dc.contributor.author | Krejsa, Martin | |
dc.contributor.author | Králik, Juraj | |
dc.date.accessioned | 2017-10-20T11:50:21Z | |
dc.date.available | 2017-10-20T11:50:21Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Journal of Multiscale Modelling. 2015, vol. 6, issue 3, art. no. 1550006. | cs |
dc.identifier.issn | 1756-9737 | |
dc.identifier.issn | 1756-9745 | |
dc.identifier.uri | http://hdl.handle.net/10084/120682 | |
dc.description.abstract | Probabilistic methods are used in engineering where a computational model contains random variables. Each random variable in the probabilistic calculations contains uncertainties. Typical sources of uncertainties are properties of the material and production and/or assembly inaccuracies in the geometry or the environment where the structure should be located. The paper is focused on methods for the calculations of failure probabilities in structural failure and reliability analysis with special attention on newly developed probabilistic method: Direct Optimized Probabilistic Calculation (DOProC), which is highly efficient in terms of calculation time and the accuracy of the solution. The novelty of the proposed method lies in an optimized numerical integration that does not require any simulation technique. The algorithm has been implemented in mentioned software applications, and has been used several times in probabilistic tasks and probabilistic reliability assessments. | cs |
dc.language.iso | en | cs |
dc.publisher | World Scientific Publishing | cs |
dc.relation.ispartofseries | Journal of Multiscale Modelling | cs |
dc.relation.uri | https://doi.org/10.1142/S1756973715500067 | cs |
dc.subject | probabilistic methods | cs |
dc.subject | reliability assessment | cs |
dc.subject | random variable | cs |
dc.subject | probability of failure | cs |
dc.subject | Direct Optimized Probabilistic Calculation (DOProC) | cs |
dc.title | Probabilistic computational methods in structural failure analysis | cs |
dc.type | article | cs |
dc.identifier.doi | 10.1142/S1756973715500067 | |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 6 | cs |
dc.description.issue | 3 | cs |
dc.description.firstpage | art. no. 1550006 | cs |
dc.identifier.wos | 000216891300001 | |