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Materials 2017, 10(9), 1024; doi:10.3390/ma10091024

Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement

School of Mechatronics Engineering, Harbin Institute of Technology, No.92, Xidazhi Street, Harbin 150001, China
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Received: 25 July 2017 / Revised: 18 August 2017 / Accepted: 30 August 2017 / Published: 3 September 2017
(This article belongs to the Special Issue Modeling and Simulation of Advanced Composite Materials)
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Abstract

Automated fiber placement (AFP) process includes a variety of energy forms and multi-scale effects. This contribution proposes a novel multi-scale low-entropy method aiming at optimizing processing parameters in an AFP process, where multi-scale effect, energy consumption, energy utilization efficiency and mechanical properties of micro-system could be taken into account synthetically. Taking a carbon fiber/epoxy prepreg as an example, mechanical properties of macro–meso–scale are obtained by Finite Element Method (FEM). A multi-scale energy transfer model is then established to input the macroscopic results into the microscopic system as its boundary condition, which can communicate with different scales. Furthermore, microscopic characteristics, mainly micro-scale adsorption energy, diffusion coefficient entropy–enthalpy values, are calculated under different processing parameters based on molecular dynamics method. Low-entropy region is then obtained in terms of the interrelation among entropy–enthalpy values, microscopic mechanical properties (interface adsorbability and matrix fluidity) and processing parameters to guarantee better fluidity, stronger adsorption, lower energy consumption and higher energy quality collaboratively. Finally, nine groups of experiments are carried out to verify the validity of the simulation results. The results show that the low-entropy optimization method can reduce void content effectively, and further improve the mechanical properties of laminates. View Full-Text
Keywords: carbon fiber-reinforced composites; automated fiber placement; multi-scale analysis; low-entropy method; processing optimization carbon fiber-reinforced composites; automated fiber placement; multi-scale analysis; low-entropy method; processing optimization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Han, Z.; Sun, S.; Fu, H.; Fu, Y. Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement. Materials 2017, 10, 1024.

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