Journal of Mechanical Science and Technology

The Korean Society of Mechanical Engineers (대한기계학회)
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Optimum Tire Contour Design Using Systematic STOM and Neural Network

  • Cho, Jin-Rae (School of Mechanical Engineering, Pusan National University) ;
  • Jeong, Hyun-Sung (School of Mechanical Engineering, Pusan National University) ;
  • Yoo, Wan-Suk (School of Mechanical Engineering, Pusan National University) ;
  • Shin, Sung-Woo (School of Mechanical Engineering, Pusan National University)
  • Published : 2004.08.01
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Abstract

An efficient multi-objective optimization method is presented making use of neural network and a systematic satisficing trade-off method (STOM), in order to simultaneously improve both maneuverability and durability of tire. Objective functions are defined as follows: the sidewall-carcass tension distribution for the former performance while the belt-edge strain energy density for the latter. A back-propagation neural network model approximates the objective functions to reduce the total CPU time required for the sensitivity analysis using finite difference scheme. The satisficing trade-off process between the objective functions showing the remarkably conflicting trends each other is systematically carried out according to our aspiration-level adjustment procedure. The optimization procedure presented is illustrated through the optimum design simulation of a representative automobile tire. The assessment of its numerical merit as well as the optimization results is also presented.

Keywords

References

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