Reliability-Based Analysis of a Portuguese Concrete Arch Bridge Employing Surrogate Modeling Techniques Based on Adaptive Sequential Sampling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F26%3A0194172" target="_blank" >RIV/00216305:26110/26:0194172 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-031-80724-4_63" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-80724-4_63</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-80724-4_63" target="_blank" >10.1007/978-3-031-80724-4_63</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Reliability-Based Analysis of a Portuguese Concrete Arch Bridge Employing Surrogate Modeling Techniques Based on Adaptive Sequential Sampling

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 selecting possible future candidates in the input domain (i.e., random variables). In the present research, adaptive sequential sampling was employed to obtain the training experimental design from a set of random variables to develop a surrogate model capable of representing the failure limit of the asset under vertical traffic loads. The surrogate model was then used to obtain the failure probability of the case study, a single-span concrete arch bridge in Portugal. The resulting reliability index was compared with the outcomes obtained in previous research. Finally, by integrating novel sampling approaches a reduction in the computational cost associated with the reliability analysis and an overall better reliability of the surrogate model for evaluating the performance limit state was obtained.

Název v anglickém jazyce

Reliability-Based Analysis of a Portuguese Concrete Arch Bridge Employing Surrogate Modeling Techniques Based on Adaptive Sequential Sampling

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 selecting possible future candidates in the input domain (i.e., random variables). In the present research, adaptive sequential sampling was employed to obtain the training experimental design from a set of random variables to develop a surrogate model capable of representing the failure limit of the asset under vertical traffic loads. The surrogate model was then used to obtain the failure probability of the case study, a single-span concrete arch bridge in Portugal. The resulting reliability index was compared with the outcomes obtained in previous research. Finally, by integrating novel sampling approaches a reduction in the computational cost associated with the reliability analysis and an overall better reliability of the surrogate model for evaluating the performance limit state was obtained.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20100 - 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

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

4th fib International Conference on Concrete Sustainability (ICCS2024)

ISBN

978-3-031-80724-4

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

516-523

Název nakladatele

SPRINGER INTERNATIONAL PUBLISHING AG

Místo vydání

CHAM

Místo konání akce

Guimarães

Datum konání akce

11. 9. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001505314100063