Investigation on Flow Accelerated Corrosion Mitigation for Secondary Circuit Piping of the Third Qinshan Nuclear Power Plant

Flow accelerated corrosion（FAC） is the main failure cause of the secondary circuit carbon steel piping in nuclear power plants.The piping failures caused by FAC have resulted in numerous unplanned outages and tragic fatalities.The existing researches focus on the main factors contributing to FAC,which include metallurgical factors,environmental factors and hydrodynamic factors. Some effective FAC management methods and programs with long term monitoring and inspection data analysis are recommended.But a comprehensive FAC management system should be developed in order to mitigate and manage FAC systematically.In this paper,the FAC influencing factors are analyzed in combination with the operating conditions of the secondary circuit piping in the Third Qinshan Nuclear Power Plant（TQNPP）,China（Third Qinshan Nuclear Power Company Limited,China）.A comprehensive FAC mitigation and management system is developed for TQNPP secondary circuit piping.The system is composed of five processes,viz.materials substitution,water chemical optimization,long-term monitor strategy for the susceptible piping,integrity evaluation of the local thinning defects,and repair or replacement.With the implementation of the five processes,the material of FAC sensitive pipe fittings are modified from carbon steel to stainless steel,N_2H_4 and NH_3 are finally selected as the water chemical regulator of secondary circuit,the secondary circuit pips are classified according to FAC susceptibility in order to conduct long term monitoring strategy,and an integrity evaluation flow for local thinning caused by FAC in carbon steel piping is developed.If the component with local thinning defects is not fit-for-service,corresponding repair or replacement should be conducted.The comprehensive FAC mitigation and management system with five interrelated processes would be a cost-effective method of increasing personnel safety,plant safety and availability.

Application of fuzzy neural network to the nuclear power plant in process fault diagnosis

The fuzzy logic and neural networks are combined in this paper, setting upthe fuzzy neural network (FNN ) ; meanwhile, the distinct differences and connections between thefuzzy logic and neural network are compared. Furthermore, the algorithm and structure of the FNN areintroduced. In order to diagnose the faults of nuclear power plant, the FNN is applied to thenuclear power planl, and the intelligence fault diagnostic system of the nuclear power plant isbuilt based on the FNN . The fault symptoms and the possibility of the inverted U-tube breakaccident of steam generator are discussed. In order to test the system' s validity, the invertedU-tube break accident of steam generator is used as an example and many simulation experiments areperformed. The test result shows that the FNN can identify the fault.

Nuclear power plant fault diagnosis based on genetic-RBF neural network

It is necessary to develop an automatic fault diagnosis system to avoid a possible nuclear disaster caused by an inaccurate fault diagnosis in the nuclear power plant by the operator. Because Radial Basis Function Neural Network (RBFNN) has the characteristics of optimal approximation and global approximation. The mixed coding of binary system and decimal system is introduced to the structure and parameters of RBFNN, which is trained in course of the genetic optimization. Finally, a fault diagnosis system according to the frequent faults in condensation and feed water system of nuclear power plant is set up. As a result, Genetic-RBF Neural Network (GRBFNN) makes the neural network smaller in size and higher in generalization ability. The diagnosis speed and accuracy are also improved.

Bayesian belief-based model for reliability improvement of the digital reactor protection system

The digital reactor protection system(RPS)is one of the most important digital instrumentation and control(I&C)systems utilized in nuclear power plants(NPPs).It ensures a safe reactor trip when the safety-related parameters violate the operational limits and conditions of the reactor.Achieving high reliability and availability of digital RPS is essential to maintaining a high degree of reactor safety and cost savings.The main objective of this study is to develop a general methodology for improving the reliability of the RPS in NPP,based on a Bayesian Belief Network(BBN)model.The structure of BBN models is based on the incorporation of failure probability and downtime of the RPS I&C components.Various architectures with dual-state nodes for the I&C components were developed for reliability-sensitive analysis and availability optimization of the RPS and to demonstrate the effect of I&C components on the failure of the entire system.A reliability framework clarified as a reliability block diagram transformed into a BBN representation was constructed for each architecture to identify which one will fit the required reliability.The results showed that the highest availability obtained using the proposed method was 0.9999998.There are 120 experiments using two common component importance measures that are applied to define the impact of I&C modules,which revealed that some modules are more risky than others and have a larger effect on the failure of the digital RPS.

