A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

Grinding chatter is a self-induced vibration which is unfavorable to precision machining processes. This paper proposes a forecasting method for grinding state identification based on bivarition empirical mode decomposition (BEMD) and least squares support vector machine (LSSVM), which allows the monitoring of grinding chatter over time. BEMD is a promising technique in signal processing research which involves the decomposition of two-dimensional signals into a series of bivarition intrinsic mode functions (BIMFs). BEMD and the extraction criterion of its true BIMFs are investigated by processing a complex-value simulation chatter signal. Then the feature vectors which are employed as an amplification for the chatter premonition are discussed. Furthermore, the methodology is tested and validated by experimental data collected from a CNC guideway grinder KD4020X16 in Hangzhou Hangji Machine Tool Co., Ltd. The results illustrate that the BEMD is a superior method in terms of processing non-stationary and nonlinear signals. Meanwhile, the peak to peak, real-time standard deviation and instantaneous energy are proven to be effective feature vectors which reflect the different grinding states. Finally, a LSSVM model is established for grinding status classification based on feature vectors, giving a prediction accuracy rate of 96%.

/pdf/grinding-chatter-detection-and-identification-based-on-bemd-1yplzzatgo.pdf

Grinding Chatter Detection and Identification Based on BEMD and LSSVM

https://cyberleninka.org/article/n/1319427.pdf

Unsteady aerodynamic modeling at high angles of attack using support vector machines

Machine Learning in Aerodynamic Shape Optimization

Parametric analyses on dynamic stall control of rotor airfoil via synthetic jet

Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-altitude Airport

In view of engineering application, it is practicable to decompose the aerodynamics into three components: the static aerodynamics, the aerodynamic increment due to steady rotations, and the aerodynamic increment due to unsteady separated and vortical flow. The first and the second components can be presented in conventional forms, while the third is described using a one-order differential equation and a radial-basis-function (RBF) network. For an aircraft configuration, the mathematical models of 6-component aerodynamic coefficients are set up from the wind tunnel test data of pitch, yaw, roll, and coupled yawroll large-amplitude oscillations. The flight dynamics of an aircraft is studied by the bifurcation analysis technique in the case of quasi-steady aerodynamics and unsteady aerodynamics, respectively. The results show that: (1) unsteady aerodynamics has no effect upon the existence of trim points, but affects their stability; (2) unsteady aerodynamics has great effects upon the existence, stability, and amplitudes of periodic solutions; and (3) unsteady aerodynamics changes the stable regions of trim points obviously. Furthermore, the dynamic responses of the aircraft to elevator deflections are inspected. It is shown that the unsteady aerodynamics is beneficial to dynamic stability for the present aircraft. Finally, the effects of unsteady aerodynamics on the post-stall maneuverability are analyzed by numerical simulation.

Qing Wang

Papers

Unsteady aerodynamic modeling at high angles of attack using support vector machines

Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-altitude Airport

Unsteady aerodynamics modeling for flight dynamics application