{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/20305"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/20305","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Modeling the microstructure development in gray iron castings","abstract":"Recent years have seen increasing use of solidification process modeling as a tool to aid in the analysis and elimination of manufacturing defects in castings. Grain size and other microstructural features such as second phase morphology and distribution are the primary factors in determining the mechanical properties in cast metals. In this work, a representation of nucleation and growth kinetics for gray cast irons, based on a statistical description of the microstructure, has been coupled with a commercial finite element method code for transient heat flow calculation to determine microstructure. Features predicted include eutectic cell size, fractions of gray and white iron, graphite morphology, percent pearlite, percent ferrite and pearlite spacing. The predicted microstructure can then he used to determine the strength and fatigue properties using published correlations. This model will provide a powerful tool in optimizing casting and design parameters of a component. The theoretical development and results of the finite element based model will be discussed and compared with experimental results.","abstract_html":"Recent years have seen increasing use of solidification process modeling as a tool to aid in the analysis and elimination of manufacturing defects in castings. Grain size and other microstructural features such as second phase morphology and distribution are the primary factors in determining the mechanical properties in cast metals. In this work, a representation of nucleation and growth kinetics for gray cast irons, based on a statistical description of the microstructure, has been coupled with a commercial finite element method code for transient heat flow calculation to determine microstructure. Features predicted include eutectic cell size, fractions of gray and white iron, graphite morphology, percent pearlite, percent ferrite and pearlite spacing. The predicted microstructure can then he used to determine the strength and fatigue properties using published correlations. This model will provide a powerful tool in optimizing casting and design parameters of a component. The theoretical development and results of the finite element based model will be discussed and compared with experimental results.","abstract_has_math":false,"creators":["Goettsch, David Douglas"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Mechanical Science and Engineering","degree_department":null,"school":null,"contributors":["Dantzig, Jonathan A."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T12:35:27Z","date_published":"2011-05-07T12:35:27Z","updated_at":"2026-07-22T22:25:15Z","subjects":["Engineering, Mechanical","Engineering, Metallurgy","Engineering, Materials Science"],"languages":["eng"],"rights":["Copyright 1991 Goettsch, David Douglas"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9210816","(UMI)AAI9210816"],"render_values":[{"text":"AAI9210816","href":null,"code":true},{"text":"(UMI)AAI9210816","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/20305","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dantzig, Jonathan A."]},{"key":"dc:creator","label":"Author","values":["Goettsch, David Douglas"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T12:35:27Z","10000-01-01","1991"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Science and Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Mechanical","Engineering, Metallurgy","Engineering, Materials Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1991 Goettsch, David Douglas"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9210816","(UMI)AAI9210816","http://hdl.handle.net/2142/20305"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Recent years have seen increasing use of solidification process modeling as a tool to aid in the analysis and elimination of manufacturing defects in castings. Grain size and other microstructural features such as second phase morphology and distribution are the primary factors in determining the mechanical properties in cast metals. In this work, a representation of nucleation and growth kinetics for gray cast irons, based on a statistical description of the microstructure, has been coupled with a commercial finite element method code for transient heat flow calculation to determine microstructure. Features predicted include eutectic cell size, fractions of gray and white iron, graphite morphology, percent pearlite, percent ferrite and pearlite spacing. The predicted microstructure can then he used to determine the strength and fatigue properties using published correlations. This model will provide a powerful tool in optimizing casting and design parameters of a component. The theoretical development and results of the finite element based model will be discussed and compared with experimental results.","Made available in DSpace on 2011-05-07T12:35:27Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9210816.pdf: 3901689 bytes, checksum: c7549312df0922e0e1332fbae1b95dce (MD5) Previous issue date: 1991","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:43:00Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:18:46-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["Modeling the microstructure development in gray iron castings"]}]}],"canonical_facts":{"dc:contributor":["Dantzig, Jonathan A."],"dc:creator":["Goettsch, David Douglas"],"dc:date":["2011-05-07T12:35:27Z","10000-01-01","1991"],"dc:description":["Recent years have seen increasing use of solidification process modeling as a tool to aid in the analysis and elimination of manufacturing defects in castings. Grain size and other microstructural features such as second phase morphology and distribution are the primary factors in determining the mechanical properties in cast metals. In this work, a representation of nucleation and growth kinetics for gray cast irons, based on a statistical description of the microstructure, has been coupled with a commercial finite element method code for transient heat flow calculation to determine microstructure. Features predicted include eutectic cell size, fractions of gray and white iron, graphite morphology, percent pearlite, percent ferrite and pearlite spacing. The predicted microstructure can then he used to determine the strength and fatigue properties using published correlations. This model will provide a powerful tool in optimizing casting and design parameters of a component. 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