{"id":{"repo_id":"unlv","oai_identifier":"oai:oasis.library.unlv.edu:rtds-2492"},"canonical_url":"https://search.dev.ndltd.org/etd/unlv/oai:oasis.library.unlv.edu:rtds-2492","repository":{"repo_id":"unlv","name":"University of Nevada - Las Vegas","base_url":"https://oasis.library.unlv.edu/do/oai/"},"display":{"title":"Improving resolution of stiff layers in soil profiles through multi-step inversion of Sasw data","abstract":"Stiff, cemented layers commonly encountered in desert soil profiles significantly affect the soil load capacity and load distribution pattern. The purpose of this research is to develop algorithms for detecting stiff layers through inversion of seismic surface wave data to generate one-dimensional shear wave velocity (VS) profiles; The inversion algorithms begin with a starting model. Development of a high-quality starting model helps ensure good results; Two inversion methods, simulated annealing (SA) and linearized inversion (LI), are applied to the problem. The SA method includes a general approach (SA-G) and an approach developed specifically to investigate stiff-inclusion systems (SA-I). Algorithms for applying these methods are developed and tested using two experimental datasets and two synthetic datasets, one of each pair being normally dispersive and the other having one or more stiff inclusions. For the stiff-inclusion experimental site, results are compared to a crosshole dataset. (Abstract shortened by UMI.).","abstract_html":"Stiff, cemented layers commonly encountered in desert soil profiles significantly affect the soil load capacity and load distribution pattern. The purpose of this research is to develop algorithms for detecting stiff layers through inversion of seismic surface wave data to generate one-dimensional shear wave velocity (VS) profiles; The inversion algorithms begin with a starting model. Development of a high-quality starting model helps ensure good results; Two inversion methods, simulated annealing (SA) and linearized inversion (LI), are applied to the problem. The SA method includes a general approach (SA-G) and an approach developed specifically to investigate stiff-inclusion systems (SA-I). Algorithms for applying these methods are developed and tested using two experimental datasets and two synthetic datasets, one of each pair being normally dispersive and the other having one or more stiff inclusions. For the stiff-inclusion experimental site, results are compared to a crosshole dataset. (Abstract shortened by UMI.).","abstract_has_math":false,"creators":["Liu, Haiyan"],"institution":"University of Nevada, Las Vegas","degree_name":"Master of Engineering (ME)","degree_level":"Thesis","degree_discipline":"Civil and Environmental Engineering","degree_department":null,"school":null,"contributors":["Barbara A. Luke"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003-01-01T08:00:00Z","date_published":"2003-01-01T08:00:00Z","updated_at":"2026-07-24T05:25:33Z","subjects":[],"languages":["English"],"rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://oasis.library.unlv.edu/rtds/1493"],"render_values":[{"text":"https://oasis.library.unlv.edu/rtds/1493","href":"https://oasis.library.unlv.edu/rtds/1493","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.25669/g1yz-9lna","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Barbara A. 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For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10.25669/g1yz-9lna","https://oasis.library.unlv.edu/rtds/1493","https://oasis.library.unlv.edu/context/rtds/article/2492/viewcontent/uc.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Stiff, cemented layers commonly encountered in desert soil profiles significantly affect the soil load capacity and load distribution pattern. The purpose of this research is to develop algorithms for detecting stiff layers through inversion of seismic surface wave data to generate one-dimensional shear wave velocity (VS) profiles; The inversion algorithms begin with a starting model. Development of a high-quality starting model helps ensure good results; Two inversion methods, simulated annealing (SA) and linearized inversion (LI), are applied to the problem. The SA method includes a general approach (SA-G) and an approach developed specifically to investigate stiff-inclusion systems (SA-I). Algorithms for applying these methods are developed and tested using two experimental datasets and two synthetic datasets, one of each pair being normally dispersive and the other having one or more stiff inclusions. For the stiff-inclusion experimental site, results are compared to a crosshole dataset. (Abstract shortened by UMI.)."]},{"key":"dc:format","label":"Dc Format","values":["pdf"]},{"key":"dc:title","label":"Title","values":["Improving resolution of stiff layers in soil profiles through multi-step inversion of Sasw data"]}]}],"canonical_facts":{"dc:contributor":["Barbara A. Luke"],"dc:creator":["Liu, Haiyan"],"dc:description.abstract":["Stiff, cemented layers commonly encountered in desert soil profiles significantly affect the soil load capacity and load distribution pattern. The purpose of this research is to develop algorithms for detecting stiff layers through inversion of seismic surface wave data to generate one-dimensional shear wave velocity (VS) profiles; The inversion algorithms begin with a starting model. Development of a high-quality starting model helps ensure good results; Two inversion methods, simulated annealing (SA) and linearized inversion (LI), are applied to the problem. The SA method includes a general approach (SA-G) and an approach developed specifically to investigate stiff-inclusion systems (SA-I). Algorithms for applying these methods are developed and tested using two experimental datasets and two synthetic datasets, one of each pair being normally dispersive and the other having one or more stiff inclusions. For the stiff-inclusion experimental site, results are compared to a crosshole dataset. (Abstract shortened by UMI.)."],"dc:format":["pdf"],"dc:identifier":["10.25669/g1yz-9lna","https://oasis.library.unlv.edu/rtds/1493","https://oasis.library.unlv.edu/context/rtds/article/2492/viewcontent/uc.pdf"],"dc:language":["English"],"dc:publisher":["University of Nevada, Las Vegas"],"dc:rights":["IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Improving resolution of stiff layers in soil profiles through multi-step inversion of Sasw data"],"dc:type":["Text"],"thesis:degree_discipline":["Civil and Environmental Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Engineering (ME)"]},"updated_at":"2026-07-24T05:25:33Z"}