Twin model-based fault detection and tolerance approach for in-core self-powered neutron detectors

The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SPNDs are indispensable for reliable reactor management.To completely extract the correlated state information of SPNDs,we constructed a twin model based on a generalized regression neural network(GRNN)that represents the common relationships among overall signals.Faulty SPNDs were determined because of the functional concordance of the twin model and real monitoring sys-tems,which calculated the error probability distribution between the model outputs and real values.Fault detection follows a tolerance phase to reinforce the stability of the twin model in the case of massive failures.A weighted K-nearest neighbor model was employed to reasonably reconstruct the values of the faulty signals and guarantee data purity.The experimental evaluation of the proposed method showed promising results,with excellent output consistency and high detection accuracy for both single-and multiple-point faulty SPNDs.For unexpected excessive failures,the proposed tolerance approach can efficiently repair fault behaviors and enhance the prediction performance of the twin model.

基于差分电感的分体式压力/差压测量系统研究

随着安全级压力/差压变送器在核工业领域的广泛应用,提高其中传感器的可靠性已成为发展重点。对国内外核安全级压力/差压测量技术进行了深入研究。采用易远传的电感式传感器结构,设计了一种基于差分电感原理的安全级分体式压力/差压测量系统。阐述了测量系统中传感器和信号处理装置的详细设计方案,并对测量电路的设计进行了分析。通过分体式的设计方案,可有效提高测量设备的耐事故性能。该方案可为国内高可靠核级压力变送器产品的研发奠定基础,适用于核级压力、液位和流量信号的测量。该方案也适用于其他恶劣环境条件下非核测量领域的变送器产品研发。

基于CFD的阀门保温层传热仿真分析

非能动二次侧余热排出(PRS)系统的蒸汽管道与主蒸汽管道相连,给水管线与PRS系统凝水管线相连。在开展系统热工流体分析时发现,若非能动二次侧余热排出系统蒸汽管线与二回路主蒸汽管线之间的蒸汽隔离阀常开,高温蒸汽直接作用于阀门,加上保温层的作用阻碍阀门散热,可能会导致蒸汽隔离阀内部温度过高,引起阀门电装无法正常动作。本文计算分析了PRS系统蒸汽隔离阀带保温层状态下的传热情况,判断阀门在高温流体下是否能保证电机的可用性。

电站仪用压缩空气供应系统冷却塔防冻措施优化

针对田湾核电站二期工程仪用压缩空气供应系统的冷却塔防冻问题,通过梳理系统流程、冷却塔工作原理及其防冻措施,结合现场发生的防冻问题,提出一系列优化措施。研究结果表明,通过完善设备保温、优化防冻回路逻辑、改进设备防风措施和紧急情况下的运行干预策略,可以有效降低仪用压缩空气供应系统因冰冻导致的不可用风险,从而确保核电站的安全稳定运行。

核电厂辅助车间集中监控技术研究

针对目前核电厂各辅助车间(BOP)采用分散监控模式带来的运行成本高的现状,设计了基于现场设备层、控制层、网络通信层和运行监控层的核电厂BOP集中监控系统,以实现各BOP的集中监控。BOP集中控制室的设置提高了BOP自动化控制水平,实现了BOP无人值守,达到了减员增效的目的。网络通信层采用冗余监控环网和冗余信息环网的网络拓扑结构,从物理层面将传输实时数据的监控网络与传输非周期性数据的信息网络分开,以分流监控数据与信息数据,从而提高网络通信层的可靠性。BOP集中监控系统采用统一的控制系统平台,减少了控制系统软硬件的备件种类、数量和设备管理费用。通过应用服务器中设计的计算机化规程系统、报警显示系统,降低了操作员的工作强度,增强了人机交互的友好性。

