Pub Date : 2024-10-22DOI: 10.1016/j.anucene.2024.110987
Zhang Dandi , Wang Shanpu , Tong Lili , Cao Xuewu
Aerosol retention inside narrow channels is the optimization direction of the leakage source term assessment for nuclear power plant containment. Based on the flow characteristics of carrier gas and the deposition characteristics of transported aerosol, a one-dimensional analysis method of aerosol retention in narrow channels is developed through considering different deposition mechanisms of inlet loss, gravity settlement, Brownian diffusion, turbulent deposition and steam condensation. The flow models of carrier gas and the retention models of aerosol are analyzed and verified, respectively. The flow of carrier gas deviates from laminar flow earlier through using the drag model of narrow channels. The prediction accuracy of aerosol penetration factor calculated by current analysis method in narrow channels is improved under laminar flow and turbulent flow through comparing with the previous calculation methods. Aerosol retention analysis is conducted on the narrow channels of steel containment under the typical severe accident. The turbulent deposition introduced by larger leakage channels increases the aerosols retention effect in narrow channels.
{"title":"Retention analysis of aerosol inside narrow channels of the containment","authors":"Zhang Dandi , Wang Shanpu , Tong Lili , Cao Xuewu","doi":"10.1016/j.anucene.2024.110987","DOIUrl":"10.1016/j.anucene.2024.110987","url":null,"abstract":"<div><div>Aerosol retention inside narrow channels is the optimization direction of the leakage source term assessment for nuclear power plant containment. Based on the flow characteristics of carrier gas and the deposition characteristics of transported aerosol, a one-dimensional analysis method of aerosol retention in narrow channels is developed through considering different deposition mechanisms of inlet loss, gravity settlement, Brownian diffusion, turbulent deposition and steam condensation. The flow models of carrier gas and the retention models of aerosol are analyzed and verified, respectively. The flow of carrier gas deviates from laminar flow earlier through using the drag model of narrow channels. The prediction accuracy of aerosol penetration factor calculated by current analysis method in narrow channels is improved under laminar flow and turbulent flow through comparing with the previous calculation methods. Aerosol retention analysis is conducted on the narrow channels of steel containment under the typical severe accident. The turbulent deposition introduced by larger leakage channels increases the aerosols retention effect in narrow channels.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110987"},"PeriodicalIF":1.9,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526850","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 : 2024-10-22DOI: 10.1016/j.anucene.2024.110986
Jingkang Li , Zunyan Hu , Zeguang Li , Liangfei Xu , Jianqiu Li
Heat pipe cooled reactors (HPRs) offer the potential to achieve load-following control without the need for control rods or drums, thereby simplifying the control system. However, during load-following operation, HPRs experience fluctuations in temperature, which can impact safety. Limited research has focused on mitigating temperature fluctuations of HPRs during dynamic power regulation leveraging their inherent load-following capabilities. This study examines the characteristics of an HPR with closed Brayton Cycle (CBC), and develops a load-following control algorithm. A simplified CBC model is proposed to facilitate control strategy analysis. Model predictive control (MPC) is employed to suppress temperature fluctuations, revealing that the dynamic response of output power under MPC resembles that of a first-order inertial system. Consequently, a power control algorithm based on first-order inertial feedforward control is introduced. Simulation results demonstrate that the proposed algorithm, with a time constant ranging between 500 and 1000 s, significantly mitigates temperature and power fluctuations in HPRs during load-following dynamic power regulation.
{"title":"Temperature fluctuation mitigation of heat pipe cooled reactor with closed Brayton cycle during load-following dynamic power regulation","authors":"Jingkang Li , Zunyan Hu , Zeguang Li , Liangfei Xu , Jianqiu Li","doi":"10.1016/j.anucene.2024.110986","DOIUrl":"10.1016/j.anucene.2024.110986","url":null,"abstract":"<div><div>Heat pipe cooled reactors (HPRs) offer the potential to achieve load-following control without the need for control rods or drums, thereby simplifying the control system. However, during load-following operation, HPRs experience fluctuations in temperature, which can impact safety. Limited research has focused on mitigating temperature fluctuations of HPRs during dynamic power regulation leveraging their inherent load-following capabilities. This study examines the characteristics of an HPR with closed Brayton Cycle (CBC), and develops a load-following control algorithm. A simplified CBC model is proposed to facilitate control strategy analysis. Model predictive control (MPC) is employed to suppress temperature fluctuations, revealing that the dynamic response of output power under MPC resembles that of a first-order inertial system. Consequently, a power control algorithm based on first-order inertial feedforward control is introduced. Simulation results demonstrate that the proposed algorithm, with a time constant ranging between 500 and 1000 s, significantly mitigates temperature and power fluctuations in HPRs during load-following dynamic power regulation.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110986"},"PeriodicalIF":1.9,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526945","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}
This study presents the results of testing nuclear data libraries by analyzing statistical criteria obtained from comparing experimental and calculated rates for (n,2n), (n,p), (n,pn), (n,nꞌγ) (n,α) and (n,γ) reactions measured on samples natNi, natZr, natNb, natCd, natTi, natCo,63(96%), 65(99.70%)Cu, 64(99.70%)Zn, natIn, natAl, natMg, natFe, natAu and natTh, which were placed in the experimental channels of micromodels of the fusion blanket.
The “fast” (the cylinder Ø 230 mm and 520 mm length was filled with ∼ 67 kg of molten salt 0.52NaF + 0.48ZrF4) and the “thermal” blanket (the same cylinder was placed in a dry channel inside a cubic container filled with water with dimensions of 52.0 × 52.0 × 52.0 cm were investigated. The reaction rates were measured using the activation method.
Modeling with transport codes MCNP5, KIR, PHITS-3.31, SuperMC3.4.0 was performed using the ENDF/B-VII.0 library for neutron transport as well as seven neutron data libraries for reaction rates simulation, including: JEFF-3.3, JENDL-4.0, ENDF/B–VIII.0, ROSFOND-2010, FENDL-3.0, TENDL − 2019 and IRDFF-II.
{"title":"Verification of nuclear data libraries used to design molten salt blankets of a fusion neutron source","authors":"Yu.E. Titarenko, S.A. Balyuk, V.F. Batyaev, V.I. Belousov, I.A. Bedretdinov, V. Yu. Blandinskiy, V.D. Davidenko, I.I. Dyachkov, V.M. Zhivun, Ya.O. Zaritstkiy, M.V. Ioannisian, A.S. Kirsanov, A.A. Kovalishin, N.A. Kovalenko, B.V. Kuteev, V.O. Legostaev, M.R. Malkov, I.V. Mednikov, K.V. Pavlov, A. Yu. Titarenko, K.G. Chernov","doi":"10.1016/j.anucene.2024.110983","DOIUrl":"10.1016/j.anucene.2024.110983","url":null,"abstract":"<div><div>This study presents the results of testing nuclear data libraries by analyzing statistical criteria obtained from comparing experimental and calculated rates for (n,2n), (n,p), (n,pn), (n,nꞌγ) (n,α) and (n,γ) reactions measured on samples <sup>nat</sup>Ni, <sup>nat</sup>Zr, <sup>nat</sup>Nb, <sup>nat</sup>Cd, <sup>nat</sup>Ti, <sup>nat</sup>Co,<sup>63(96%), 65(99.70%)</sup>Cu, <sup>64(99.70%)</sup>Zn, <sup>nat</sup>In, <sup>nat</sup>Al, <sup>nat</sup>Mg, <sup>nat</sup>Fe, <sup>nat</sup>Au and <sup>nat</sup>Th, which were placed in the experimental channels of micromodels of the fusion blanket.</div><div>The “fast” (the cylinder Ø 230 mm and 520 mm length was filled with ∼ 67 kg of molten salt 0.52NaF + 0.48ZrF4) and the “thermal” blanket (the same cylinder was placed in a dry channel inside a cubic container filled with water with dimensions of 52.0 × 52.0 × 52.0 cm were investigated. The reaction rates were measured using the activation method.</div><div>Modeling with transport codes MCNP5, KIR, PHITS-3.31, SuperMC3.4.0 was performed using the ENDF/B-VII.0 library for neutron transport as well as seven neutron data libraries for reaction rates simulation, including: JEFF-3.3, JENDL-4.0, ENDF/B–VIII.0, ROSFOND-2010, FENDL-3.0, TENDL − 2019 and IRDFF-II.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110983"},"PeriodicalIF":1.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142527012","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 : 2024-10-21DOI: 10.1016/j.anucene.2024.110997
