Strategies for reducing cost of Engineering Optimisation

风电场模拟中CFD方法的改进。该项目旨在推进风能领域CFD模拟过程中使用的数值方法。该项目有两个截然不同的研究领域：涡轮机水平和农场水平。在涡轮机层面，正在利用GPU技术开发速度更快、高保真、适合优化的数值方法。随后，代码将与布里斯托尔大学开发的结构求解器和奇异值分解形状优化框架相结合，以促进涡轮叶片的气动结构优化。在农场一级，正在开发一种GPU加速求解器，以结合滑移面网格，允许以较低的计算成本对多个移动的涡轮叶片进行建模。该项目这一部分的主要目标是捕捉涡轮叶片上的非定常尾迹效应，从而能够更准确地更准确地预测叶片的疲劳寿命行为。

Improvements on CFD methods used in wind farm simulations. This project seeks to advance numerical methods used during CFD simulations in the wind energy sector. The project has two distinct fields of study: turbine level, and farm level. At turbine level GPU technology is being utilised develop faster, high-fidelity numerical methods, suitable for optimisation. Following this, the code will be coupled with a structural solver and SVD shape optimisation framework developed at the University of Bristol, to facilitate Aero-structural optimisation of turbine blades. At the farm level, a GPU accelerated solver is being developed to incorporate slip-plane meshing, allowing the modelling of multiple moving turbine blades at a reduced computational cost. The key aim for this part of the project is to capture unsteady wake effects on turbine blades, and thus be able to more accurately more and predict the fatigue life behavior of the blades.