In this paper, we present numerical modelling for the investigation of dynamic responses of a floating offshore wind turbine subject to focused waves. The modelling was carried out using a Computational Fluid Dynamics (CFD) tool. We started with the generation of a focused wave in a numerical wave tank based on a first-order irregular wave theory, then validated the developed numerical method for wave-structure interaction via a study of floating production storage and offloading (FPSO) to focused wave. Subsequently, we investigated the wave-/wind-structure interaction of a fixed semi-submersible platform, a floating semi-submersible platform and a parked National Renewable Energy Laboratory (NREL) 5 MW floating offshore wind turbine. To understand the nonlinear effect, which usually occurs under severe sea states, we carried out a systematic study of the motion responses, hydrodynamic and mooring tension loads of floating offshore wind turbine (FOWT) over a range of wave steepness, and compared the results obtained from two potential flow theory tools with each other, i.e., Électricité de France (EDF) in-house code and NREL Fatigue, Aerodynamics, Structures, and Turbulence (FAST). We found that the nonlinearity of the hydrodynamic loading and motion responses increase with wave steepness, revealed by higher-order frequency response, leading to the appearance of discrepancies among different tools.

The paper introduces a set of modelling methods to predict the failure probability of offshore wind turbines in the China coastal waters. In detail, a series of full-set three-dimensional meteorology simulations are conducted using the Weather Research and Forecast (WRF) model to provide the extreme wind fields while the extreme wave fields are predicted according to the conditional probability model. After the extreme wind and wave fields are prepared, the ultimate loads on the three critical parts of an OC4-DeepCwind semisubmersible wind turbine are simulated using the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) code, which in turn leads to the prediction of the failure probability. It has been found that the OC4-DeepCwind semisubmersible constructed in the Taiwan Strait has higher chance to fail under typhoon conditions than in other parts of the China coastal waters, showing a maximum failure probability of 0.6. In addition, the failure probabilities in the South and East China Sea are in the range of 0.3-0.45. The probability densities of the ultimate loads show, in some cases, a bimodal shape, which indicates that the loads as well as the failure probability are not in a simple linear relationship with the extreme wind speeds and wave heights/periods.

With the setting of wind energy harvesting moving from coastal waters to deep waters, the South China Sea has been deemed to offer great potential for the construction of floating wind farms thanks to the abundance of wind energy resources. An engineering model describing the wind profiles and wave spectra specific to the South China Sea conditions, which is the precondition for offshore wind farm construction, has, however, not yet been proposed. In the present study, a series of numerical simulations have been conducted using the Weather Forecast and Research model. Through analyzing the wind and wave information extracted from the numerical simulation results, engineering models to calculate vertical profiles of wind speeds and wave spectra have been postulated. While the present paper focuses on the wind profile model, a companion paper articulates the wave spectrum model. For wind profiles under typhoon conditions, the power-law and log-law models have been found applicable under the condition that the Hellmann exponent $\mathsf{\alpha }$ or the friction velocity $u_{*}$ are modified to vary with the wind strength. For wind profiles under non-typhoon conditions, the log-law model is revised to take into consideration the influence of the atmospheric stability.

In mechanical, electrical, and plumbing (MEP) systems, logic chains refer to the upstream and downstream connections between MEP components. Generating the logic chains of MEP systems can improve the efficiency of facility management (FM) activities, such as locating components and retrieving relevant maintenance information for prompt failure detection or for emergency responses. However, due to the amount of equipment and components in commercial MEP systems, manually creating such logic chains is tedious and fallible work. This paper proposes an approach to generate the logic chains of MEP systems using building information models (BIMs) semi-automatically. The approach consists of three steps: (1) the parametric and nonparametric spatial topological analysis within MEP models to generate a connection table, (2) the transformation of MEP systems and custom information requirements to generate the pre-defined and user-defined identification rules, and (3) the logic chain completion of MEP model based on the graph data structure. The approach was applied to a real-world project, which substantiated that the approach was able to generate logic chains of 15 MEP systems with an average accuracy of over 80%.