Journal article 1189 views
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys
Computational Materials Science, Volume: 32, Issue: 3-4, Pages: 480 - 488
Swansea University Author: Leo Prakash
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DOI (Published version): 10.1016/j.commatsci.2004.09.017
Abstract
Pressure die cast AZ91 magnesium alloy contains both shrinkage and gas microporosity. Quantification and characterization of shrinkage and gas microporosity is expected to be useful to understand the processing-properties-microstructure correlations. However, conventional image analysis techniques d...
Published in: | Computational Materials Science |
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2005
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URI: | https://cronfa.swan.ac.uk/Record/cronfa17642 |
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2015-11-02T14:35:32.4912795 v2 17642 2014-04-01 Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys bd72868c48af6c0b04bf9f6bb48ce324 0000-0002-8812-8927 Leo Prakash Leo Prakash true false 2014-04-01 EAAS Pressure die cast AZ91 magnesium alloy contains both shrinkage and gas microporosity. Quantification and characterization of shrinkage and gas microporosity is expected to be useful to understand the processing-properties-microstructure correlations. However, conventional image analysis techniques do not permit a separate quantification and characterization of shrinkage and gas microporosity. A computational microstructural (image) analyzing technique has been developed by the use of a programming language to quantify and analyze the microporosity. The shrinkage microporosity and gas microporosity were separated by the above technique and the size distributions of the above micropores were quantified. A microstructural montage from the AZ91 magnesium alloy is created for getting better and consistent results. In addition the image analyzing technique is used to measure the nearest neighbor distance of the shrinkage and the gas microporosity, and to quantify the clustering tendency of the porosity. A new parameter is defined to characterize the affinity of gas pores with the shrinkage pores and vice versa. Journal Article Computational Materials Science 32 3-4 480 488 Gas pores; Shrinkage pores; Quantification; Computational microstructure analysis; Nearest neighbor distribution; Size distribution 3 3 2005 2005-03-03 10.1016/j.commatsci.2004.09.017 COLLEGE NANME Engineering and Applied Sciences School COLLEGE CODE EAAS Swansea University 2015-11-02T14:35:32.4912795 2014-04-01T10:12:44.4853120 Faculty of Science and Engineering School of Engineering and Applied Sciences - Materials Science and Engineering D.G. Leo Prakash 1 B. Prasanna 2 Doris Regener 3 Leo Prakash 0000-0002-8812-8927 4 |
title |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys |
spellingShingle |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys Leo Prakash |
title_short |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys |
title_full |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys |
title_fullStr |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys |
title_full_unstemmed |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys |
title_sort |
Computational microstructure analyzing technique for quantitative characterization of shrinkage and gas pores in pressure die cast AZ91 magnesium alloys |
author_id_str_mv |
bd72868c48af6c0b04bf9f6bb48ce324 |
author_id_fullname_str_mv |
bd72868c48af6c0b04bf9f6bb48ce324_***_Leo Prakash |
author |
Leo Prakash |
author2 |
D.G. Leo Prakash B. Prasanna Doris Regener Leo Prakash |
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Journal article |
container_title |
Computational Materials Science |
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32 |
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3-4 |
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480 |
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2005 |
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Swansea University |
doi_str_mv |
10.1016/j.commatsci.2004.09.017 |
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Faculty of Science and Engineering |
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Faculty of Science and Engineering |
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facultyofscienceandengineering |
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Faculty of Science and Engineering |
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School of Engineering and Applied Sciences - Materials Science and Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Materials Science and Engineering |
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description |
Pressure die cast AZ91 magnesium alloy contains both shrinkage and gas microporosity. Quantification and characterization of shrinkage and gas microporosity is expected to be useful to understand the processing-properties-microstructure correlations. However, conventional image analysis techniques do not permit a separate quantification and characterization of shrinkage and gas microporosity. A computational microstructural (image) analyzing technique has been developed by the use of a programming language to quantify and analyze the microporosity. The shrinkage microporosity and gas microporosity were separated by the above technique and the size distributions of the above micropores were quantified. A microstructural montage from the AZ91 magnesium alloy is created for getting better and consistent results. In addition the image analyzing technique is used to measure the nearest neighbor distance of the shrinkage and the gas microporosity, and to quantify the clustering tendency of the porosity. A new parameter is defined to characterize the affinity of gas pores with the shrinkage pores and vice versa. |
published_date |
2005-03-03T18:36:42Z |
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1821522266357235712 |
score |
11.047674 |