Shinkyu Jeong

Efficient Global Optimization of Vortex Generators on a Super Critical Infinite-Wing Using Kriging-Based Surrogate Models

Multi-objective optimization of vortex generators (VGs) on a transonic infinite-wing is performed using computational fluid dynamics (CFD) and the multi-objective genetic algorithm (MOGA) coupled with surrogate models. VG arrangements are defined by five design variables: height, length, incidence angle, chord location, and spacing. The objective functions are to maximize lift-drag ratio at low angle of attack, to maximize lift coefficient at high angle of attack, and to shift chordwise separation location to downstream at high angle of attack. In order to evaluate these objective functions of each individual in MOGA, the ordinary Kriging surrogate model and the radial basis function (RBF)/Kriging-hybrid surrogate model are employed because CFD analysis of the wing with VGs requires a large computational time. Non-dominated solutions are classified into five clusters which have different aerodynamic characteristics. Comparing five clusters, it is revealed that the balance among three objective functions is controlled mainly by VG height, spacing, and their ratio. The solutions in each cluster have specific values of these three parameters, which identify the aerodynamic characteristics. Additionally, appropriate values of design variables for generating the vortex most efficiently are investigated.

Multi-Objective Aerodynamic Optimization of Elements' Setting for High-lift Airfoil Using Kriging Model

In this paper, a multi-objective design optimization for a three-element airfoil consisted of a slat, a main wing, and a flap was carried out. The objective functions were defined as the maximization of lift coefficient at landing (Cl8) and near stall (Cl20)conditions simultaneously. Genetic Algorithm (GA) was used as an optimizer. Although it has advantage of global exploration, its computational cost is expensive. To reduce the computational cost, the kriging model which was constructed based on several sample designs was introduced. The solution space was explored based on the maximization of Expected Improvement (EI) value corresponding to objective functions on the kriging model to consider the predicted value by kriging model and its uncertainty. The improvement of the model and the exploration of the optimum can be advanced at the same time by maximizing EI value. In this study, 90 sample points are evaluated using the Reynolds averaged Navier-Stokes simulation (RANS) for the construction of the kriging model. Through the present exploration process, several designs were obtained with better performance than the baseline setting in each objective function. Functional Analysis of Variance (ANOVA) which is one of the data mining techniques showing the effect of each design variable on the objectives is applied. Main-effects of the design variables are calculated to recognize which design variable has the effect on the objective functions. This result suggests that the gap and the deflection of the flap have a remarkable effect on each objective function and the gap of the slat has an effect on Cl20.

Efficient Design Exploration of Nacelle Chine Installation in Wind Tunnel Testing

Design exploration of a nacelle chine installation was crried out. The nacelle chine is a device to improve the stall performance when multi-element high-lift devices were deployed. In this study, an efficient design process using Kriging surrogate model was proposed to decide the nacelle chine installation point in wind tunnel tests. The design process called ‘efficient design optimization (EGO)’ was conducted in the wind tunnel testing of JAXA high-lift aircraft model at JAXA Large-scale Lowspeed Wind Tunnel. The objective function for the EGO was to maximize the maximum lift. The installation points of the chine on the engine nacelle in the axial and chord-wise direction were designed, while the geometry of the chine was fixed. Through the design process in the wind tunnel test, an accurate surrogate model of the maximum lift by the chine location was efficiently obtained using expected improvement values as a criterion to select additional evaluation points. This method makes it possible not only to improve the accuracy of the response surface but also to explore the global optimum efficiently. Through this test, EGO process could be successfully applied to the design based on the wind tunnel test result.

Efficient Aeroelastic Analysis Using Unstructured CFD Method and Reduced-Order Unsteady Aerodynamic Model

Flutter computations are presented for the AGARD 445.6 wing model and the WingPylon-Nacelle configuration model using a fully implicit aeroelastic unstructured-mesh Euler solver coupled with a linear structural dynamics solver and Reduced-Order Model (ROM) based on the Volterra theory. The ROM is used for the rapid evaluation of nonlinear generalized unsteady aerodynamic forces (GAFs) both in a time-domain and a frequencydomain. The convolved time-domain GAFs agree well with direct computation results, and the frequency-domain GAFs at distinct values of reduced frequency are computed from the time-domain GAF responses to unit-amplitude harmonic excitation of elastic modes using a simple convolution scheme. The frequency-domain GAFs are processed using the Roger’s approximation method in order to generate an unsteady aerodynamic state-space ROM, which is used for creating an aeroelastic state-spa ce model. The aeroelastic state-space model is solved as a complex eigenvalue problem using MATLAB’s ® Toolbox to obtain V-g plots. The ROM-based flutter analysis is rapid and yields accurate results compared with experiment, direct simulation results and linear ae rodynamics results by MSC/NASTRAN.

Aerodynamic Optimization of High-Wing Configuration for Near Future Aircraft

This paper presents the aerodynamic optimization of high-wing configuration. The present optimization aims to explore the fuselage-wing shape suitable for high-wing configuration as near-future aircraft, which is capable to install higher bypass ratio engines, using computational fluid dynamics simulation and the Kriging-surrogate-assisted genetic algorithm. First, we optimize the fuselage upper surface including fairing for the high-wing configuration and investigate the interference effect between the fuselage upper surface and the wing. Second, the aircraft nose shape is also optimized together with the fuselage upper surface to achieve higher lift generated by the fuselage itself. Finally, both the fuselage shape and the wing shape are optimized to improve lift-to-drag ratio (L/D) by alleviating shock wave without spoiling the lift generation mechanisms established in the first and the second optimizations. The final optimized configuration reduces shock wave and achieves much higher lift coefficient of 0.742, which is generated by not only the wing but also the fuselage, than the low-wing DLR-F6 configuration.

Improvement of Nonlinear Lateral Characteristics of Lifting-Body Type Reentry Vehicle Using Optimization Algorithm

The nonlinear lateral characteristics of a lifting-body type reentry vehicle were improved. First, the reasons for the nonlinear lateral characteristics were investigated by CFD analysis. The results indicated that fins mounted on the Japan Aerospace Exploration Agency’s (JAXA) baseline lifting-body configuration cause unsymmetrical development of vortices and result in nonlinear lateral characteristics. An efficient optimization algorithm, called EGOMOP (Efficient Global Optimization for Multi-Objective Problems), was adopted to improve these nonlinear lateral characteristics. EGOMOP predicts potential optimum solutions based on the probability estimated by the Kriging model. The computational time for optimization was markedly reduced due to use of the Kriging model. Further investigations were also performed to determine the effects of the upswept upper-aft and swept-back fin angles. The results indicated that the swept-back fin angle is an important factor controlling the lateral characteristics of the lifting-body type reentry vehicle.

Supersonic inverse design method for wing-fuselage design

Publisher Summary In this chapter, a three-dimensional supersonic wing design method that can determine both the warp and thickness at the same time is developed. The present method is extended from Takanashis inverse design method used for the transonic wing design. Takanashi solved the inverse problem by using the integral form of the transonic small perturbation equation with ‘residual-correction’ concept. This paper will discuss the mathematical formulation of the present method, and show two design results. One is for an isolated-wing configuration and the other is for a wing‑fuselage combination that is the baseline design of the National Aerospace Laboratorys experimental scaled supersonic transport (SST). The inverse problem in the aerodynamic shape design is to find a geometry that yields a specified surface pressure distribution. The procedure of finding a corresponding geometry in the present method is described as follows. First, a target pressure distribution and an initial geometry are inputted to a design system, and then the surface pressure distribution of this initial geometry is obtained by the flow analysis. In this design system, inverse calculation stage is separated from the flow analysis stage. Thus, any type of analysis, even an experiment, can be used for the flow analysis tool. In this study, the Euler/Navier‑Stokes solver is used for the flow analysis. the pressure difference is calculate from the computed and target pressure distributions. Using this pressure difference as a boundary condition, a geometry correction is obtained by solving the linearized small perturbation (LSP) equation. By modifying the initial geometry with the geometry correction, a new geometry is produced.