蒸汽介质下的温度传感器响应时间研究

根据堆型研发设计对温度传感器的响应时间需求,针对温度传感器无法给出蒸汽介质下响应时间具体数值的问题,研究了基于11种工况的蒸汽介质下响应时间测量仿真分析和试验。通过仿真,研究了不同蒸汽介质工况下对温度传感器响应时间的影响与变化规律。结合11种工况的试验结果数据,得出实际蒸汽介质下各种因素组合影响的温度传感器动态响应结果。该研究具有实践指导意义,能推动保护功能的设计固化。该研究可为核电工程提供一定的理论参考。

光学双基站空间定位测量系统在核电厂波动管安装中的应用研究

在核电厂运行过程中,作为稳压器与主管道热段连接的通道,稳压器可通过波动管调节主回路系统冷却剂的工作压力,避免因压力过高或过低而引发事故。波动管安装施工涉及管线长,焊口多,安装精度要求高,需要进行精确的组对和安装过程控制。本文主要描述了采用自主研发的高精密光学双基站空间定位测量系统实现波动管安装的工艺方法,从测量控制网布设、波动管本体尺寸测量、接管管嘴测量、模拟组对等方面开展应用研究,通过模拟组对可提前确定管道坡口的预制加工尺寸,相较于实际拼接后再进行手工量取的传统方式,能够大幅缩短现场施工工期,同时对波动管本体尺寸进行了重复性测量,其3次测量结果互差最大为0.11 mm,满足核电厂三维测量两次互差小于0.3 mm的精度要求,验证了该系统能够较好地满足现场使用需求。

基于多层次神经网络与多点位的核电站高压开关设备无线测温方法

光线条件、视角和拍摄距离等因素影响下,温感成像质量较差,且数据泄露或被篡改的风险较大,高压开关设备温度信息存在偏差或不稳定线性,导致无线测温过程的温度拟合增益系数较低。为此,提出基于多层次神经网络与多点位的核电站高压开关设备无线测温方法。通过放射性结构的拍摄点位布设方案,获取温感图像,并对其进行灰度阈值分割处理;采用领域平均法,结合多点位需求,对获取到的二值温感图像进行平滑处理,并构建多层次神经网络,将二值温感图像作为输入,通过卷积层以及激活函数,增强其非线性映射能力,分析与计算具有平滑期望值的无线测温结果即设备表面的温度值预测值。实验结果表明,该方法应用后,测温结果的温度拟合增益系数更高,具备更为理想的测温精度,为核电站高压开关设备的无线测温提供了准确、可靠的技术支持。

核电厂运行阶段安全文化评价指标体系研究

为培育良好的核电厂运行阶段安全文化,通过分析核电厂运行特征,总结已有的核安全文化评价指标体系和评价模型,构建核电厂运行阶段安全文化评价指标体系,划分为价值观、行为、系统和环境4个层次,并细分出13个二级指标和61个三级指标;在此基础上,考虑到指标之间的非独立性和可能存在的相互影响关系,提出一种基于决策试验和评价实验法(DEMATEL)以及网络层次分析法(ANP)相结合的综合方法,确定指标体系的权重。结果表明:该方法结合调研数据,可得到核安全文化评价指标权重,并甄别出改善核安全文化的关键在于决策层的安全意识、以身作则等指标,为核电厂运行阶段安全文化的培育提供指导。

