Reliability analysis of planar steel trusses based on p-box models
Introduction. The development of probabilistic approaches to the assessment of mechanical safety of bearing structural elements is one of the most relevant areas of research in the construction industry. In this research, probabilistic methods are developed to perform the reliability analysis of ste...
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Online Access: | https://doi.org/10.22227/1997-0935.2021.2.153-167 |
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doaj-31ce8cf8da64409aa9d92cc89cee98512021-03-17T09:23:54ZengMoscow State University of Civil Engineering (MGSU)Vestnik MGSU 1997-09352021-02-0116215316710.22227/1997-0935.2021.2.153-167Reliability analysis of planar steel trusses based on p-box modelsAnastasia A. Soloveva0Sergey A. Solovev1Vologda State University (VSU)Vologda State University (VSU)Introduction. The development of probabilistic approaches to the assessment of mechanical safety of bearing structural elements is one of the most relevant areas of research in the construction industry. In this research, probabilistic methods are developed to perform the reliability analysis of steel truss elements using the p-box (probability box) approach. This approach ensures a more conservative (interval-based) reliability assessment made within the framework of attaining practical objectives of the reliability analysis of planar trusses and their elements. The truss is analyzed as a provisional sequential mechanical system (in the language of the theory of reliability) consisting of elements that represent reliability values for each individual bar and truss node in terms of all criteria of limit states. Materials and methods. The co-authors suggest using p-blocks consisting of two boundary distribution functions designated for modeling random variables in the mathematical models of limit states performed within the framework of the truss reliability analysis instead of independent true functions of the probability distribution of random variables. Boundary distribution functions produce a probability distribution domain in which a true distribution function of a random variable is located. However this function is unknown in advance due to the aleatory and epistemic uncertainty. The choice of a p-block for modeling a random variable will depend on the type and amount of statistical information about the random variable. Results. The probabilistic snow load model and the numerical simulation of tests of steel samples of truss rods are employed to show that p-box models are optimal for modeling random variables to solve numerous practical problems of the probabilistic assessment of reliability of structural elements. The proposed p-box snow load model is based on the Gumbel distribution. The mathematical model used to perform the reliability analysis of planar steel truss elements is proposed. The co-authors provide calculation formulas to assess the reliability of a truss element for different types of p-blocks used to describe random variables depending on the amount of statistical data available. Conclusions. The application of statistically unsubstantiated hypotheses for choosing the probability distribution law or assessing the parameters of the probability distribution of a random variable leads to erroneous assessments of the reliability of structural elements, including trusses. P-boxes ensure a more careful reliability assessment of a structural element, but at the same time this assessment is less informative, as it is presented in the form of an interval. A more accurate reliability interval requires interval-based assessments of distribution parameters or types of p-boxes applied to mathematical models of the limit state, which entails an increase in the economic and labor costs of the statistical data.https://doi.org/10.22227/1997-0935.2021.2.153-167reliabilityprobability of failurep-boxesplanar trussinterval-based assessmentsnow loaduncertainty |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Anastasia A. Soloveva Sergey A. Solovev |
spellingShingle |
Anastasia A. Soloveva Sergey A. Solovev Reliability analysis of planar steel trusses based on p-box models Vestnik MGSU reliability probability of failure p-boxes planar truss interval-based assessment snow load uncertainty |
author_facet |
Anastasia A. Soloveva Sergey A. Solovev |
author_sort |
Anastasia A. Soloveva |
title |
Reliability analysis of planar steel trusses based on p-box models |
title_short |
Reliability analysis of planar steel trusses based on p-box models |
title_full |
Reliability analysis of planar steel trusses based on p-box models |
title_fullStr |
Reliability analysis of planar steel trusses based on p-box models |
title_full_unstemmed |
Reliability analysis of planar steel trusses based on p-box models |
title_sort |
reliability analysis of planar steel trusses based on p-box models |
publisher |
Moscow State University of Civil Engineering (MGSU) |
series |
Vestnik MGSU |
issn |
1997-0935 |
publishDate |
2021-02-01 |
description |
Introduction. The development of probabilistic approaches to the assessment of mechanical safety of bearing structural elements is one of the most relevant areas of research in the construction industry. In this research, probabilistic methods are developed to perform the reliability analysis of steel truss elements using the p-box (probability box) approach. This approach ensures a more conservative (interval-based) reliability assessment made within the framework of attaining practical objectives of the reliability analysis of planar trusses and their elements. The truss is analyzed as a provisional sequential mechanical system (in the language of the theory of reliability) consisting of elements that represent reliability values for each individual bar and truss node in terms of all criteria of limit states.
Materials and methods. The co-authors suggest using p-blocks consisting of two boundary distribution functions designated for modeling random variables in the mathematical models of limit states performed within the framework of the truss reliability analysis instead of independent true functions of the probability distribution of random variables. Boundary distribution functions produce a probability distribution domain in which a true distribution function of a random variable is located. However this function is unknown in advance due to the aleatory and epistemic uncertainty. The choice of a p-block for modeling a random variable will depend on the type and amount of statistical information about the random variable.
Results. The probabilistic snow load model and the numerical simulation of tests of steel samples of truss rods are employed to show that p-box models are optimal for modeling random variables to solve numerous practical problems of the probabilistic assessment of reliability of structural elements. The proposed p-box snow load model is based on the Gumbel distribution. The mathematical model used to perform the reliability analysis of planar steel truss elements is proposed. The co-authors provide calculation formulas to assess the reliability of a truss element for different types of p-blocks used to describe random variables depending on the amount of statistical data available.
Conclusions. The application of statistically unsubstantiated hypotheses for choosing the probability distribution law or assessing the parameters of the probability distribution of a random variable leads to erroneous assessments of the reliability of structural elements, including trusses. P-boxes ensure a more careful reliability assessment of a structural element, but at the same time this assessment is less informative, as it is presented in the form of an interval. A more accurate reliability interval requires interval-based assessments of distribution parameters or types of p-boxes applied to mathematical models of the limit state, which entails an increase in the economic and labor costs of the statistical data. |
topic |
reliability probability of failure p-boxes planar truss interval-based assessment snow load uncertainty |
url |
https://doi.org/10.22227/1997-0935.2021.2.153-167 |
work_keys_str_mv |
AT anastasiaasoloveva reliabilityanalysisofplanarsteeltrussesbasedonpboxmodels AT sergeyasolovev reliabilityanalysisofplanarsteeltrussesbasedonpboxmodels |
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