Reliability based design of engineering systems with monotonic models

M. Rajabalinejad, C. Spitas

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


A computationally efficient Bayesian Monte Carlo for Monotonic (BMCM) models for reliability based design of engineering systems is described in this paper. The model employs Gaussian distribution and monotonicity principles that have been implemented in the Dynamic Bounds (DB) method (Rajabalinejad 2009) integrated with a Bayesian Monte Carlo (BMC) technique. Signficant improvements in the computational speed of coupled DB and BMC methods are realized by incorporating a weighted logical dependence between neighboring points of the Limit-State Equation (LSE) as prior information and global uncertaintiy concept for quantifying variations of the controlling input variables. The outcomes of preceding simulations are factored in subsequent calculations to accelerate computing efficiency of the Monte Carlo method. The theory and numerical algorithms of the BMCM are described in this paper, and extension of the BMCM to multi-dimensional problems is provided.
Original languageEnglish
Title of host publicationAdvances in Safety, Reliability and Risk Management
Subtitle of host publicationESREL 2011
EditorsChristophe Berenguer, Antoine Grall, Carlos Guedes Soares
PublisherCRC Press (Taylor & Francis)
ISBN (Print)978-041568379-1
Publication statusPublished - 2011
EventEuropean Safety and Reliability Conference, ESREL 2011 - Troyes, France
Duration: 18 Sept 201122 Sept 2011


ConferenceEuropean Safety and Reliability Conference, ESREL 2011
Abbreviated titleESREL


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