{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/80034"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/80034","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Statistical Inference of Heterogeneous Surface Catalycity Models Using Simulated Laser Absorption Spectroscopy in Reacting Flow","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Adowski, Timothy; 0000-0001-6215-0379"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Bauman, Paul","Mechanical and Aerospace Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-07-30T15:12:00Z","date_published":"2019-07-30T15:12:00Z","updated_at":"2026-07-27T19:05:23Z","subjects":["aerospace engineering"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/80034","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bauman, Paul","Mechanical and Aerospace Engineering"]},{"key":"dc:creator","label":"Author","values":["Adowski, Timothy; 0000-0001-6215-0379"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-07-30T15:12:00Z","2019","2019-05-17 17:19:17"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["aerospace engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/80034"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","With the current widespread availability of large scale computing resources, modeling of complex physical systems governed by partial differential equations (PDEs) is becoming commonplace in many engineering and scientific disciplines. Methods and tools to gain an understanding of the effects of uncertainty in the predicted states of these complex systems are of great current interest. A critical step towards this goal is the solution of statistical inverse problems to allow us to incorporate uncertainty in underlying physical models, and subsequently into model predictions. The development of such methodologies and tools are at the forefront of research in computational science and high-performance computing and is a major open problem in general.This dissertation focuses on the development of a computational framework for solving statistical inverse problems in complex multiphysics systems, with application to heterogeneous surface catalycity in the context of chemically reacting flows. Furthermore, this work provides infrastructure for experimental design in the presence of uncertainty wherein the selection of experimental scenarios to gather data is informed by a quantitative comparison of simulated potential experiments. These developments provide a robust framework to facilitate minimizing the number of costly physical experiments that must be performed in order to best inform the unknown model parameters."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Statistical Inference of Heterogeneous Surface Catalycity Models Using Simulated Laser Absorption Spectroscopy in Reacting Flow"]}]}],"canonical_facts":{"dc:contributor":["Bauman, Paul","Mechanical and Aerospace Engineering"],"dc:creator":["Adowski, Timothy; 0000-0001-6215-0379"],"dc:date":["2019-07-30T15:12:00Z","2019","2019-05-17 17:19:17"],"dc:description":["Ph.D.","With the current widespread availability of large scale computing resources, modeling of complex physical systems governed by partial differential equations (PDEs) is becoming commonplace in many engineering and scientific disciplines. Methods and tools to gain an understanding of the effects of uncertainty in the predicted states of these complex systems are of great current interest. A critical step towards this goal is the solution of statistical inverse problems to allow us to incorporate uncertainty in underlying physical models, and subsequently into model predictions. The development of such methodologies and tools are at the forefront of research in computational science and high-performance computing and is a major open problem in general.This dissertation focuses on the development of a computational framework for solving statistical inverse problems in complex multiphysics systems, with application to heterogeneous surface catalycity in the context of chemically reacting flows. Furthermore, this work provides infrastructure for experimental design in the presence of uncertainty wherein the selection of experimental scenarios to gather data is informed by a quantitative comparison of simulated potential experiments. These developments provide a robust framework to facilitate minimizing the number of costly physical experiments that must be performed in order to best inform the unknown model parameters."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/80034"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["aerospace engineering"],"dc:title":["Statistical Inference of Heterogeneous Surface Catalycity Models Using Simulated Laser Absorption Spectroscopy in Reacting Flow"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:23Z"}