Thermo-Mechanical Coupled Analysis-Based Design of Ventilated Brake Disc Using Genetic Algorithm and Particle Swarm Optimization

Rahul Patil, Ali Belhocine, Dinesh Shinde
2021-08-24

SCID:  54.1/yv6nkpmq
The brake discs are subjected to thermal load due to sliding by the brake pad and fluctuating loads because of the braking load. This combined loading problem requires simulation using coupled thermo-mechanical analysis for design evaluation. This work presents a combined thermal and mechanical finite element analysis (FEA) and evolutionary optimization-based novel approach for estimating the optimal design parameters of the ventilated brake disc. Five parameters controlling the design: inboard plate thickness, outboard plate thickness, vane height, effective offset, and center hole radius were considered, and simulation runs were planned. A total of 27 brake disc designs with design parameters as recommended by the Taguchi method (L27) were modeled using SolidWorks, and the FEA simulation runs were carried out using the ANSYS thermal and structural analysis tool. The fatigue life results were analyzed using a three-dimensional (3D) surface plot for the effect of the design parameters on the response, contour plots for the determination of maximum response, and statistical regression analysis for model interpretation and predictive modeling. Finally, the two most accurate and widely used evolutionary optimization algorithms: genetic algorithm (GA) and particle swarm optimization (PSO) were applied to determine the optimal design parameters for the ventilated brake disc. The brake disc of design parameters predicted by GA and PSO gives a 12.74% higher fatigue life compared to parametric analysis. These results have shown that the developed approach can be utilized effectively and reliably for solving the design of ventilated brake disc problem in the industry.
Publication Details
Publication Date
2021-08-24
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Rahul Patil
Ali Belhocine
Dinesh Shinde
Explore More Research
Use the citation graph to discover related papers and expand your research horizons.
Click any node to explore
Download PDF
100%