Paridie Ahmed M, Ene Nicoleta M
University of Toledo, college of engineering, MIME department, USA.
Heliyon. 2023 May 22;9(6):e16129. doi: 10.1016/j.heliyon.2023.e16129. eCollection 2023 Jun.
The paper investigates theoretically the effect of the geometry of the elastic rings of an air journal bearing on the elastic rings dynamic coefficients. The physical finite element method (FEM) model used to obtain the dynamic coefficients of the rings is discussed. A theoretical model is implemented to predict the effect of the geometrical parameters on the dynamic coefficients of the elastic rings. The effect of the geometrical parameters on the dynamic coefficients at different frequencies is studied using FEM. The elastic geometry that result in desired dynamic coefficients is demonstrated. Since predicting the dynamic coefficients for all possible ring geometries using FEM would be computationally expensive. A neural network (NN) is trained to predict the dynamic coefficients for all possible ring geometries generated by the different ring geometrical parameters within a given input domain. The NN results are compared to the experimentally verified FEM results and the results are in good agreement.
本文从理论上研究了空气径向轴承弹性环的几何形状对弹性环动力系数的影响。讨论了用于获得弹性环动力系数的物理有限元法（FEM）模型。建立了一个理论模型来预测几何参数对弹性环动力系数的影响。利用有限元法研究了几何参数对不同频率下动力系数的影响。展示了能产生所需动力系数的弹性几何形状。由于使用有限元法预测所有可能的弹性环几何形状的动力系数在计算上成本过高，因此训练了一个神经网络（NN）来预测在给定输入域内由不同弹性环几何参数生成的所有可能弹性环几何形状的动力系数。将神经网络的结果与经过实验验证的有限元法结果进行比较，结果吻合良好。
