Factors Influencing Accurate Shock Vortex Interaction Prediction on F-16XL Aircraft

Tomac, Maximilian; Jirasek, Adam; Rizzi, Arthur

doi:10.2514/6.2014-0420

Cited by 5 publications

(7 citation statements)

References 6 publications

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“…A more interesting case would be a 3g transonic condition, for which the deflections would be much higher. Such a case is FC79 at 3.7g, which was also investigated by Boelens and by Tomac et al [5,18]. Their CFD results showed higher suction levels mainly on the outboard 50 deg swept panel as compared with flight data.…”

Section: Discussionmentioning

confidence: 71%

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Computation of Aeroelastic Effects on F-16XL at Flight Conditions FC70 and FC25

Rizzi¹,

Tomac²,

Jirasek

et al. 2017

Journal of Aircraft

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This article presents an aeroelastic study of CAWAPI F-16XL aircraft. The structural model of this aircraft is not publicly available and is therefore replaced by a structural model estimate that is constructed based on data available in public literature. The aeroelastic solution is done using solution for two flight conditions -FC70 and FC25. The primary task is to assess the importance of the aeroelastic effects on the FC70 solution and to assess whether large discrepancies are observed at flight condition FC70 between the computational and experimental data.

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Section: Discussionmentioning

confidence: 71%

“…9 Rigid and elastic aircraft configuration, FC25. [18] for more information about this family of grids and how they have been used in CAWAPI-1 and CAWAPI-2.…”

Section: A Cfd Code Edgementioning

confidence: 99%

Computation of Aeroelastic Effects on F-16XL at Flight Conditions FC70 and FC25

Rizzi¹,

Tomac²,

Jirasek

et al. 2017

Journal of Aircraft

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“…Highly adapted meshes are needed to resolve the interaction of the weak vortex with the relatively strong shock waves. Tomac 7 [2014] has used a grid adaption technique in three steps. The first adaptation uses a gradient sensor to mainly seek out shock waves, the second adaptation uses the lamda2 sensor [Le Moigne 8 , 2004] that tracks vortex cores (as seen in Figure 2), and the third adaptation is again the gradient sensor.…”

Section: Increasingmentioning

confidence: 99%

“…The results of one such sequence, that of increasing shock strength at constant low alpha (i.e. constant, weak vortex) was shown in Figure 15 Tomac 7 [2014] has studied this suite of flight conditions with RANS analysis and EARSM turbulence modeling with three distinct grids plus adaption along with associated aircraft modeling. Their first grid models the wing as a single solid element (as do all the other contributors with their grids).…”

Section: A Mach Sweep At Low Alpha: Fc68 -Fc69 -Fc70mentioning

confidence: 99%

“…In order to get some kind of a handle on this open issue, Tomac 7 [2014] has developed a surface geometry and associated computational grid that accounts for the three control surfaces of the F16-XL, the leading edge flaps, the elevens and the ailerons taking into account as much of the incomplete data that is available to us. The result is an aircraft model where the inner wing is a two-element geometry and the outer wing a three-element geometry where the control surface area predominates over the central core element.…”

Section: Control Surfacesmentioning

confidence: 99%

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What Was Learned in Predicting Slender Airframe Aerodynamics with the F-16XL Aircraft

Rizzi

Luckring

2017

Journal of Aircraft

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The CAWAPI-2 coordinated project has been underway to improve CFD predictions of slender airframe aerodynamics. The work is focused on two flow conditions and leverages a unique flight data set obtained with the F-16XL aircraft for comparison and verification. These conditions, a low-speed high angle-of-attack case and a transonic low angle-of-attack case, were selected from a prior prediction campaign wherein the CFD failed to provide acceptable results. In re-visiting these two cases, approaches for improved results include better, denser grids using more grid adaptation to local flow features as well as unsteady higher-fidelity physical modeling like hybrid RANS/URANS-LES methods. The work embodies predictions from multiple numerical formulations that are contributed from multiple organizations where some authors investigate other possible factors that could explain the discrepancies in agreement, e.g. e ects due to deflected control surfaces during the flight tests, as well as static aeroelastic deflection of the outer wing. This paper presents the synthesis of all the results and findings and draws some conclusions that lead to an improved understanding of the underlying flow physics, and finally making the connections between the physics and aircraft features.

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