Aircraft Aerodynamic Design : Geometry and Optimization. için kapak resmi
Aircraft Aerodynamic Design : Geometry and Optimization.
Başlık:
Aircraft Aerodynamic Design : Geometry and Optimization.
Yazar:
Sóbester, András.
ISBN:
9781118534717
Yazar Ek Girişi:
Basım Bilgisi:
1st ed.
Fiziksel Tanımlama:
1 online resource (265 pages)
Seri:
Aerospace Series
İçerik:
AIRCRAFT AERODYNAMIC DESIGN -- Contents -- Series Preface -- Preface -- 1 Prologue -- 2 Geometry Parameterization: Philosophy and Practice -- 2.1 A Sense of Scale -- 2.1.1 Separating Shape and Scale -- 2.1.2 Nondimensional Coefficients -- 2.2 Parametric Geometries -- 2.2.1 Pre-Optimization Checks -- 2.3 What Makes a Good Parametric Geometry: Three Criteria -- 2.3.1 Conciseness -- 2.3.2 Robustness -- 2.3.3 Flexibility -- 2.4 A Parametric Fuselage: A Case Study in the Trade-Offs of Geometry Optimization -- 2.4.1 Parametric Cross-Sections -- 2.4.2 Fuselage Cross-Section Optimization: An Illustrative Example -- 2.4.3 A Parametric Three-Dimensional Fuselage -- 2.5 A General Observation on the Nature of Fixed-Wing Aircraft Geometry Modelling -- 2.6 Necessary Flexibility -- 2.7 The Place of a Parametric Geometry in the Design Process -- 2.7.1 Optimization: A Hierarchy of Objective Functions -- 2.7.2 Competing Objectives -- 2.7.3 Optimization Method Selection -- 2.7.4 Inverse Design -- 3 Curves -- 3.1 Conics and Bézier Curves -- 3.1.1 Projective Geometry Construction of Conics -- 3.1.2 Parametric Bernstein Conic -- 3.1.3 Rational Conics and Bézier Curves -- 3.1.4 Properties of Bézier Curves -- 3.2 Bézier Splines -- 3.3 Ferguson's Spline -- 3.4 B-Splines -- 3.5 Knots -- 3.6 Nonuniform Rational Basis Splines -- 3.7 Implementation in Rhino -- 3.8 Curves for Optimization -- 4 Surfaces -- 4.1 Lofted, Translated and Coons Surfaces -- 4.2 Bézier Surfaces -- 4.3 B-Spline and Nonuniform Rational Basis Spline Surfaces -- 4.4 Free-Form Deformation -- 4.5 Implementation in Rhino -- 4.5.1 Nonuniform Rational Basis Splines-Based Surfaces -- 4.5.2 Free-Form Deformation -- 4.6 Surfaces for Optimization -- 5 Aerofoil Engineering: Fundamentals -- 5.1 Definitions, Conventions, Taxonomy, Description -- 5.2 A 'Non-Taxonomy' of Aerofoils -- 5.2.1 Low-Speed Aerofoils.

5.2.2 Subsonic Aerofoils -- 5.2.3 Transonic Aerofoils -- 5.2.4 Supersonic Aerofoils -- 5.2.5 Natural Laminar Flow Aerofoils -- 5.2.6 Multi-Element Aerofoils -- 5.2.7 Morphing and Flexible Aerofoils -- 5.3 Legacy versus Custom-Designed Aerofoils -- 5.4 Using Legacy Aerofoil Definitions -- 5.5 Handling Legacy Aerofoils: A Practical Primer -- 5.6 Aerofoil Families versus Parametric Aerofoils -- 6 Families of Legacy Aerofoils -- 6.1 The NACA Four-Digit Section -- 6.1.1 A One-Variable Thickness Distribution -- 6.1.2 A Two-Variable Camber Curve -- 6.1.3 Building the Aerofoil -- 6.1.4 Nomenclature -- 6.1.5 A Drawback and Two Fixes -- 6.1.6 The Distribution of Points: Sampling Density Variations and Cusps -- 6.1.7 A MATLAB® Implementation -- 6.1.8 An OpenNURBS/Rhino-Python Implementation -- 6.1.9 Applications -- 6.2 The NACA Five-Digit Section -- 6.2.1 A Three-Variable Camber Curve -- 6.2.2 Nomenclature and Implementation -- 6.3 The NACA SC Families -- 6.3.1 SC(2) -- 7 Aerofoil Parameterization -- 7.1 Complex Transforms -- 7.1.1 The Joukowski Aerofoil -- 7.2 Can a Pair of Ferguson Splines Represent an Aerofoil? -- 7.2.1 A Simple Parametric Aerofoil -- 7.3 Kulfan's Class- and Shape-Function Transformation -- 7.3.1 A Generic Aerofoil -- 7.3.2 Transforming a Legacy Aerofoil -- 7.3.3 Approximation Accuracy -- 7.3.4 The Kulfan Transform as a Filter -- 7.3.5 Computational Implementation -- 7.3.6 Class- and Shape-Function Transformation in Optimization: Global versus Local Search -- 7.3.7 Capturing the Shared Features of a Family of Aerofoils -- 7.4 Other Formulations: Past, Present and Future -- 8 Planform Parameterization -- 8.1 The Aspect Ratio -- 8.1.1 Induced Drag -- 8.1.2 Structural Efficiency -- 8.1.3 Airport Compatibility -- 8.1.4 Handling -- 8.2 The Taper Ratio -- 8.3 Sweep -- 8.3.1 Terminology -- 8.3.2 Sweep in Transonic Flight.

