. . . . "P(GAP105/12/1146), S" . . "978-80-214-4871-1" . . "Svratka" . . . . "Meta-models (or surrogate models, formerly response surfaces) are getting popular in engineering designs. They are used to simulate the behaviour of structures with less computational demands than the original model (e.g. finite element models). It is still necessary to evaluate this expensive original model few times in some specified points called Design of Experiments (DoE). The first DoE is usually just space-filling to cover up the whole design space and the meta-model built with an initial DoE is therefore not very accurate everywhere. Other points are added to the meta-model to improve accuracy at important regions. In this paper, various updates of meta-models are reviewed from different points of view. Unfortunately, there is a distinction between updates even in reliability assessment and reliability-based design optimization research areas."@en . "Adaptive update of surrogate models for reliability-based design optimization: A review"@en . "2"^^ . "Posp\u00ED\u0161ilov\u00E1, Ad\u00E9la" . . . "21110" . "2"^^ . "Lep\u0161, Mat\u011Bj" . "1610" . "[51D2580003C9]" . "Adaptive update of surrogate models for reliability-based design optimization: A review" . "Adaptive update of surrogate models for reliability-based design optimization: A review"@en . . . "Vysok\u00E9 u\u010Den\u00ED technick\u00E9 v Brn\u011B" . . . "Surrogate models; Adaptive update; Reliability-based design optimization; Design of Experiments"@en . "Adaptive update of surrogate models for reliability-based design optimization: A review" . "RIV/68407700:21110/14:00217846" . . "2014-05-12+02:00"^^ . "20 th International Conference Engineering Mechanics 2014" . "RIV/68407700:21110/14:00217846!RIV15-MSM-21110___" . "4"^^ . . . "Meta-models (or surrogate models, formerly response surfaces) are getting popular in engineering designs. They are used to simulate the behaviour of structures with less computational demands than the original model (e.g. finite element models). It is still necessary to evaluate this expensive original model few times in some specified points called Design of Experiments (DoE). The first DoE is usually just space-filling to cover up the whole design space and the meta-model built with an initial DoE is therefore not very accurate everywhere. Other points are added to the meta-model to improve accuracy at important regions. In this paper, various updates of meta-models are reviewed from different points of view. Unfortunately, there is a distinction between updates even in reliability assessment and reliability-based design optimization research areas." . "1805-8248" . "Brno" . .