Investigation of reliability method formulations in Dakota/UQ.
- The University of Notre Dame, Notre Dame, IN
Reliability methods are probabilistic algorithms for quantifying the effect of simulation input uncertainties on response metrics of interest. In particular, they compute approximate response function distribution statistics (probability, reliability and response levels) based on specified input random variable probability distributions. In this paper, a number of algorithmic variations are explored for both the forward reliability analysis of computing probabilities for specified response levels (the reliability index approach (RIA)) and the inverse reliability analysis of computing response levels for specified probabilities (the performance measure approach (PMA)). These variations include limit state linearizations, probability integrations, warm starting and optimization algorithm selections. The resulting RIA/PMA reliability algorithms for uncertainty quantification are then employed within bi-level and sequential reliability-based design optimization approaches. Relative performance of these uncertainty quantification and reliability-based design optimization algorithms are presented for a number of computational experiments performed using the DAKOTA/UQ software.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 961638
- Report Number(s):
- SAND2004-3218J
- Journal Information:
- Proposed for publication in Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance., Journal Name: Proposed for publication in Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance. Journal Issue: 3 Vol. 3
- Country of Publication:
- United States
- Language:
- English
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