Doctor of Philosophy
Civil and Environmental Engineering
Tropical cyclone (TC) induces strong winds, heavy rainfalls, and storm surge. They cause fatalities and property damages, especially in the coastal regions that are prone to TC hazards. The TC wind or wave assessments were reported in the literature. The assessment provides the required hazard characterizations for assessing the reliability and risk of structures such as onshore and offshore wind turbines (WTs). The present study considered sites near the coastline of mainland China. It is focused on 1) the assessment of using different historical best-track datasets on the development of stochastic TC track models and on the estimated TC wind hazard, 2) the establishment of a procedure to assess the joint TC wind and wave hazards, to assess their correlation, and the joint probabilistic model, 3) the development of a database-driven simulation-based (DDSB) framework to estimate the reliability of offshore WTs, and 4) the calibration of the design TC wind and wave loads and companion load factors for designing monopile onshore and offshore monopole WTs for selected target reliability indices, and recommend site-dependent and information-sensitive design TC wind and wave loads for such WTs.
For the analysis, both the historical best-track datasets from China Meteorological Administration (CMA) and from Joint Typhoon Warning Center (JTWC) are considered for developing the physical-based beta-advection model. The impact of using one or the other track database on the TC wind hazard is quantified. Based on the stochastic TC track model, available TC wind and wave field models, the joint TC wind and wave hazard is assessed. The quantified TC hazard indicates that the correlation of the extreme (annual or event-based) TC wind speed and wave height should not be neglected. It is proposed that the joint TC wind and wave hazards to assess the reliability of offshore WTs can be carried out according to a database-driven simulation-based procedure. This allows the combined use of synthetic tracks database, the prepared wind and wave fields database, and the structural response database of WTs subjected to combined wind and wave actions. The application of this procedure is shown for a semi-submersible WT. Moreover, the procedure is used to carry out reliability-based calibration of design TC wind and wave loads by considering monopile WTs that are placed on the onshore or offshore locations that are near the coastline of mainland China. Simple to use empirical equations are developed to evaluate the required return periods for evaluating the design TC wind and wave loads. These equations depend on the coefficient of variation of the annual maximum TC wind speed and significant wave height and the selected target reliability index. Also, maps of the required return periods, ranging from 50 to 500 years for two considered tolerable failure probability levels, are given for calculating the design wind load and wave load. The calibration analysis results also indicate that the companion load factor of 0.9 is to be considered for the wave load if the TC wind load is taken as the principal load and the wave force is dominated by the drag force component. This companion load factor becomes 0.85 if the TC wave load is dominated by the inertial force component. Also, the companion load factor of 0.85 for the wind load should be considered if the wave load acts as the principal load.
Summary for Lay Audience
Tropical cyclone (TC) induces strong winds, heavy rainfalls, and storm surge and causes devastating damages to properties and fatalities. This thesis mainly focused on the TC hazard assessment and the reliability analysis for wind turbines (WTs). TC wind and wave assessment provides the wind speed and wave height for various return periods for offshore sites. To facilitate and inform the design of structures for civil engineers, structural reliability analysis then needs to be carried out to examine the safety level implied in the current design codes or to recommend the safety factors for design code making.
The first topic of this thesis is about TC hazard modelling. In detail, chapter two presented a physical-based TC track model using environmental datasets. Furthermore, two historical best-track datasets are accessed and used to establish this track model. The differences between the historical and simulated tracks for statistics of TC characteristics and T-return period wind values were compared; chapter three uses a parametric wave model to assess TC wave hazard. This model is simple to use with only three input parameters. The marginal and joint probabilistic distributions for wind and wave were assessed, and the load combination analysis for offshore wind turbine design was carried out. Moreover, the hazard deaggregation analysis was performed, which is beneficial for the TC risk mitigations.
The remaining topic is about the reliability analysis for wind turbines subjected to TC hazards. Chapter four developed a database-driven simulation-based (DDSB) framework, which was mainly based on several synthesized databases. This procedure was applied to evaluate the failure probability of a floating WT located in the offshore region in China; chapter five carried out the reliability-based design code calibration for the onshore and offshore monopile WT. The site-specified wind and wave return periods were identified and simple to use empirical equations were developed to evaluate such required return periods. The companion load combination factors for TC wind and wave loads are calibrated.
In short, this thesis established the novel TC hazard wind and wave assessment approaches, developed a simulation-based framework for reliability assessment for offshore structures, and carried out the reliability-based design code calibration for WTs. This study could be valuable to enhance our understanding of TC risk for WT.
Sheng, Chao, "Assessment of Tropical Cyclone Wind and Wave Hazards and Their Effect on the Reliability of Wind Turbines" (2022). Electronic Thesis and Dissertation Repository. 8396.
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