Advanced methods for the design of foundations for offshore wind energy structures

海上风能结构基础设计的先进方法

• 批准号: 2887289
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2887289
• 关键词: Advanced; methods; design; foundations; offshore

Advanced methods for the design of foundations for offshore wind energy structuresWith a large proportion of global greenhouse gas emissions coming from energy, the continued uptake of renewable energy sources is vital. Offshore wind forms an important component of the UK's energy supply. This motivates the exploration of novel engineering techniques to continue to increase the commercial viability of offshore wind. This project falls within the EPSRC wind power theme. The research will focus on geotechnical elements of offshore wind turbines, focussing on the behaviour of foundations.There is scope for the application of advanced computational procedures and data-driven approaches in all stages of an offshore wind project's lifecycle, from site selection to asset protection. The proposed research will focus on the development of these methods for the prediction of behaviour and design of foundations. The research will likely focus on monopile foundations, which form the most common foundation type for offshore wind turbines. The target audience for this research would be practitioners, with a research aim of developing novel, robust analysis techniques that can improve the design of foundations of offshore wind energy structures. The objective of these techniques will be to be rapid, whilst approaching the accuracy of computationally expensive high-fidelity models. This will enable more accurate parametric study and optioneering from designers, creating more optimal, cost-effective designs.Three-dimensional finite element analysis is typically employed for high fidelity modelling of soil-structure interaction of monopiles. This is computationally expensive, limiting its use for parametric study and optioneering. The research will explore methods to create models which are rapid, approaching the accuracy of three-dimensional finite element analysis. This can be achieved by creating surrogate machine learning models for the three-dimensional finite element analysis. Training data can be generated from the three-dimensional finite element analysis, capturing relevant information about the foundation's behaviour. Machine learning surrogate models can be trained on this data, with the aim of making rapid, accurate predictions. Previous research has applied this approach to make predictions of the foundations macro-element stiffness, which would be applied as a support condition at the base of models of the turbine super-structure. The student is currently sitting taught modules at the start of the course as part of the EPSRC funded Wind and Marine Energy Systems and Structures centre for doctoral training, so the research carried out may differ from the preliminary aims outlined in this description.

高级方法用于设计近海风能结构的基础，其中很大一部分来自能源的全球温室气体排放，可再生能源的持续吸收至关重要。海上风是英国能源供应的重要组成部分。这激发了对新型工程技术的探索，以继续提高海上风的商业生存能力。该项目属于EPSRC风电主题。该研究将重点关注海上风力涡轮机的岩土元素，重点关注地基的行为。 。拟议的研究将重点介绍这些方法的发展，以预测基础的行为和设计。这项研究可能会集中在单一基础上，该基础构成了海上风力涡轮机的最常见基础类型。这项研究的目标受众将是从业者，其研究目的是开发新颖的，可靠的分析技术，可以改善海上风能结构的基础设计。这些技术的目的将是快速的，同时接近计算昂贵的高保真模型的准确性。这将使更准确的参数研究和设计师的选项，创建更具最佳的，具有成本效益的设计。三维有限元分析通常用于对单物体土壤结构相互作用的高保真建模。这在计算上很昂贵，限制了其用于参数研究和选项的使用。该研究将探索创建快速模型的方法，以接近三维有限元分析的准确性。这可以通过为三维有限元分析创建替代机器学习模型来实现。可以从三维有限元分析中生成培训数据，从而捕获有关基金会行为的相关信息。机器学习替代模型可以在此数据上进行培训，目的是进行快速，准确的预测。先前的研究应用了这种方法来预测基础宏观元素刚度，该刚度将作为涡轮机超结构模型底部的支撑条件应用。该学生目前在课程开始时就坐着教授模块，这是EPSRC资助的风能和海洋能源系统与结构中心的博士培训中心，因此进行的研究可能与此描述中概述的初步目标有所不同。