Development of Adaptive CFD Tools for Study of Tornadic Wind Field

除美国外，加拿大龙卷风的报告频率比其他任何国家都要高。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。由于依赖于现场观测和实验室实验的龙卷风动力学研究通常是昂贵的、受限的和耗时的，主要通过大涡模拟(LES)或雷诺平均N-S(RANS)方法进行计算机模拟已成为揭示龙卷风风场复杂特征的一个更有吸引力的研究方向。然而，这两种湍流模型都有其各自的缺陷，如果在整个龙卷风模拟过程中只使用一种湍流模型，则可能会限制计算机模拟方法的适用性。此外，大多数龙卷风数值模拟都是使用商业软件包进行的，这些软件包往往无法生成适用于各种与时间相关的龙卷风情况的适当自适应网格。为了克服龙卷风模型界面临的这些主要瓶颈，这项研究将包括两个目标：(1)基于部分分辨数值模拟(PRNS)的概念开发一个新的龙卷风模式，使LES、RANS和Direct Navier-Stokes(DNS)方法能够统一为一个无缝的混合方法，更适合于模拟各种龙卷风风场；以及(2)推导出全新的基于三维RANS的后验误差估计框架，该框架可以独立地指导有限元网格适应不同的时间相关龙卷风情景，而不需要根据具体情况选择适应标准。这两个气流的结果将在商业计算流体动力学(CFD)代码中实施，并借助于一套广泛的用户设计子程序，目标是对不同部署的地面结构配置上的各种龙卷风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提高抗风能力提供有价值的见解和指导。

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.