{"678307":{"#nid":"678307","#data":{"type":"event","title":"PhD Defense by Nadine Fahed","body":[{"value":"\u003Cp\u003ESchool of Civil and Environmental Engineering\u003C\/p\u003E\u003Cp\u003EPh.D. Thesis Defense Announcement\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EINPUT-STATE ESTIMATION OF INELASTIC STRUCTURAL SYSTEMS: THEORETICAL FRAMEWORK AND EXPERIMENTAL VALIDATION\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EBy\u003Cstrong\u003E\u0026nbsp;Nadine Fahed\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdvisors:\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. Lauren Stewart (CEE) \u0026amp; Dr. Yang Wang (CEE)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECommittee Members:\u003Cstrong\u003E\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. Ryan Sherman (CEE)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. Danny Smyl (CEE)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDr. Gilbert Hegemier (UCSD)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EDate and Time:\u003Cstrong\u003E\u0026nbsp; November 21, 2024.\u0026nbsp; 12:00 pm EST (9:00 am PT)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ELocation:\u0026nbsp;Price Gilbert 4222\u003C\/p\u003E\u003Cp\u003EVirtual:\u0026nbsp;\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/95533168584\u0022\u003E\u003Cstrong\u003Ehttps:\/\/gatech.zoom.us\/j\/95533168584\u003C\/strong\u003E\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESystem identification through online estimation algorithms allows for a\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ecomprehensive understanding, prediction, and assessment of the intricate\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ebehaviors exhibited by complex in-situ systems in a variety of applications. This\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emodel-based technique leverages the system\u0027s noisy output data and integrates\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eexisting mathematical physics-based models to infer the unknown inputs or\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eunobservable dynamic states. The adoption of these online techniques in real-world\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Esettings has gained momentum over the past several years, owing to their ease of\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eimplementation, the robustness and reliability of the results, and the continuous\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eadvancements in sensing technologies. Furthermore, when structural systems are loaded beyond their elastic limit, they exhibit inelastic behavior which necessitate\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Edifferent methods to accommodate this complex nonlinear phenomenon. This\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Edissertation contributes to this research area by developing a robust framework that\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eintegrates hysteretic models with nonlinear stochastic filtering methods to quantify\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ethe input characteristics of systems exhibiting inelastic behavior due to material\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eplasticity.\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003ETowards this goal, an input-state estimator for linear systems is first\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eestablished. The estimator is designed to reduce the dependency on heuristically\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Echosen input statistics by incorporating an online input covariance updating routine.\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003ENumerical and experimental validation is conducted, the results of which highlight\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ethe robustness of the estimator in successfully tracking the input and state time\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Ehistory for various initialized input statistics. The estimator is then extended to\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Enonlinear systems using an Extended Kalman framework. To efficiently model the\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Esystem dynamics in the presence of hysteresis or plastic deformation, two modeling\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eapproaches of the continuum system are explored: an equivalent single degree of\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Efreedom formulation combined with a uniaxial Bouc-Wen model and a planar\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emultiaxial hysteretic beam model. A comprehensive numerical validation of the\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eproposed framework is conducted to gain insight into the performance of the\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Einelastic models and the estimation algorithm. The results underscored the\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eeffectiveness of the proposed estimator and integrated models in successfully\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Echaracterizing the input and states in the presence of nonlinearities in the system.\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003EFinally, the framework is experimentally validated using data collected from a beam\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Esubjected to an impact at its midspan. The novel estimator, along with the integrated\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emodels, adequately tracked the impulsive load. As such, these efforts represent an\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Eimportant contribution to the experimental validation of joint input-state estimation\u003C\/strong\u003E\u003Cbr\u003E\u003Cstrong\u003Emethods for inelastic continuum structures subjected to high-rate dynamic inputs.\u003C\/strong\u003E\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EINPUT-STATE ESTIMATION OF INELASTIC STRUCTURAL SYSTEMS: THEORETICAL FRAMEWORK AND EXPERIMENTAL VALIDATION\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"INPUT-STATE ESTIMATION OF INELASTIC STRUCTURAL SYSTEMS: THEORETICAL FRAMEWORK AND EXPERIMENTAL VALIDATION"}],"uid":"27707","created_gmt":"2024-11-08 19:52:36","changed_gmt":"2024-11-08 19:53:07","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-11-21T12:00:00-05:00","event_time_end":"2024-11-21T14:00:00-05:00","event_time_end_last":"2024-11-21T14:00:00-05:00","gmt_time_start":"2024-11-21 17:00:00","gmt_time_end":"2024-11-21 19:00:00","gmt_time_end_last":"2024-11-21 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Price Gilbert 4222","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}