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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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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. |
format | Online Article Text |
id | pubmed-5615679 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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