4 edition of Robust airfoil optimization to achieve consistent drag reduction over a mach range found in the catalog.
Robust airfoil optimization to achieve consistent drag reduction over a mach range
by National Aeronautics and Space Administration, Langley Research Center, Available from NASA Center for AeroSpace Information in Hampton, Va, Hanover, MD
Written in English
|Statement||Wu Li, Luc Huyse, Sharon Padula.|
|Series||ICASE report -- no. 2001-22., [NASA contractor report] -- NASA/CR-2001-211042., NASA contractor report -- NASA CR-211042.|
|Contributions||Huyse, Luc., Padula, Sharon., Langley Research Center.|
|The Physical Object|
Get this from a library! Robust airfoil optimization to achieve consistent drag reduction over a mach range. [Wu Li; Luc Huyse; Sharon Padula; Langley Research Center.]. On the Importance of Appropriately Representing Uncertainty in Robust Airfoil Optimization are set to a = 2, b = 2 and the range is over [-1,1], and when interval analysis is used these same bounds, [-1,1], are used. These forms of u are illustrated in ﬁgure 2.
The focus of this chapter is on the shape optimization of the Busemann-type biplane airfoil for drag reduction under both non-lifting and lifting conditions using genetic algorithms. The concept of biplane airfoil was first introduced by Adolf Busemann in Under design conditions at a specific supersonic flow speed, the Busemann biplane airfoil eliminates all wave drag due to Cited by: 1. The transonic case was also considered as most commercial airliners fly near Mach one. It is shown that the section deformation can be effective in reducing the drag .
To reduce pitching moment and drag coefficient under dynamic stall condition, a new airfoil has been optimized based on the OA airfoil by employing the present optimal method. Due to the inhibition of leading edge vortex, the peaks of pitching moment and drag coefficient of the optimized airfoil are decreased about % and % at point 1 Cited by: A practical procedure for the design of low-drag supersonic airfoils is demonstrated, using an optimization program based on a gradient algorithm coupled with an aerodynamic analysis program which incorporates a unitary compression/ expansion formula for inviscid C p distribution valid over a wide range of supersonic Mach numbers. Results are presented for low-drag Cited by: 5.
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ROBUST AIRFOIL OPTIMIZATION TO ACHIEVE CONSISTENT DRAG REDUCTION OVER A MACH RANGE * WU Lit, LUC HUYSE$, AND SHARON PADULA§ Abstract. We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free.
Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range Wu Li Old Dominion University, Norfolk, Virginia Luc Huyse ICASE, Hampton, Virginia Sharon Padula NASA Langley Research Center, Hampton, Virginia ICASE NASA Langley Research Center Hampton, Virginia Operated by Universities Space Research Association August An airfoil shape optimization method that reduces drag over a range of free stream Mach numbers is sought.
We show that one acceptable choice is a weighted multipoint optimization method using more design points than there are free-design variables. Alternate methods that use far fewer design points are by: Li W, Hyuse L, Padula S () Robust airfoil optimization to achieve consistent drag reduction over a Mach range.
NASA/CR NASA Langley Research CenterCited by: 5. Approach to Aerodynamic Design Through Numerical Optimization. “ Robust Airfoil Optimization to Achieve Consistent Drag Reduction over a Mach Range,” Structural and Multidisciplinary Optimization, Vol.
24, No. 1,pp. 38– doi: Cited by: Continuation Multilevel Monte Carlo Evolutionary Algorithm for Robust Aerodynamic Shape Design Huyse L. and Padula S., “ Robust Airfoil Optimization to Achieve Drag Reduction over a Range of Mach Numbers,” Structural and Multidisciplinary “ A Fast Robust Optimization Methodology Based on Polynomial Chaos and Evolutionary Algorithm Cited by: 1.
Figure 2: One-point optimized airfoil geometry and objective function versus number of design DOFs. the entire drag polar of each airfoil tells a very diﬀerent story.
As the number of DOFs is increased, the drag reduction is attained over an ever-narrower CL range. Figure 3 shows that the polar curve takes on a cusped form, so that theFile Size: KB.
OPTIMIZATIONS OF AIRFOIL AND WING USING GENETIC ALGORITHM Figure 4 shows the flowchart describing the GA application to aerodynamic optimization for an airfoil (or a wing).
The CFD solver (ARC2D or KTRAN) calculates the objective function (Cl/Cd) and sends it to GA, which uses it as a fitness value. For the 3D wing configuration, a.
Now assume it is desired to find the airfoil that minimizes the drag coeffi- cient CD with constraints on lift coefficient CL, thickness-to-chord ratio, t/c, etc., at a specified Mach number and angle of attack. Airfoil Optimization with XFOIL.
Using the average of three different points helps to achieve good performance over a range of angles of attack. The angles of attack considered in the objective function were4, and 7 degrees.
Well, I guess the way to do it is to test each airfoil at a range of AoA, and select the best for that airfoil. An airfoil shape optimization method that reduces drag over a range of free stream Mach numbers is sought.
We show that one acceptable choice is a weighted multipoint optimization method using more. The optimization scheme adjusts design variables to optimize the objective function.
For this project, we chose to maximize the average of CL/CD at three different angles of attack. Using the average of three different points helps to achieve good performance over a range of angles of attack.
application to airfoil design is presented by Huyse et al. [17–19]. Later approaches, called the proﬁle optimization method and the modiﬁed proﬁle optimization method, are developed for achieving consistent drag reduction over a given Mach range with far fewer design points than are required for the multipoint optimization.
The robust airfoil optimization is aimed to minimize mean values and variances of drag coefficients while satisfying the lift and thickness constraints over a range of Mach numbers. A multi-objective estimation of distribution algorithm is applied to the robust airfoil optimization on the base of the RAE benchmark by: By using the above methods, a multi-objective robust optimization was conducted for NASA SC airfoil.
After performing robust airfoil optimization, the mean value of drag coefficient at Ma– and the mean value of lift coefficient at post stall regime (Ma) have been improved by % and %.Cited by: Li W, Huyse L, Padula S.
Robust airfoil optimization to achieve consistent drag reduction over a Mach range. Report No.: NASA/CR; Google ScholarCited by: The robust airfoil shape optimization is a direct method for drag reduction over a given range of operating conditions and has three advantages: (1) it prevents severe degradation in.
A robust aerodynamic shape optimization technique using computational fluid dynamics (CFD) was developed to design for six sigma airfoils which were free from the drag divergence over a range of.
ing robust aerodynamic airfoil design optimization problem considering the robustness of lift to drag ratio L/D when ﬂight Mach number M∞ disperses around with its standard deviation of Maximize: mean value of L/D Minimize: standard deviation of L/D (4) An optimized airfoil conﬁguration is deﬁned by the B-spline curves.
This paper is concerned with robust aerodynamic design of compressor blades against erosion. The proposed approach combines a multiobjective genetic algorithm with geometry modeling methods, high-fidelity computational fluid dynamics, and surrogate models to arrive at robust designs on a limited computational by:.
Robust aerodynamic shape optimization—From a circle to an airfoil. W e now consider the ADODG RANS airfoil optimization problem, we obtained a reduction of drag .optimization airfoil is often ill posed and suffering from the drastic increase of drag coefficient at off-design points, even though the drag coefficient of it at design point has been optimized well.
Therefore, in order to achieve a consistent reduction of drag coefficient over a range of Mach number, e.g.,we have.The aerodynamic robust optimization design system established in this article consists of improved BP net- work, reliable CFD technique and genetic algorithm, so it is efficient, reliable and with high-order accuracy.
References  Li W, Huyse L, Padula S. Robust airfoil optimization to achieve consistent drag reduction over a Mach by: 5.