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

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 efficie...

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Detalles Bibliográficos
Autores principales: Han, Zhenyu, Sun, Shouzheng, Fu, Hongya, Fu, Yunzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5615679/
https://www.ncbi.nlm.nih.gov/pubmed/28869520
http://dx.doi.org/10.3390/ma10091024
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author Han, Zhenyu
Sun, Shouzheng
Fu, Hongya
Fu, Yunzhong
author_facet Han, Zhenyu
Sun, Shouzheng
Fu, Hongya
Fu, Yunzhong
author_sort Han, Zhenyu
collection PubMed
description 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.
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spelling pubmed-56156792017-09-28 Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement Han, Zhenyu Sun, Shouzheng Fu, Hongya Fu, Yunzhong Materials (Basel) Article 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. MDPI 2017-09-03 /pmc/articles/PMC5615679/ /pubmed/28869520 http://dx.doi.org/10.3390/ma10091024 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Han, Zhenyu
Sun, Shouzheng
Fu, Hongya
Fu, Yunzhong
Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement
title Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement
title_full Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement
title_fullStr Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement
title_full_unstemmed Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement
title_short Multi-Scale Low-Entropy Method for Optimizing the Processing Parameters during Automated Fiber Placement
title_sort multi-scale low-entropy method for optimizing the processing parameters during automated fiber placement
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5615679/
https://www.ncbi.nlm.nih.gov/pubmed/28869520
http://dx.doi.org/10.3390/ma10091024
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