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The critical speed of aircraft tires was approximated with the use of the finite element method. The model used shell elements with a fourier expansion in the circumferential direction and included moderate rotation and transverse shear deformation effects. The model linearized the equations of motion about an equilibrium point with the assumption of small dynamic displacements superimposed onto a large nonlinear equilibrium state. Application models were created for main landing gear (MLG) bias tires for the F-16, Space Shuttle Orbiter and Hypervelocity Vehicle (HVV) aircraft. The model performed well in all cases with adequate agreement with experimental results.

This paper applies a wheel fatigue life prediction technique based on strain survey data to predicting the fatigue life of two F-16 main landing gear wheels. Parametric studies were performed on inflation pressure, tire type and loading condition. The results of this study indicate that for the block 30 wheel, the radial tire distributes the load to the wheel much differently than the bias tire. Also, the F-16 block 40 wheel is stressed much greater than the block 30 wheel for the same tire type during qualification testing.

This paper presents typical tire models used by the aerospace community for studying landing gear shimmy. Closed form solutions were developed for the tire models and fit to different types of laboratory tire data. The laboratory tests include the traditional windup tests on a Tire Force Machine, dynamic non-rolling tests on the dynamometer and tire force machine, and dynamic yaw and rolling tests on the dynamometer. Both bias and radial tire designs were studied in both the new and worn condition. Based on the testing performed, significantly different tire property information is obtained. For example, torsional stiffness measured for the non-rolling condition was nearly three times larger than that measured for the rolling tire. Also, very large differences in the torsional damping coefficient between tire types were only evident through dynamic yaw and rolling testing.