A new simulation and optimisation platform for marine technology

全新的海洋技术仿真和优化平台

• 批准号: EP/M011054/1
• 负责人: Matthew Piggott
• 金额: $ 55.39万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FM011054%2F1
• 关键词: new; simulation; optimisation; platform; marine

The coastal zone plays a crucial part in addressing two of the most pressing issues facing humanity: energy supply and water resources. Marine renewable energy and desalination are both characterised by the deployment of relatively small-scale technology (for example, tidal turbines, or desalination plant outfalls) in large-scale ocean flows. Understanding the multi-scale interactions between sub-metre scale installations and ocean currents over tens of kilometres is crucial for assessing environmental impacts, and for optimisation to minimise project costs or maximise profits. The vast range of scales and physical processes involved, and the need to optimise complex coupled systems, represent highly daunting software development and computational challenges. Geographically, the UK is uniquely positioned to become a world leader in marine renewable energy, but adequate software will be a key factor in determining the success of this new industry.To address this need, this project will re-engineer a unique CFD to marine scale modelling package to provide performance-portability, future-proofing and substantially increased capabilities. To motivate this we will target two applications: renewable energy generation via tidal turbine arrays and dense water discharge from desalination plants. Both are characterised by a common wide range of spatial and temporal scales, the need for design optimisation and accurate impact assessments, and a current lack of the required software.This project will build upon several world-leading open source software projects from the assembled multi-disciplinary research team. This team already has a long and successful track record of working together on the development of high quality open source software which is able to exploit large-scale high performance computing and has been used widely in academia and industry. In addition, the project has assembled a wide range of suitable project partners to aid in the delivery of the project as well as to promote longer term impact. These include complementary centres of excellence in cutting-edge software development, industry leaders in the targeted application areas, marine consultancies, and those contributing to environmental regulation.

沿海地区在解决人类面临的两个最紧迫的问题方面发挥着关键作用：能源供应和水资源。海洋可再生能源和海水淡化的特点都是在大规模海洋流动中部署相对较小规模的技术(例如潮汐涡轮机或海水淡化厂排污口)。了解亚米级设施与数十公里洋流之间的多尺度相互作用，对于评估环境影响以及优化项目成本或最大化利润至关重要。涉及范围广泛的规模和物理过程，以及优化复杂耦合系统的需要，都是非常令人望而生畏的软件开发和计算挑战。在地理上，英国在成为海洋可再生能源的世界领导者方面具有独特的地位，但足够的软件将是决定这一新行业成功的关键因素。为了满足这一需求，该项目将重新设计一个独特的CFD到海洋规模的建模程序包，以提供性能可携带性、面向未来和大幅增强的能力。为了推动这一目标，我们将瞄准两个应用：通过潮汐涡轮机阵列产生可再生能源，以及从海水淡化厂排放浓水。这两个项目的特点都是具有共同的广泛的空间和时间尺度，需要优化设计和准确的影响评估，以及目前缺乏所需的软件。这个项目将建立在汇集的多学科研究团队的几个世界领先的开放源码软件项目的基础上。这个团队在开发能够利用大规模高性能计算的高质量开源软件方面已经有了长期和成功的记录，并在学术界和工业界得到了广泛的应用。此外，该项目还召集了一大批合适的项目合作伙伴，以协助项目的实施，并促进更长期的影响。其中包括尖端软件开发方面的互补性卓越中心、目标应用领域的行业领先者、海洋咨询公司，以及那些对环境监管做出贡献的公司。

项目成果

Optimising tidal range power plant operation

• DOI: 10.1016/j.apenergy.2017.12.052
• 发表时间: 2018-02
• 期刊: Applied Energy
• 影响因子: 11.2
• 作者: A. Angeloudis;S. Kramer;A. Avdis;M. Piggott

Efficient unstructured mesh generation for marine renewable energy applications

• DOI: 10.1016/j.renene.2017.09.058
• 发表时间: 2018-02
• 期刊: Renewable Energy
• 影响因子: 8.7
• 作者: A. Avdis;A. Candy;Jon Hill;S. Kramer;M. Piggott

On the potential of linked-basin tidal power plants: An operational and coastal modelling assessment

关于相连盆地潮汐发电厂的潜力：运营和沿海建模评估

• DOI: 10.1016/j.renene.2020.03.167
• 发表时间: 2020
• 期刊: Renewable Energy
• 影响因子: 8.7
• 作者: Angeloudis A

Integration of cost modelling within the micro-siting design optimisation of tidal turbine arrays

• DOI: 10.1016/j.renene.2015.06.013
• 发表时间: 2016
• 期刊: Renewable Energy
• 影响因子: 8.7
• 作者: D. Culley;S. Funke;S. Kramer;M. Piggott

A surrogate-model assisted approach for optimising the size of tidal turbine arrays

• DOI: 10.1016/j.ijome.2017.05.001
• 发表时间: 2017-09
• 期刊: International Journal of Marine Energy
• 作者: D. Culley;S. Funke;S. Kramer;M. Piggott