Exploration of Adaptive Sequential Sampling in the Definition of Surrogate Models for the Rare Event Estimation in Transportation Assets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F24%3APU155253" target="_blank" >RIV/00216305:26110/24:PU155253 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-60271-9_34" target="_blank" >http://dx.doi.org/10.1007/978-3-031-60271-9_34</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-60271-9_34" target="_blank" >10.1007/978-3-031-60271-9_34</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Exploration of Adaptive Sequential Sampling in the Definition of Surrogate Models for the Rare Event Estimation in Transportation Assets

Popis výsledku v původním jazyce

Adaptive sequential sampling provides a good technique to refine and increase the accuracy of surrogate models, used for reliability analysis, based on the selection of possible future candidates in the input domain (i.e., random variables). In the present research, different methodologies for obtaining the training sample for a surrogate model were explored, considering sample size, distribution of the points, and identification of the failure region. The effects on the reliability of the slope stability under vertical loading based on the safety factors from Bishop's simplified method were obtained. The results reinforce the importance of the characteristics of the training sample used for the application of surrogate models to describe limit states and their accuracy when employed for the computation of the reliability index.

Název v anglickém jazyce

Exploration of Adaptive Sequential Sampling in the Definition of Surrogate Models for the Rare Event Estimation in Transportation Assets

Popis výsledku anglicky

Adaptive sequential sampling provides a good technique to refine and increase the accuracy of surrogate models, used for reliability analysis, based on the selection of possible future candidates in the input domain (i.e., random variables). In the present research, different methodologies for obtaining the training sample for a surrogate model were explored, considering sample size, distribution of the points, and identification of the failure region. The effects on the reliability of the slope stability under vertical loading based on the safety factors from Bishop's simplified method were obtained. The results reinforce the importance of the characteristics of the training sample used for the application of surrogate models to describe limit states and their accuracy when employed for the computation of the reliability index.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20101 - Civil engineering

Projekt

<a href="/cs/project/GF22-06684K" target="_blank" >GF22-06684K: Stochastická únava betonu řešená přístupy založenými na disipaci energie s ohledem na vzájemné působení časových a teplotních účinků</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

20th International Probabilistic Workshop IPW 2024, Lecture Notes in Civil Engineering 494

ISBN

978-3-031-60271-9

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

366-376

Název nakladatele

SPRINGER INTERNATIONAL PUBLISHING AG

Místo vydání

CHAM

Místo konání akce

Guimarães

Datum konání akce

8. 5. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001323733800036