A Stochastic Modeling Method of Non-equal Diameter Pore with Optimal Distribution Function for Meso-structure of Atmospheric Ice
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Abstract:
The macroscopic mechanical properties of atmospheric ice are affected by the mesoscopic pore structure, while traditional approaches to simulating still have certain limitations. To more accurately represent the mesoscopic structure of porous atmospheric ice, a new modeling method based on statistical principles is proposed. Firstly, the statistical information of atmospheric ice pore diameter is obtained by image recognition. Then, the optimal distribution function that matches the real distribution state of pore diameter is identified using a goodness-of-fit test. Next, a novel approach for deriving the geometric size of atmospheric ice models is introduced, and a method for generating random pore position and diameter data is provided. Finally, a pore intersection determination module is added to construct the mesoscopic model of atmospheric ice. The results demonstrate that the quantitative information of the pores in the generated atmospheric ice model is in good agreement with the experimental results, illustrating the accuracy and feasibility of the modeling method. Moreover, the influence of model parameters on porosity accuracy is systematically discussed. When the number of model pores reaches 50, a good balance between model accuracy and cost can be achieved. Thus, this study provides a novel method to characterize the mesoscopic features of atmospheric ice, and lays a foundation for the related simulation.
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The work was supported by the National Natural Science Foundation of China (No.12132019).
HUANG Yongjie, NI Zhangsong, YI Xian, YU Xinning, XUE Ming. A Stochastic Modeling Method of Non-equal Diameter Pore with Optimal Distribution Function for Meso-structure of Atmospheric Ice[J]. Transactions of Nanjing University of Aeronautics & Astronautics,2023,(5):555-565