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Fatigue analysis incorporating explicit finite element simulation was conducted on a forged magnesium wheel model where a rotating bend moment was applied to the hub to simulate rotary fatigue testing. Based on wheel fatigue design criteria and a developed fatigue post-processor, the safety factor of fatigue failure was calculated for each finite element. Fatigue failure was verified through experimental testing. Design modifications were proposed by increasing the spoke thickness. Further numerical and experimental testing indicated that the modified design passed the rotary fatigue test.

Explicit finite element simulations were conducted on an aluminum wheel model where a rotating bend moment was applied on its hub to simulate wheel cornering fatigue testing. A post-processor was developed to calculate equivalent von Mises alternating and mean stresses from stress tensor. The safety factors of fatigue design for each finite element were determined to assess the fatigue performance by utilizing the Goodman linear relationship. Elements with low safety factors were identified due to the prescribed boundary conditions and stress concentrations arising from wheel geometry.

In the present study, a design of experiment (DOE) technique, the Taguchi method, was used to develop as-cast high strength aluminum alloys with element additions of Si, Cu, Ni and Sr. The Taguchi method uses a special design of orthogonal arrays to study all the designed factors with a minimum of experiments at a relatively low cost. The element factors chosen for this study were Si, Cu, Ni and Sr content in the designed aluminum-based alloys. For each factor, three different levels of weight percentages were selected (Si: 6, 9, 12%, Cu: 3, 5, 7%, Ni: 0.5, 1, 1.5% and Sr: 0.01, 0.02, 0.03%). Tensile properties such as ultimate tensile strength, yield strength and elongation at failure were selected as three individual responses to evaluate the engineering performance of the designed alloys. The results of the factor response analysis were used to derive the optimal level combinations.