A Rapid Synthesis Method to Develop Conceptual Design Transonic Wing Lofts

Donovan, Shane; Takahashi, Timothy T.

doi:10.2514/6.2010-9025

Cited by 11 publications

(6 citation statements)

References 2 publications

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“…Mason asserts that the Korn Equation "identifies the connection between drag divergence Mach number and airfoil lift and thickness at the drag divergence Mach number." [15] Mason explains that this relationship was largely empirically derived with computational aerodynamic methods. The Korn Equation is presented as:…”

Section: Prior Artmentioning

confidence: 97%

“…Mason introduced the concept of the "Korn Equation" as a means to understand the attainable transonic limits of thick, cambered airfoils [15]. Mason asserts that the Korn Equation "identifies the connection between drag divergence Mach number and airfoil lift and thickness at the drag divergence Mach number."…”

Section: Prior Artmentioning

confidence: 99%

“…Equation 15 is very quickly recognized as being elegant and quite simple to implement. Because the drag divergence Mach number has a one-to-one correlation with the critical Mach number of an airfoil, the Korn However appealing the Korn equation appears to be for design, the authors' began to sense its limitation when using it to allocate spanwise thickness and camber distributions on finite wings.…”

Section: Prior Artmentioning

confidence: 99%

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Allocating Section Thickness and Camber for Transonic Wing Design

Kady

Takahashi

2014

52nd Aerospace Sciences Meeting

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The ability to empirically allocate the spanwise distribution of thickness across a wing during the earliest phases of conceptual design is extremely useful. Quantitative statistical design for system optimization studies requires a reliable allocation process, directly traceable to a final loft. In choosing the local section thickness ratio of a wing, there are multiple considerations which are at first, somewhat unintuitive to make. For each strip, from root to tip, the allowable wing thickness as well as the necessary camber and incidence depends broadly upon the local lift the strip must sustain as well as the design Mach number for the incoming flows. The difficulty in developing a concise technique or equation to simultaneously determine thickness and camber stems from a cross-coupling of common design variables. A statistical study of potential flow solutions lead to develop a technique which the reader may use to supplant the Korn Equation, choosing specific rather than generalized theoretically attainable airfoils to meet specific lift and critical Mach number conditions. Subtle, yet important, non-linearities were found in the coupling between allowable thickness, critical Mach number and design lift coefficient. Nomenclature CL = Lift CoefficientCL max = Maximum Lift Coefficient CL des = Design Point Lift Coefficient Cp = Dimensionless Pressure Coefficient = (P-P  )/q Cp* = Dimensionless Pressure Coefficient corresponding to the Sonic Condition L/D = Lift-to-Drag Ratio M = Mach number M cr = Critical Mach Number (where flow first goes sonic) M des = Design Mach Number M dd = Drag Divergence Mach Number (where pressure drag losses due to shock formation become significant) P = Pressure q = Dynamic Pressure t/c = Wing Section Thickness-to-Chord Ratio V = Velocity  = Angle of Attack (degrees)  = Prandtl-Glauert Factor  = Potential  = Specific Heat Ratio of Air (typically 1.4)

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Section: Prior Artmentioning

confidence: 97%

Section: Prior Artmentioning

confidence: 99%

Section: Prior Artmentioning

confidence: 99%

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Allocating Section Thickness and Camber for Transonic Wing Design

Kady

Takahashi

2014

52nd Aerospace Sciences Meeting

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“…Küchemann & Weber 25 , Mason 17 , Donovan & Takahashi 18 , and Takahashi, Dulin & Kady 26 describe more complex methods to select the wing thickness of a conceptual aircraft loft. Incorporating too thick of a wing will induce more suction (lower C p_min on the upper surface) which tends to reduce the critical Mach number at a given sweep angle; excess thickness can cause flow separation near the trailing edge due to a strong adverse pressure gradient arising from the thickness.…”

Section: B Main Wingmentioning

confidence: 99%

“…Along with these, government "legacy" codes, our team incorporated an ASU developed point-mass simulation Mission Code. We also developed a wing thickness allocation tool based upon the swept-wing Korn equation 17,18 , and a point-performance "SkyMap" tool 19 to compute energy-maneuverability style aircraft-performance suitable to choose optimum climb speeds and other important design parameters 20 .…”

