Reliability of Nuclear Power Plants

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.

Foreword by Philippe Le Poac xi

Foreword by Antoine Grall xvii

Preface xxi

André Lannoy

Acknowledgments xxiii

André Lannoy

Author Biographies xxv

Chapter 1 Aims and Introduction 1

André Lannoy

1.1 The aims of this work 1

1.2 Reliability, an application of probability theory 2

1.2.1 What is reliability? 2

1.2.2 The early days of reliability 3

1.2.3 The birth of modern reliability 5

1.2.4 The development of modern reliability 1948–1960 5

1.2.5 The advent of reliability specialists 1960–1974 6

1.2.6 The “safety culture decade” 1975–1990 7

1.2.7 Maximizing efficiency, performances and profits 1990–2007 8

1.2.8 The return to safety, risk aversion 2007–2020 9

1.3 Generating nuclear power 10

1.4 Presentation of the book’s content 15

1.5 References 17

Chapter 2 Input Data: Operation Feedback and Expertise 21

André Lannoy and Emmanuel Remy

2.1 The purposes of operation feedback 21

2.2 What is operation feedback? 23

2.3 The operation feedback approach 25

2.4 “Event” operation feedback 28

2.5 “Equipment” operation feedback 29

2.5.1 The maintenance model: an approach according to function 29

2.5.2 Failure analysis 31

2.5.3 Failure criteria 33

2.5.4 Data quality 33

2.6 Reliability analysis 35

2.6.1 The components studied 35

2.6.2 Data characteristics 36

2.6.3 Principles of simple reliability data estimation for PSAs 38

2.7 Conclusion 39

2.8 References 41

Chapter 3 The Principles of Calculating Reliability in Level 1 PSAs 43

Marc Bouissou

3.1 Introduction 43

3.2 The basis of all calculations: an exponential approximation 45

3.2.1 The principle of exponential approximations 45

3.2.2 NRI exponential approximation 46

3.3 The models used 48

3.3.1 Event trees 48

3.3.2 Fault trees 51

3.4 Quantification of PSAs 54

3.4.1 Calculating the probability of UCs that are conditional on an initiator 55

3.4.2 Calculating importance factors 57

3.4.3 The uncertainty calculation 59

3.5 The question of the level of detail 60

3.6 Practical problems: model size, high probabilities 62

3.6.1 Model size and combinatorial explosion 63

3.6.2 Fire, flood and earthquake PSAs: the problem of high probabilities 64

3.7 “Cousin” models of PSA models 65

3.7.1 Event sequence diagrams 65

3.7.2 Bow tie diagram 66

3.7.3 Boolean logic-driven Markov processes 66

3.8 How can we improve the precision of classic PSAs? 70

3.8.1 Principles of the I&AB method 70

3.8.2 What gains does I&AB allow? 71

3.8.3 Numerical application of I&AB 72

3.9 A line of research: “dynamic PSAs” 75

3.10 Software for carrying out PSAs 76

3.11 References 78

Chapter 4 Structural Reliability: General Presentation, Applications for Nuclear Power Plants 83

Emmanuel Ardillon

4.1 General presentation of SRA 83

4.1.1 Why SRA? 83

4.1.2 What does SRA consist of? 86

4.1.3 Old foundations but a recent history 87

4.1.4 SRA: from the R-S elementary case (resistance-stress method) to the general case 88

4.1.5 A brief overview of calculation methods 90

4.1.6 OpenTURNS: the processing tool for uncertainty quantifications co-developed and used at EDF 95

4.2 Structural reliability in the nuclear power generation industry 97

4.2.1 Optimizing the maintenance policy for steam generators 98

4.2.2 Risk of fast fracture of PWR reactor pressure vessels 98

4.3 The pressurizer, an example of an exploratory exercise in the application of probabilistic approaches 100

4.4 Probabilistic optimization of the maintenance of nuclear power plant steel components 102

4.4.1 Introduction 102

4.4.2 Specifying the problem (stage A) 103

4.4.3 Uncertainty quantification (stage B) 105

4.4.4 Uncertainty propagation: calculating the overall risk of thinning points (stage C) 106

4.4.5 Using probabilistic results: determining points to repair 107

4.4.6 Conclusion and perspectives on this application 108

4.5 Structural reliability for hydroelectricity – the reliability of penstocks: evaluation of calculation values for mechanical strength diagnostics 110

