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NOVÁK, D. SLOWIK, O. NOVÁK, L. STRAUSS, A. LEHKÝ, D.
Originální název
Statistical and sensitivity analyses of prestressed concrete girders failing in shear
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
A complex approach to probabilistic analysis and design of precast pre-stressed concrete girders failing in shear is presented. Experimental studies have been performed on full scale prestressed concrete roof elements and scaled laboratory tested elements, they served as basis for deterministic nonlinear modelling with model updating of precast members and subsequent probabilistic evaluation of structural response variability. The results are used as thresholds for loading of produced structural elements and probabilistic design procedure as less conservative method compared to classical partial safety factor based design and alternative ECOV method. An important task in structural reliability analysis is to determine the significance of basic random variables. Two alternative approaches are utilized: Nonparametric rank-order sensitivity and analysis based on partial coefficient of variation. These methods were applied and compared for precast prestressed concrete girders. Such an information was used for proper set up of stochastic model and response surfaces and subsequent determination of selected uncertain design parameters followed by load-bearing capacity and reliability assessment.
Klíčová slova
Shear failure, pre-stressed girder, safety factors, ECoV method, nonparametric sensitivity
Autoři
NOVÁK, D.; SLOWIK, O.; NOVÁK, L.; STRAUSS, A.; LEHKÝ, D.
Vydáno
6. 8. 2017
ISBN
978-3-903024-28-1
Kniha
12th International Conference on Structural Safety & Reliability (ICOSSAR 2017)
Strany od
1793
Strany do
1802
Strany počet
10
BibTex
@inproceedings{BUT142539, author="Drahomír {Novák} and Ondřej {Slowik} and Lukáš {Novák} and Alfred {Strauss} and David {Lehký}", title="Statistical and sensitivity analyses of prestressed concrete girders failing in shear", booktitle="12th International Conference on Structural Safety & Reliability (ICOSSAR 2017)", year="2017", pages="1793--1802", isbn="978-3-903024-28-1" }