Spectral/hp element simulation of flow past a Formula One front wing: Validation against experiments

Buscariolo, Filipe Fabian; Hoessler, Julien; Moxey, David; Jassim, Ayad; Gouder, Kevin; Basley, Jérémy; Murai, Yushi; Assi, Gustavo R. S.; Sherwin, Spencer J.

doi:10.1016/j.jweia.2021.104832

Cited by 12 publications

(14 citation statements)

References 13 publications

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“…The Imperial Front Wing (IFW), shown in Figure 1, was a model given to Imperial College London based on an unraced front wing specification of the McLaren MP4-17D. It has been the subject of two experimental campaigns at Imperial College London Buscariolo et al (2019); Pegrum (2006) and two computational campaigns Buscariolo et al (2019); Lombard (2017).…”

Section: Imperial Front Wingmentioning

confidence: 99%

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Large Eddy Simulation of an Inverted Multi-Element Wing in Ground Effect

Slaughter

Moxey

Sherwin

2022

Preprint

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Due to the proprietary nature of modern motorsport and Formula 1, current scientific literature lacks relevant studies and benchmarks that can be used to test and validate new methods. Due to the release of a free geometry - the Imperial Front Wing - we present a computational study of a multi-element aerofoil at a ride height of 0.36h/c and a Reynolds Number of 2.2 × 105. A 0.16c slice of the Imperial has been examined using high-order Spectral/hp Element Methods. Time averaged force data is presented finding lift and drag coefficients of -8.33 and 0.17 respectively. Transient analysis of the force- and surface pressure data resulted in salient mode identification with respect to the transition mechanisms of each element.The mainplane and flap laminar separation were studied and the cross-spectral phase presented for the lower frequency modes. At a St=40 an in-phase relationship was identified between mainplane and flap Laminar Separation Bubbles, whilst at St=60 a distinct out-of-phase relationship was identified. Wake results including wake-momentum deficit and turbulent kinetic energy plots have been presented - showing wake meandering and subsequent break down due to a Kelvin-Helmholtz instability. These results, particularly the transition mechanisms will allow for the construction of a data set to validate novel methods in this area.

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Section: Imperial Front Wingmentioning

confidence: 99%

“…The case has a Reynolds Number of 2.2 × 10 5 based on the the mainplane chord of 0.25m. Similar to the cases of Pegrum (2006); Buscariolo et al (2019); Lombard (2017) a ride height of 0.36h/c has been chosen, set from the footplate of the full geometry. A slice is then taken at Y=250mm in CAD to create the full geometry.…”

Section: Setupmentioning

confidence: 99%

Large Eddy Simulation of an Inverted Multi-Element Wing in Ground Effect

Slaughter

Moxey

Sherwin

2022

Preprint

Self Cite

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“…Here, we consider the flow past a Formula 1 front wing with a relatively complex geometry, supported by the availability of a CAD model and experimental results [60]. We refer to this test case as the Imperial Front Wing, originally based on the front wing and endplate design of the McLaren 17D race car [11]. The panel of Figure 10 gives an overview of the Imperial Front Wing geometry.…”

Section: Viscous Flow Past a Formula 1 Front Wingmentioning

confidence: 99%

Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics

Ranocha,

Dalcin,

Parsani

et al. 2021

Preprint

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We develop error-control based time integration algorithms for compressible fluid dynamics (CFD) applications and show that they are efficient and robust in both the accuracy-limited and stability-limited regime. Focusing on discontinuous spectral element semidiscretizations, we design new controllers for existing methods and for some new embedded Runge-Kutta pairs. We demonstrate the importance of choosing adequate controller parameters and provide a means to obtain these in practice. We compare a wide range of error-control-based methods, along with the common approach in which step size control is based on the Courant-Friedrichs-Lewy (CFL) number. The optimized methods give improved performance and naturally adopt a step size close to the maximum stable CFL number at loose tolerances, while additionally providing control of the temporal error at tighter tolerances. The numerical examples include challenging industrial CFD applications.

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“…We consider the flow past a Formula 1 front wing with a relatively complex geometry. We refer to this test case, originally based on the front wing and endplate design of the McLaren 17D race car (Pegrum 2007; Buscariolo et al, 2019), as the Imperial front wing. Figure 2 gives a three-dimensional overview of the wing geometry.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of relaxation Runge–Kutta methods

Rogowski

Dalcín

Parsani

et al. 2022

The International Journal of High Performance Computing Applica

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Recently, global and local relaxation Runge–Kutta methods have been developed for guaranteeing the conservation, dissipation, or other solution properties for general convex functionals whose dynamics are crucial for an ordinary differential equation solution. These novel time integration procedures have an application in a wide range of problems that require dynamics-consistent and stable numerical methods. The application of a relaxation scheme involves solving scalar nonlinear algebraic equations to find the relaxation parameter. Even though root-finding may seem to be a problem technically straightforward and computationally insignificant, we address the problem at scale as we solve full-scale industrial problems on a CPU-powered supercomputer and show its cost to be considerable. In particular, we apply the relaxation schemes in the context of the compressible Navier–Stokes equations and use them to enforce the correct entropy evolution. We use seven different algorithms to solve for the global and local relaxation parameters and analyze their strong scalability. As a result of this analysis, within the global relaxation scheme, we recommend using Brent’s method for problems with a low polynomial degree and of small sizes for the global relaxation scheme, while secant proves to be the best choice for higher polynomial degree solutions and large problem sizes. For the local relaxation scheme, we recommend secant. Further, we compare the schemes’ performance using their most efficient implementations, where we look at their effect on the timestep size, overhead, and weak scalability. We show the global relaxation scheme to be always more expensive than the local approach—typically 1.1–1.5 times the cost. At the same time, we highlight scenarios where the global relaxation scheme might underperform due to its increased communication requirements. Finally, we present an analysis that sets expectations on the computational overhead anticipated based on the system properties.

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Spectral/hp element simulation of flow past a Formula One front wing: Validation against experiments

Cited by 12 publications

References 13 publications

Large Eddy Simulation of an Inverted Multi-Element Wing in Ground Effect

Large Eddy Simulation of an Inverted Multi-Element Wing in Ground Effect

Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics

Performance analysis of relaxation Runge–Kutta methods

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