3 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

- 209 Want to read
- 19 Currently reading

Published
**2001** by National Aeronautics and Space Administration, Langley Research Center, Available from NASA Center for AeroSpace Information in Hampton, Va, Hanover, MD .

Written in English

- Drag reduction.,
- Airfoils.,
- Aerodynamic drag.,
- Mach number.,
- Optimization.,
- Robustness (Mathematics).

**Edition Notes**

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 | |
---|---|

Format | Microform |

Pagination | 1 v. |

ID Numbers | |

Open Library | OL16050922M |

technique, a drag reduction of % is achieved for the NACA case, reducing the total number of drag counts from to Employing the BandAids technique yields a % drag reduction, from to The RAE case exhibited a drag reduction from to counts, a % decrease using BandAids. Uncertainty quantification by geometric characterization of sensitivity spaces Uncertainty quantification by geometric characterization of sensitivity spaces Mohammadi, Bijan We propose a systematic procedure for both aleatory and epistemic uncertainty quantification of numerical simulations through geometric characteristics of global Author: Mohammadi, Bijan. FLETCHER, Roger The Barzilai Borwein Method - Steepest Descent Resurgent Abstract: The Barzilai Borwein method is a steepest descent method for unconstrained optimization that differs from the usual steepest descent method in the way that the step length is chosen.

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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 Robust airfoil optimization to achieve consistent drag reduction over a mach range book 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 Robust airfoil optimization to achieve consistent drag reduction over a mach range book 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. Robust airfoil optimization to achieve consistent drag reduction over a mach range book 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 [1] Li W, Huyse L, Padula S. Robust airfoil optimization to achieve consistent drag reduction over a Mach by: 5. Metric-Based Mathematical Derivation of Efficient Airfoil Design Variables.

“ Robust Aerofoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range,” Structural and Multidisciplinary Optimization, Vol. 24, No. 1,pp. 38– doi: Cited by: However, these modes are dependent on the training library, and so a benchmark performance measure, called the airfoil technology factor, has also been incorporated into the scheme to allow intelligent metric-based filtering, or design space reduction, of the training library to ensure efficient airfoil deformation modes are by: 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. 8th World Congress on Structural and Multidisciplinary Optimization June 1 - 5,Lisbon, Portugal 1 Robust shape optimization in aeronautics Jordi Pons-Prats1, Gabriel Bugeda 2, Eugenio Oñate 3, Francisco Zárate 4, Jorge Hurtado 5 1 CIMNE – UPC, International Center for Numerical Methods in engineering, Technical University of Catalonia, Barcelona,Cited by: 4.

Airfoil design and optimization by the one‐shot method Kuruvila, G.; Ta'asan, S.; Salas, M.D. Robust airfoil optimization to achieve consistent drag reduction over a mach range.

Robust Multi-Objective Optimization in Aerodynamics using MGDA Daigo Maruyama1 Project-Team OPALE Research Report N° — December — 20 pages. Abstract: This study deals with robust design optimization strategies in aerodynamics, by considering geometric parameters as uncertainty factors, with application to transonic airfoil by: 1.

SYN code. All the points on the airfoil are used as design parameters which are in numbers. Case 1: RAE airfoil at Reynolds number In this case the optimization method is applied to a RAE airfoil at Mach number The constraint of constant lift coe cient is xed at Figure 1 presents the.

and drag with respect to the design parameters are efficiently calculated using a discrete adjoint formulation [3]. F_c. Design variables and box constraints for the airfoil The objective is lift-constrained (Cl _ Cl*) minimization of the drag Cd over the Mach range M • [, ].

f mindeD Cd(d,M) over M • [,] () subject to Cited by: Minimize drag coefficient at single cruise flight condition subject to a thickness and trailing edge angle constraint. Matlab's fmincon function was used to. general, the high-fidelity CFD models used in deterministic shape optimization are expensive in terms of computational cost if applied to robust design.

In this paper, we are concerned with robust design optimization (RDO) of the transonic RAE airfoil, which is a test case in the FP7 European project UMRIDA [1]. The func. Mach is because such airfoil can suppress the backward movement of shock wave occurred over the upper surface of airfoil against increment in ﬂight Mach number, and eventually it results in smaller change in pitching-down moment produced in the rear part of airfoil against increment in ﬂight Mach number.

In fig13 we have plots of the airfoil over a range of Rn's. Presumably the same airfoil over a range of speed variation. The alpha being held at +4°. We see a significant increase in the Cl.

But I see that as more due to the camber variation and basically changing to a trailing edge cusp which strongly aft loads the airfoil and produces more lift. An Integrated Method for Airfoil Pdf Joshua B. Okrent Figure Pdf G. Powers in Front of a U-2 Dragon Lady ([9]) In the modern era, UAVs are used widely among all branches of the armed forces, intelligence agencies, federal, and local law enforcement agencies, as well as civilian agenciesAuthor: Joshua B.

Okrent. Download Xoptfoil for free. Airfoil optimization with Xfoil. Airfoil optimization using the highly-regarded Xfoil engine for aerodynamic calculations.

Starting with a seed airfoil, Xoptfoil uses particle swarm, genetic algorithm and direct search methodologies to perturb the geometry and maximize performance.4/5.Optimization of 2-D Flap Geometry Using Matlab and Fun3D Gregory D.

Howe1 Ebook Institute of Technology, Atlanta, GA, This paper describes work done in the process of creating a workable system for the optimization of two-element high-lift airfoil design based on a fixed "cruise configuration" baseline.