{"id":{"repo_id":"queens","oai_identifier":"oai:queensu.scholaris.ca:1974/36415"},"canonical_url":"https://search.dev.ndltd.org/etd/queens/oai:queensu.scholaris.ca:1974/36415","repository":{"repo_id":"queens","name":"Queens University","base_url":"https://qspace.library.queensu.ca/server/oai/request"},"display":{"title":"Reliability analyses for foundation and soil reinforcement applications","abstract":"Geotechnical engineering is moving towards performance-based design using probabilistic approaches. This thesis focuses on the reliability analysis for selected topics including pile foundations, mechanically stabilized earth (MSE) walls and soil nail walls. The lognormal distribution is widely used to represent geotechnical parameters, such as pile resistance model bias, due to its non-negative property and mathematical simplicity. However, pile resistance bias data may exhibit multi-modal behaviour and complex tails not captured by lognormal distributions. This thesis uses the Kernel distribution to fit the measured bias data and proposes for the first time a non-parametric framework for reliability analysis and resistance factor calibration of pile foundations. The sensitivity of the probability of failure and resistance factor to probability distribution type is evaluated. A closed-form solution and Monte Carlo simulation methods are commonly used for the reliability analysis of mechanically stabilized earth (MSE) walls. Although widely adopted elsewhere, the first order reliability method (FORM) has not been applied to MSE walls. The thesis modifies an existing spreadsheet-based FORM framework to incorporate model uncertainty and presents the first application of FORM to MSE walls. Sensitivity indicators are used to quantify the relative influence of each probabilistic input parameter to identify the most influential parameter. Soil nails may be inserted into soils with bedding structures at different orientations. This thesis examines for the first time the influence of such cases on probabilistic margins of safety for a typical soil nail arrangement by assigning rotated anisotropic random fields of soil strength parameters aligned with the bedding structure. The results using rotated anisotropic random fields on statistical outcomes for the computed global factor of safety are compared to results using homogeneous and isotropic random fields, and deterministic analyses. The range of factor of safety for all random field cases is small and remains in the vicinity of the deterministic value. This is ascribed to the soil nails anchoring the entire reinforced soil domain together and preventing preferential failure paths. The thesis is in manuscript form. The four main chapters (papers) share the common theme of reliability analysis of geotechnical soil-structure systems.","abstract_html":"Geotechnical engineering is moving towards performance-based design using probabilistic approaches. This thesis focuses on the reliability analysis for selected topics including pile foundations, mechanically stabilized earth (MSE) walls and soil nail walls. The lognormal distribution is widely used to represent geotechnical parameters, such as pile resistance model bias, due to its non-negative property and mathematical simplicity. However, pile resistance bias data may exhibit multi-modal behaviour and complex tails not captured by lognormal distributions. This thesis uses the Kernel distribution to fit the measured bias data and proposes for the first time a non-parametric framework for reliability analysis and resistance factor calibration of pile foundations. The sensitivity of the probability of failure and resistance factor to probability distribution type is evaluated. A closed-form solution and Monte Carlo simulation methods are commonly used for the reliability analysis of mechanically stabilized earth (MSE) walls. Although widely adopted elsewhere, the first order reliability method (FORM) has not been applied to MSE walls. The thesis modifies an existing spreadsheet-based FORM framework to incorporate model uncertainty and presents the first application of FORM to MSE walls. Sensitivity indicators are used to quantify the relative influence of each probabilistic input parameter to identify the most influential parameter. Soil nails may be inserted into soils with bedding structures at different orientations. This thesis examines for the first time the influence of such cases on probabilistic margins of safety for a typical soil nail arrangement by assigning rotated anisotropic random fields of soil strength parameters aligned with the bedding structure. The results using rotated anisotropic random fields on statistical outcomes for the computed global factor of safety are compared to results using homogeneous and isotropic random fields, and deterministic analyses. The range of factor of safety for all random field cases is small and remains in the vicinity of the deterministic value. This is ascribed to the soil nails anchoring the entire reinforced soil domain together and preventing preferential failure paths. The thesis is in manuscript form. The four main chapters (papers) share the common theme of reliability analysis of geotechnical soil-structure systems.","abstract_has_math":false,"creators":["Wang, Sutang"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Civil Engineering","school":null,"contributors":[],"advisors":["Bathurst, Richard"],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-05-21","date_published":"2026-05-21","updated_at":"2026-07-27T20:35:21Z","subjects":["Compression piles","Mechanically stabilized earth (MSE) walls","Soil nail walls","Kernel distribution","Reliability theory-based design","Resistance factor calibration","Bootstrapping","First order reliability method (FORM)","Reliability index","Probability of failure","Finite difference model (FDM)","Numerical modelling","Soil bedding structure","Rotated anisotropic random field"],"languages":["eng"],"rights":["Attribution-NonCommercial-NoDerivatives 4.0 International"],"rights_urls":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1974/36415","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Civil Engineering"]},{"key":"dc:contributor.supervisor","label":"Supervisor","values":["Bathurst, Richard"]},{"key":"dc:creator","label":"Author","values":["Wang, Sutang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-05-21T18:15:24Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-05-21"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Compression piles","Mechanically stabilized earth (MSE) walls","Soil