基于纹理合成优化算法的多相非均质材料二维微观结构表征与重建

Two-Dimensional Microstructure Characterization and Reconstruction of Heterogeneous Materials Based on Texture Synthesis Optimization Algorithm

材料微观结构表征与重建(Microstructure characterization and reconstruction,MCR)可用于建立加工-结构-属性(Processing-Structure-Property,PSP)关系,已成为计算材料学与材料设计的研究重点。通过阈值分割将多相非均质材料的金相照片识别为由不同相构成的纹理,结合多分辨率高斯金字塔进行重建。以各相占比为目标参数,对颗粒补充后的重建结果进行面积分数迭代优化,提出了一种面积分数可控的MCR纹理合成算法。利用该优化算法对多相非均质铝硅聚苯酯(AlSi-PHB)封严涂层微观组织进行表征重建,PHB和孔隙两相的两点相关函数计算结果证实了算法的有效性。在此基础上,将两组金相照片作为原始图像,重建20组模型,重建结果的两点相关函数误差最大为8.8×10^(-5)。本研究为多相非均质材料的准确重建提供了解决途径。

Microstructure characterization and reconstruction(MCR)can be used to establish the processing-structure--property(PSP)relationship,which has become the focus of computational materials science and material design.In this paper,threshold segmentation is used to identify the metallographic photos of heterogeneous materials as textures composed of different phases,combined with multi-resolution Gaussian pyramids for reconstruction.The reconstruction results after particle number supplement are iteratively optimized with percentage of each phase as target parameter.Thereby,this paper proposes an innovative MCR texture synthesis algorithm with controllable area fraction,which is used to reconstruct the microstructure of heterogeneous AlSi-PHB seal coating.Two-point correlation functions of PHB phase and pore are utilized to confirm the effectiveness of the proposed algorithm.On this basis,two sets of metallographic photos are used to reconstruct 20 sets of models,and the maximum error of the two-point correlation function of the reconstructed results is 8.8×10^(-5).This paper provides a solution for the accurate reconstruction of heterogeneous materials.