차량 현가 부품의 근사 다목적 설계 최적화에 대한 메타모델 영향도 = Meta-model Effects on Approximate Multi-objective Design Optimization of Vehicle Suspension Components

다국어 초록 (Multilingual Abstract)

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle—a car suspension component—considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

목차 (Table of Contents)

• ABSTRACT
• 1. 서론
• 2. 근사화 및 최적화 이론
• 3. 넉클의 구조해석 및 최적설계 정식화
• 4. 다목적 근사 최적화 결과 및 고찰
• 4. 결론
• REFERENCES

참고문헌 (Reference)

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