Numerical simulation and modelling of non-equilibrium flows in hydro-power applications

水力发电应用中非平衡流的数值模拟和建模

• 批准号: 514642-2017
• 负责人: Piomelli, Ugo
• 金额: $ 3.42万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=662238
• 关键词: Numerical; simulation; modelling; non; equilibrium

This proposal addresses a problem of critical importance for the hydroelectric power industry, the development**of accurate models for the prediction of the flow over rough surfaces, in turbulence far from equilibrium. Two**cases will be considered: a separating flow in a curved duct, and the flow in a rough channel undergoing system**rotation. We will use direct and large-eddy simulations (DNS and LES) of turbulence to validate the models**for the Reynolds-Averaged Navier-Stokes equations that are commonly used in industry. Although the DNS**and LES will be performed at Reynolds numbers lower than those in actual applications, the LES should be**able to achieve the fully rough regime that allows to extend the simulation results to practical applications. The**proposed research will benefit Canada in several ways: first, it will train one PhD student and one PDF in the**computational sciences; secondly, it will generate fundamental knowledge on the physics of rough-wall**boundary layers in the presence of swirl, curvature, system rotation and separation. Finally, it will develop**prediction models that will benefit the power generation industry (and may be extended to other areas of**application), and can potentially result in significant efficiency increases and financial savings.

这一建议解决了一个对水电行业至关重要的问题，即开发准确的模型来预测远离平衡的湍流中粗糙表面上的流动。将考虑两种**情形：弯曲管道中的分离流动和经历系统**旋转的粗糙通道中的流动。我们将使用湍流的直接和大涡模拟(DNS和LES)来验证工业中常用的雷诺平均Navier-Stokes方程的模型。虽然数值模拟和大涡模拟的雷诺数都小于实际应用中的雷诺数，但大涡模拟应该能够**达到完全粗略的状态，从而将模拟结果扩展到实际应用中。**拟议的研究将在几个方面使加拿大受益：第一，它将在**计算科学方面培训一名博士生和一名PDF；第二，它将产生关于存在漩涡、曲率、系统旋转和分离的粗糙壁**边界层物理的基本知识。最后，它将开发**预测模型，这些模型将使发电行业受益(并可能扩展到**应用的其他领域)，并可能显著提高效率和节省资金。