{"id":{"repo_id":"vcu","oai_identifier":"oai:scholarscompass.vcu.edu:etd-1354"},"canonical_url":"https://search.dev.ndltd.org/etd/vcu/oai:scholarscompass.vcu.edu:etd-1354","repository":{"repo_id":"vcu","name":"Virginia Commonwealth University","base_url":"https://scholarscompass.vcu.edu/do/oai/"},"display":{"title":"GENERATION, MECHANICAL AND STATISTICAL ANALYSIS, AND FEM SIMULATION OF FRACTURE OF REPEATABLE RANDOM ROUGH SURFACES","abstract":"Natural weathering and wear of structural materials in service nearly always generate surface roughness, and follow the Central Limit Theorem prediction for surface topology. This study couples experimental and statistical theory, and FEM to extend knowledge of life of materials from initial service surface conditions through surface damage accumulation. Statistical moments and other parameters were correlated with fracture locations probability (H/N), versus auto correlation length, and depth. As the surface grows to a full Gaussian, H/N increases its dependence on profile’s Average and RMS Roughness, and derived parameters. This dependence shows an asymptotic limit behavior that approaches agreeably Griffith’s crack criterion, though with multiple pit locations. Importantly, a Transitional Region was observed, below which the probable location of fracture is uncorrelated to the parameters studied. This is because introduced roughness is insufficient to compete with impurities, internal and external manufacturing flaws, and scratches, due to handling and machining, on the samples.","abstract_html":"Natural weathering and wear of structural materials in service nearly always generate surface roughness, and follow the Central Limit Theorem prediction for surface topology. This study couples experimental and statistical theory, and FEM to extend knowledge of life of materials from initial service surface conditions through surface damage accumulation. Statistical moments and other parameters were correlated with fracture locations probability (H/N), versus auto correlation length, and depth. As the surface grows to a full Gaussian, H/N increases its dependence on profile’s Average and RMS Roughness, and derived parameters. This dependence shows an asymptotic limit behavior that approaches agreeably Griffith’s crack criterion, though with multiple pit locations. Importantly, a Transitional Region was observed, below which the probable location of fracture is uncorrelated to the parameters studied. This is because introduced roughness is insufficient to compete with impurities, internal and external manufacturing flaws, and scratches, due to handling and machining, on the samples.","abstract_has_math":false,"creators":["Medina, Hector"],"institution":null,"degree_name":"Master of Science","degree_level":"Thesis","degree_discipline":"Mechanical and Nuclear Engineering","degree_department":null,"school":null,"contributors":["Brian Hinderliter"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-04-11T07:00:00Z","date_published":"2012-04-11T07:00:00Z","updated_at":"2026-07-24T05:53:48Z","subjects":["random","roughness","fracture","PMMA","surface","mechanical","statistics","Engineering"],"languages":[],"rights":["© The Author"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarscompass.vcu.edu/etd/355"],"render_values":[{"text":"https://scholarscompass.vcu.edu/etd/355","href":"https://scholarscompass.vcu.edu/etd/355","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.25772/X1PG-MA04","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Brian Hinderliter"]},{"key":"dc:creator","label":"Author","values":["Medina, Hector"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2017-05-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical and Nuclear Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["random","roughness","fracture","PMMA","surface","mechanical","statistics","Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["© The Author"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.25772/X1PG-MA04","https://scholarscompass.vcu.edu/etd/355"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Natural weathering and wear of structural materials in service nearly always generate surface roughness, and follow the Central Limit Theorem prediction for surface topology. This study couples experimental and statistical theory, and FEM to extend knowledge of life of materials from initial service surface conditions through surface damage accumulation. Statistical moments and other parameters were correlated with fracture locations probability (H/N), versus auto correlation length, and depth. As the surface grows to a full Gaussian, H/N increases its dependence on profile’s Average and RMS Roughness, and derived parameters. This dependence shows an asymptotic limit behavior that approaches agreeably Griffith’s crack criterion, though with multiple pit locations. Importantly, a Transitional Region was observed, below which the probable location of fracture is uncorrelated to the parameters studied. This is because introduced roughness is insufficient to compete with impurities, internal and external manufacturing flaws, and scratches, due to handling and machining, on the samples."]},{"key":"dc:title","label":"Title","values":["GENERATION, MECHANICAL AND STATISTICAL ANALYSIS, AND FEM SIMULATION OF FRACTURE OF REPEATABLE RANDOM ROUGH SURFACES"]}]}],"canonical_facts":{"dc:contributor":["Brian Hinderliter"],"dc:creator":["Medina, Hector"],"dc:date.available":["2017-05-14T07:00:00Z"],"dc:description.abstract":["Natural weathering and wear of structural materials in service nearly always generate surface roughness, and follow the Central Limit Theorem prediction for surface topology. This study couples experimental and statistical theory, and FEM to extend knowledge of life of materials from initial service surface conditions through surface damage accumulation. Statistical moments and other parameters were correlated with fracture locations probability (H/N), versus auto correlation length, and depth. As the surface grows to a full Gaussian, H/N increases its dependence on profile’s Average and RMS Roughness, and derived parameters. This dependence shows an asymptotic limit behavior that approaches agreeably Griffith’s crack criterion, though with multiple pit locations. Importantly, a Transitional Region was observed, below which the probable location of fracture is uncorrelated to the parameters studied. This is because introduced roughness is insufficient to compete with impurities, internal and external manufacturing flaws, and scratches, due to handling and machining, on the samples."],"dc:identifier":["https://doi.org/10.25772/X1PG-MA04","https://scholarscompass.vcu.edu/etd/355"],"dc:rights":["© The Author"],"dc:subject":["random","roughness","fracture","PMMA","surface","mechanical","statistics","Engineering"],"dc:title":["GENERATION, MECHANICAL AND STATISTICAL ANALYSIS, AND FEM SIMULATION OF FRACTURE OF REPEATABLE RANDOM ROUGH SURFACES"],"thesis:degree_discipline":["Mechanical and Nuclear Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T05:53:48Z"}