Development of machine learning approaches to geotechnical design of marine renewable energy foundations
Development of machine learning approaches to geotechnical design of marine renewable energy foundations
批准号:
2611858
负责人:
金额:
$0.0万
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
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英文摘要
This project will develop an optimisation tool that allows for geotechnical and foundation design considerations to be incorporated into windfarm layout optimisation, along with the wind and energy generation conditions that are typically focused on in literature. After developing a Neural Network based automated design tool that rapidly emulates cutting edge single monopile design techniques, optimisation and/or genetic programming will be used to carry out whole site design based on various design constraints. The project is directly applicable to the ongoing efforts to transition to renewable energy.The automated pile design methodology will be validated and tested using laboratory tests carried out with the geotechnical centrifuge and/or numerical modelling. The windfarm layout optimisation methodology will be demonstrated using site data from windfarm developments.The project will take advantage of the extensive geotechnical laboratory facilities alongside maritime and machine learning strengths at Southampton.
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国内基金
海外基金
Understanding structural evolution of galaxies with machine learning
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批准号:
-
项目类别:省市级项目
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资助金额:10.0万元
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批准年份:2022
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负责人:Nicola Rosario Napolitano
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依托单位:
非标准随机调度模型的最优动态策略
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批准号:71071056
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项目类别:面上项目
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资助金额:28.0万元
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批准年份:2010
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负责人:吴贤毅
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依托单位:
微生物发酵过程的自组织建模与优化控制
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批准号:60704036
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项目类别:青年科学基金项目
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资助金额:21.0万元
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批准年份:2007
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负责人:高学金
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依托单位: