In this study,a multi-physics and multi-scale coupling program,Fluent/KMC-sub/NDK,was developed based on the user-defined functions(UDF)of Fluent,in which the KMC-sub-code is a sub-channel thermal-hydraulic code and t...In this study,a multi-physics and multi-scale coupling program,Fluent/KMC-sub/NDK,was developed based on the user-defined functions(UDF)of Fluent,in which the KMC-sub-code is a sub-channel thermal-hydraulic code and the NDK code is a neutron diffusion code.The coupling program framework adopts the"master-slave"mode,in which Fluent is the master program while NDK and KMC-sub are coupled internally and compiled into the dynamic link library(DLL)as slave codes.The domain decomposition method was adopted,in which the reactor core was simulated by NDK and KMC-sub,while the rest of the primary loop was simulated using Fluent.A simulation of the reactor shutdown process of M2LFR-1000 was carried out using the coupling program,and the code-to-code verification was performed with ATHLET,demonstrating a good agreement,with absolute deviation was smaller than 0.2%.The results show an obvious thermal stratification phenomenon during the shutdown process,which occurs 10 s after shutdown,and the change in thermal stratification phenomena is also captured by the coupling program.At the same time,the change in the neutron flux density distribution of the reactor was also obtained.展开更多
目前核电运行管理系统存在数据接口不统一、设备状态数字化表达程度差等缺陷,为适应未来智慧核电的需要,将数字孪生理论与实时数据对接技术、图形可视化手段相结合,基于钍基熔盐固态仿真堆(Thorium Molten Salt Reactor-Solid Fuel,TMSR...目前核电运行管理系统存在数据接口不统一、设备状态数字化表达程度差等缺陷,为适应未来智慧核电的需要,将数字孪生理论与实时数据对接技术、图形可视化手段相结合,基于钍基熔盐固态仿真堆(Thorium Molten Salt Reactor-Solid Fuel,TMSR-SF0)实例,提出一套完整的数据监控与可视化技术方案。首先,建立熔盐堆反应装置数字映射模型,并完成在Unity引擎的模型对接及虚拟场景渲染;其次,基于Node-EPICS事件驱动与Socket.io套接字实现时空数据关联;最后,基于XCharts可视化框架提出集中显示实时数据的可视化方法,保证数据的可解释性,便于对数据的实时分析。经实践验证,该方案为TMSR-SF0的数据监控系统开发提供了有效技术支撑,数据更新周期为100 ms,且具备全流程数据采集、网络通信、图元动态展示等功能,有助于操作人员对核反应装置的在线监视与运行管理,为核电领域监控技术的数字化转型发展提供了参考。展开更多
This work illustrates the innovative results obtained by applying the recently developed the 2<sup>nd</sup>-order predictive modeling methodology called “2<sup>nd</sup>- BERRU-PM”, where the ...This work illustrates the innovative results obtained by applying the recently developed the 2<sup>nd</sup>-order predictive modeling methodology called “2<sup>nd</sup>- BERRU-PM”, where the acronym BERRU denotes “best-estimate results with reduced uncertainties” and “PM” denotes “predictive modeling.” The physical system selected for this illustrative application is a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. This benchmark is modeled using the neutron transport Boltzmann equation (involving 21,976 uncertain parameters), the solution of which is representative of “large-scale computations.” The results obtained in this work confirm the fact that the 2<sup>nd</sup>-BERRU-PM methodology predicts best-estimate results that fall in between the corresponding computed and measured values, while reducing the predicted standard deviations of the predicted results to values smaller than either the experimentally measured or the computed values of the respective standard deviations. The obtained results also indicate that 2<sup>nd</sup>-order response sensitivities must always be included to quantify the need for including (or not) the 3<sup>rd</sup>- and/or 4<sup>th</sup>-order sensitivities. When the parameters are known with high precision, the contributions of the higher-order sensitivities diminish with increasing order, so that the inclusion of the 1<sup>st</sup>- and 2<sup>nd</sup>-order sensitivities may suffice for obtaining accurate predicted best- estimate response values and best-estimate standard deviations. On the other hand, when the parameters’ standard deviations are sufficiently large to approach (or be outside of) the radius of convergence of the multivariate Taylor-series which represents the response in the phase-space of model parameters, the contributions stemming from the 3<sup>rd</sup>- and even 4<sup>th</sup>-order sensitivities are necessary to ensure consistency between the computed and measured response. In such cases, the use of展开更多
