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Image based in silico characterisation of the effective thermal properties of a graphite foam
Carbon, Volume: 143, Pages: 542 - 558
Swansea University Author: Llion Evans
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DOI (Published version): 10.1016/j.carbon.2018.10.031
Abstract
Functional materials' properties are influenced by microstructures which can be changed during manufacturing. A technique is presented which digitises graphite foam via X-ray tomography and converts it into image-based models to determine properties in silico. By simulating a laser flash analys...
Published in: | Carbon |
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ISSN: | 00086223 |
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2019
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URI: | https://cronfa.swan.ac.uk/Record/cronfa44838 |
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2019-10-18T14:12:17Z |
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2019-10-18T11:58:04.8337124 v2 44838 2018-10-10 Image based in silico characterisation of the effective thermal properties of a graphite foam 74dc5084c47484922a6e0135ebcb9402 0000-0002-4964-4187 Llion Evans Llion Evans true false 2018-10-10 ACEM Functional materials' properties are influenced by microstructures which can be changed during manufacturing. A technique is presented which digitises graphite foam via X-ray tomography and converts it into image-based models to determine properties in silico. By simulating a laser flash analysis its effective thermal conductivity is predicted. Results show ∼1% error in the direction the foam was ‘grown’ during manufacturing but is significantly less accurate in plane due to effective thermal conductivity resulting from both the foam's microstructure and graphite's crystalline structure. An empirical relationship is found linking these by using a law of mixtures. A case study is presented demonstrating the technique's use to simulate a heat exchanger component containing graphite foam with micro-scale accuracy using literature material properties for solid graphite. Compared against conventional finite element modelling there is no requirement to firstly experimentally measure the foam's effective bulk properties. Additionally, improved local accuracy is achieved due to exact location of contact between the foam and other parts of the component. This capability will be of interest in design and manufacture of components using graphite materials. The software used was developed by the authors and is open source for others to undertake similar studies. Journal Article Carbon 143 542 558 00086223 X-ray tomography, Graphite foam, Image-based modelling, Finite element method, Virtual characterisation, Thermal conductivity 31 3 2019 2019-03-31 10.1016/j.carbon.2018.10.031 COLLEGE NANME Aerospace, Civil, Electrical, and Mechanical Engineering COLLEGE CODE ACEM Swansea University UKRI, EP/R012091/1 2019-10-18T11:58:04.8337124 2018-10-10T14:17:14.8045482 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Ll.M. Evans 1 L. Margetts 2 P.D. Lee 3 C.A.M. Butler 4 E. Surrey 5 Llion Evans 0000-0002-4964-4187 6 0044838-11032019103311.pdf 44838.pdf 2019-03-11T10:33:11.7500000 Output 3131745 application/pdf Version of Record true 2019-03-10T00:00:00.0000000 Released under the terms of a Creative Commons Attribution License (CC-BY). true eng |
title |
Image based in silico characterisation of the effective thermal properties of a graphite foam |
spellingShingle |
Image based in silico characterisation of the effective thermal properties of a graphite foam Llion Evans |
title_short |
Image based in silico characterisation of the effective thermal properties of a graphite foam |
title_full |
Image based in silico characterisation of the effective thermal properties of a graphite foam |
title_fullStr |
Image based in silico characterisation of the effective thermal properties of a graphite foam |
title_full_unstemmed |
Image based in silico characterisation of the effective thermal properties of a graphite foam |
title_sort |
Image based in silico characterisation of the effective thermal properties of a graphite foam |
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74dc5084c47484922a6e0135ebcb9402 |
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74dc5084c47484922a6e0135ebcb9402_***_Llion Evans |
author |
Llion Evans |
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Ll.M. Evans L. Margetts P.D. Lee C.A.M. Butler E. Surrey Llion Evans |
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10.1016/j.carbon.2018.10.031 |
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description |
Functional materials' properties are influenced by microstructures which can be changed during manufacturing. A technique is presented which digitises graphite foam via X-ray tomography and converts it into image-based models to determine properties in silico. By simulating a laser flash analysis its effective thermal conductivity is predicted. Results show ∼1% error in the direction the foam was ‘grown’ during manufacturing but is significantly less accurate in plane due to effective thermal conductivity resulting from both the foam's microstructure and graphite's crystalline structure. An empirical relationship is found linking these by using a law of mixtures. A case study is presented demonstrating the technique's use to simulate a heat exchanger component containing graphite foam with micro-scale accuracy using literature material properties for solid graphite. Compared against conventional finite element modelling there is no requirement to firstly experimentally measure the foam's effective bulk properties. Additionally, improved local accuracy is achieved due to exact location of contact between the foam and other parts of the component. This capability will be of interest in design and manufacture of components using graphite materials. The software used was developed by the authors and is open source for others to undertake similar studies. |
published_date |
2019-03-31T13:37:25Z |
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1821322243980918784 |
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11.048042 |