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dc.contributor.advisorGriffiths, D. V.
dc.contributor.authorBen Hassine, Jomâa
dc.date.accessioned2018-12-12T23:07:48Z
dc.date.accessioned2022-02-03T13:11:58Z
dc.date.available2018-12-12T23:07:48Z
dc.date.available2022-02-03T13:11:58Z
dc.date.issued2018
dc.identifierBenHassine_mines_0052E_11634.pdf
dc.identifierT 8627
dc.identifier.urihttps://hdl.handle.net/11124/172809
dc.descriptionIncludes bibliographical references.
dc.description2018 Fall.
dc.description.abstractWind turbine foundations transfer dynamic and highly eccentric loads to variable soils. The design of such foundations involves the verification of multiple limit states to ensure proper operation of the turbine and avoid catastrophic failures. An optimal foundation design minimizes cost while meeting all relevant limit states at quantifiable and acceptable risks. This dissertation explores three common limit states that are relevant to the design of shallow, gravity based, wind turbine foundations using a fully-probabilistic Monte Carlo Simulation (MCS) method, termed in this work as the direct Reliability Based Design (d-RBD) method. The three limit states are foundation tilt, rotational stiffness and bearing capacity. For each of these limit states, design variables are randomized using predefined probability density functions. The d-RBD method involves running Monte Carlo Simulations to produce realizations covering potential combinations of design decision variables such as foundation dimensions (e.g. width and/or depth). The d-RBD method uses Bayesian conditional probability theory to select the geometry combinations that meet the predefined target probability of failure. With this approach, a single MCS run is needed to identify pools of acceptable designs for each limit state from which an optimal design meeting all limit states can be selected. This dissertation introduces d-RBD as a direct, fully probabilistic design procedure that offers important advantages over global factor (ASD/WSD) or partial factor (LSD/LRFD) design methods. For each of the limit states under consideration, d-RBD is used to highlight the cost of uncertainty, rank the design variables by their importance and assess the effects of pertinent variability assumptions. The findings from this work are relevant to ongoing efforts to develop international and U.S. standards for the design of wind turbine support structures and their foundations.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2018 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectfoundation design
dc.subjectMonte Carlo simulation
dc.subjectwind energy
dc.subjectlimit state design
dc.subjectdesign optimization
dc.subjectreliability-based design
dc.titleDirect reliability-based design (d-RBD) of shallow wind turbine foundations
dc.typeText
dc.contributor.committeememberJohnson, Kathryn E.
dc.contributor.committeememberKiousis, Panagiotis Demetrios, 1956-
dc.contributor.committeememberGuerra, Andres
thesis.degree.nameDoctor of Philosophy (Ph.D.)
thesis.degree.levelDoctoral
thesis.degree.disciplineCivil and Environmental Engineering
thesis.degree.grantorColorado School of Mines


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