Abstract
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 language | English |
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| Title of host publication | Advances in Safety, Reliability and Risk Management |
| Subtitle of host publication | ESREL 2011 |
| Editors | Christophe Berenguer, Antoine Grall, Carlos Guedes Soares |
| Publisher | CRC Press (Taylor & Francis) |
| Pages | 112-115 |
| ISBN (Print) | 978-041568379-1 |
| Publication status | Published - 2011 |
| Event | European Safety and Reliability Conference, ESREL 2011 - Troyes, France Duration: 18 Sept 2011 → 22 Sept 2011 |
Conference
| Conference | European Safety and Reliability Conference, ESREL 2011 |
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| Abbreviated title | ESREL |
| Country/Territory | France |
| City | Troyes |
| Period | 18/09/11 → 22/09/11 |