Section: Introductionmentioning

confidence: 99%

Multi-Disciplinary Optimization of a Near Sonic Airliner

Mirochnitchenko

Swann

Stallings

et al. 2015

56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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In the highly competitive world of commercial passenger aircraft, many have attempted to create an aircraft that completes its mission efficiently without sacrificing speed. Many believe that these parameters are mutually exclusive; high speed flight comes with a loss of efficiency. In this paper we rebut that proposition and propose a design that combines both speed and efficiency. Here, we size and configure a commercial transport aircraft with mission parameters similar to a Boeing 737-900 but with a significantly higher cruise speed and lower fuel burn. Our transonic cruise airliner carries up to 215 passengers in a single class high-density layout, flying a mission of 3,235 nM plus a 200 nM divert to alternate at a Mach 0.95 cruise. It performs this mission more efficiently than a Boeing 737-900. A byproduct of this design for maximum performance and minimum fuel burn is an aircraft that cruises at a high altitude (46,000-ft) and greatly exceeds the take-off and landing capability of conventional airliners (an estimated take-off field length less than 5,200 feet at maximum takeoff weight and an estimated landing distance at maximum landing weight less than 3,500 feet). This study documents our MDO tool construction process. It also explains our reasoning, developed by performing numerous MDO trade studies, which leads us to a novel configuration.Pressure Coefficient (i.e. at Mach=0) D = Drag (lbf) _ = Dynamic yaw coefficient E = Modulus of elasticity (lbf/in 2 ) F = Force (lbf) FF = Fuel flow (lbm/hr) I = Moment of Inertia k = Airfoil technology factor L/D = Lift to drag ratio λ = Taper ratio LCDP = Lateral Control Departure Parameter Λ LE = Leading edge sweep (deg) M cruise = Mach number at cruise M D = Mach number during dive maneuver M(L/D) = Aerodynamic efficiency parameter MTOW = Maximum takeoff weight (lbm) MZFW = Maximum zero fuel weight (lbm) n = Load factor (g's) n z_max = Maximum load factor along the z axis (g's) OEW = Operational empty weight (lbm) ROC = Rate of climb (ft/min) SET = Specific excess thrust S L = Landing field length (ft) SM = Static margin SR = Specific range (nM) S ref = Wing reference area (ft 2 ) S TOBFL = Take-off balanced field length (ft) W/S = Wing loading (lbm/ft 2 ) σ = Density ratio of air relative to sea-level T = Thrust (lbf) TOP 25 = Take-off parameter t/c = Wing thickness (%) T/W = Thrust to weight ratio (lbf/lbm) V = Air speed (nm/hr) V A = Design maneuvering speed V C = Design cruise speed V D = D e s i g n d i v e s p e e d V E = Design slow down speed V F = Design flap speed V H = Design level flight speed ω dr = Dutch roll natural frequency (Hz) ω sp = Short period natural frequency (Hz)

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RPAS Design : an MDO Approach

Aliaga-Aguilar¹

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Unmanned aircraft and, particularly, RPAS (Remotely Piloted Aircraft Systems) are nowadays experiencing great growth both in the military and civil industries. This is due to the fact that removing the need to be manned has enabled the improvement of their endurance, range, and overall performance while, at the same time, reducing the risk to which human lives were exposed. In addition, RPAS can be made much smaller. This decrease of mass and size increases the variety of missions they can perform. However, the design process to manufacture such aircraft is often long and costly, which prevents small companies from undertaking it. Multidisciplinary Design Optimization (MDO) is an engineering field whose focus is to solve highly complex problems by the means of optimization techniques. It has been used in the design of commercial aircraft for a long time, but integrating the various engineering disciplines that take part in designing an RPAS within an MDO to simplify the design process is a challenge. In addition, there is an ample variety of architectures for MDO projects and, the reasons to choose a particular one, have to be discussed on a case by case basis. During the last years, distributed architectures have become widespread, given that they can take advantage of parallel computing (even with graphical platforms) and reduce computing time. Adapting the formulation of a problem to a particular vii Dissertation Overview Chapter 1: This is the introduction to the thesis. It presents the evolution of RPAS and the current state of the art both in MDO and in RPAS design methodologies. Chapter 2 introduces the Generic Parameter Penalty Architecture (GPPA): a new, flexible MDO architecture, oriented towards the solution of engineering problems that present different levels of complexity. Chapter 3 introduces the RPAS Advanced MDO Platform (RAMP). A new MDO environment aimed at the design of small RPAS. Chapters 4-7 present RAMP's main analysis models: aerodynamics, structure, economy and pricing, propulsion, and performance. Chapter 8 presents an application case of RAMP to a real-world mission. Chapter 8 does so by limiting RAMP's configuration availability to just classical. This provides the opportunity to compare its results to most commercially available RPAS, while Chapter 9 unleashes RAMP's full capabilities to also consider Blended Wing Body (BWB) and Canard configurations. Chapter 9 presents results for the various tests and hypothesis that are presented in the thesis, while Chapter 10 serves to give shape to the conclusions of the thesis and the future lines of research.

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A Rapid Synthesis Method to Develop Conceptual Design Transonic Wing Lofts

Cited by 11 publications

References 2 publications

Allocating Section Thickness and Camber for Transonic Wing Design

Allocating Section Thickness and Camber for Transonic Wing Design

Multi-Disciplinary Optimization of a Near Sonic Airliner

RPAS Design : an MDO Approach

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