PROBABILISTIC APPROACH FOR ASSESSING THE ROBUSTNESS OF STRUCTURAL SYSTEMS MADE OF PRECAST AND MONOLITHIC REINFORCED CONCRETE
https://doi.org/10.33979/2073-7416-2023-108-4-93-105
Abstract
With the help of probabilistic modeling, the issues related to the assessment of the robustness of structural systems made of prefabricated and monolithic reinforced concrete in an accidental design situation are considered.
The paper considers the concept of analyzing the reliability of structural systems and differentiating risks in accidental design situations. The existing probabilistic models of the basic variables included in the functions of loads and resistances are analyzed. Statistical parameters of the uncertainty of the resistance model are obtained and integrated in the form of a basic variable with probability modeling.
Probabilistic modeling of structural systems made of precast and monolithic reinforced concrete, designed according to the current standards of the Republic of Belarus, was carried out using the Monte Carlo method. The functions of the limiting state of the structural system in an accidental design situation with the sudden removal of the central column of the first floor are determined. As a result, values of failure probabilities and corresponding reliability indices were obtained for the considered constructive systems.
About the Authors
A. A. Lizahub
Brest State Technical University
Belarus
Belarus
Lizahub Aliaksandr Al., master of eng. science, junior research fellow of BL «RCIC»
Brest
A. V. Tur
Brest State Technical University
Belarus
Belarus
Tur Andrei V., PhD, associate professor, head the department of architecture
Brest
V. V. Tur
Brest State Technical University
Belarus
Belarus
Tur Viktor V., doctor in technical sciences, head the department of concrete technology and construction materials
Brest
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Review
For citations:
Lizahub A.A., Tur A.V., Tur V.V. PROBABILISTIC APPROACH FOR ASSESSING THE ROBUSTNESS OF STRUCTURAL SYSTEMS MADE OF PRECAST AND MONOLITHIC REINFORCED CONCRETE. Building and Reconstruction. 2023;(4):93-105. (In Russ.) https://doi.org/10.33979/2073-7416-2023-108-4-93-105
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