Shinde, DineshÖktem, HasanUygur, İlyas2023-07-262023-07-2620220954-40892041-3009https://doi.org/10.1177/09544089221116166https://hdl.handle.net/20.500.12684/13245Brake discs are critical automobile components that provide the braking effect and ultimately ensure the safety of passengers. Because of intermittent braking operations, brake discs are subjected to fluctuating loads and are provided with ventilation to facilitate cooling. The present study utilized a combination of response surface methodology parametric analysis, finite element analysis, statistical analysis, predictive modeling, and design optimization. Based on the response surface methodology design of experimental runs, ventilated brake discs were modeled considering the critical design parameters, viz., radius of center hole, thickness of inboard and outboard plate, height of vanes, and offset. Using finite element analysis, the brake discs were simulated under actual braking conditions for fatigue life cycles. Thirty-two (32) trial finite element analysis trials were performed. The obtained results were interpreted using ANOVA and an effective predictive model was established. Parametric analysis was performed using plots of response surface methodology and contours to predict the optimal parameter settings. In addition, two nature-inspired optimization techniques, the genetic algorithm and particle swarm optimization, were implemented and the optimal design parameter settings were determined for maximum fatigue life. The genetic algorithm and particle swarm optimization produced 7.67% better results than the parametric analysis, clearly demonstrating that the proposed design techniques exhibited significant performance improvement compared to widely used classical techniques.en10.1177/09544089221116166info:eu-repo/semantics/closedAccessVentilated Brake Disc; Response Surface Methodology; Finite Element Analysis; Genetic Algorithm; Particle Swarm OptimizationX-Type Lattice; Genetic Algorithm; Fatigue Life; Structural Optimization; Process Parameters; Behavior; System; Wear; Squeal; ModelArticle2-s2.0-85135167003WOS:000832733000001Q3Q3