Parametric RVE‐Based Simulation and Analysis of Stiffness Prediction for Braiding‐Needling Composites: Manufacturing and Structural Parameters Coupling
Source abstract
Abstract
ABSTRACT The braiding‐needling (BN) process enhances the delamination resistance of composites by redirecting in‐plane fibers into the through‐thickness direction, demonstrating significant engineering potential. However, predictive models that explicitly incorporate both manufacturing parameters and structural features of BN composites remain limited. In this study, a parameterized representative volume element (RVE)‐based finite element framework is developed and validated for needled‐reinforced BN composites, enabling process‐informed prediction of their effective mechanical properties. First, the RVE size and needle hole distribution are determined under varying manufacturing constraints. Micro‐computed tomography (CT) is then employed to characterize the cross‐sectional geometries of yarns and needled fiber bundles, based on which the finite element model is constructed. The predicted equivalent stiffness agrees well with in‐plane tensile test results, with a deviation of 7.8%, validating the proposed framework. Furthermore, the influences of key process parameters—including braiding angle, needle spacing, and needle hole radius—on the effective mechanical properties are systematically quantified. The proposed framework provides a quantitative and process‐aware tool for the integrated optimization of manufacturing and structural parameters in BN composites.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Mechanical Behavior of Composites · Textile materials and evaluations · Composite Structure Analysis and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Nanjing University of Aeronautics and Astronautics College of Mechanical and Electrical Engineering Nanjing Jiangsu China
State Key Laboratory of Mechanics and Control for Mechanical Structures Nanjing Jiangsu China
Funding
National Natural Science Foundation of China · China Postdoctoral Science Foundation
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