融合多源数据的防热多孔材料渗透率预测方法OA

Ablative thermal protection is an important thermal protection method for hypersonic vehicles.Porous pyro-lyzed carbon for thermal protection materials are a type of ablative thermal protective material,whose permeability sig-nificantly influences transport characteristics.To address the issue of difficulty in obtaining empirical coefficients in per-meability formulas for thermal protective porous materials,a multi-source heterogeneous dataset is constructed,incor-porating material microstructure images and macroscopic structural characteristic parameters(maximum flow and frac-tal dimension).A particle-based method named direct simulation Monte Carlo is employed to calculate the permeabil-ity of the microstructure.Based on this,three permeability prediction methods using multi-source heterogeneous data fusion strategies are proposed:a decision-level fusion strategy,a fusion strategy based on direct concatenation of multi-source data features,and a fusion strategy based on a cross-modal attention mechanism for multi-source data.By comparing the predictive performance of the three fusion strategies,the strategy based on the cross-modal atten-tion mechanism demonstrates the best performance.This strategy captures the relationship between image convolu-tional features and structural parameters and dynamically adjusts the weights between them.On the test set,the coef-ficient of determination is 0.949 7,and the Mean Absolute Percentage Error is 5.29%.Compared with single-source data-driven permeability prediction models,the coefficient of determination improves by 6%,and the Mean Absolute Percentage Error decreases by 41%.This method enables efficient and accurate prediction of permeability,providing technical support for the refined design of thermal protection structures in actual hypersonic vehicles.