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A novel probabilistic approach to the plastic analysis of steel moment frames
The limit plastic analysis procedure based on the basic mechanism determination is a classic procedure for fast analysis of structures, which results in determining the critical collapse mechanism of structures with acceptable precision and without prior information on structural details. However, this procedure loses efficiency in high-rise structures since it becomes a labor-intensive and almost impossible assignment. With the aid of optimization algorithms, this defect can be obviated. This paper implemented a novel approach to the probabilistic assessment of plastic analysis theory. Besides, two popular optimization algorithms, the dolphin echolocation, and the bat algorithm were employed for the optimization process of the plastic analysis method. The chaos was implemented in DE algorithms to have better global convergence. The first- and second-order reliability methods (FORM and SORM) were employed to formulate the limit state function in the reliability analysis. The limit state function was defined based on the critical load factor of two sample frames. Within the classic plastic analysis, the dolphin echolocation exhibited a 100% convergence reliability to the actual response in both sample frames, while the bat algorithm had 90% and 80% of reliability for samples one and two, respectively. Overall, both algorithms predicted the critical collapse mode of sample frames accurately. The FORM analysis revealed the approximate reliability index of two for both frames. Sensitivity measures based on the probabilistic approach also determined the most influential random variables in the probability of failure in both sample frames.
A novel probabilistic approach to the plastic analysis of steel moment frames
The limit plastic analysis procedure based on the basic mechanism determination is a classic procedure for fast analysis of structures, which results in determining the critical collapse mechanism of structures with acceptable precision and without prior information on structural details. However, this procedure loses efficiency in high-rise structures since it becomes a labor-intensive and almost impossible assignment. With the aid of optimization algorithms, this defect can be obviated. This paper implemented a novel approach to the probabilistic assessment of plastic analysis theory. Besides, two popular optimization algorithms, the dolphin echolocation, and the bat algorithm were employed for the optimization process of the plastic analysis method. The chaos was implemented in DE algorithms to have better global convergence. The first- and second-order reliability methods (FORM and SORM) were employed to formulate the limit state function in the reliability analysis. The limit state function was defined based on the critical load factor of two sample frames. Within the classic plastic analysis, the dolphin echolocation exhibited a 100% convergence reliability to the actual response in both sample frames, while the bat algorithm had 90% and 80% of reliability for samples one and two, respectively. Overall, both algorithms predicted the critical collapse mode of sample frames accurately. The FORM analysis revealed the approximate reliability index of two for both frames. Sensitivity measures based on the probabilistic approach also determined the most influential random variables in the probability of failure in both sample frames.
A novel probabilistic approach to the plastic analysis of steel moment frames
Asian J Civ Eng
Abdulwahed, Larah R. (Autor:in)
Asian Journal of Civil Engineering ; 24 ; 1001-1014
01.06.2023
14 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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