Flow Simulations around a Generic Ground Transportation System: Using Immersed Boundary Method

Zhang

Flow Turbulence Combust

et al. 2018

Recent experimental investigations by McArthur et al. (J. Fluids Struct. 66, 293-314, 2016) in the wake of a simplified heavy vehicle or commonly known as the ground transportation system (GTS) model has shown that the flow topology is invariant over a large range of Reynolds numbers [2.7 × 10 4 − 2 × 10 6 ]. Numerical simulations are performed to investigate the initial flow topology at a Reynolds number of 2.7 × 10 4 , using well-resolved large eddy simulations (LES). In the vertical midplane behind the GTS, a flow state which is anti-symmetric to that reported in McArthur et al. (J. Fluids Struct. 66, 293-314, 2016) is observed here, thereby, confirming the possibility of occurrence of the complementary bi-stable flow state. The occurrence of this bi-stable state does not depend on the ground clearance between the GTS and the ground plane, as a similar flow topology is observed at both small and large gap heights. Furthermore, the flow topology in the vertical midplane is also found to be insensitive to the incoming flow for small yaw angles. However, complex flow behaviour is observed in the wake for larger yaw angles, where the flow topology in the vertical midplane becomes nearly symmetric, while an asymmetric flow topology is now observed in the lateral midplane in the near wake. Furthermore, the corner vortices which originate from either side at the front of the model merge in the far wake, leading to a large vortex structure nearly equal to the height of the model. The near-wake topology of the GTS is analysed and compared with previous studies for a range of scenarios, and the forces on the GTS are computed.

Section: Introductionmentioning

confidence: 99%

An LES Investigation of the Near-Wake Flow Topology of a Simplified Heavy Vehicle

Zhang

Flow Turbulence Combust

et al. 2018

“…The mean flow topology in this plane is asymmetrical, and consists of a large triangular-shaped vortex on one side, with an elliptical-shaped vortex located opposite to it, and a pair of counter-rotating vortices is observed in the lateral midplane (also see McArthur et al (2016) and Rao et al (2018b) for a detailed description of the flow topology). Previous studies using RANS (Reynolds-averaged Navier-Stokes) turbulence models have failed to accurately predict the asymmetrical flow topology in the vertical midplane (Salari et al (2004), Roy et al (2006), Ghias et al (2008)). LES for a truncated GTS model by Ortega et al (2004) and detached eddy simulations (DES) by Unaune et al (2005) showed a flow topology in the vertical midplane which is anti-symmetric to that observed in the experiments, while the URANS (unsteady Reynolds-averaged Navier-Stokes) k À ε RNG turbulence model used by Gunes (2010) showed a flow topology similar to the experimental studies at Re ¼ 2 Â 10 6 .…”

Section: Introductionmentioning

confidence: 99%

Investigation of the near-wake flow topology of a simplified heavy vehicle using PANS simulations

Journal of Wind Engineering and Industrial Aerodynamics

Zhang

et al. 2018

The near-wake flow topology of a ground transportation system (GTS) is investigated using partially-averaged Navier-Stokes (PANS) simulations at Re ¼ 2:7 Â 10 4. Recent numerical investigations for the GTS model using large eddy simulations (LES) showed an anti-symmetric flow topology (flow state II) in the vertical midplane compared to that observed in previous experimental studies (flow state I). The geometrical configuration of the GTS permits bi-stable behaviour, and the realisation of each of the two flow states, which are characterised by an asymmetrical flow topology, is achieved by varying the differencing scheme for the convective flux in the PANS simulations; AVL SMART schemes predict flow state I, while central differencing scheme (CDS) predicts flow state II. When the GTS model was placed away from the ground plane, the AVL SMART scheme fails to predict the flow asymmetry resulting in a pair of symmetrical vortices in the vertical midplane, while flow state II topology is observed when CDS is used. The switch from flow state I (II) to flow state II (I) is achieved by changing the numerical scheme from AVL SMART (CDS) to CDS (AVL SMART), with an intermediate transient-symmetric (TS) state being observed during the switching process. The numerical scheme in the PANS simulations thus plays a critical role in determining the initial flow topology in the near wake of the GTS.

“…In the vertical midplane, the flow field is characterised by a tiny vortex close to the base (A), adjoining a large triangular shaped vortex (B) and a smaller vortex (C) on the opposite side of vortex (B). Flow predictions using RANS fails to predict this asymmetrical flow topology, with a pair of symmetric vortices in both the lateral and the vertical midplanes [12] [13].…”

Section: Bi-stable Behaviour In the Wake Of A Heavy Vehiclementioning

confidence: 99%

Partially-Averaged Navier-Stokes Simulations in Engineering Flows

Krajnović

Proceeding of 3rd Thermal and Fluids Engineering Conference (TFEC)

et al. 2018

This paper presents the most recent applications of the Partially-Averaged Navier-Stokes equations for engineering flows together with the review of the previous work in the field. Partially-Averaged Navier Stokes (PANS) simulation has been successfully used for several different applications of flows around ground vehicles. Examples of flows studied using PANS are that of the flow around square-back Ahmed body, flow around simplified passenger vehicle influenced by crosswinds, flow around simplified intercity trains, to the influence of passive and active flow control on the reduction of the aerodynamic drag on simplified vehicles. The idea of the application of hybrid methods such as PANS is to decrease the resolution requirements that are needed in turbulence resolving simulations such as LES. The resolution requirements of LES are normally very high in the near-wall regions, and this is where the PANS method is expected to activate more turbulence modelling, and thereby decrease the computational effort. The PANS method used by the authors is based on the variable switching coefficient that regulates the amount of the turbulence modelling in the simulation. Previous studies have shown that such implementation of PANS is in line with the requirements that PANS should adapt to the computational grid. The most recent predictions range from simplified ground vehicle flow, flow around a freight train locomotive to the investigation of active flow control for trucks and ships. The new predictions show good agreement with the experimental observations.