Yukio Nakajima

Hydroplaning Analysis by FEM and FVM: Effect of Tire Rolling and Tire Pattern on Hydroplaning

Abstract We established the new numerical procedure for hydroplaning. We considered the following three important factors; fluid/structure interaction, tire rolling, and practical tread pattern. The tire was analyzed by the finite element method with Lagrangian formulation, and the fluid was analyzed by the finite volume method with Eulerian formulation. Since the tire and the fluid can be modeled separately and their coupling is computed automatically, the fluid/structure interaction of the complex geometry, such as the tire with the tread pattern, can be analyzed. Since we focused the aim of the simulation on dynamic hydroplaning with thick water films, we ignored the effect of fluid viscosity. We verified the predictability of the hydroplaning simulation in the different parameters such as the water flow, the velocity dependence of hydroplaning, and the effect of the tread pattern on hydroplaning. These parameters could be predicted qualitatively. We also developed the procedure of the global‐local ana...

Optimization of Construction of Tire Reinforcement by Genetic Algorithm

A new tire design procedure capable of determining the optimum tire construction was developed by combining a finite element method approach with mathematical programming and a genetic algorithm (GA). Both procedures successfully generated optimized belt structures. The design variables in the mathematical programming were belt angle and belt width. Using the merits of a GA which enabled the use of discrete variables, the design variables in the GA were not only the topology of the belt and belt angle but also the belt material. Furthermore, a discrete objective function such as the number of parts could be optimized in the GA. The optimized structure obtained by the GA was verified to increase the cornering stiffness more than 15 percent as compared with the control structure in an indoor drum test.

Application of genetic algorithms for optimization of tire pitch sequences

A simple genetic algorithms (GAs) has been applied to generate the optimum pitch sequence. Though a simple GAs worked properly, there was the problem of the premature convergence. To solve this problem, we introduced the new operator named the growth and combined it with a simple GAs. The growth operator, which is a kind of the hill-climbing technique, has the function to get the local optimum in a small CPU time.The GA with growth generated better sequence than a simple GAs. The GA with growth was verified not to have the premature convergence even in the smaller population size. The optimum pitch sequence generated by the GA with growth improved the noise performance such as pass-by noise compared with the current pitch sequence.