Development of Adaptive CFD Tools for Study of Tornadic Wind Field

开发用于研究龙卷风场的自适应 CFD 工具

• 批准号: 239167-2012
• 负责人: Cao, Jun
• 金额: $ 1.46万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570586
• 关键词: Development; Adaptive; CFD; Tools; Study

Tornadoes are more frequently reported in Canada than any other country except the United States. This type of disastrous weather may inflict colossal property damage and even take numerous human lives. Since the study of tornado dynamics relying on field observations and laboratory experiments is usually expensive, restrictive, and time-consuming, computer simulation mainly via the large eddy simulation (LES) or the Reynolds average Navier-Stokes (RANS) method has become a more attractive research direction in shedding light on the intricate characteristics of a tornadic wind field. However, these two turbulence models have their respective drawbacks, which might confine the applicability of the computer modeling approach if only one turbulence model is employed throughout a tornado simulation. Also, most tornado numerical simulations are performed using commercial software packages that are often incapable of generating properly adaptive meshes suitable for various time-dependent tornado cases. In order to overcome such major bottlenecks faced by the tornado modeling community, this research will be composed of two objectives: (1) developing a novel tornado model based on the partially resolved numerical simulation (PRNS) concept so that the LES, RANS and the Direct Navier-Stokes (DNS) methods can be unified into a seamless hybrid, more suitably accommodating the need for simulation of various tornadic wind fields; and (2) deriving a brand new 3-D RANS-based a posteriori error estimation framework that can independently guide a finite element mesh to be adapted for different time-dependent tornado scenarios without needing to select adaptive criteria on a case-by-case basis. The outcome of the two streams will be implemented in commercial computational fluid dynamics (CFD) code with the aid of an extensive suite of user-designed subroutines targeted at adaptive simulation of a variety of tornadic wind fields over configurations of differently deployed surface constructions. Using the adaptive simulation results, the impact of tornadoes on ground buildings will be more accurately examined, leading to valuable insight and guidance for improving design of constructions towards better wind-resistant capabilities.

加拿大比除美国以外的任何其他国家都更频繁地报告龙卷风。这种灾害性天气可能造成巨大的财产损失，甚至夺去无数人的生命。由于龙卷风动力学的研究依赖于现场观测和实验室实验通常是昂贵的，限制性的，和耗时的，主要通过大涡模拟（LES）或雷诺平均Navier-Stokes（RANS）方法的计算机模拟已成为一个更有吸引力的研究方向，揭示龙卷风风场的复杂特性。然而，这两个湍流模型有各自的缺点，这可能会限制计算机建模方法的适用性，如果只有一个湍流模型是采用整个龙卷风模拟。此外，大多数龙卷风的数值模拟是使用商业软件包，往往无法生成适当的自适应网格适合于各种时间依赖的龙卷风的情况下进行。为了克服龙卷风数值模拟所面临的主要瓶颈，本研究将包括两个目标：（1）发展一种基于部分分辨数值模拟（PRNS）概念的新型龙卷风模型，使LES、RANS和直接Navier-Stokes（DNS）方法能够统一为一种无缝的混合方法，更适合于各种龙卷风风场的模拟需要;以及（2）导出全新的基于3-D RANS的后验误差估计框架，其可以独立地引导有限元网格适应于不同的时间相关龙卷风场景，而不需要在逐个情况的基础上选择自适应准则。这两个流的结果将在商业计算流体动力学（CFD）代码中实施，并借助一套广泛的用户设计的子程序，这些子程序的目标是在不同部署表面结构的配置上对各种龙卷风风场进行自适应模拟。使用自适应模拟结果，将更准确地检查龙卷风对地面建筑物的影响，从而为改善建筑物的设计以提高抗风能力提供有价值的见解和指导。