Process‐Informed Multiscale Prediction of Nonlinear Compressive Behavior in Direct Compounded Compression Molded Short Fiber Composite Lattice Structures

ABSTRACT Direct compounded compression molding (DCCM) offers an efficient route for producing SFRTP lattice structures, but predicting their nonlinear compressive behavior is challenging due to spatially heterogeneous fiber orientations from the molding process. This study presents a process‐informed multiscale framework for such prediction. At the process scale, Moldflow simulation predicts fiber orientation tensors across lattice regions, validated by metallographic image analysis with a 7.89% relative error. At the material scale, a unit cell model with fiber‐matrix interfacial cohesive behavior captures the SFRTP's nonlinear response. A transversely isotropic elastoplastic surrogate model and orientation‐averaging method yield region‐specific constitutive properties. At the structural scale, these properties are assigned separately to struts and four joint types in a refined finite element model. The predicted maximum stress error in the nonlinear stage is 3.8%, a significant improvement over the previous homogeneous assignment strategy, which had a 12.28% error. This framework efficiently incorporates process‐induced local anisotropy into structural analysis of compression‐molded short‐fiber composite lattices, reducing the need for exhaustive region‐by‐region mechanical characterization.

Authors

Institutions

Publication Details

Journal
Polymer Composites
Published
2026-08-28
DOI
https://doi.org/10.1002/pc.71573
Primary Topic
Composite Material Mechanics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Process‐Informed Multiscale Prediction of Nonlinear Compressive Behavior in Direct Compounded Compression Molded Short Fiber Composite Lattice Structures

Ting Wu, Haoyu Shi, Jianguo Liang, Jianglin Liu et al.
Polymer Composites
Composite Material Mechanics
article

Process‐Informed Multiscale Prediction of Nonlinear Compressive Behavior in Direct Compounded Compression Molded Short Fiber Composite Lattice Structures

Ting Wu, Haoyu Shi, Jianguo Liang, Jianglin Liu, Zhandong Wang, Runtian Zhao, Sizheng Gai
article en

Abstract

ABSTRACT Direct compounded compression molding (DCCM) offers an efficient route for producing SFRTP lattice structures, but predicting their nonlinear compressive behavior is challenging due to spatially heterogeneous fiber orientations from the molding process. This study presents a process‐informed multiscale framework for such prediction. At the process scale, Moldflow simulation predicts fiber orientation tensors across lattice regions, validated by metallographic image analysis with a 7.89% relative error. At the material scale, a unit cell model with fiber‐matrix interfacial cohesive behavior captures the SFRTP's nonlinear response. A transversely isotropic elastoplastic surrogate model and orientation‐averaging method yield region‐specific constitutive properties. At the structural scale, these properties are assigned separately to struts and four joint types in a refined finite element model. The predicted maximum stress error in the nonlinear stage is 3.8%, a significant improvement over the previous homogeneous assignment strategy, which had a 12.28% error. This framework efficiently incorporates process‐induced local anisotropy into structural analysis of compression‐molded short‐fiber composite lattices, reducing the need for exhaustive region‐by‐region mechanical characterization.

Polymer Composites
Shanghai FRP Research Institute (China) (CN), Xinjiang Institute of Engineering (CN), Taiyuan University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 18%
Composite Material Mechanics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.