Reliability of Nuclear Power Plants: Methods, Data and Applications

ISBN-13: 9781786307613 / Angielski / Twarda / 2022 / 304 str.

Lannoy

Spis treści

Foreword by Philippe Le Poac xiForeword by Antoine Grall xviiPreface xxiAndré LannoyAcknowledgments xxiiiAndré LannoyAuthor Biographies xxvChapter 1 Aims and Introduction 1André Lannoy1.1 The aims of this work 11.2 Reliability, an application of probability theory 21.2.1 What is reliability? 21.2.2 The early days of reliability 31.2.3 The birth of modern reliability 51.2.4 The development of modern reliability 1948-1960 51.2.5 The advent of reliability specialists 1960-1974 61.2.6 The "safety culture decade" 1975-1990 71.2.7 Maximizing efficiency, performances and profits 1990-2007 81.2.8 The return to safety, risk aversion 2007-2020 91.3 Generating nuclear power 101.4 Presentation of the book's content 151.5 References 17Chapter 2 Input Data: Operation Feedback and Expertise 21André Lannoy and Emmanuel Remy2.1 The purposes of operation feedback 212.2 What is operation feedback? 232.3 The operation feedback approach 252.4 "Event" operation feedback 282.5 "Equipment" operation feedback 292.5.1 The maintenance model: an approach according to function 292.5.2 Failure analysis 312.5.3 Failure criteria 332.5.4 Data quality 332.6 Reliability analysis 352.6.1 The components studied 352.6.2 Data characteristics 362.6.3 Principles of simple reliability data estimation for PSAs 382.7 Conclusion 392.8 References 41Chapter 3 The Principles of Calculating Reliability in Level 1 PSAs 43Marc Bouissou3.1 Introduction 433.2 The basis of all calculations: an exponential approximation 453.2.1 The principle of exponential approximations 453.2.2 NRI exponential approximation 463.3 The models used 483.3.1 Event trees 483.3.2 Fault trees 513.4 Quantification of PSAs 543.4.1 Calculating the probability of UCs that are conditional on an initiator 553.4.2 Calculating importance factors 573.4.3 The uncertainty calculation 593.5 The question of the level of detail 603.6 Practical problems: model size, high probabilities 623.6.1 Model size and combinatorial explosion 633.6.2 Fire, flood and earthquake PSAs: the problem of high probabilities 643.7 "Cousin" models of PSA models 653.7.1 Event sequence diagrams 653.7.2 Bow tie diagram 663.7.3 Boolean logic-driven Markov processes 663.8 How can we improve the precision of classic PSAs? 703.8.1 Principles of the I&AB method 703.8.2 What gains does I&AB allow? 713.8.3 Numerical application of I&AB 723.9 A line of research: "dynamic PSAs" 753.10 Software for carrying out PSAs 763.11 References 78Chapter 4 Structural Reliability: General Presentation, Applications for Nuclear Power Plants 83Emmanuel Ardillon4.1 General presentation of SRA 834.1.1 Why SRA? 834.1.2 What does SRA consist of? 864.1.3 Old foundations but a recent history 874.1.4 SRA: from the R-S elementary case (resistance-stress method) to the general case 884.1.5 A brief overview of calculation methods 904.1.6 OpenTURNS: the processing tool for uncertainty quantifications co-developed and used at EDF 954.2 Structural reliability in the nuclear power generation industry 974.2.1 Optimizing the maintenance policy for steam generators 984.2.2 Risk of fast fracture of PWR reactor pressure vessels 984.3 The pressurizer, an example of an exploratory exercise in the application of probabilistic approaches 1004.4 Probabilistic optimization of the maintenance of nuclear power plant steel components 1024.4.1 Introduction 1024.4.2 Specifying the problem (stage A) 1034.4.3 Uncertainty quantification (stage B) 1054.4.4 Uncertainty propagation: calculating the overall risk of thinning points (stage C) 1064.4.5 Using probabilistic results: determining points to repair 1074.4.6 Conclusion and perspectives on this application 1084.5 Structural reliability for hydroelectricity - the reliability of penstocks: evaluation of calculation values for mechanical strength