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.

加拿大发生龙卷风的频率高于除美国以外的任何其他国家。这种灾难性天气可能会造成巨大的财产损失，甚至夺去无数人的生命。由于依赖现场观测和实验室实验的龙卷风动力学研究通常成本高昂、限制性大且耗时，因此主要通过大涡模拟（LES）或雷诺平均纳维-斯托克斯（RANS）方法进行计算机模拟已成为一种更有效的方法。揭示龙卷风场复杂特征的有吸引力的研究方向。然而，这两种湍流模型都有各自的缺点，如果在整个龙卷风模拟中仅采用一种湍流模型，则可能会限制计算机建模方法的适用性。此外，大多数龙卷风数值模拟是使用商业软件包执行的，这些软件包通常无法生成适合各种依赖时间的龙卷风情况的适当自适应网格。为了克服龙卷风建模界面临的主要瓶颈，本研究将由两个目标组成：（1）开发一种基于部分解析数值模拟（PRNS）概念的新型龙卷风模型，使 LES、RANS 和直接纳维斯托克斯（DNS）方法可以统一为无缝混合，更适合适应各种龙卷风场模拟的需要； (2) 推导一个全新的基于 3-D RANS 的后验误差估计框架，该框架可以独立指导有限元网格适应不同的时间相关龙卷风场景，而无需根据具体情况选择自适应标准基础。这两个流的结果将在商业计算流体动力学（CFD）代码中实现，并借助一套广泛的用户设计的子程序，这些子程序旨在对不同部署的表面结构的配置上的各种龙卷风场进行自适应模拟。利用自适应模拟结果，将更准确地检查龙卷风对地面建筑物的影响，从而为改进建筑设计以获得更好的抗风能力提供宝贵的见解和指导。