Stochastic dynamic analysis of an offshore wind turbine (OWT) structure plays an important role in the structural safety evaluation and reliability assessment of the structure. In this paper, the OWT structure is simplified as a linear single-degree-of-freedom (SDOF) system and the corresponding joint probability density function (PDF) of the dynamic response is calculated by the implementation of the path integration (PI) method. Filtered Gaussian white noise, which is obtained from the utilization of a second-order filter, is considered as horizontal wind excitation and used to excite the SDOF system. Thus, the SDOF model and the second-order linear filter model constitute a four-dimensional dynamic system. Further, a detailed three-dimensional finite element model is applied to obtain the natural frequency of the OWT and the efficient PI method, which is modified based on the fast Fourier transform (FFT) convolution method, is also utilized to reduce the execution time to obtain the PDF of the response. Two important parameters of wind conditions, i.e., horizontal mean wind speed and turbulence standard deviation, are investigated to highlight the influences on the PDF of the dynamic response and the reliability of the OWT.

The construction of reservoir dams has changed the environment and natural properties of the river course, and deep-water reservoirs present an obvious phenomenon of thermal stratification. Low-temperature outflow water in spring and summer will have a negative impact on the downstream ecological environment. Therefore, it is necessary to take selective withdrawal measures to regulate low-temperature outflow water. The temperature-control curtain project has the advantages of low cost, convenient construction and wide application. Based on the topographic data, a laboratory test model for regulating outflow temperature by a temperature-control curtain is established. A high-power electric heating system is adopted to form a nonlinear thermal stratification. The accuracy of the test data is verified by the prototype observed water temperature. The main parameters affecting the outflow temperature are investigated, including thermal stratification, flow height above the temperature-control curtain, water level, and discharge flow. The results show the following: firstly, the outflow temperature mainly depends on the thermal stratification, decreases with the increase of water level, and increases with the increase of discharge flow; secondly, the effect of a temperature-control curtain on improving the outflow temperature is directly related to the thermal stratification in different months, and the improvement effect is better in spring and summer; finally, the improvement effect increases with the decrease of flow height above the temperature-control curtain, increases with the increase of water level, and decreases with the increase of discharge flow.

Low-temperature discharged water from thermally-stratified reservoirs in spring and summer will have a negative environmental impact on fish breeding and agricultural irrigation downstream. The temperature-control curtain (TCC) is a selective withdrawal structure that can effectively change the discharged water temperature. Compared with a traditional selective withdrawal project, a TCC project has the advantages of low cost and simple construction and can even be added to operating reservoirs without impacting power generation. Analysis of the load characteristics is the key to the application of TCC engineering. This paper establishes a three-dimensional numerical model simulation and verifies it with physical model experimental results. The crucial parameters affecting the load characteristics of TCC are investigated, including the water blocking rate, area ratio, inclination ratio, inflow velocity, and water temperature stratification ratio. The results show that: (1) This numerical simulation approach can be used to predict the drag coefficient and the load of a TCC; (2) the water blocking rate has the greatest influence on the drag coefficient, and it is the most critical indicator of the TCC load; and (3) the drag coefficient exponentially increases with an increasing water blocking rate, quadratically increases with an increasing area ratio, linearly increases with an increasing inclination ratio, and linearly increases with an increasing water temperature stratification ratio.