Yi Li
Shanghai Jiao Tong University
TensorOrientation tensorFinite element methodComposite materialRepresentative elementary volumeCompression moldingMaterials scienceVoronoi diagramModelling methodsMolding (process)FiberMicrostructureOrientation (computer vision)Substructure
Publications 3
#1Yi Li (NU: Northwestern University)H-Index: 2
#2Zhangxing Chen (Chongqing University)H-Index: 5
Last. Hongyi Xu (Ford Motor Company)H-Index: 13
view all 6 authors...
Abstract To establish an integrated Processing-Microstructure-Property workflow for the prediction of material behaviors, this paper presents a new stochastic pseudo-3D microstructure reconstruction method for Sheet Molding Compounds (SMC) chopped fiber composites. The proposed method captures the bi-level microstructural features of SMC composites. At the higher level, a Voronoi diagram-based algorithm is developed to reconstruct the unique substructure features of SMC fiber tows. The geometry ...
8 CitationsSource
#1Zhangxing Chen (Chongqing University)H-Index: 7
#2Yi Li (SJTU: Shanghai Jiao Tong University)H-Index: 2
Last. Xuming Su (Ford Motor Company)H-Index: 18
view all 11 authors...
2 CitationsSource
#1Yi Li (NU: Northwestern University)H-Index: 2
Last. Hongyi Xu (Ford Motor Company)H-Index: 13
view all 3 authors...
To provide a seamless integration of manufacturing processing simulation and fiber microstructure modeling, two new stochastic 3D microstructure reconstruction methods are proposed for two types of random fiber composites: random short fiber composites, and Sheet Molding Compounds (SMC) chopped fiber composites. A Random Sequential Adsorption (RSA) algorithm is first developed to embed statistical orientation information into 3D RVE reconstruction of random short fiber composites. For the SMC co...