{"id":{"repo_id":"embry-riddle","oai_identifier":"oai:commons.erau.edu:db-theses-1299"},"canonical_url":"https://search.dev.ndltd.org/etd/embry-riddle/oai:commons.erau.edu:db-theses-1299","repository":{"repo_id":"embry-riddle","name":"Embry Riddle Aeronautical University","base_url":"https://commons.erau.edu/do/oai/"},"display":{"title":"Composite Structure Ultimate Strength Prediction from Acoustic Emission Amplitude Data","abstract":"<p>The acoustic emission (AE) given off by a structure as it is stressed provides a passive means to characterize flaw growth activity in complex structures. This thesis demonstrates how the qualitative analysis of AE data can be refined to provide a quantitative tool for predicting the ultimate strength of composite tensile test specimens. From an original sample set of only six specimens, a multivariate statistical analysis was used to generate an ultimate strength prediction equation. The variables of the multivariate statistical analysis were obtained through the mathematical modeling of the specimen’s AE amplitude distributions produced during proof testing. Ultimate strengths were then accurately predicted at proof stresses less than 25% of the expected failure stress for five randomly drawn tensile coupons. The results of this and previously conducted composite pressure vessel research demonstrate the ability to accurately predict ultimate strengths in composite structures using AE amplitude distribution data.</p>","abstract_html":"&lt;p&gt;The acoustic emission (AE) given off by a structure as it is stressed provides a passive means to characterize flaw growth activity in complex structures. This thesis demonstrates how the qualitative analysis of AE data can be refined to provide a quantitative tool for predicting the ultimate strength of composite tensile test specimens. From an original sample set of only six specimens, a multivariate statistical analysis was used to generate an ultimate strength prediction equation. The variables of the multivariate statistical analysis were obtained through the mathematical modeling of the specimen’s AE amplitude distributions produced during proof testing. Ultimate strengths were then accurately predicted at proof stresses less than 25% of the expected failure stress for five randomly drawn tensile coupons. The results of this and previously conducted composite pressure vessel research demonstrate the ability to accurately predict ultimate strengths in composite structures using AE amplitude distribution data.&lt;/p&gt;","abstract_has_math":false,"creators":["Walker, James Lewis, II"],"institution":null,"degree_name":"Master of Science in Aeronautical Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Aeronautical Science","degree_department":null,"school":null,"contributors":["Eric v. K. Hill","David Kim","Habib Eslami"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1990,"date_issued":"1990-12-01T08:00:00Z","date_published":"1990-12-01T08:00:00Z","updated_at":"2026-07-27T19:26:16Z","subjects":["composite structure","acoustic emission","Aerospace Engineering","Other Mechanical Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/db-theses/219","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Eric v. K. 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This thesis demonstrates how the qualitative analysis of AE data can be refined to provide a quantitative tool for predicting the ultimate strength of composite tensile test specimens. From an original sample set of only six specimens, a multivariate statistical analysis was used to generate an ultimate strength prediction equation. The variables of the multivariate statistical analysis were obtained through the mathematical modeling of the specimen’s AE amplitude distributions produced during proof testing. Ultimate strengths were then accurately predicted at proof stresses less than 25% of the expected failure stress for five randomly drawn tensile coupons. The results of this and previously conducted composite pressure vessel research demonstrate the ability to accurately predict ultimate strengths in composite structures using AE amplitude distribution data.</p>"]},{"key":"dc:title","label":"Title","values":["Composite Structure Ultimate Strength Prediction from Acoustic Emission Amplitude Data"]}]}],"canonical_facts":{"dc:contributor":["Eric v. K. Hill","David Kim","Habib Eslami"],"dc:creator":["Walker, James Lewis, II"],"dc:description.abstract":["<p>The acoustic emission (AE) given off by a structure as it is stressed provides a passive means to characterize flaw growth activity in complex structures. This thesis demonstrates how the qualitative analysis of AE data can be refined to provide a quantitative tool for predicting the ultimate strength of composite tensile test specimens. From an original sample set of only six specimens, a multivariate statistical analysis was used to generate an ultimate strength prediction equation. The variables of the multivariate statistical analysis were obtained through the mathematical modeling of the specimen’s AE amplitude distributions produced during proof testing. Ultimate strengths were then accurately predicted at proof stresses less than 25% of the expected failure stress for five randomly drawn tensile coupons. The results of this and previously conducted composite pressure vessel research demonstrate the ability to accurately predict ultimate strengths in composite structures using AE amplitude distribution data.</p>"],"dc:identifier":["https://commons.erau.edu/db-theses/219"],"dc:subject":["composite structure","acoustic emission","Aerospace Engineering","Other Mechanical Engineering"],"dc:title":["Composite Structure Ultimate Strength Prediction from Acoustic Emission Amplitude Data"],"thesis:degree_discipline":["Aeronautical Science"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Aeronautical Engineering"]},"updated_at":"2026-07-27T19:26:16Z"}