Validation of CFD predictions for flow over a full-scale formula student vehicle using PIV in real conditions

Oskar Wengrzyn
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Abstract

Computational Fluid Dynamics (CFD) predictions are becoming an industry standard. They allow for making accurate predictions of complex problems without requiring extensive real-world testing, as well as saving time and money. However, it has been proven many times that the classic Reynoldsaveraged Navier – Stokes (RANS) approach has its flaws and fails to provide highly accurate predictions. Even though CFD only approaches a physical solution, which can be reached only in very specific applica-tions, it usually provides enough precision for engineering purposes. To reach a convergence with real-world physics, plenty of factors must be taken into consideration like mesh, boundary conditions, and turbulence models. In order to obtain a CFD simulation that accurately represents real physics, some kind of real-world validation must take place. For aerodynamics, it is usually done in wind tunnels, which are expensive to run but provide controllable conditions to match those specified in CFD. One of the many methods used to validate the calculations is Particle Image Velocimetry (PIV). This study tries to validate CFD of a Formula Student car using PIV, but in realworld conditions, without wind tunnel. The compact size of equipment required for PIV testing and flexibility of CFD boundary conditions allow for that.
在实际条件下使用PIV验证全尺寸方程式学生车辆流动的CFD预测
计算流体动力学(CFD)预测正在成为行业标准。它们允许对复杂问题做出准确的预测,而不需要大量的实际测试,同时也节省了时间和金钱。然而,已经多次证明,经典的雷诺平均纳维-斯托克斯(RANS)方法有其缺陷,无法提供高度准确的预测。尽管CFD只接近物理解决方案,只有在非常特定的应用中才能达到,但它通常为工程目的提供了足够的精度。为了达到与现实世界物理的收敛,必须考虑许多因素,如网格、边界条件和湍流模型。为了获得准确代表真实物理的CFD模拟,必须进行某种真实世界的验证。对于空气动力学,通常在风洞中进行,风洞的运行成本很高,但提供了与CFD中指定的条件相匹配的可控条件。用于验证计算的许多方法之一是粒子图像测速(PIV)。本研究试图利用PIV验证学生方程式赛车的CFD,但在现实条件下,没有风洞。PIV测试所需设备的紧凑尺寸和CFD边界条件的灵活性允许这一点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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