Monte Carlo Simulation in Dependability Analysis Monte Carlo Simulation in Dependability Analysis
ISTE Invoiced

Monte Carlo Simulation in Dependability Analysis

Franck Bayle et autres
    • 134,99 €
    • 134,99 €

Description de l’éditeur

System dependability is a complex task to grasp and analyze since it encompasses reliability, maintainability, availability, failure mode analysis and feared events. For operational safety analyses, reliability is a quantitative basis for the other disciplines of maintainability, availability and safety. Reliability metrics such as failure rate or MTBF are often misused as they are only valid for low-maintenance applications, and wrongly for others, as MTBF is only relevant for availability. In addition, in operational safety, many equations do not have explicit solutions, and Monte Carlo simulations are a little-used way of obtaining and/or confirming the solution obtained by numerical methods.

Monte Carlo Simulation in Dependability Analysis fills this gap as best as we can. This task is a difficult one, since operational safety is a cross-disciplinary activity in the engineering sciences – cross-disciplinary in that it must be present throughout a product’s life cycle.

GENRE
Science et nature
SORTIE
2025
12 novembre
LANGUE
EN
Anglais
LONGUEUR
304
Pages
ÉDITIONS
Wiley
DÉTAILS DU FOURNISSEUR
John Wiley & Sons Ltd
TAILLE
51,1
Mo
Product Maturity, Volume 2 Product Maturity, Volume 2
2022
Product Maturity 1 Product Maturity 1
2022
Reliability of Maintained Systems Subjected to Wear Failure Mechanisms Reliability of Maintained Systems Subjected to Wear Failure Mechanisms
2019
Geopolitics and Energy Transition 1 Geopolitics and Energy Transition 1
2024
Cybersecurity and Traceability in Factory 4.0 Cybersecurity and Traceability in Factory 4.0
2026
Tourism and Gastronomy Tourism and Gastronomy
2026
History of Earth Sciences History of Earth Sciences
2026
Finite Element Thermography Finite Element Thermography
2026
Artificial Intelligence for Sustainable Energy Systems 1 Artificial Intelligence for Sustainable Energy Systems 1
2026