly. High-fidelity calculations of the bundle section suggest that the pressure field exhibits non-uniform “high-pressure” and “low-pressure” regions along the wire-winding direction. The predicted pressure drop shows good agreement with the Cheng and Todreas correlation, with a maximum relative deviation of less than 9 %. The coolant velocity distribution was found to be opposite to the pressure field, with lower velocities inside the “high-pressure” regions. Strong fluctuations of transverse secondary flows were observed among different subchannels, and their intensity increased near the spacers, reaching a maximum of 0.33. The average coolant temperature in the edge and corner channels tended to be lower than the bulk average, while the highest coolant temperature, up to 684 K, occurred within the internal subchannels. The Nusselt number distribution indicates that heat transfer becomes nearly fully developed between the 5th and 6th pitches. The wall hot-spot factor was larger in the internal channels, reflecting a less uniform wall temperature compared with the cross-sectional average. Furthermore, the strongest coolant temperature fluctuations were located between the edge and outer internal channels, whereas the maximum turbulent Prandtl number appeared in the internal subchannels.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"229 ","pages":"Article 112066"},"PeriodicalIF":2.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838565","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 : 2026-05-01Epub 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":"2026-05-01","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 : 2026-05-01Epub 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.
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