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Blind Predictions and Uncertainty in the Simulation of Reinforced Concrete Structures

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F28399269%3A_____%2F25%3AN0000017" target="_blank" >RIV/28399269:_____/25:N0000017 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi-org.ezproxy.techlib.cz/10.1002/cepa.3354" target="_blank" >https://doi-org.ezproxy.techlib.cz/10.1002/cepa.3354</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/cepa.3354" target="_blank" >10.1002/cepa.3354</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Blind Predictions and Uncertainty in the Simulation of Reinforced Concrete Structures

  • Original language description

    Nonlinear analysis of reinforced concrete structures is becoming a standard tool for both the assessment of existing structures and the design of new ones. This trend is supported by new safety formats for nonlinear analysis introduced in the fib Model Code 2010 and incorporated in the new Eurocode (prEN 1992-1-1:2022). A key challenge is the evaluation and management of uncertainties. This paper focuses on the model uncertainty in ultimate and serviceability limit states, including crack width estimation. The significant insights into modeling uncertainty are provided by the recent blind prediction competitions, which offer a practical benchmark for assessing the robustness and reliability of nonlinear models and software tools. This paper highlights the findings from several such competitions. A key limitation is that the material uncertainties are typically neglected, meaning that the most accurate predictions often result from a chance rather than from the consistently reliable modeling.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>ost</sub> - Miscellaneous article in a specialist periodical

  • CEP classification

  • OECD FORD branch

    20101 - Civil 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

    2025

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    ce/papers

  • ISSN

    2509-7075

  • e-ISSN

    2509-7075

  • Volume of the periodical

    Vol. 8

  • Issue of the periodical within the volume

    3-4

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    9

  • Pages from-to

    241 - 249

  • UT code for WoS article

  • EID of the result in the Scopus database