Emil Fridman , Jacob D. Smith , Dan Kotlyar
This study explores the calculation of Reference Discontinuity Factors (RDFs) using the Serpent Monte Carlo code, focusing on the methodology and potential pitfalls. In two-step reactor analyses, consistently generated RDFs are crucial for aligning homogeneous nodal diffusion results with the reference heterogeneous transport solution. However, the Serpent internal diffusion solver, based on the Analytic Function Expansion Nodal (AFEN) method, may not be compatible with other nodal methods such as the Nodal Expansion Method (NEM). Additionally, the solver can suffer from instabilities, particularly in multi-group calculations, leading to erroneous RDFs. Despite these challenges, Serpent can generate the necessary raw data for RDF calculation, which can be accurately processed using external diffusion solvers. Two numerical examples − a 1D fuel-reflector model and a 2D SMR core model − illustrate the effects of consistent and inconsistent RDFs on simulation accuracy. The study emphasizes the importance of using compatible diffusion solvers and thoroughly assessing RDFs to avoid errors in reactor simulations.
本研究探讨了使用 Serpent Monte Carlo 代码计算参考不连续因子 (RDF)，重点是计算方法和潜在误区。在两步反应器分析中，一致生成的 RDF 对于使均质节点扩散结果与参考异质输运解决方案保持一致至关重要。然而，基于解析函数展开节点法（AFEN）的蛇形内部扩散求解器可能与节点展开法（NEM）等其他节点法不兼容。此外，该求解器可能会出现不稳定的情况，特别是在多组计算中，从而导致错误的 RDF。尽管存在这些挑战，Serpent 仍能生成 RDF 计算所需的原始数据，并使用外部扩散求解器对其进行精确处理。两个数值实例--1D 燃料反射器模型和 2D SMR 核心模型--说明了一致和不一致的 RDF 对模拟精度的影响。该研究强调了使用兼容的扩散求解器和彻底评估 RDF 以避免反应堆模拟错误的重要性。
{"title":"Insights into calculating Reference Discontinuity Factors with Serpent Monte Carlo code","authors":"Emil Fridman , Jacob D. Smith , Dan Kotlyar","doi":"10.1016/j.anucene.2024.110997","DOIUrl":"10.1016/j.anucene.2024.110997","url":null,"abstract":"<div><div>This study explores the calculation of Reference Discontinuity Factors (RDFs) using the Serpent Monte Carlo code, focusing on the methodology and potential pitfalls. In two-step reactor analyses, consistently generated RDFs are crucial for aligning homogeneous nodal diffusion results with the reference heterogeneous transport solution. However, the Serpent internal diffusion solver, based on the Analytic Function Expansion Nodal (AFEN) method, may not be compatible with other nodal methods such as the Nodal Expansion Method (NEM). Additionally, the solver can suffer from instabilities, particularly in multi-group calculations, leading to erroneous RDFs. Despite these challenges, Serpent can generate the necessary raw data for RDF calculation, which can be accurately processed using external diffusion solvers. Two numerical examples − a 1D fuel-reflector model and a 2D SMR core model − illustrate the effects of consistent and inconsistent RDFs on simulation accuracy. The study emphasizes the importance of using compatible diffusion solvers and thoroughly assessing RDFs to avoid errors in reactor simulations.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110997"},"PeriodicalIF":1.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526943","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}
Pub Date : 2024-10-21DOI: 10.1016/j.anucene.2024.110965
E. Adam Paxton , Jiejie Wu , Tim Hicks , Slimane Doudou , David Applegate , Robert Mason , Andrew Price , Liam Payne
Nuclear Waste Services is tasked with disposal of the UK’s higher-activity radioactive waste in a Geological Disposal Facility. The disposal of fissile nuclides requires a demonstration that there is no significant concern from criticality, i.e. a fission chain reaction. While waste packages will initially be emplaced in a subcritical configuration, over the long timescales following closure there is potential for waste packages to degrade and for nuclides to be dispersed in the subsurface by groundwater, leading to the potential for a critical system forming. To facilitate modelling, a codebase has been developed which interfaces a probabilistic simulation tool (GoldSim) with a neutron transport code (MONK/MCNP). This allows large ensemble simulations to be run iteratively to determine limiting fissile masses which satisfy a criticality safety criterion. This paper documents the main algorithms and methodologies implemented within this framework, and provides background and example results illustrating the application to post-closure criticality modelling.
