Foreword; Preface; Contents; Part I: Fundamentals of Simulation in Reliability and Availability Issues; Chapter 1: Reliability Estimation by Advanced Monte Carlo Simulation; 1.1 Introduction; 1.2 Simulation Methods Implemented in this Study; 1.2.1 The Subset Simulation Method; 1.2.2 The Line Sampling Method; 1.3 Simulation Methods Considered for Comparison; 1.3.1 The Importance Sampling Method; 1.3.2 The Dimensionality Reduction Method; 1.3.3 The Orthogonal Axis Method; 1.4 Application 1: the Cracked-plate Model; 1.4.1 The Mechanical Model; 1.4.2 The Structural Reliability Model.
Text of Note
1.4.3 Case Studies1.4.4 Results; 1.5 Application 2: Thermal-fatigue Crack Growth Model; 1.5.1 The Mechanical Model; 1.5.2 The Structural Reliability Model; 1.5.3 Case Studies; 1.5.4 Results; 1.6 Summary and Critical Discussion of the Techniques; Appendix 1. Markov Chain Monte Carlo Simulation; Appendix 2. The Line Sampling Algorithm; References; Chapter 2: Dynamic Fault Tree Analysis: Simulation Approach; 2.1 Fault Tree Analysis: Static Versus Dynamic; 2.2 Dynamic Fault Tree Gates; 2.3 Effect of Static Gate Representation in Place of Dynamic Gates; 2.4 Solving Dynamic Fault Trees.
Text of Note
2.5 Modular Solution for Dynamic Fault Trees2.6 Numerical Method; 2.6.1 PAND Gate; 2.6.2 SEQ Gate; 2.6.3 SPARE Gate; 2.7 Monte Carlo Simulation Approach for Solving Dynamic Fault Trees; 2.7.1 PAND Gate; 2.7.2 SPARE Gate; 2.7.3 FDEP Gate; 2.7.4 SEQ Gate; 2.8 Example 1: Simplified Electrical (AC) Power Supply System of Typical Nuclear Power Plant; 2.8.1 Solution with Analytical Approach; 2.8.2 Solution with Monte Carlo Simulation; 2.9 Example 2: Reactor Regulation System of a Nuclear Power Plant; 2.9.1 Dynamic Fault Tree Modeling; 2.10 Summary; References.
Text of Note
4.1.1 Density-based Methods4.1.2 Hazard-based Methods; 4.2 Generating Stochastic Processes; 4.2.1 Counting Processes; 4.2.2 Poisson Processes; 4.2.3 Renewal Processes; 4.2.4 Alternating Renewal Processes; 4.2.5 Nonhomogeneous Poisson Processes; 4.2.6 Markov Models; 4.2.7 Other Variants; 4.2.8 Random Process Generation; 4.3 Survival Models Involving Covariates; 4.3.1 Accelerated Life Model; 4.3.2 Proportional Hazards Model; 4.3.3 Random Lifetime Generation; 4.4 Conclusions and Further Reading; References; Part II: Simulation Applications in Reliability.
Text of Note
Chapter 3: Analysis and Improvements of Path-based Methods for Monte Carlo Reliability Evaluation of Static Models3.1 Introduction; 3.2 Standard Monte Carlo Reliability Evaluation; 3.3 A Path-based Approach; 3.4 Robustness Analysis of the Algorithm; 3.5 Improvement; 3.6 Acceleration by Randomized Quasi-Monte Carlo; 3.6.1 Quasi-Monte Carlo Methods; 3.6.2 Randomized Quasi-Monte Carlo Methods; 3.6.3 Application to Our Static Reliability Problem; 3.6.4 Numerical Results; 3.7 Conclusions; References; Chapter 4: Variate Generation in Reliability; 4.1 Generating Random Lifetimes.
0
8
8
8
8
SUMMARY OR ABSTRACT
Text of Note
Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life s.
ACQUISITION INFORMATION NOTE
Source for Acquisition/Subscription Address
Springer
Stock Number
978-1-84882-212-2
OTHER EDITION IN ANOTHER MEDIUM
Title
Simulation methods for reliability and availability of complex systems.