4.6 Conclusion 112

4.7 References 113

Chapter 5 Probabilistic and Statistical Modeling for the Reliability of Industrial Equipment 117

Emmanuel Remy

5.1 Introduction 117

5.2 Some general preliminary remarks 118

5.3 Nonparametric approaches 124

5.4 Parametric models 126

5.4.1 Introduction 126

5.4.2 Some models adapted to non-repairable components 127

5.4.3 Taking account of influencing factors 132

5.4.4 Imperfect maintenance models for repairable equipment 135

5.4.5 Stochastic degradation models 140

5.5 Frequentist inference 147

5.6 Bayesian statistics 153

5.7 Model validation and selection 157

5.8 Case study for illustration 160

5.9 Openings and prospects for R&D 163

5.10 Software tools 164

5.11 References 164

Chapter 6 The Human and Organizational Dimensions of Reliability and Nuclear Safety 171

Nicolas Dechy, Yves Dien And Jean-François Vautier

6.1 Introduction and historical context in the nuclear field 171

6.2 Definition of the human and organizational dimensions of dependability and nuclear safety 173

6.3 Theories on accidents and reliability 175

6.4 Human and social sciences methods for collecting and analyzing data 181

6.5 Making human activities reliable 183

6.5.1 “Human error”: man is a fallible reliability agent 183

6.5.2 Training 185

6.5.3 Applying the procedure or demonstrating skills? 187

6.5.4 Analyzing real activity and work situations 188

6.5.5 Man–machine interfaces: the case of control rooms 189

6.5.6 Consideration of HOFs during design and modifications 190

6.5.7 Operation actions and their feasibility 191

6.5.8 Quantitative approach to human reliability 192

6.5.9 HF in maintenance interventions 193

6.6 Making the organization of work and risk management reliable 194

6.6.1 Quality approach and safety management systems 195

6.6.2 Safety culture 196

6.6.3 Forward planning of skills and workforce – human resources management 197

6.6.4 Managing safety on a daily basis and decision-making 198

6.6.5 Risk analysis, anticipation 199

6.6.6 Adaptation, resilience, emergency and crisis 201

6.6.7 Event analysis and the operating experience feedback process 202

6.6.8 Conducting organizational change 203

6.6.9 Organizing maintenance and subcontractors’ work 204

6.7 Cross-cutting aspects 206

6.7.1 The challenges of integration, organization and time 206

6.7.2 The contribution of the systemic approach 207

6.7.3 Reflexivity and critical approach 209

6.7.4 HOF specialists and HOF relays: the contribution of HOF networks 209

6.8 Conclusion and perspectives 210

6.9 References 211

Chapter 7 From Too Little to Too Much: The Impact of Big Data 225

André Lannoy and Emmanuel Remy

7.1 Introduction 225

7.2 Toward a better understanding? 227

7.2.1 New ways of collecting operation feedback 227

7.2.2 The importance of pre-processing and validation 229

7.2.3 A more accurate vision of the usage profile 230

7.2.4 Toward big data methods 231

7.2.5 Reliability approaches 232

7.2.6 A posteriori processing or visualization 236

7.3 Diagnostics and prognostics 236

7.3.1 Diagnostics 236

7.3.2 The prognostics 238

7.3.3 Classical reliability models for prognostics 239

7.4 Trust 240

7.5 Conclusion and perspectives 241

7.6 References 242

Chapter 8 Conclusions and Prospects 245

André Lannoy

8.1 Nuclear power plants and the progress of reliability 246

8.2 Challenges linked to reliability? 248

8.3 Prospects for future 249

8.3.1 Operational feedback data and data quality 249

8.3.2 On system reliability 250

8.3.3 On the reliability of structures 251

8.3.4 On data from big data and the reliability of equipment 252

8.3.5 On the reliability of organizations and activities 253

8.4 References 255

List of Authors 257

Index 259