核电厂地下管网结构化数据建模研究

在数字化设计平台建设过程中,为了解决缺少专业设计软件的情况下少量地下管网模型的生产和集成问题,需要建立一种与设计软件解绑的建模方式。通过研究使用结构化的管网数据驱动生成三维模型的方法,实现核电厂已有地下管道和管道附属物快速逆向建模,进一步实现核电厂室外工程设计模型和施工模型的集成与应用。

核电厂核级测量仪表调试方法优化探讨

保证核级测量仪表的精准度,才能促进核电机组安全稳定运行。针对核级测量仪表的调试问题进行研究,采用文献总结法、案例分析法,从核级测量仪表调试的重要性入手,针对通道验证试验、量程修正试验提出优化方法,并对优化效果进行评价。研究结果显示通过优化调试方法,不仅提高了仪表调试效率和准确性,而且实现了调试管理的智能化,可在实际工作中推广应用。

核电厂防火工程计量与计价方法研究

本文针对核电厂防火封堵工程计量与计价方法进行了深入研究。对核电厂防火封堵工程的重要性和相关技术进行了分析和总结。探讨了当前常见的计量与计价方法,并对各种方法的优缺点进行了比较。最后,提出了一种综合考虑成本与效益的计量与计价方法,并进行了实证分析。本文的研究成果对核电厂防火封堵工程的管理和优化具有一定的指导意义,具有一定的理论与实际价值。

电厂侧储能系统网络安全防护研究

在电厂侧储能系统接入电网后,新增的储能监控系统与电厂原有生产监控系统及电网调度系统之间将产生大量的信息交换,这种情况可能会引发电力监控系统网络安全防护问题.为了防范和解决这些问题,需要在设计阶段按照网络安全防护规则来进行相应的设计和规划.文章主要探讨了电厂侧储能系统的网络安全防护问题,旨在提高其网络安全性能,保障电力系统的稳定运行.

基于大数据技术的电厂智感安防立体防控网络构建研究

文章旨在构建一个基于大数据技术的电厂智感安防立体防控网络,并探讨其在提升电厂安全管理和运营效率方面的潜力。通过对海量数据进行深度挖掘和分析,该网络可以实现对电厂各个环节的实时监测和预警。然而,要实现这一目标,仍然面临数据采集、处理、融合与分析等挑战。因此,文章还研究了流式计算技术、整合大数据技术以及构建整合和共享机制等方面的解决方案。

核电管道弯曲半径检测方法研究

核电管道弯曲半径的检测属于大直径小圆弧测量范畴,针对管道弯曲直径较大、弯管外缘形状不规则而难以对半径准确测量问题,提出新的检测思路。该文使用激光跟踪仪采集管道表面三维点数据,结合SA测量分析软件模拟管道三维特征量,计算实际弯曲角度,建立评价基准面即管道中分面,在中分面上截取弯曲段内外圆弧轮廓点数据,依据图纸理论半径并兼顾管道实际弯曲角度,CAD辅助作图,统一圆弧唯一中心,精确界定圆弧轮廓边界,计算截取点到中心距离,更为合理的评价弯曲半径值,保证弯曲半径的测量评价不脱离管道整体结构尺寸链。该文方法与标准数模比对法的测量结果偏差为0.43 mm,满足相对公差±10 mm的要求,得到更为准确的检测结果。

基于LSTM的核电站除氧器水位控制系统隐蔽攻击方法研究

针对实现核电站除氧器水位控制系统的隐蔽攻击需要受攻击对象具备高精度估计模型的问题,提出了一种基于长短期记忆(LSTM)神经网络的隐蔽攻击方法。该方法将核电站除氧器水位控制系统中获得的反馈控制器输出信号与输入信号作为LSTM的数据集,通过训练得到高精度的估计模型,此估计模型被用于设计隐蔽攻击器,向受攻击对象施加攻击信号,从而实现隐蔽攻击。最后,通过仿真实验验证了该方法的有效性和隐蔽性。结果表明:该方法对核电站除氧器的水位造成一定影响的同时具有较高的隐蔽性。