nail walls","Kernel distribution","Reliability theory-based design","Resistance factor calibration","Bootstrapping","First order reliability method (FORM)","Reliability index","Probability of failure","Finite difference model (FDM)","Numerical modelling","Soil bedding structure","Rotated anisotropic random field"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Attribution-NonCommercial-NoDerivatives 4.0 International"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1974/36415"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Geotechnical engineering is moving towards performance-based design using probabilistic approaches. This thesis focuses on the reliability analysis for selected topics including pile foundations, mechanically stabilized earth (MSE) walls and soil nail walls. The lognormal distribution is widely used to represent geotechnical parameters, such as pile resistance model bias, due to its non-negative property and mathematical simplicity. However, pile resistance bias data may exhibit multi-modal behaviour and complex tails not captured by lognormal distributions. This thesis uses the Kernel distribution to fit the measured bias data and proposes for the first time a non-parametric framework for reliability analysis and resistance factor calibration of pile foundations. The sensitivity of the probability of failure and resistance factor to probability distribution type is evaluated. A closed-form solution and Monte Carlo simulation methods are commonly used for the reliability analysis of mechanically stabilized earth (MSE) walls. Although widely adopted elsewhere, the first order reliability method (FORM) has not been applied to MSE walls. The thesis modifies an existing spreadsheet-based FORM framework to incorporate model uncertainty and presents the first application of FORM to MSE walls. Sensitivity indicators are used to quantify the relative influence of each probabilistic input parameter to identify the most influential parameter. Soil nails may be inserted into soils with bedding structures at different orientations. This thesis examines for the first time the influence of such cases on probabilistic margins of safety for a typical soil nail arrangement by assigning rotated anisotropic random fields of soil strength parameters aligned with the bedding structure. The results using rotated anisotropic random fields on statistical outcomes for the computed global factor of safety are compared to results using homogeneous and isotropic random fields, and deterministic analyses. The range of factor of safety for all random field cases is small and remains in the vicinity of the deterministic value. This is ascribed to the soil nails anchoring the entire reinforced soil domain together and preventing preferential failure paths. The thesis is in manuscript form. The four main chapters (papers) share the common theme of reliability analysis of geotechnical soil-structure systems."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["PhD"]},{"key":"dc:title","label":"Title","values":["Reliability analyses for foundation and soil reinforcement applications"]}]}],"canonical_facts":{"dc:contributor.department":["Civil Engineering"],"dc:contributor.supervisor":["Bathurst, Richard"],"dc:creator":["Wang, Sutang"],"dc:date.accessioned":["2026-05-21T18:15:24Z"],"dc:date.issued":["2026-05-21"],"dc:description.abstract":["Geotechnical engineering is moving towards performance-based design using probabilistic approaches. This thesis focuses on the reliability analysis for selected topics including pile foundations, mechanically stabilized earth (MSE) walls and soil nail walls. The lognormal distribution is widely used to represent geotechnical parameters, such as pile resistance model bias, due to its non-negative property and mathematical simplicity. However, pile resistance bias data may exhibit multi-modal behaviour and complex tails not captured by lognormal distributions. This thesis uses the Kernel distribution to fit the measured bias data and proposes for the first time a non-parametric framework for reliability analysis and resistance factor calibration of pile foundations. The sensitivity of the probability of failure and resistance factor to probability distribution type is evaluated. A closed-form solution and Monte Carlo simulation methods are commonly used for the reliability analysis of mechanically stabilized earth (MSE) walls. Although widely adopted elsewhere, the first order reliability method (FORM) has not been applied to MSE walls. The thesis modifies an existing spreadsheet-based FORM framework to incorporate model uncertainty and presents the first application of FORM to MSE walls. Sensitivity indicators are used to quantify the relative influence of each probabilistic input parameter to identify the most influential parameter. Soil nails may be inserted into soils with bedding structures at different orientations. This thesis examines for the first time the influence of such cases on probabilistic margins of safety for a typical soil nail arrangement by assigning rotated anisotropic random fields of soil strength parameters aligned with the bedding structure. The results using rotated anisotropic random fields on statistical outcomes for the computed global factor of safety are compared to results using homogeneous and isotropic random fields, and deterministic analyses. The range of factor of safety for all random field cases is small and remains in the vicinity of the deterministic value. This is ascribed to the soil nails anchoring the entire reinforced soil domain together and preventing preferential failure paths. The thesis is in manuscript form. The four main chapters (papers) share the common theme of reliability analysis of geotechnical soil-structure systems."],"dc:description.degree":["PhD"],"dc:identifier.uri":["https://hdl.handle.net/1974/36415"],"dc:language.iso":["eng"],"dc:rights":["Attribution-NonCommercial-NoDerivatives 4.0 International"],"dc:rights.uri":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:subject":["Compression piles","Mechanically stabilized earth (MSE) walls","Soil nail walls","Kernel distribution","Reliability theory-based design","Resistance factor calibration","Bootstrapping","First order reliability method (FORM)","Reliability index","Probability of failure","Finite difference model (FDM)","Numerical modelling","Soil bedding structure","Rotated anisotropic random field"],"dc:title":["Reliability analyses for foundation and soil reinforcement applications"],"dc:type":["thesis"]},"updated_at":"2026-07-27T20:35:21Z"}