- Library Home /
- Search Collections /
- Open Collections /
- Browse Collections /
- International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015) /
- Small-sample probabilistic simulation software tool...
Open Collections
International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)
Small-sample probabilistic simulation software tool FReET Novák, Drahomír; Vořechovský, Miroslav
Abstract
The objective of the paper is to present methods and software for the efficient statistical, sensitivity and reliability assessment of infrastructure. A special attention is devoted to small-sample simulation techniques which have been developed for the analysis of computationally intensive problems. The paper shows the possibility of "randomizing" computationally intensive problems in the sense of the Monte Carlo type simulation. In order to keep the number of required simulations at an acceptable level, optimized Latin Hypercube Sampling is utilized. The technique is used for simulation of random variables and random fields. Sensitivity analysis is based on nonparametric rank-order correlation coefficients. Statistical correlation is imposed by the stochastic optimization technique – simulated annealing. A hierarchical sampling approach has been developed for the extension of the sample size in Latin Hypercube Sampling, enabling the addition of simulations to a current sample set while maintaining the desired correlation structure. The paper continues with a brief description of the user-friendly implementation of the theory within FReET commercial multipurpose reliability software.
Item Metadata
Title |
Small-sample probabilistic simulation software tool FReET
|
Creator | |
Contributor | |
Date Issued |
2015-07
|
Description |
The objective of the paper is to present methods and software for the efficient statistical,
sensitivity and reliability assessment of infrastructure. A special attention is devoted to small-sample
simulation techniques which have been developed for the analysis of computationally intensive problems.
The paper shows the possibility of "randomizing" computationally intensive problems in the
sense of the Monte Carlo type simulation. In order to keep the number of required simulations at an
acceptable level, optimized Latin Hypercube Sampling is utilized. The technique is used for simulation
of random variables and random fields. Sensitivity analysis is based on nonparametric rank-order correlation
coefficients. Statistical correlation is imposed by the stochastic optimization technique – simulated
annealing. A hierarchical sampling approach has been developed for the extension of the sample
size in Latin Hypercube Sampling, enabling the addition of simulations to a current sample set while
maintaining the desired correlation structure. The paper continues with a brief description of the user-friendly
implementation of the theory within FReET commercial multipurpose reliability software.
|
Genre | |
Type | |
Language |
eng
|
Notes |
This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.
|
Date Available |
2015-05-26
|
Provider |
Vancouver : University of British Columbia Library
|
Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
|
DOI |
10.14288/1.0076194
|
URI | |
Affiliation | |
Citation |
Haukaas, T. (Ed.) (2015). Proceedings of the 12th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP12), Vancouver, Canada, July 12-15.
|
Peer Review Status |
Unreviewed
|
Scholarly Level |
Faculty
|
Rights URI | |
Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada