Estimation of Aircraft-Dependent Bumpiness Severity in Turbulent Flight

Atmospheric turbulence threatens flight safety of civil aviation aircraft by inducing aircraft bumpiness. A severity estimation method of aircraft bumpiness in turbulent flight is explored according to in-situ Eddy Dissipation Rate (EDR) indicator. With the turbulence intensity derived from EDR value, a time series of longitudinal and vertical turbulence was generated according to von Karman turbulence model. In order to obtain the vertical acceleration response of aircraft, the continuous change of aerodynamic force on the assembly of wing and horizontal tail was computed by Unsteady Vortex Lattice Method (UVLM). The computing accuracy was improved by using semi-circle division and assigning the vortex rings on the mean camber surface. Furthermore, the adverse effects of control surface deflections on bumpiness severity estimation can be effectively removed by separating turbulence-induced and aircraft maneuvers-induced aerodynamic force change. After that, the variance of vertical acceleration, as the severity indicator of aircraft bumpiness, was obtained by Welch spectrum estimation. With the refined grid level, the pitching moment change due to control surface deflections can be solved accurately by UVLM. The instantaneous acceleration change obtained by UVLM approximates recorded acceleration data with better accuracy than linear transfer function model. A further test with a set of flight data on the same airway shows that compared with in-situ EDR indicator, the proposed method gives an aircraft-dependent estimation of bumpiness severity, which can not only be used to estimate in-situ bumpiness but also be applied to forecast the bumpiness severity of other different aircrafts.

[1]  L. Cortelezzi,et al.  Vortex Flow and Aerodynamic Performance of a Reverse Delta Wing , 2020 .

[2]  Sergio Preidikman,et al.  Modified Unsteady Vortex-Lattice Method to Study Flapping Wings in Hover Flight , 2013 .

[3]  Ruxandra Botez,et al.  A new non-linear vortex lattice method: Applications to wing aerodynamic optimizations , 2016 .

[5]  Rongshun Huang,et al.  Estimating Eddy Dissipation Rate with QAR Flight Big Data , 2019, Applied Sciences.

[6]  Philip G. Gill Objective verification of World Area Forecast Centre clear air turbulence forecasts , 2014 .

[7]  Joseba Murua,et al.  Induced-Drag Calculations in the Unsteady Vortex Lattice Method , 2013 .

[8]  Zhenxing Gao,et al.  A Method for Estimating Aircraft Vertical Acceleration and Eddy Dissipation Rate in Turbulent Flight , 2020, Applied Sciences.

[9]  Gao Zhenxing,et al.  Generation and Application of Spatial Atmospheric Turbulence Field in Flight Simulation , 2009 .

[10]  Brett Newman,et al.  Aircraft Acceleration Prediction Due to Atmospheric Disturbances with Flight Data Validation , 2004 .

[11]  Corinne S. Morse,et al.  Real-time estimation of atmospheric turbulence severity from in-situ aircraft measurements , 1995 .

[12]  Rod Frehlich,et al.  Simulation of Three-Dimensional Turbulent Velocity Fields , 2001 .

[13]  Yi Liu,et al.  Gust response analysis and wind tunnel test for a high-aspect ratio wing , 2016 .

[14]  Larry B. Cornman,et al.  Description and Derived Climatologies of Automated In Situ Eddy-Dissipation-Rate Reports of Atmospheric Turbulence , 2014 .

[15]  Tongguang Wang,et al.  A Simplified Free Vortex Wake Model of Wind Turbines for Axial Steady Conditions , 2018 .

[16]  Dan D. Vicroy,et al.  Effect of spatial wind gradients on airplane aerodynamics , 1989 .

[17]  Timothy A. Lewis,et al.  Flight Data Analysis and Simulation of Wind Effects During Aerial Refueling , 2008 .

[18]  Joseba Murua,et al.  Applications of the unsteady vortex-lattice method in aircraft aeroelasticity and flight dynamics , 2012 .

[19]  Zhenxing Gao,et al.  Acceleration-Based In Situ Eddy Dissipation Rate Estimation with Flight Data , 2020, Atmosphere.