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Reliability (Engineering) --- Risk assessment --- Fiabilité --- Evaluation du risque --- Computer simulation --- Simulation par ordinateur --- Statistical methods. --- Fiabilité --- Computer simulation.
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Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.
Monte Carlo method. --- Reliability (Engineering) -- Simulation methods. --- Risk analysis. --- Engineering & Applied Sciences --- Mechanical Engineering --- Civil & Environmental Engineering --- Industrial & Management Engineering --- Applied Mathematics --- Civil Engineering --- Reliability (Engineering) --- Reliability of equipment --- Systems reliability --- Artificial sampling --- Model sampling --- Monte Carlo simulation --- Monte Carlo simulation method --- Stochastic sampling --- Simulation methods. --- Engineering. --- Computer mathematics. --- Probabilities. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Computational Science and Engineering. --- Probability Theory and Stochastic Processes. --- Engineering --- Maintainability (Engineering) --- Probabilities --- Systems engineering --- Plant performance --- Safety factor in engineering --- Structural failures --- Games of chance (Mathematics) --- Mathematical models --- Numerical analysis --- Numerical calculations --- Stochastic processes --- Computer science. --- Distribution (Probability theory. --- Mathematical and Computational Engineering. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Informatics --- Science --- Engineering analysis --- Mathematical analysis --- Mathematics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Computer mathematics --- Electronic data processing
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Reliability (Engineering). --- Risk assessment. --- Reliability (Engineering) --- Risk assessment --- Fiabilité --- Evaluation du risque --- International financial management
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The necessity of expertise for tackling the complicated and multidisciplinary issues of safety and risk has slowly permeated into all engineering applications so that risk analysis and management has gained a relevant role, both as a tool in support of plant design and as an indispensable means for emergency planning in accidental situations. This entails the acquisition of appropriate reliability modeling and risk analysis tools to complement the basic and specific engineering knowledge for the technological area of application. Aimed at providing an organic view of the subject, this book pro
Reliability (Engineering) --- Risk assessment. --- Reliability of equipment --- Systems reliability --- Engineering --- Maintainability (Engineering) --- Probabilities --- Systems engineering --- Plant performance --- Safety factor in engineering --- Structural failures --- Analysis, Risk --- Assessment, Risk --- Risk analysis --- Risk evaluation --- Evaluation
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Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.
Operational research. Game theory --- Probability theory --- Mathematics --- Applied physical engineering --- Engineering sciences. Technology --- Computer science --- analyse (wiskunde) --- waarschijnlijkheidstheorie --- stochastische analyse --- computers --- economie --- informatica --- wiskunde --- informaticaonderzoek --- ingenieurswetenschappen --- kansrekening --- computerkunde
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Electricity --- Applied physical engineering --- Production management --- Mass communications --- Computer science --- Equipment, services, installations in buildings --- elektrische netwerken --- informatica --- kwaliteitscontrole --- communicatietechnologie --- elektrische machines --- elektriciteitsdistributie
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International financial management --- Reliability (Engineering) --- Risk assessment. --- Risk assessment --- Fiabilité --- Evaluation du risque --- Problems, exercises, etc. --- Problèmes et exercices --- Reliability (Engineering). --- Fiabilité --- Problèmes et exercices
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The safe management of the complex distributed systems and critical infrastructures which constitute the backbone of modern industry and society entails identifying and quantifying their vulnerabilities to design adequate protection, mitigation, and emergency action against failure. In practice, there is no fail-safe solution to such problems and various frameworks are being proposed to effectively integrate different methods of complex systems analysis in a problem-driven approach to their solution. Vulnerable Systems reflects the current state of knowledge on the procedures which are being put forward for the risk and vulnerability analysis of critical infrastructures. Classical methods of reliability and risk analysis, as well as new paradigms based on network and systems theory, including simulation, are considered in a dynamic and holistic way. Readers of Vulnerable Systems will benefit from its structured presentation of the current knowledge base on this subject. It will enable graduate students, researchers and safety and risk analysts to understand the methods suitable for different phases of analysis and to identify their criticalities in application.
Infrastructure (Economics). --- Social capital (Sociology). --- Technology assessment -- United States. --- Infrastructure (Economics) --- Public works --- National security --- System analysis --- Engineering & Applied Sciences --- Chemical & Materials Engineering --- Business & Economics --- Mechanical Engineering --- Economic History --- Technology - General --- Industrial & Management Engineering --- Materials Science --- Risk assessment --- Security measures --- Quality control. --- Engineering. --- Complexity, Computational. --- Reliability. --- Industrial safety. --- Electrical engineering. --- Power electronics. --- Quality Control, Reliability, Safety and Risk. --- Complexity. --- Power Electronics, Electrical Machines and Networks. --- Communications Engineering, Networks. --- Factory management --- Industrial engineering --- Reliability (Engineering) --- Sampling (Statistics) --- Standardization --- Quality assurance --- Quality of products --- System safety. --- Production of electric energy or. --- Telecommunication. --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Construction --- Industrial arts --- Technology --- Safety, System --- Safety of systems --- Systems safety --- Accidents --- Industrial safety --- Systems engineering --- Prevention --- Computational complexity. --- Complexity, Computational --- Electronic data processing --- Machine theory --- Industrial accidents --- Industries --- Job safety --- Occupational hazards, Prevention of --- Occupational health and safety --- Occupational safety and health --- Prevention of industrial accidents --- Prevention of occupational hazards --- Safety, Industrial --- Safety engineering --- Safety measures --- Safety of workers --- System safety --- Dependability --- Trustworthiness --- Conduct of life --- Electric engineering --- Engineering --- Electronics, Power --- Electric power --- Electronics
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