{"title":"A computational framework to support probabilistic criticality modelling for the geological disposal of radioactive waste","authors":"E. Adam Paxton , Jiejie Wu , Tim Hicks , Slimane Doudou , David Applegate , Robert Mason , Andrew Price , Liam Payne","doi":"10.1016/j.anucene.2024.110965","DOIUrl":"10.1016/j.anucene.2024.110965","url":null,"abstract":"<div><div>Nuclear Waste Services is tasked with disposal of the UK’s higher-activity radioactive waste in a Geological Disposal Facility. The disposal of fissile nuclides requires a demonstration that there is no significant concern from criticality, i.e. a fission chain reaction. While waste packages will initially be emplaced in a subcritical configuration, over the long timescales following closure there is potential for waste packages to degrade and for nuclides to be dispersed in the subsurface by groundwater, leading to the potential for a critical system forming. To facilitate modelling, a codebase has been developed which interfaces a probabilistic simulation tool (GoldSim) with a neutron transport code (MONK/MCNP). This allows large ensemble simulations to be run iteratively to determine limiting fissile masses which satisfy a criticality safety criterion. This paper documents the main algorithms and methodologies implemented within this framework, and provides background and example results illustrating the application to post-closure criticality modelling.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110965"},"PeriodicalIF":1.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526942","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 : 2024-10-21DOI: 10.1016/j.anucene.2024.110996
Hyoin Lee , Jaedeok Ko , Ji Hwan Jeong
A series of experiments was conducted to investigate the flow of aqueous foam and the associated frictional pressure drop over a foam quality range of 0.170 to 0.908. Various foam flow regimes were observed, including wet foam, wet-dry mixed foam, transitional slug-wet foam, and slug-wet foam. These regimes varied even at identical foam qualities, depending on the gas and liquid velocities. The frictional pressure drops were measured across different foam flow regimes, exhibiting variation based on foam quality, as well as liquid and gas flow rates. An empirical correlation for the Fanning friction factor of foam flows was developed, demonstrating superior agreement with two independent experimental data sets, with an error margin of ±5.4 %. These findings offer valuable insights into foam flow behavior and frictional pressure losses in horizontal pipes, which are critical for optimizing decontamination processes in nuclear facilities.
{"title":"Development of a friction factor correlation for a foam flow in a horizontal circular pipe","authors":"Hyoin Lee , Jaedeok Ko , Ji Hwan Jeong","doi":"10.1016/j.anucene.2024.110996","DOIUrl":"10.1016/j.anucene.2024.110996","url":null,"abstract":"<div><div>A series of experiments was conducted to investigate the flow of aqueous foam and the associated frictional pressure drop over a foam quality range of 0.170 to 0.908. Various foam flow regimes were observed, including wet foam, wet-dry mixed foam, transitional slug-wet foam, and slug-wet foam. These regimes varied even at identical foam qualities, depending on the gas and liquid velocities. The frictional pressure drops were measured across different foam flow regimes, exhibiting variation based on foam quality, as well as liquid and gas flow rates. An empirical correlation for the Fanning friction factor of foam flows was developed, demonstrating superior agreement with two independent experimental data sets, with an error margin of ±5.4 %. These findings offer valuable insights into foam flow behavior and frictional pressure losses in horizontal pipes, which are critical for optimizing decontamination processes in nuclear facilities.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110996"},"PeriodicalIF":1.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526941","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 : 2024-10-21DOI: 10.1016/j.anucene.2024.110976
Mohamed S. El_Tokhy, H. Kasban, Elsayed H. Ali
