RESEARCH PAPER
Dynamic reliability calculation of random structures by conditional probability method
1
Department of Structural Engineering, Faculty of Civil Engineering, Akademicka 5, Silesian University of Technology, Poland
2
Department of Structural Engineering, Faculty of Civil Engineering, Doctoral School, Akademicka 2, Silesian University of Technology, Poland
3
Department of Civil Engineering, Sir Syed University of Engineering and Technology, Pakistan
4
Department of Civil Engineering, Shanghai Jiao Tong University, China
5
Department of Disaster Mitigation for Structures, Tongji University, China
These authors had equal contribution to this work
Submission date: 2023-10-11
Final revision date: 2023-12-14
Acceptance date: 2024-01-12
Online publication date: 2024-01-17
Publication date: 2024-01-17
Corresponding author
Bilal Ahmed
Department of Structural Engineering, Silesian University of Technology, Akademicka 2A, 44-100, Gliwice, Poland
Department of Structural Engineering, Silesian University of Technology, Akademicka 2A, 44-100, Gliwice, Poland
Eksploatacja i Niezawodność – Maintenance and Reliability 2024;26(2):181133
HIGHLIGHTS
- The Conditional probability method for dynamic reliability.
- The Kriging model for numerical sampling method.
- The Kriging sampling process.
KEYWORDS
TOPICS
ABSTRACT
For the composite random reliability problem, based on the Markov hypothesis of the dynamic
response spanning action, two procedures of conditional probability explanation are accomplished: to
derive the 2nd-order approximate expression for the calculation of the dynamic reliability of the
random structure based on Taylor expansion method; secondly is to determine a mathematical
sampling technique based on the Kriging model derive from the statistical analysis. Between them, the
sampling procedure by the Kriging interpolation model meets the nonlinear correlation among dynamic
reliability and structural random boundaries. Consequently, the finite element results can be used
instantly to anatomize the significance of random structural parameters on dynamic reliability, avoiding
the tedious and cumbersome theoretical derivation. The numerical example outcomes demonstrate
that the numerical sampling method established upon the Kriging model is inconsiderate to the ratio to
represent the dispersion and has additional benefits in computational verisimilitude and calculation
productivity
| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
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