In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background even...In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background events as well as the details of event selection and background estimation. This study investigates a ＂sampling and mixing＂ method used for producing large MC data samples for the Daya Bay reactor neutrino experiment. We designed a simple, generic mixing algorithm and generated large MC data samples for physics analysis from several samples according to their respective event rates. Basic plots based on the mixed data are shown.展开更多
基金supported by Science and Technology on Reactor System Design Technology Laboratory,Chengdu,China(LRSDT2020106)
文摘In this study,a multi-physics and multi-scale coupling program,Fluent/KMC-sub/NDK,was developed based on the user-defined functions(UDF)of Fluent,in which the KMC-sub-code is a sub-channel thermal-hydraulic code and the NDK code is a neutron diffusion code.The coupling program framework adopts the"master-slave"mode,in which Fluent is the master program while NDK and KMC-sub are coupled internally and compiled into the dynamic link library(DLL)as slave codes.The domain decomposition method was adopted,in which the reactor core was simulated by NDK and KMC-sub,while the rest of the primary loop was simulated using Fluent.A simulation of the reactor shutdown process of M2LFR-1000 was carried out using the coupling program,and the code-to-code verification was performed with ATHLET,demonstrating a good agreement,with absolute deviation was smaller than 0.2%.The results show an obvious thermal stratification phenomenon during the shutdown process,which occurs 10 s after shutdown,and the change in thermal stratification phenomena is also captured by the coupling program.At the same time,the change in the neutron flux density distribution of the reactor was also obtained.
文摘This work illustrates the innovative results obtained by applying the recently developed the 2<sup>nd</sup>-order predictive modeling methodology called “2<sup>nd</sup>- BERRU-PM”, where the acronym BERRU denotes “best-estimate results with reduced uncertainties” and “PM” denotes “predictive modeling.” The physical system selected for this illustrative application is a polyethylene-reflected plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. This benchmark is modeled using the neutron transport Boltzmann equation (involving 21,976 uncertain parameters), the solution of which is representative of “large-scale computations.” The results obtained in this work confirm the fact that the 2<sup>nd</sup>-BERRU-PM methodology predicts best-estimate results that fall in between the corresponding computed and measured values, while reducing the predicted standard deviations of the predicted results to values smaller than either the experimentally measured or the computed values of the respective standard deviations. The obtained results also indicate that 2<sup>nd</sup>-order response sensitivities must always be included to quantify the need for including (or not) the 3<sup>rd</sup>- and/or 4<sup>th</sup>-order sensitivities. When the parameters are known with high precision, the contributions of the higher-order sensitivities diminish with increasing order, so that the inclusion of the 1<sup>st</sup>- and 2<sup>nd</sup>-order sensitivities may suffice for obtaining accurate predicted best- estimate response values and best-estimate standard deviations. On the other hand, when the parameters’ standard deviations are sufficiently large to approach (or be outside of) the radius of convergence of the multivariate Taylor-series which represents the response in the phase-space of model parameters, the contributions stemming from the 3<sup>rd</sup>- and even 4<sup>th</sup>-order sensitivities are necessary to ensure consistency between the computed and measured response. In such cases, the use of
基金Supported by Chinese Academy of SciencesNational Natural Science Foundation of China(10225524, 10475086, 10535050, 10575056 and Y2118M005C)Ministry of Science and Technology of China
文摘In reactor neutrino experiments, the analysis of time correlations between different physical events is an important task. Such analysis can help to understand the physical mechanisms of the signal and background events as well as the details of event selection and background estimation. This study investigates a ＂sampling and mixing＂ method used for producing large MC data samples for the Daya Bay reactor neutrino experiment. We designed a simple, generic mixing algorithm and generated large MC data samples for physics analysis from several samples according to their respective event rates. Basic plots based on the mixed data are shown.
