An adaptive surface for improved modelling of rough wall bounded turbulence

用于改进粗糙壁边界湍流建模的自适应表面

• 批准号: DP240101743
• 负责人: Prof Nicholas Hutchins
• 金额: $ 32.22万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2024
• 资助国家: 澳大利亚
• 起止时间: 2024-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP240101743
• 关键词: adaptive; surface; improved; modelling; rough

This project aims to improve the prediction of drag where fluid flows over rough surfaces. This is a significant problem, with the uncertainty in drag penalty prediction for shipping alone exceeding ten billion dollars annually. The societal importance of these flows demands action, yet novel approaches must be sought to efficiently explore the wide range of roughness types encountered in practice. An adaptive surface is proposed, where a roughness configuration can be dialled in at the press of a button, to rapidly converge on improved models. A key outcome of this project will be improved predictive models of drag for rough wall flows. Benefits will include improved efficiencies and reduced emissions across a wide range of industries.

该项目的目的是改善流体在粗糙表面上流动的阻力预测。这是一个重大的问题，单独运输的阻力惩罚预测的不确定性每年超过1000亿美元。这些流量的社会重要性需要采取行动，但是必须寻求新颖的方法，以有效地探索实践中遇到的各种粗糙度类型。提出了一个自适应表面，可以在按钮的按下可以拨入粗糙度配置，以快速收敛改进的模型。该项目的关键结果将是改进粗糙壁流的阻力预测模型。收益将包括提高效率和各种行业的排放量减少。