Preliminary Failure Modes and Effects Analysis of the US DCLL Test Blanket Module

This report presents the results of a preliminary failure modes and effects analysis (FMEA) of a small tritium-breeding test blanket module design for the International Thermonuclear Experimental Reactor. The FMEA was quantified with “generic” component failure rate data, and the failure events are binned into postulated initiating event families and frequency categories for safety assessment. An appendix to this report contains repair time data to support an occupational radiation exposure assessment for test blanket module maintenance

Preliminary Failure Modes and Effects Analysis of the US DCLL Test Blanket Module

This report presents the results of a preliminary failure modes and effects analysis (FMEA) of a small tritium-breeding test blanket module design for the International Thermonuclear Experimental Reactor. The FMEA was quantified with “generic” component failure rate data, and the failure events are binned into postulated initiating event families and frequency categories for safety assessment. An appendix to this report contains repair time data to support an occupational radiation exposure assessment for test blanket module maintenance

Guideline for Selection of Systems, Structures and Components to be considered in Ageing PSA

The guideline intends to provide a practical approach and to recommend the methods to be used in selection/prioritization of components, systems and structures (SSC) sensitive to ageing and important from risk point of view in operating nuclear power plants. The approach intends to ensure that the selection process will be carried out and documented in a uniform and consistent manner. The methods suitable for selection are briefly presented, and their advantages and disadvantages are specified. A list of generic ageing mechanisms, the factors favorable for their occurrence and some sensitive materials are provided in appendices. In the appendices are presented also the specific approaches and criteria used for SSC prioritization and selection in case studies performed in the frame of Ageing PSA task 3 activities. The guideline was developed in the frame of EC JRC Ageing PSA Network (APSA) activities.JRC.DDG.F.5-Safety of present nuclear reactor

Development of maintenance framework for modern manufacturing systems

Modern manufacturing organizations are designing, building and operating large, complex and often ‘one of a kind’ assets, which incorporate the integration of various systems under modern control systems. Due to such complexity, machines failures became more difficult to interpret and rectify and the existing maintenance strategies became obsolete without development and enhancement. As a result, the need for more advanced strategies to ensure effective maintenance applications that ensures high operation efficiency arise. The current research aims to investigate the existing maintenance strategies, the levels of machines complexity and automation within manufacturing companies from different sectors and sizes including, oil and gas, food and beverages, automotive, aerospace, and Original Equipment Manufacturer. Results analysis supports in the development of a modern maintenance framework that overcome the highlighted results and suits modern manufacturing assets using systematic approaches and utilisation of pillars from Total productive maintenance (TPM, Reliability Centred Maintenance (RCM) and Industry 4.0

Maintenance models applied to wind turbines. A comprehensive overview

Producción CientíficaWind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models

A Framework for Remaining Useful Life Prediction of Steam Turbines Applicable to Various Data Types

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2018. 8. 윤병동.최근 발전사간 경쟁이 치열해짐에 따라 발전 산업에서는 운전 비용을 절감하고 핵심 설비의 수명을 연장하는데 많은 노력을 기울이고 있다. 한편 운전 시간이 설계 수명에 근접함에 따라 증기터빈과 같은 핵심 설비의 열화가 가속되고 크고 작은 고장이 많이 발생하고 있다. 가속화된 열화나 예기치 못한 손상으로 발전소가 정지되면 막대한 경제적 손실과 국가적인 재해를 야기할 수 있다. 이에 따라 안정적인 설비의 운전을 가능케 하는 다양한 기술들이 개발되고 있으며 최근 들어 더욱 많은 각광을 받고 있는 시스템 건전성 관리 기술은 효과적으로 시스템의 상태를 감지, 진단, 그리고 예지하여 관리자가 유지 보수에 있어 필요한 결정을 내릴 수 있도록 도와준다. 특히 최적 유지정비 관점에서 적합한 방법론을 통해 예측된 잔존유효수명은 설비 수명에 정확한 정보를 기반으로 효과적인 유지 정비를 가능하게 한다. 증기 터빈은 발전소 수명을 결정하는 핵심 설비이기 때문에 발전소의 최적 운영을 위해 활용 가능한 정보를 최대한 활용하여 운전 중인 증기터빈의 잔존유효수명을 정확하게 예측하는 방법론의 개발이 매우 중요하다. 이에 본 박사학위 논문에서는 (1) 증기 터빈에 대한 고장모드영향분석과 연계한 잔존유효수명 예측 프레임워크, 그리고 이를 바탕으로 한 (2) 손상 성장 모델 (데이터 기반 방법론), (3) 크리프-피로 손상 상호작용을 고려한 모드 의존 손상 모델 (모델 기반 방법론) 등의 연구를 제안한다. 첫 번째 연구에서는 고장모드영향분석에 기반하여 증기터빈의 잔존유효수명을 예측하는 프레임워크를 제안한다. 프레임워크는 측정된 데이터에 기반한 방법론과 손상 모델에 기반한 방법론으로 구성된다. 오프라인이나 온라인과 같이 다른 목적으로 잔존유효수명을 예측할 때 불확실도를 평가하고 감소시킬 수 있도록 불확실도를 정량화하는 절차를 포함하였다. 두 번째 연구에서는 데이터 기반 방법론을 이용해 증기터빈의 잔존유효수명을 평가할 수 있는 손상 성장 모델의 개발을 목적으로 한다. 잔존유효수명은 손상 인자로부터 손상 성장 모델을 연계하여 예측한다. 현장에서 측정된 경도값으로부터 손상인자의 확률분포를 추정하고 손상의 성장을 평가할 때 불확실도를 고려하기 위해 베이지안 방법을 사용하였다. 제안된 손상 성장 모델을 통해 기저부하나 첨두부하에 사용되는 증기터빈의 종류에 상관없이 정확한 잔존유효수명 예측이 가능하다는 것을 검증하였다. 마지막 연구에서는 모델 기반 방법론을 이용해 크리프와 피로 상호작용이 고려된 모드 기반 손상모델을 제안하였다. 손상기구에 따른 재료 데이터를 통계적 기법으로 분석하고 실 증기터빈의 형상 정보와 운전정보를 이용해 기저부하와 첨두부하 터빈을 대상으로 크리프 및 피로 손상율을 계산하였다. 각각 계산된 손상율 결과와 크리프-피로 상호작용 모델을 통해 운전모드 또는 손상모드에 따른 증기터빈에서의 크리프와 피로 상호작용 효과를 분석하였다. Abstract i List of Tables viii List of Figures x Nomenclatures xiv Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Research Scope and Overview 4 1.3 Dissertation Layout 7 Chapter 2 Literature Review 8 2.1 Life Prediction Methodologies of Steam Turbine 8 2.1.1 Destructive Method 11 2.1.2 Non-destructive Method 11 2.1.3 Analytical Method 13 2.1.4 Summary and Discussion 13 2.2 Data-driven and Model-based Life Prediction 15 2.2.1 Data-driven Approach 21 2.2.2 Model-based Approach 21 2.3 Empirical Model-based Life Prediction 15 2.3.1 On-site Data Measurement 18 2.3.2 Bayesian Inference 19 2.3.3 Summary and Discussion 20 2.4 Damage Model-based Life Prediction 21 2.4.1 Creep or Fatigue Damage Model Analysis 22 2.4.2 Creep-Fatigue Damage Summation Model analysis 23 2.4.3 Summary and Discussion 27 Chapter 3 A Practical RUL Prediction Framework of Steam Turbine with FMEA Analysis 28 3.1 Overview of Steam Turbines 28 3.2 FMEA for Steam Turbines 31 3.3 A Framework for RUL Prediction of Steam Turbine 34 3.4 Summay and Discussion 38 Chapter 4 A Bayesian Approach for RUL Prediction of Steam Turbines with Damage Growth Model 39 4.1 Characteristics of On-site Measurement Data 40 4.2 Measured Data based Damage Indices 46 4.3 Damage Growth Model using Sporadically Measured and Heterogeneous On-site Data 51 4.3.1 Proposed Damage Growth Model 51 4.3.2 Bayesian Updating Scheme of the Damage Growth Model 58 4.3.3 Damage Growth Model Updating 60 4.4 Predicting the Remaining Useful Life(RUL) of Steam Turbines 68 4.4.1 Damage Threshold 68 4.4.2 Validation of the Proposed Damage Growth Model 72 4.4.3 RUL Prediction 74 4.5 Summary and Discussion 78 Chapter 5 Mode-Dependent Damage Assessment for Steam Turbines with Creep-Fatigue Interaction Model 80 5.1 Dominant Damage Mechanisms of Steam Turbine 82 5.2 Typical Opeation Data of Steam Turbine 83 5.3 Dominant Damage Model of Steam Turbine 86 5.3.1 Creep Damage Model 86 5.3.2 Fatigue Damage Model 88 5.3.3 Creep-Fatigue Damage Model 90 5.4 Statiatical Damage Calculation for Steam Turbine 91 5.4.1 Statistical Characterization of Creep-Fatigue Damage Data 91 5.4.2 Creep Damage Calculation with Steady State Stress 94 5.4.3 Fatigue Damage Calculation with Transient Strain 95 5.5 Mode-Dependent Multiple Damage Interaction Model 100 5.5.1 Estimation of Damage Interaction Parameters 100 5.5.2 Validation of Mode-Dependent Model 101 5.5.3 Effect of Mode-dependence Effects on Multiple Damage 104 5.5.4 Case Study : Risk Assessment 108 5.6 Summary and Discussion 111 Chapter 6 Conclusions 113 6.1 Contributions and Impacts 113 6.2 Suggestions for Future Research 116 References 119 국문 초록 142Docto

