Abstract Currently, no model could be used to readily predict the TCR of baring outer ring/bearing housing interface, then a thermal contact conductance (TCC) model between cylindrical surfaces with transition fits is constructed. The topography is described by the fractal geometry to characterize the multiscale and self-affinity behaviors and two stochastic variables are introduced into the fractal function to guarantee the random and disordered features. Then the contact states of contact points are analyzed, and a new fractal inner contact model is established. An effective contact factor is introduced to modify the contact parameters. Eventually, the predictive model of TCCs is constructed by summing up the TCCs of all the contacting protrusions with different scales. To demonstrate the validity of the TCC model, the measuring setup of TCCs was developed, and then the tests were conducted. The results show that the average deviations between the measured data and predicted TCCs are 10.25% and 8.73% for SS304 and carbon steel, respectively. When the effective contact factor is not considered, the average deviations between the predicted TCCs and measured data are 25.47% and 20.61% for SS304 and carbon steel, respectively. Then the necessity to introduce the effective contact factor is verified. For SS304, the prediction accuracy of the present model is 15.22%, 56.36%, and 31.55% higher than that of the present model without effective contact factor, M-T model, and Zou model, respectively. For carbon steel, the prediction accuracy of the present model is 11.88%, 63.76%, and 34.87% higher than that of the present model without effective contact factor, M-T model, and Zou model, respectively. Finally, the effects of the surface roughness, the protrusion top radius, the effective contact factor, and the transition fit on TCC are discussed. The results show that TCC decreases with surface roughness. The TCC with different protrusion top radii is greater than that with identical top radius. The TCC increases with the effective contact factor slowly and then the growth rate increases rapidly. Besides, the TCC increases with transition fit sharply at the early stage, and then increases slowly for both SS304 and carbon steel.

中文翻译：

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轴承外圈/轴承座界面的热接触传导建模

摘要 目前，尚无模型可用于轻松预测轴承外圈/轴承座界面的TCR，因此构建了过渡配合圆柱表面之间的热接触传导（TCC）模型。地形由分形几何描述以表征多尺度和自亲和行为，并在分形函数中引入两个随机变量以保证随机和无序特征。然后分析了接触点的接触状态，建立了新的分形内接触模型。引入有效接触因子来修改接触参数。最终，通过将所有不同尺度的接触突起的TCC相加，构建TCC的预测模型。为了证明 TCC 模型的有效性，开发了 TCC 的测量装置，然后进行了测试。结果表明，SS304 和碳钢的实测数据和预测的 TCC 之间的平均偏差分别为 10.25% 和 8.73%。当不考虑有效接触系数时，SS304 和碳钢的预测 TCC 和测量数据之间的平均偏差分别为 25.47% 和 20.61%。然后验证了引入有效接触因子的必要性。对于SS304，本模型的预测精度分别比没有有效接触因子的本模型、MT模型和Zou模型提高了15.22%、56.36%和31.55%。对于碳钢，本模型的预测精度比没有有效接触因子的本模型预测精度提高了11.88%、63.76%和34.87%，分别为 MT 模型和 Zou 模型。最后，讨论了表面粗糙度、突起顶部半径、有效接触因子和过渡配合对 TCC 的影响。结果表明，TCC随着表面粗糙度的增加而降低。不同突起顶部半径的TCC大于相同顶部半径的TCC。TCC随着有效接触因子的增加缓慢增加，然后增长速度迅速增加。此外，TCC 在早期随过渡配合急剧增加，然后对于 SS304 和碳钢均缓慢增加。不同突起顶部半径的TCC大于相同顶部半径的TCC。TCC随着有效接触因子的增加缓慢增加，然后增长速度迅速增加。此外，TCC 在早期随过渡配合急剧增加，然后对于 SS304 和碳钢均缓慢增加。不同突起顶部半径的TCC大于相同顶部半径的TCC。TCC随着有效接触因子的增加缓慢增加，然后增长速度迅速增加。此外，随着过渡配合，TCC 在早期急剧增加，然后对于 SS304 和碳钢均缓慢增加。