Diagnosing problems in industrial processes has always been a complex challenge, frequently obstructed by the complex structure of these systems. The present study presents a robust methodology integrating nuclear radiotracer data with machine learning approaches to improve diagnosis. Radiotracers are used to measure residence time distribution (RTD) as a crucial diagnostic technology. Experiments utilize a Flow Rig System (FRS) to simulate industrial conditions, where a Tc-99 m radiotracer (1 mCi) is injected in Dirac form and monitored with sodium iodide scintillation detectors integrated with an ALTAIX data acquisition system (DAS). Machine learning algorithms are subsequently employed to categorize four RTD signals: normal RTD, small exchange RTD, recirculation RTD, and parallel flow RTD. Identifying these signal kinds is essential for precise system diagnostics. We utilize deep learning via Convolutional Neural Networks (CNNs) for feature extraction and an Artificial Neural Network (ANN) for classification. Additionally, the Binary Tree Growth Algorithm (BTGA) is employed to refine feature selection, improving model efficacy and decreasing processing demands. The deep learning model attains complete identification accuracy while implementing the HP classifier, which enhances processing time and precision. We simulate RTD signals for two scenarios − Perfect Mixers in Series (PMS) and Perfect Mixers with Exchange (PMSEX). We corroborate our results by comparing them with RTD simulation tools, demonstrating significant correlation and concordance. Our Results highlight the efficacy of combining advanced machine learning approaches with new real-time data modelling to enhance diagnostics efficiency and reliability in industrial operations. This method offers a revolutionary technique to improve process optimization and defect identification.
诊断工业流程中的问题一直是一项复杂的挑战，这些问题经常受到这些系统复杂结构的阻碍。本研究提出了一种将核放射性示踪剂数据与机器学习方法相结合的稳健方法，以改进诊断。放射性示踪剂用于测量停留时间分布（RTD），是一项重要的诊断技术。实验利用流动钻机系统（FRS）模拟工业条件，以狄拉克形式注入 Tc-99 m 放射性示踪剂（1 mCi），并通过与 ALTAIX 数据采集系统（DAS）集成的碘化钠闪烁探测器进行监测。随后采用机器学习算法对四种热电阻信号进行分类：正常热电阻、小交换热电阻、再循环热电阻和平行流热电阻。识别这些信号类型对于精确的系统诊断至关重要。我们通过卷积神经网络（CNN）进行特征提取，并利用人工神经网络（ANN）进行分类，从而实现深度学习。此外，我们还采用了二叉树生长算法（BTGA）来完善特征选择，从而提高模型效率并降低处理需求。在实施 HP 分类器的同时，深度学习模型达到了完全的识别精度，从而提高了处理时间和精度。我们模拟了两种情况下的热电阻信号--串联完美混合器（PMS）和交换完美混合器（PMSEX）。通过与热电阻模拟工具进行比较，我们证实了我们的结果，显示出显著的相关性和一致性。我们的成果凸显了将先进的机器学习方法与新的实时数据建模相结合，以提高工业运行中的诊断效率和可靠性的功效。这种方法为改进流程优化和缺陷识别提供了革命性的技术。
{"title":"Malfunction diagnosis based on residence time distribution of radiotracer signals in industrial processes using machine learning techniques","authors":"Mohamed S. El_Tokhy, H. Kasban, Elsayed H. Ali","doi":"10.1016/j.anucene.2024.110976","DOIUrl":"10.1016/j.anucene.2024.110976","url":null,"abstract":"<div><div>Diagnosing problems in industrial processes has always been a complex challenge, frequently obstructed by the complex structure of these systems. The present study presents a robust methodology integrating nuclear radiotracer data with machine learning approaches to improve diagnosis. Radiotracers are used to measure residence time distribution (RTD) as a crucial diagnostic technology. Experiments utilize a Flow Rig System (FRS) to simulate industrial conditions, where a Tc-99 m radiotracer (1 mCi) is injected in Dirac form and monitored with sodium iodide scintillation detectors integrated with an ALTAIX data acquisition system (DAS). Machine learning algorithms are subsequently employed to categorize four RTD signals: normal RTD, small exchange RTD, recirculation RTD, and parallel flow RTD. Identifying these signal kinds is essential for precise system diagnostics. We utilize deep learning via Convolutional Neural Networks (CNNs) for feature extraction and an Artificial Neural Network (ANN) for classification. Additionally, the Binary Tree Growth Algorithm (BTGA) is employed to refine feature selection, improving model efficacy and decreasing processing demands. The deep learning model attains complete identification accuracy while implementing the HP classifier, which enhances processing time and precision. We simulate RTD signals for two scenarios − Perfect Mixers in Series (PMS) and Perfect Mixers with Exchange (PMSEX). We corroborate our results by comparing them with RTD simulation tools, demonstrating significant correlation and concordance. Our Results highlight the efficacy of combining advanced machine learning approaches with new real-time data modelling to enhance diagnostics efficiency and reliability in industrial operations. This method offers a revolutionary technique to improve process optimization and defect identification.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110976"},"PeriodicalIF":1.9,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526944","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}
