PhD Dissertation – Xuan Li

Date of Event: 08/26/2020

Start Time: 11:00 am


Department of Civil & Environmental Engineering
University of Connecticut

Xuan Li
PhD dissertation

11:00 AM – Wednesday, August 26th, 2020



Advisory Committee:

Dr. Wei Zhang (Major Advisor)
Dr. Richard Christenson (Associate Advisor)
Dr. Amvrossios C. Bagtzoglou (Associate Advisor)
Dr. Jiong Tang (Associate Advisor)

Dynamic Performance of Coastal and Offshore Structures under Combined Wind and Wave Loadings


Civil structures located in the coastal or offshore regions are subjected to continuous wind and wave loads and structural reliability and survivability could be deteriorated significantly especially during extreme weather events. Detailed analyses of wind and wave characteristics, interactions between wind and wave loads and structures, and structural performances under such loads are essential to be carried out. Depending on structural locations, both environmental characteristics and structural types might be substantially different, and therefore focuses on the structural performance are usually different. Structures located in the coastal region are subjected to wind and wave with less dependency and coastal structural assessment is usually performed under extreme weather events with high return period to inspect the structural survivability. Meanwhile, waves usually get dissipated while arriving at the shorelines by some resilience options. However, offshore structures located in deep seas are subjected to higher wind and more violent wave with strong correlations. The complicated and harsh environmental conditions at deep seas could inevitability result in larger structural dynamic responses. With years of service, fatigue damages could be critical and affect structural safety and serviceability.

A general numerical framework in structural performance assessment for both coastal and offshore structures under wind and wave loads is developed in this dissertation. Two typical coastal and offshore structures are discussed. For coastal residential buildings, a combination of computational fluid dynamics (CFD) simulation and finite element modeling (FEM) is implemented to evaluate the building vulnerability during extreme weather events. Furthermore, the effect of breakwaters serving as the coastal protective measure on the building safety is also investigated. For floating offshore wind turbines, both statistical models and machine learning models are applied to evaluate fatigue damage accumulations considering uncertainties from realistic environmental conditions. The canonical vine (C-vine) copula model is established to model the multivariate dependency structure for on-site wind and wave-related environmental parameters. Two surrogate models, including the Kriging model and the artificial neural network (ANN), are used to efficiently predict short-term fatigue damages at critical locations. A novel physics-informed deep learning model is also established to efficiently obtain structural dynamic responses under different disturbances.


Published: August 14, 2020