Frost growth on cold surfaces is a transient process with coupled heat and mass transfer. Due to multiple factors such as humidity, temperature, flow velocity and constantly changing thermal properties as frost grows, precise prediction can be challenging. Especially when the geometry of the frosting surfaces gets complicated, it requires a balance of computing accuracy and efficiency. In this work, a numerical model is developed to predict frost growth considering the effect of the above parameters. Mixture model is adapted to improve the computational efficiency and the unstructured grids add the flexibility to extend the model to complex geometries. The predicted frost growth rate matches well with the experimental data reported in the literature under similar conditions. The model predicts reasonable growth trend of frost as the surface temperature, air temperature, humidity and flow velocity vary. The surface wettability effect is well captured at the early stage of frosting and it shows a higher frost growth rate on surfaces with a higher wettability.
翻译:由于湿度、温度、流动速度等多种因素,以及随着冰冻的生长而不断变化的热特性,精确的预测可能具有挑战性。特别是当霜冻表面的几何学变得复杂时,需要平衡计算准确性和效率。在这项工作中,考虑到上述参数的影响,开发了一个数字模型,以预测冻土的生长。对混合模型进行了调整,以提高计算效率和非结构化网格增加灵活性,将模型扩展至复杂的地貌。预测的霜冻生长率与文献中所报告的类似条件下的实验数据非常吻合。模型预测的霜冻生长趋势合理,因为地表温度、空气温度、湿度和流动速度各不相同。表层湿度效应在冰冻的早期阶段得到了很好的捕捉,并显示地表的霜生长率较高,湿度较高。