Nowadays, many researches are persistently exploring to comprehend the various characteristic of the supercritical fluid natural circulation loop (SCFNCL) such as use of SCFNCL at normal operating condition as well as a passive system for heat removal from the core, steady state and transient behavior of the loop, heat transfer rate, heat transfer coefficient and optimizing mass flow rate of the loop. In last two decade, a significant research has been seen in the form of analytical, computational and experimental works which highlight the notable use of SCFNCL as an active and passive system in nuclear power plant (NPPs). However, very limited state of arts have been reported based on the loop geometry and their effects, different types of supercritical fluids (SCFs) and applications of the loops. Therefore, steady and transient behaviours of loop in single and parallel channels, thermal–hydraulic (TH) instability, effects of the geometrical and operating parameters on SCFNCL and deterioration of heat transfer (DHT) in SCFNCL are the main emphasis of this review. Performance criteria such as instability, transient, and steady-state requirements, along with methods for containing instability, have been covered. It even emphasizes how crucial it is to validate the numerical codes. Since nuclear reactors use coupled SCFNCL as passive cooling systems, different topologies and combinations of fluids are shown. Very limited experimental studies have been reported in the coupled loop, an initial analysis was conducted and the results demonstrated the effectiveness of the system. The review also demonstrated the need for numerical analysis with using different supercritical fluids and combine with the NPP systems as well as experimental investigations, which can be connected to applications in renewable and sustainable energy.
{"title":"A comprehensive overview of advancements, applications, and impact of supercritical fluid natural circulation loops","authors":"Santosh Kumar Rai , Pardeep Kumar , Mukesh Tiwari , Vinay Panwar , Dinesh Kumar , Vipin Kumar Sharma","doi":"10.1016/j.anucene.2024.110971","DOIUrl":"10.1016/j.anucene.2024.110971","url":null,"abstract":"<div><div>Nowadays, many researches are persistently exploring to comprehend the various characteristic of the supercritical fluid natural circulation loop (SCFNCL) such as use of SCFNCL at normal operating condition as well as a passive system for heat removal from the core, steady state and transient behavior of the loop, heat transfer rate, heat transfer coefficient and optimizing mass flow rate of the loop. In last two decade, a significant research has been seen in the form of analytical, computational and experimental works which highlight the notable use of SCFNCL as an active and passive system in nuclear power plant (NPPs). However, very limited state of arts have been reported based on the loop geometry and their effects, different types of supercritical fluids (SCFs) and applications of the loops. Therefore, steady and transient behaviours of loop in single and parallel channels, thermal–hydraulic (TH) instability, effects of the geometrical and operating parameters on SCFNCL and deterioration of heat transfer (DHT) in SCFNCL are the main emphasis of this review. Performance criteria such as instability, transient, and steady-state requirements, along with methods for containing instability, have been covered. It even emphasizes how crucial it is to validate the numerical codes. Since nuclear reactors use coupled SCFNCL as passive cooling systems, different topologies and combinations of fluids are shown. Very limited experimental studies have been reported in the coupled loop, an initial analysis was conducted and the results demonstrated the effectiveness of the system. The review also demonstrated the need for numerical analysis with using different supercritical fluids and combine with the NPP systems as well as experimental investigations, which can be connected to applications in renewable and sustainable energy.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110971"},"PeriodicalIF":1.9,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526849","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 : 2024-10-19DOI: 10.1016/j.anucene.2024.110973
Yiqian Sun , Meiqi Song , Chunjing Song , Meng Zhao , Yanhua Yang
