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Resistance Model Uncertainty in Non-Linear Numerical Analyses of Ultra-High-Performance Reinforced Concrete Beams in Flexure

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21610%2F24%3A00378077" target="_blank" >RIV/68407700:21610/24:00378077 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.ctresources.info/ccc/pub.html?f=v9cst24" target="_blank" >https://www.ctresources.info/ccc/pub.html?f=v9cst24</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.4203/ccc.9.9.3" target="_blank" >10.4203/ccc.9.9.3</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Resistance Model Uncertainty in Non-Linear Numerical Analyses of Ultra-High-Performance Reinforced Concrete Beams in Flexure

  • Original language description

    This study presents the bending resistance model uncertainty and corresponding partial factors when performing a design or an assessment of ultra-high-performance reinforced concrete (UHPC) beams via non-linear finite element analyses (NLFEA). UHPC beams that have been both experimentally tested and simulated via NLFEA are considered, as documented in the literature, treating each source as presenting a unique modelling hypothesis of the beams' bending behaviour. A probabilistic analysis through Bayesian updating processes these uncertainties, updating prior distributions of resistance model uncertainty with data from various modelling hypothesis to estimate posterior distributions and the final average posterior distribution. The coefficient of variation and mean value of the average posterior distribution is used to calibrate corresponding partial factors in accordance with the the global safety format for NLFEAs proposed by codes and literature.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20102 - Construction engineering, Municipal and structural engineering

Result continuities

  • Project

    <a href="/en/project/GA24-10892S" target="_blank" >GA24-10892S: Machine Learning for Multiscale Modelling of Spatial Variability and Fracture for Sustainable Concrete Structures</a><br>

  • Continuities

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

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the Fifteenth International Conference on Computational Structures Technology

  • ISBN

  • ISSN

    2753-3239

  • e-ISSN

    2753-3239

  • Number of pages

    11

  • Pages from-to

  • Publisher name

    Civil-Comp Press

  • Place of publication

    Edinburgh

  • Event location

    Praha

  • Event date

    Sep 4, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article