基于深度学习的不连续纤维血小板复合材料微观结构重构实验验证

IF 2.6 4区 工程技术 Q2 MECHANICS Journal of Applied Mechanics-Transactions of the Asme Pub Date : 2023-11-02 DOI:10.1115/1.4063983
Mohammad Nazmus Saquib, Richard Larson, Siavash Sattar, Jiang Li, Sergey Kravchenko, Oleksandr Kravchenko
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引用次数: 0

摘要

摘要提出了一种利用人工智能(MR-AI)进行微结构重建的新方法,以非破坏性地测量预浸血小板成型复合材料(PPMC)板的平均随机纤维取向分布(FOD)。MR-AI方法使用PPMC板表面的热应变分量作为深度学习模型的输入,该模型可以预测整个PPMC体积中局部穿透厚度平均纤维取向状态的分布。采用带有加热台和数字图像相关(DIC)的实验装置测量了PPMC板表面的热应变。然后用光学显微镜测量PPMC板横截面的FOD。光学显微镜图像的FOD测量与MR-AI预测的FOD比较有利。所提出的方法为快速、无损地检测成型复合材料中制造引起的FOD提供了机会。
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Experimental Validation of Reconstructed Microstructure via Deep Learning in Discontinuous Fiber Platelet Composite
Abstract A novel approach for microstructure reconstruction using artificial intelligence (MR-AI) was proposed to non-destructively measure the through-thickness average stochastic fiber orientation distribution (FOD) in a prepreg platelet molded composite (PPMC) plate. MR-AI approach uses thermal strain components on the surfaces of a PPMC plate as input to the deep learning model, which allows to predict a distribution of local through-thickness average fiber orientation state in the entire PPMC volume. The experimental setup with a heating stage and digital image correlation (DIC) was used to measure thermal strains on the surface of PPMC plate. Optical microscopy was then used to measure FOD in the cross-section of PPMC plate. FOD measurements from optical microscopy imagery compared favorably with FOD prediction by MR-AI. The proposed methodology opens the opportunity for rapid, non-destructive inspection of manufacturing induced FOD in molded composites.
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来源期刊
CiteScore
4.80
自引率
3.80%
发文量
95
审稿时长
5.8 months
期刊介绍: All areas of theoretical and applied mechanics including, but not limited to: Aerodynamics; Aeroelasticity; Biomechanics; Boundary layers; Composite materials; Computational mechanics; Constitutive modeling of materials; Dynamics; Elasticity; Experimental mechanics; Flow and fracture; Heat transport in fluid flows; Hydraulics; Impact; Internal flow; Mechanical properties of materials; Mechanics of shocks; Micromechanics; Nanomechanics; Plasticity; Stress analysis; Structures; Thermodynamics of materials and in flowing fluids; Thermo-mechanics; Turbulence; Vibration; Wave propagation
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