Experimental and Numerical Investigation of the DrivAer Model

Heft, Angelina; Indinger, Thomas; Adams, Nikolaus A.

doi:10.1115/fedsm2012-72272

Cited by 61 publications

(53 citation statements)

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“…In addition each configuration were tested with and without a rolling road to test the effect of ground simulation. Previous numerical simulations by TUM focused only on the fastback configuration with a single turbulence model [3]. Whilst some effort was made to ensure mesh convergence and to investigate the effect of the several geometry variations, no investigation was made into different turbulence models or the other two DrivAer configurations.…”

Section: Drivaer Automotive Modelmentioning

confidence: 99%

“…A recent addition to the openly available car geometries is the DrivAer model [3,4]. In these experiments three car configurations (shown in Figure 4(a)) were subject to a wind tunnel investigation, where global loads were obtained as well as surface pressure information in key areas over and under the vehicles.…”

Section: Drivaer Automotive Modelmentioning

confidence: 99%

“…Whilst some effort was made to ensure mesh convergence and to investigate the effect of the several geometry variations, no investigation was made into different turbulence models or the other two DrivAer configurations. The turbulence model in question, the k − ω SST [9] model was used in the study of [3] and also in this research. The model in [3] used a mesh that did not resolve the near-wall region which makes any direct comparison difficult, however some key flow areas, such as the bonnet/windscreen intersection, show the same trend between the previously mentioned work and the authors previous work.…”

Section: Drivaer Automotive Modelmentioning

confidence: 99%

“…The turbulence model in question, the k − ω SST [9] model was used in the study of [3] and also in this research. The model in [3] used a mesh that did not resolve the near-wall region which makes any direct comparison difficult, however some key flow areas, such as the bonnet/windscreen intersection, show the same trend between the previously mentioned work and the authors previous work. Whilst they showed excellent agreement for the drag coefficient, the pressure distribution over the top and bottom of the car differs from the experiment suggesting that a certain amount of error cancellation is present.…”

Section: Drivaer Automotive Modelmentioning

confidence: 99%

“…The solution domain of the DIT calculation is cubic with length 2π. The solution domain is meshed with three grids consisting of 32 3 , 64 3 & 128 3 cubic and equidistant cells. Periodic boundary conditions are imposed in each direction.…”

Section: Validation Of Des -Decaying Isotropic Turbulencementioning

confidence: 99%

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Section: Drivaer Automotive Modelmentioning

confidence: 99%

Section: Drivaer Automotive Modelmentioning

confidence: 99%

Section: Drivaer Automotive Modelmentioning

confidence: 99%

Section: Drivaer Automotive Modelmentioning

confidence: 99%

Section: Validation Of Des -Decaying Isotropic Turbulencementioning

confidence: 99%

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Assessment of RANS and DES methods for realistic automotive models

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Reducing memory requirements of unsteady adjoint by synergistically using check‐pointing and compression

Margetis

Papoutsis‐Kiachagias

Giannakoglou

2022

Numerical Methods in Fluids

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The unsteady adjoint method used in gradient‐based optimization in 2D and, particularly, 3D industrial problems modeled by unsteady PDEs may have significant storage requirements and/or computational cost. The reason for this is that the backward in time integration of the adjoint equations requires the previously computed instantaneous flow fields to be available at each time‐step. This article proposes remedies to this problem, by extending/upgrading relevant techniques proposed by the group of authors as well as other researchers. Their applicability is wide, even if these remedies are herein demonstrated in shape optimization problems in unsteady fluid mechanics. Check‐pointing is in widespread use as it reduces the memory footprint and CPU cost of the optimization with a controllable computational overhead. Alternatively, flow field time‐series can be stored in a lossless or lossly compressed form. The novelty of this article is the development of a Compressed Coarse‐grained Check‐Pointing strategy for second‐order accurate schemes in time, by optimally combining check‐pointing and lossy compression. The latter includes (a) the incremental Proper Generalized Decomposition (iPGD) algorithm and (b) a hybridization of the iPGD with the ZFP and Zlib algorithms. This is implemented within OpenFOAM, which is used to solve the flow and adjoint equations and conduct the optimization, and assessed in 2D/3D aerodynamic shape optimization problems on unstructured grids. Effectiveness in data reduction, computational cost, and reconstruction accuracy are compared, vis‐à‐vis also to the “standard” binomial check‐pointing technique after adjusting it to second‐order accurate schemes in time.

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On the Performance of Oversampling Techniques for Class Imbalance Problems

Kong

Rios

Kowalczyk

et al. 2020

Lecture Notes in Computer Science

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Although over 90 oversampling approaches have been developed in the imbalance learning domain, most of the empirical study and application work are still based on the "classical" resampling techniques. In this paper, several experiments on 19 benchmark datasets are set up to study the efficiency of six powerful oversampling approaches, including both "classical" and new ones. According to our experimental results, oversampling techniques that consider the minority class distribution (new ones) perform better in most cases and RACOG gives the best performance among the six reviewed approaches. We further validate our conclusion on our real-world inspired vehicle datasets and also find applying oversampling techniques can improve the performance by around 10%. In addition, seven data complexity measures are considered for the initial purpose of investigating the relationship between data complexity measures and the choice of resampling techniques. Although no obvious relationship can be abstracted in our experiments, we find F1v value, a measure for evaluating the overlap which most researchers ignore, has a strong negative correlation with the potential AUC value (after resampling).

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Experimental and Numerical Investigation of the DrivAer Model

Cited by 61 publications

References 0 publications

Assessment of RANS and DES methods for realistic automotive models

Assessment of RANS and DES methods for realistic automotive models

Reducing memory requirements of unsteady adjoint by synergistically using check‐pointing and compression

On the Performance of Oversampling Techniques for Class Imbalance Problems

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