To study the fault intelligent detection and diagnosis method of nuclear power plant systems and improve the detection and diagnosis effect of internal fault of nuclear power plant Chemical and Volume control System (CVS), this study presents an intelligent Fault Detection and Diagnosis model for the Chemical and Volume control System (FDD-CVS) in nuclear power plants (NPPs). The model is based on failure mode and effects analysis of the CVS system and is implemented by combining kernel principal component analysis (KPCA) with decision tree and support vector machine (SVM). FDD-CVS can rapidly and visually recognize faults in CVS based on independent time-point system parameters, and it is capable of diagnosing fault types and specific fault locations. The model is characterized by clear principles, hierarchical diagnostics, fast diagnostic speed, and visualized results. The model is trained and tested by using the data of the passive nuclear power simulation analyzer. The fault detection rate of FDD-CVS is 96.38%, the false alarm rate is 4.34%, and the average accuracy rate is 98.40%. Overall, the fault monitoring and diagnostic method proposed in this article is innovative and provides valuable references for fault diagnosis research in nuclear power plants.
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Pub Date : 2024-10-19DOI: 10.1016/j.anucene.2024.110992
A. Kamkar, M. Abbasi
Enhancing the safety of nuclear power plants relies on the prompt and accurate identification of potential anomalies within the reactor. This paper explores the application of machine learning techniques for the identification and localization of perturbed fuel assemblies in WWER-type reactors. Various machine learning classifiers, spanning the decision tree, random forest, k-nearest neighbors, multilayer perceptron, support vector machine, and 1D-convolutional neural network, are scrutinized for their performance under diverse conditions.
The methodology encompasses data collection, data preprocessing, hyperparameter tuning, and model evaluation. The necessary dataset is generated using DYNOSIM to simulate all conceivable scenarios related to fuel assembly vibration in a WWER-type reactor. In addition to assessing the models under clear and complete input conditions, a sensitivity analysis is performed to gauge the models’ resilience to detector failures and the introduction of white noise. A comparative analysis of the six machine learning classification models reveals that multilayer perceptron, support vector machine, and 1D-convolutional neural network display the most sturdy classification performance, achieving accuracies of 76.38 %, 70.85 %, and 74.64 %, respectively.
{"title":"A comparative study of machine learning approaches for identification of perturbed fuel assemblies in WWER-type nuclear reactors","authors":"A. Kamkar, M. Abbasi","doi":"10.1016/j.anucene.2024.110992","DOIUrl":"10.1016/j.anucene.2024.110992","url":null,"abstract":"<div><div>Enhancing the safety of nuclear power plants relies on the prompt and accurate identification of potential anomalies within the reactor. This paper explores the application of machine learning techniques for the identification and localization of perturbed fuel assemblies in WWER-type reactors. Various machine learning classifiers, spanning the decision tree, random forest, k-nearest neighbors, multilayer perceptron, support vector machine, and 1D-convolutional neural network, are scrutinized for their performance under diverse conditions.</div><div>The methodology encompasses data collection, data preprocessing, hyperparameter tuning, and model evaluation. The necessary dataset is generated using DYNOSIM to simulate all conceivable scenarios related to fuel assembly vibration in a WWER-type reactor. In addition to assessing the models under clear and complete input conditions, a sensitivity analysis is performed to gauge the models’ resilience to detector failures and the introduction of white noise. A comparative analysis of the six machine learning classification models reveals that multilayer perceptron, support vector machine, and 1D-convolutional neural network display the most sturdy classification performance, achieving accuracies of 76.38 %, 70.85 %, and 74.64 %, respectively.</div></div>","PeriodicalId":8006,"journal":{"name":"Annals of Nuclear Energy","volume":"211 ","pages":"Article 110992"},"PeriodicalIF":1.9,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142526852","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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