Methods and Systems for Fault Diagnosis in Nuclear Power Plants

This research mainly deals with fault diagnosis in nuclear power plants (NPP), based on a framework that integrates contributions from fault scope identification, optimal sensor placement, sensor validation, equipment condition monitoring, and diagnostic reasoning based on pattern analysis. The research has a particular focus on applications where data collected from the existing SCADA (supervisory, control, and data acquisition) system is not sufficient for the fault diagnosis system. Specifically, the following methods and systems are developed. A sensor placement model is developed to guide optimal placement of sensors in NPPs. The model includes 1) a method to extract a quantitative fault-sensor incidence matrix for a system; 2) a fault diagnosability criterion based on the degree of singularities of the incidence matrix; and 3) procedures to place additional sensors to meet the diagnosability criterion. Usefulness of the proposed method is demonstrated on a nuclear power plant process control test facility (NPCTF). Experimental results show that three pairs of undiagnosable faults can be effectively distinguished with three additional sensors selected by the proposed model. A wireless sensor network (WSN) is designed and a prototype is implemented on the NPCTF. WSN is an effective tool to collect data for fault diagnosis, especially for systems where additional measurements are needed. The WSN has distributed data processing and information fusion for fault diagnosis. Experimental results on the NPCTF show that the WSN system can be used to diagnose all six fault scenarios considered for the system. A fault diagnosis method based on semi-supervised pattern classification is developed which requires significantly fewer training data than is typically required in existing fault diagnosis models. It is a promising tool for applications in NPPs, where it is usually difficult to obtain training data under fault conditions for a conventional fault diagnosis model. The proposed method has successfully diagnosed nine types of faults physically simulated on the NPCTF. For equipment condition monitoring, a modified S-transform (MST) algorithm is developed by using shaping functions, particularly sigmoid functions, to modify the window width of the existing standard S-transform. The MST can achieve superior time-frequency resolution for applications that involves non-stationary multi-modal signals, where classical methods may fail. Effectiveness of the proposed algorithm is demonstrated using a vibration test system as well as applications to detect a collapsed pipe support in the NPCTF. The experimental results show that by observing changes in time-frequency characteristics of vibration signals, one can effectively detect faults occurred in components of an industrial system. To ensure that a fault diagnosis system does not suffer from erroneous data, a fault detection and isolation (FDI) method based on kernel principal component analysis (KPCA) is extended for sensor validations, where sensor faults are detected and isolated from the reconstruction errors of a KPCA model. The method is validated using measurement data from a physical NPP. The NPCTF is designed and constructed in this research for experimental validations of fault diagnosis methods and systems. Faults can be physically simulated on the NPCTF. In addition, the NPCTF is designed to support systems based on different instrumentation and control technologies such as WSN and distributed control systems. The NPCTF has been successfully utilized to validate the algorithms and WSN system developed in this research. In a real world application, it is seldom the case that one single fault diagnostic scheme can meet all the requirements of a fault diagnostic system in a nuclear power. In fact, the values and performance of the diagnosis system can potentially be enhanced if some of the methods developed in this thesis can be integrated into a suite of diagnostic tools. In such an integrated system, WSN nodes can be used to collect additional data deemed necessary by sensor placement models. These data can be integrated with those from existing SCADA systems for more comprehensive fault diagnosis. An online performance monitoring system monitors the conditions of the equipment and provides key information for the tasks of condition-based maintenance. When a fault is detected, the measured data are subsequently acquired and analyzed by pattern classification models to identify the nature of the fault. By analyzing the symptoms of the fault, root causes of the fault can eventually be identified