{"id":{"repo_id":"texas","oai_identifier":"oai:repositories.lib.utexas.edu:2152/23383"},"canonical_url":"https://search.dev.ndltd.org/etd/texas/oai:repositories.lib.utexas.edu:2152/23383","repository":{"repo_id":"texas","name":"University of Texas","base_url":"https://repositories.lib.utexas.edu/server/oai/request"},"display":{"title":"Analysis of gas differential diffusion through porous media using prompt gamma activation analysis","abstract":"Accurate estimates for the molecular transport coefficients are critical to predicting the movement of gases in geological media. Here I present a novel methodology for using prompt gamma activation analysis to measure the effective diffusivity of noble gases in a porous medium. I also present a model to estimate the connectivity parameter of a soil from measurements of its saturated conductivity, macro porosity, and pore volume and pore surface fractal dimensions. Experiments with argon or xenon diffusing through a nitrogen saturated geological media were conducted. The noble gas concentration variations at its source were measured using prompt gamma activation analysis and later compared to a numerical diffusion model to estimate the effective diffusion coefficient. Numerical simulations using the estimated diffusivity and the experimental argon data produced results with a correlation parameter R² = 0.98. However, neglecting transport mechanisms other than diffusion largely under-predicted the xenon depletion rates observed during the first hours of experiment. To explain these results, a second model was developed which included the effect of pressure gradients and bulk convection that might arise from the faster molecular migration of the light species in a non-equimolar system and gravitational currents. Finally, the fractal model developed for this dissertation was used to estimate the connectivity parameters and walking fractal dimension of a group of geological samples that were previously characterized. This model successfully predicted positive connectivity factors and walking fractal dimensions between two and three for every sample analyzed.","abstract_html":"Accurate estimates for the molecular transport coefficients are critical to predicting the movement of gases in geological media. Here I present a novel methodology for using prompt gamma activation analysis to measure the effective diffusivity of noble gases in a porous medium. I also present a model to estimate the connectivity parameter of a soil from measurements of its saturated conductivity, macro porosity, and pore volume and pore surface fractal dimensions. Experiments with argon or xenon diffusing through a nitrogen saturated geological media were conducted. The noble gas concentration variations at its source were measured using prompt gamma activation analysis and later compared to a numerical diffusion model to estimate the effective diffusion coefficient. Numerical simulations using the estimated diffusivity and the experimental argon data produced results with a correlation parameter R² = 0.98. However, neglecting transport mechanisms other than diffusion largely under-predicted the xenon depletion rates observed during the first hours of experiment. To explain these results, a second model was developed which included the effect of pressure gradients and bulk convection that might arise from the faster molecular migration of the light species in a non-equimolar system and gravitational currents. Finally, the fractal model developed for this dissertation was used to estimate the connectivity parameters and walking fractal dimension of a group of geological samples that were previously characterized. This model successfully predicted positive connectivity factors and walking fractal dimensions between two and three for every sample analyzed.","abstract_has_math":false,"creators":["Rios-Perez, Carlos Alfredo, 1981-"],"institution":"The University of Texas at Austin","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Deinert, Mark"],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-12","date_published":"2013-12","updated_at":"2026-07-24T05:01:22Z","subjects":["Prompt gamma activation analysis","Differential diffusion","Fractals","Connectivity parameter"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2152/23383","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Deinert, Mark"]},{"key":"dc:creator","label":"Author","values":["Rios-Perez, Carlos Alfredo, 1981-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-03T16:40:10Z"]},{"key":"dc:date.issued","label":"Date","values":["2013-12"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Texas at Austin"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Prompt gamma activation analysis","Differential diffusion","Fractals","Connectivity parameter"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/2152/23383"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["text"]},{"key":"dc:description.abstract","label":"Abstract","values":["Accurate estimates for the molecular transport coefficients are critical to predicting the movement of gases in geological media. Here I present a novel methodology for using prompt gamma activation analysis to measure the effective diffusivity of noble gases in a porous medium. I also present a model to estimate the connectivity parameter of a soil from measurements of its saturated conductivity, macro porosity, and pore volume and pore surface fractal dimensions. Experiments with argon or xenon diffusing through a nitrogen saturated geological media were conducted. The noble gas concentration variations at its source were measured using prompt gamma activation analysis and later compared to a numerical diffusion model to estimate the effective diffusion coefficient. Numerical simulations using the estimated diffusivity and the experimental argon data produced results with a correlation parameter R² = 0.98. However, neglecting transport mechanisms other than diffusion largely under-predicted the xenon depletion rates observed during the first hours of experiment. To explain these results, a second model was developed which included the effect of pressure gradients and bulk convection that might arise from the faster molecular migration of the light species in a non-equimolar system and gravitational currents. Finally, the fractal model developed for this dissertation was used to estimate the connectivity parameters and walking fractal dimension of a group of geological samples that were previously characterized. This model successfully predicted positive connectivity factors and walking fractal dimensions between two and three for every sample analyzed."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Analysis of gas differential diffusion through porous media using prompt gamma activation analysis"]}]}],"canonical_facts":{"dc:contributor.advisor":["Deinert, Mark"],"dc:creator":["Rios-Perez, Carlos Alfredo, 1981-"],"dc:date.accessioned":["2014-03-03T16:40:10Z"],"dc:date.issued":["2013-12"],"dc:description":["text"],"dc:description.abstract":["Accurate estimates for the molecular transport coefficients are critical to predicting the movement of gases in geological media. Here I present a novel methodology for using prompt gamma activation analysis to measure the effective diffusivity of noble gases in a porous medium. I also present a model to estimate the connectivity parameter of a soil from measurements of its saturated conductivity, macro porosity, and pore volume and pore surface fractal dimensions. Experiments with argon or xenon diffusing through a nitrogen saturated geological media were conducted. The noble gas concentration variations at its source were measured using prompt gamma activation analysis and later compared to a numerical diffusion model to estimate the effective diffusion coefficient. Numerical simulations using the estimated diffusivity and the experimental argon data produced results with a correlation parameter R² = 0.98. However, neglecting transport mechanisms other than diffusion largely under-predicted the xenon depletion rates observed during the first hours of experiment. To explain these results, a second model was developed which included the effect of pressure gradients and bulk convection that might arise from the faster molecular migration of the light species in a non-equimolar system and gravitational currents. Finally, the fractal model developed for this dissertation was used to estimate the connectivity parameters and walking fractal dimension of a group of geological samples that were previously characterized. This model successfully predicted positive connectivity factors and walking fractal dimensions between two and three for every sample analyzed."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/2152/23383"],"dc:subject":["Prompt gamma activation analysis","Differential diffusion","Fractals","Connectivity parameter"],"dc:title":["Analysis of gas differential diffusion through porous media using prompt gamma activation analysis"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["The University of Texas at Austin"]},"updated_at":"2026-07-24T05:01:22Z"}