Reliability based topology optimization of thermoelastic structures using bi-directional evolutionary structural optimization method

• Published in: International journal of mechanics and materials in design Vol. 19; no. 3; pp. 605 - 620
• Main Authors: Habashneh, Muayad, Rad, Majid Movahedi
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2023; Springer Nature B.V
• Subjects: Beams (structural); Characterization and Evaluation of Materials; Classical Mechanics; Design optimization; Engineering; Engineering Design; Impact analysis; Monte Carlo simulation; Nonlinearity; Normal distribution; Optimization; Random variables; Reliability; Sensitivity analysis; Solid Mechanics; Statistical analysis; Topology optimization; BESO; Topology optimization; Thermoelastic; Reliability based design
• ISSN: 1569-1713; 1573-8841
• DOI: 10.1007/s10999-023-09641-0

The aim of this paper is to propose a novel computational technique of applying reliability-based design to thermoelastic structural topology optimization. Therefore, the optimization of thermoelastic structures' topology based on reliability-based design is considered by utilizing geometrical nonlinearity analysis. For purposes of introducing reliability-based optimization, the volume fraction parameter is viewed as a random variable with a normal distribution having a mean value and standard deviation. The Monte Carlo simulation approach for probabilistic designs is used to calculate the reliability index, which is used as a constraint related to the volume fraction constraint of the deterministic problem. A new bi-directional evolutionary structural optimization scheme is developed, in which a geometrically nonlinear thermoelastic model is applied in the sensitivity analysis. The impact of changing the constraint of a defined volume of the required design in deterministic problems is examined. Additionally, the impact of altering the reliability index in probabilistic problems is investigated. The effectiveness of the suggested approach is shown using a benchmark problem. Additionally, this research takes into account probabilistic thermoelastic topology optimization for a 2D L-shaped beam problem.