Reliability-based Design Optimization of Steel-Concrete Composite Beams Using Genetic Algorithm and Monte Carlo Simulation
Received: 23 September 2022 | Revised: 13 October 2022 | Accepted: 15 October 2022 | Online: 24 October 2022
Corresponding author: T. H. Nguyen
Abstract
Steel-Concrete Composite (SCC) beams have been commonly used in civil and industrial buildings. It is the main bearing structure and accounts for 30-40% of the structural cost. Therefore, the optimal design with minimum weight and safety structure of the SCC beams is very important. Reliability is an important part of structural safety. Design according to reliability has been included in standards such as ISO 2394:2012, JB50153-92, and BS 5760-0:2014. This article aims to propose and apply a design optimization algorithm for the reliability-based design of SCC beams. The reliability-based design optimization of the SCC beams combines the safety conditions of EC-4, Genetic Algorithm, and Monte Carlo simulation. The numerical results show that with safety probability constraint conditions Ps=98%, the cross-section of the SCC beams can be reduced from IPE 400 to IPE 300.
Keywords:
design optimization, Genetic algorithm (GA), Monte Carlo simulations, steel-concrete composite beams, reliabilityDownloads
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