Fatigue Design of Leaf Spring Using Artificial Neural Network |
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| Journal | Key Engineering Materials (Volumes 326 - 328) |
|---|---|
| Volume | Experimental Mechanics in Nano and Biotechnology |
| Edited by | Soon-Bok Lee and Yun-Jae Kim |
| Pages | 1083-1086 |
| DOI | 10.4028/www.scientific.net/KEM.326-328.1083 |
| Citation | Won Seok Jung et al., 2006, Key Engineering Materials, 326-328, 1083 |
| Online since | December, 2006 |
| Authors | Won Seok Jung, Dong Ho Bae, Gee Wook Song, Jung Seob Hyun, Bum Shin Kim |
| Keywords | Artificial Neural Network (ANN), Fatigue Design, Fatigue Strength, Leaf Spring, Maximum Stress, Suspension |
| Abstract | The vehicle suspension system is directly influenced to ride and handling. Therefore, the major components of the vehicle suspension system should have enough fatigue strength during its lifetime to protect passenger from the traffic accident. Spring is one of the major suspension part of vehicle. Thus, in this paper, a fatigue design method for leaf spring was proposed. At first, numerical stress analysis for leaf spring assembly was performed. On the base of the analysis results, fatigue strength of leaf spring was assessed. And next, after studying numerically on geometrical parameters of leaf spring assembly, an economical prediction method of fatigue design criterion for leaf spring assembly using the theory of artificial neural network was developed and certified its usefulness. Without performing a lot of additional fatigue test for a long time, fatigue design criterion for a new leaf spring assembly having different geometry can be predicted on the base of the already obtained fatigue data. |
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