Liu, N.; Liu, X.; Jiang, Y.; Liu, P.; Gao, Y.; Ding, H.; Zhao, Y. Bionic Optimization Design and Fatigue Life Prediction of Honeycomb Structure Wheel Hub. Preprints2024, 2024081556. https://doi.org/10.20944/preprints202408.1556.v1
APA Style
Liu, N., Liu, X., Jiang, Y., Liu, P., Gao, Y., Ding, H., & Zhao, Y. (2024). Bionic Optimization Design and Fatigue Life Prediction of Honeycomb Structure Wheel Hub. Preprints. https://doi.org/10.20944/preprints202408.1556.v1
Chicago/Turabian Style
Liu, N., Hang Ding and Yujun Zhao. 2024 "Bionic Optimization Design and Fatigue Life Prediction of Honeycomb Structure Wheel Hub" Preprints. https://doi.org/10.20944/preprints202408.1556.v1
Abstract
According to the honeycomb structure, the preliminary design of bionic wheel hub for finite element analysis, in the working condition of a wheel by the force is through the spokes pointing to the center, the working condition of two wheel by the force is through the two spokes pointing to the center, and the ordinary wheel stress and displacement value results compared, observed the maximum stress value appears in the connection between the center of the wheel and the spokes, and predict the fatigue life of the preliminary design of bionic wheel. Using finite element analysis and response surface optimization analysis method for numerical simulation, through two optimization results show that, in the use of response surface analysis model optimization, the optimized bionic wheel maximum stress is 109.34MPa, compared with the ordinary wheel maximum stress 119.77MPa, the maximum stress reduced by 8.7%. The mass of the ordinary wheel is 34.02Kg, using the response surface optimization method, the optimized wheel mass is 29.89Kg, the mass reduced by 12.13%. The optimized wheel fatigue analysis, in the stress of 109.34MPa, load loading times at least 4.217e+005, in the position at the junction with the half shaft. In line with the national standard GB/T 5334-2021[16] for commercial vehicle wheel fatigue life requirements.
Keywords
finite element analysis; response surface optimization design; bionic design; fatigue life prediction
Subject
Engineering, Mechanical Engineering
Copyright:
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