diagnostics 1104.6 Conclusion 1124.7 References 113Chapter 5 Probabilistic and Statistical Modeling for the Reliability of Industrial Equipment 117Emmanuel Remy5.1 Introduction 1175.2 Some general preliminary remarks 1185.3 Nonparametric approaches 1245.4 Parametric models 1265.4.1 Introduction 1265.4.2 Some models adapted to non-repairable components 1275.4.3 Taking account of influencing factors 1325.4.4 Imperfect maintenance models for repairable equipment 1355.4.5 Stochastic degradation models 1405.5 Frequentist inference 1475.6 Bayesian statistics 1535.7 Model validation and selection 1575.8 Case study for illustration 1605.9 Openings and prospects for R&D 1635.10 Software tools 1645.11 References 164Chapter 6 The Human and Organizational Dimensions of Reliability and Nuclear Safety 171Nicolas Dechy, Yves Dien And Jean-François Vautier6.1 Introduction and historical context in the nuclear field 1716.2 Definition of the human and organizational dimensions of dependability and nuclear safety 1736.3 Theories on accidents and reliability 1756.4 Human and social sciences methods for collecting and analyzing data 1816.5 Making human activities reliable 1836.5.1 "Human error": man is a fallible reliability agent 1836.5.2 Training 1856.5.3 Applying the procedure or demonstrating skills? 1876.5.4 Analyzing real activity and work situations 1886.5.5 Man-machine interfaces: the case of control rooms 1896.5.6 Consideration of HOFs during design and modifications 1906.5.7 Operation actions and their feasibility 1916.5.8 Quantitative approach to human reliability 1926.5.9 HF in maintenance interventions 1936.6 Making the organization of work and risk management reliable 1946.6.1 Quality approach and safety management systems 1956.6.2 Safety culture 1966.6.3 Forward planning of skills and workforce - human resources management 1976.6.4 Managing safety on a daily basis and decision-making 1986.6.5 Risk analysis, anticipation 1996.6.6 Adaptation, resilience, emergency and crisis 2016.6.7 Event analysis and the operating experience feedback process 2026.6.8 Conducting organizational change 2036.6.9 Organizing maintenance and subcontractors' work 2046.7 Cross-cutting aspects 2066.7.1 The challenges of integration, organization and time 2066.7.2 The contribution of the systemic approach 2076.7.3 Reflexivity and critical approach 2096.7.4 HOF specialists and HOF relays: the contribution of HOF networks 2096.8 Conclusion and perspectives 2106.9 References 211Chapter 7 From Too Little to Too Much: The Impact of Big Data 225André Lannoy and Emmanuel Remy7.1 Introduction 2257.2 Toward a better understanding? 2277.2.1 New ways of collecting operation feedback 2277.2.2 The importance of pre-processing and validation 2297.2.3 A more accurate vision of the usage profile 2307.2.4 Toward big data methods 2317.2.5 Reliability approaches 2327.2.6 A posteriori processing or visualization 2367.3 Diagnostics and prognostics 2367.3.1 Diagnostics 2367.3.2 The prognostics 2387.3.3 Classical reliability models for prognostics 2397.4 Trust 2407.5 Conclusion and perspectives 2417.6 References 242Chapter 8 Conclusions and Prospects 245André Lannoy8.1 Nuclear power plants and the progress of reliability 2468.2 Challenges linked to reliability? 2488.3 Prospects for future 2498.3.1 Operational feedback data and data quality 2498.3.2 On system reliability 2508.3.3 On the reliability of structures 2518.3.4 On data from big data and the reliability of equipment 2528.3.5 On the reliability of organizations and activities 2538.4 References 255List of Authors 257Index 259

O autorze

Andre Lannoy is an engineer-researcher, doctor in detonics, former scientific advisor at EDF R&D and author or co-author of many books, articles and communications. He also chairs the IMdR (Institut pour la Maîtrise des Risques) product commission, France, and is an honorary member of the European Safety, Reliability & Data Association.