The Effect of Engine Location on the Aerodynamic Efficiency of a Flying-V Aircraft

Pascual, Berta Rubio; Vos, Roelof

doi:10.2514/6.2020-1954

Cited by 10 publications

(10 citation statements)

References 14 publications

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“…The engine location corresponds with the result of Rubio Pascual and Vos, both placing it at 14% of the semispan [31]. The location of the nose and main landing gear for the FV-900 is at at 16.8% and 58.0% of the aircraft length measured from the nose respectively, which closely resembles the results of Bourget placing the gears at 12.6% and 58% respectively [12].…”

Section: Validation Of the Weight Estimation Methods For The Flying-vsupporting

confidence: 70%

Conceptual Design of a Flying-V Aircraft Family

Oosterom

Vos

2022

AIAA AVIATION 2022 Forum

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Section: Validation Of the Weight Estimation Methods For The Flying-vsupporting

confidence: 70%

Conceptual Design of a Flying-V Aircraft Family

Oosterom

Vos

2022

AIAA AVIATION 2022 Forum

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“…The final aerodynamic model structure for the longitudinal coefficients after de-orthogonalizating is shown below, and the values of the parameters including their confidence bounds (confidence level α = 0.05 → 95%) are presented in Tables 2, 3, and 4. 4 4.088…”

Section: B Polynomial Model Estimationmentioning

confidence: 99%

“…Moreover, the wing parameterization utilized an oval fuselage cross section, a structurally efficient pressure vessel devised by Vos et al [3]. Rubio Pascual and Vos showed that the installation of over-the-wing turbofan engines is very sensitive to location and could cause a penalty in aerodynamic efficiency of 10% [4]. An impression of the Flying V is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Model Identification of the Flying V from Wind Tunnel Data

García

2020

Aiaa Aviation 2020 Forum

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The aerodynamic model identification of a novel aircraft configuration known as the "Flying V" is presented. A global longitudinal aerodynamic model is estimated using static wind tunnel data from a 4.6% sub-scale model. The aerodynamic model structure, unknown a priori, is determined from the data using a modified stepwise regression technique. Orthogonal polynomial models using Multivariate Orthogonal Functions and non-orthogonal spline models in the angle-of-attack dimension are defined for the estimation of the measured aerodynamic coefficients. The estimated models are validated against a partition of the data not used for the estimation, which shows that an adequate model fit and good prediction capabilities are attained. Spline models achieve better results in terms of fitting and show a better matching between the estimation and validation data. All estimated models are considered adequate, with a maximum relative Root Mean Square error below 8% for the polynomial models and below 3% for the spline models. Nomenclature Latin Symbols b Wing span of the half model, [m] c Reference chord, [m] C X , C Y , C Z Force coefficients in body axes, [N] C l , C m , C n Moment coefficients in body axes, [N•m] F Force [N] G Orthogonalization matrix J OLS cost function L, M, N Roll, pitch and yaw moment, [N•m] M Moment, [N•m] n Number of regressors in model N Number of samples p j Original regressors, j = 1, 2, ..., n q Dynamic pressure, [kg•m/s 2 ] S Wing area, [m 2 ] v Residual vector V Wind speed, [m/s] V Dimensionless wind speed, [-] x State vector X Regression matrix X, Y, Z Aerodynamic forces in body axes, [N] y Output vector z Measurement vector Greek Symbols α Angle of attack, [deg, rad] δ Control surface deflection [deg] θ Parameter vector ξ j

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“…In Ref. [5] the installation effects of over-the-wing turbofan engines on the Flying V were investigated, concluding that engine location plays an important role in the aircraft lift-to-drag-ratio, leading to penalties up to 10% compared to the engine-off configuration. A recent study into the conceptual design of a three-member family of Flying-V aircraft has shown a 20% reduction in fuel use over the design range of 15,000km [6].…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Model Identification of the Flying V from Sub-Scale Flight Test Data

García

Brown

Atherstone

et al. 2022

AIAA SCITECH 2022 Forum

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This paper presents the identification of the aerodynamic model of the "Flying-V", a novel aircraft configuration. The aerodynamic model is estimated using flight test data from a 4.6% sub-scale model. The dataset includes longitudinal and lateral-directional maneuvers performed by both the pilot and the autopilot to excite the aircraft dynamic modes. The so-called Two-Step Method is used to decouple and simplify the aerodynamic identification problem; the state estimation step is performed by an Iterated Extended Kalman Filter, and the parameter-estimation step using ordinary least squares. A stepwise regression technique and previous knowledge from wind-tunnel tests are combined to select the model structure, and the identified model is validated using a third of the gathered data. The estimated models are parsimonious and considered adequate in terms of model fit, with a maximum relative Root Mean Square Error of 10% for the worst validation case. For the considered location of the center of gravity and flight conditions, the estimated aerodynamic derivatives confirm that the aircraft is longitudinally stable, both statically and dynamically; and that it is also laterally and directionally statically stable. The analysis of the dynamic modes of the sub-scale model showed stable short period and roll subsidence modes, a lightly damped Dutch roll mode, and lightly damped/unstable phugoid and spiral modes.

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The Effect of Engine Location on the Aerodynamic Efficiency of a Flying-V Aircraft

Cited by 10 publications

References 14 publications

Conceptual Design of a Flying-V Aircraft Family

Conceptual Design of a Flying-V Aircraft Family

Aerodynamic Model Identification of the Flying V from Wind Tunnel Data

Aerodynamic Model Identification of the Flying V from Sub-Scale Flight Test Data

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