8.3.3 Sweep in Supersonic Flight -- 8.3.4 Forward Sweep -- 8.3.5 Variable Sweep -- 8.3.6 Swept-Wing 'Growth' -- 8.4 Wing Area -- 8.4.1 Constraints on the Wing Area -- 8.5 Planform Definition -- 8.5.1 From Sketch to Geometry -- 8.5.2 Introducing Scaling Factors: A Design Heuristic and a Simple Example -- 8.5.3 More Complex Planforms and an Additional Scaling Factor -- 8.5.4 Spanwise Chord Variation -- 9 Three-Dimensional Wing Synthesis -- 9.1 Fundamental Variables -- 9.1.1 Twist -- 9.1.2 Dihedral -- 9.2 Coordinate Systems -- 9.2.1 Cartesian Systems -- 9.2.2 A Wing-Bound, Curvilinear Dimension -- 9.3 The Synthesis of a Nondimensional Wing -- 9.3.1 Example: A Blended Box Wing -- 9.3.2 Example: Parameterization of a Blended Winglet -- 9.4 Wing Geometry Scaling. A Case Study: Design of a Commuter Airliner Wing -- 9.5 Indirect Wing Geometry Scaling -- 10 Design Sensitivities -- 10.1 Analytical and Finite-Difference Sensitivities -- 10.2 Algorithmic Differentiation -- 10.2.1 Forward Propagation of Tangents -- 10.2.2 Reverse Mode -- 10.3 Example: Differentiating an Aerofoil from Control Points to Lift Coefficient -- 10.4 Example Inverse Design -- 11 Basic Aerofoil Analysis: A Worked Example -- 11.1 Creating the .dat and .in files using Python -- 11.2 Running XFOIL from Python -- 12 Human-Powered Aircraft Wing Design: A Case Study in Aerodynamic Shape Optimization -- 12.1 Constraints -- 12.2 Planform Design -- 12.3 Aerofoil Section Design -- 12.4 Optimization -- 12.4.1 NACA Four-Digit Wing -- 12.4.2 Ferguson Spline Wing -- 12.5 Improving the Design -- 13 Epilogue: Challenging Topological Prejudice -- References -- Index -- EULA.
Özet:
Optimal aircraft design is impossible without a parametric representation of the geometry of the airframe. We need a mathematical model equipped with a set of controls, or design variables, which generates different candidate airframe shapes in response to changes in the values of these variables. This model's objectives are to be flexible and concise, and capable of yielding a wide range of shapes with a minimum number of design variables. Moreover, the process of converting these variables into aircraft geometries must be robust. Alas, flexibility, conciseness and robustness can seldom be achieved simultaneously. Aircraft Aerodynamic Design: Geometry and Optimization addresses this problem by navigating the subtle trade-offs between the competing objectives of geometry parameterization. It beginswith the fundamentals of geometry-centred aircraft design, followed by a review of the building blocks of computational geometries, the curve and surface formulations at the heart of aircraft geometry. The authors then cover a range of legacy formulations in the build-up towards a discussion of the most flexible shape models used in aerodynamic design (with a focus on lift generating surfaces). The book takes a practical approach and includes MATLAB®, Python and Rhinoceros® code, as well as 'real-life' example case studies. Key features:  Covers effective geometry parameterization within the context of design optimization Demonstrates how geometry parameterization is an important element of modern aircraft design Includes code and case studies which enable the reader to apply each theoretical concept either as an aid to understanding or as a building block of their own geometry model Accompanied by a website hosting codes Aircraft Aerodynamic Design: Geometry and Optimization is a practical guide for researchers and practitioners in the aerospace

industry, and a reference for graduate and undergraduate students in aircraft design and multidisciplinary design optimization.
Notlar:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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