The exact placement of the laminar–turbulent transition has a significant effect on relevant characteristics of the boundary layer and aerodynamics, such as drag, heat transfer and flow separation on e.g. wings and turbine blades. Tripping, which fixes the transition position, has been a valuable aid to wind-tunnel testing during the past 70 years, because it makes the transition independent of the local condition of the free-stream. Tripping helps to obey flow similarity for scaled models and serves as a passive control mechanism. Fundamental fluid-mechanics studies and many engineering developments are based on tripped cases. Therefore, it is essential for computational fluid dynamics (CFD) simulations to replicate the same forced transition, in spite of the advanced improvements in transition modelling. In the last decade, both direct numerical simulation (DNS) and large-eddy simulations (LES) include tripping methods in an effort to avoid the need for modeling the complex mechanisms associated with the natural transition process, which we would like to bring over to Reynolds-averaged Navier–Stokes (RANS) turbulence models. This paper investigates the implementation and performance of such a technique in RANS and specifically in the \(k-\omega\) SST model. This study assesses RANS tripping with three alternatives: First, a recent approach of turbulence generation, denoted as turbulence-injection method (kI), is evaluated and investigated through different test cases; second, a predefined transition point is used in a traditional transition model (denoted as IM method); and third a novel formulation combining the two previous methods is proposed, denoted \(\gamma -k\)I. The model is compared with DNS, LES and experimental data in a variety of test cases ranging from a turbulent boundary layer on a flat plate to the three-dimensional (3D) flow over a wing section. The desired tripping is achieved at the target location and the simulation results compare very well with the reference results. With the application of the novel model, the challenging transition region can be excluded from a simulation, and consequently more reliable results can be provided.

层状紊流过渡的确切位置，对边界层和空气动力学的相关特性，如阻力，热传递和流动上分离显著效果例如机翼和涡轮叶片。在过去的 70 年中，固定过渡位置的跳闸一直是风洞测试的宝贵帮助，因为它使过渡与当地的自由流条件无关。跳闸有助于遵守比例模型的流动相似性，并作为一种被动控制机制。基本的流体力学研究和许多工程开发都是基于绊倒的案例。因此，尽管过渡建模有了先进的改进，但计算流体动力学 (CFD) 模拟必须复制相同的强制过渡。在过去十年中，直接数值模拟 (DNS) 和大涡模拟 (LES) 都包括跳闸方法，以避免对与自然过渡过程相关的复杂机制进行建模，我们想把它带到雷诺平均 Navier-Stokes (RANS) 湍流模型中。本文研究了这种技术在 RANS 中的实现和性能，特别是在\(k-\omega\) SST 模型。本研究使用三种替代方案评估 RANS 跳闸：首先，通过不同的测试案例评估和研究了最近的湍流生成方法，称为湍流注入方法 ( k I)；其次，在传统的过渡模型（表示为IM方法）中使用预定义的过渡点；第三，提出了一种结合前两种方法的新公式，表示为\(\gamma -k\)I. 将模型与 DNS、LES 和各种测试案例中的实验数据进行比较，从平板上的湍流边界层到机翼截面上的三维 (3D) 流动。在目标位置实现了所需的跳闸，并且仿真结果与参考结果非常相近。通过应用新模型，可以从模拟中排除具有挑战性的过渡区域，从而可以提供更可靠的结果。