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Response Surface Technique for Static Aeroelastic Optimization on a High-Aspect-Ratio Wing

JOURNAL OF AIRCRAFT 2009年第4期46卷 1444-1450页

作者： Yang, Guowei Chen, Dawei Cui, Kai Chinese Acad Sci Key Lab High Temp Gas Dynam Inst Mech Beijing 100190 Peoples R China

Yang et al study the response surface technique for static aeroelastic optimization on a high-aspect-ration wing. A quadratic polynomial response surface model is put forward based on the CFD-based static aeroelastic ... 详细信息

关键词： High Aspect Ratio CFD Aerodynamic Performance Aerodynamic Configurations Finite Element Modeling Mean Aerodynamic Chord multi objective genetic algorithm Aircraft Configurations Structural Optimization Structural Modeling

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multidisciplinary Code Coupling for Analysis and Optimization of Aeroelastic Systems

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JOURNAL OF AIRCRAFT 2009年第6期46卷 1938-1944页

作者： Nikbay, Melike Oncu, Levent Aysan, Ahmet Istanbul Tech Univ Fac Aeronaut & Astronaut Astronaut Engn Dept TR-34469 Istanbul Turkey

This paper presents a practical methodology for static aeroelastic analysis and aeroelastic optimization via coupling of high-fidelity commercial codes. A finite-volume-based flow solver FLUENT is used to solve three-dimensional Elder equations, Gambit is used to generate mesh in the fluid domain, and CATIA is used to model parametric solid geometry. Abaqus. a structural finite element method solver. is used to compute the structural response of the aeroelastic system. The mesh-based parallel-code coupling interface MpCCI is used to exchange the pressure land displacement information between FLUENT and Abaqus to perform a loosely coupled aeroelastic analysis by a staggered algorithm, and modeFRONTIER software is used as the optimization driver for scheduling a nondominated sorting genetic algorithm initiated with design of experiments. First. an AGARD 445.6 wing configuration is optimized with objectives of maximum lift/drag ratio and minimum weight. Optimization variables are chosen as sweep angle at the quarter-chord and the taper ratio of the wing. Second, a more realistic wing model, ARW-2, is optimized for thickness values of the inner ribs and spars. Aeroelastic analysis produce consistent results with experimental data.. and the applied optimization methodology results in Pareto-optimal solutions.

关键词： Dynamic Aeroelastic Analysis FLUENT Computer Aided Engineering Nastran Structural Finite Elements Angle of Attack multi objective genetic algorithm Sweep Angle Structural Displacement Euler Equations

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multiple objective optimization and inverse design of axial turbomachinery blades

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JOURNAL OF PROPULSION AND POWER 2008年第5期24卷 1093-1099页

作者： Larocca, Francesco Politecn Torino Dipartimento Ingn Aeronaut & Spaziale I-10129 Turin Italy

An optimization procedure, based on a method for solving inverse problems for the design of whole multistage axial turbines and compressors, is presented in the paper. A simplified axisymmetric model of three-dimensional axial turbomachines is adopted in which volume forces replace the stator and rotor. The tangential component of such blade forces represents the design parameters that are defined through the optimization algorithm, whereas the stream surfaces that represent the stators and rotors are obtained by solving the inverse How problem governed by the time-dependent Enter equations. The current optimization procedure takes into account some three-dimensional effects, such as lean and sweep, in the early stages of the design of blade rows by directly controlling the blade loading. The optimization process is based on a multi-objective genetic algorithm in which a search for an optimal Pareto front is performed. Some preliminary numerical examples, which refer to the design of a linear cascade and compressor stage, are discussed.

关键词： Turbomachinery Blading Blade Loading Flow Velocity Inverse Problems Camber multi objective genetic algorithm Euler Equations Design of Compressor Mass Flow CFD Analysis

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multi-objective Optimization of Perturbed Impulsive Rendezvous Trajectories Using Physical Programming

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2008年第6期31卷 1829-1832页

作者： Luo, Ya-zhong Tang, Guo-jin Parks, Geoff Natl Univ Def Technol Coll Aerosp & Mat Engn Changsha 410073 Hunan Peoples R China Univ Cambridge Dept Engn Engn Design Ctr Cambridge CB2 1PZ England

Recently, it has been shown that taking the total velocity characteristic, the time of flight, and the trajectory safety into consideration and constructing a multi-objective optimization problem is an attractive and realistic proposition for rendezvous trajectory design. Luo et al. [1] formulated the multi-objective linearized rendezvous optimization problem and solved it through the multi-objective genetic algorithm NSGA-II. It was shown that the tradeoffs between time of flight, propellant cost, and trajectory safety are quickly established using NSGA-II. In recognition of the drawbacks associated with linearized rendezvous equations, this study was expanded to a nonlinear two-body rendezvous by using NSGA-II and a Lambert algorithm. The nonlinear two-body multi-objective model is more accurate and suitable for more problems in comparison with linearized rendezvous models, which are limited to circular and near-rendezvous. However, the two-body model still does not take into account trajectory perturbations, such as nonspherical perturbations and atmospheric drag, which exist in real operational missions. Thus, it is desirable to be able to obtain Pareto-optimal solutions for perturbed rendezvous trajectories.

关键词： Sequential Quadratic Programming Propellant Spacecraft Trajectory Optimization multi objective genetic algorithm Annealing Lambert algorithm multi objective Evolutionary algorithms Pareto Optimality Perigee Stochastic Optimization

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Tilt control design for high-speed trains: a study on multi-objective tuning approaches

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VEHICLE SYSTEM DYNAMICS 2008年第Sup1期46卷 535-547页

作者： Zamzuri, Hairi Zolotas, Argyrios C. Goodall, Roger M. Univ Loughborough Dept Elect & Elect Engn Loughborough Leics England Univ Teknol Malaysia Coll Sci & Technol Kuala Lumpur Malaysia

This paper presents work on it hybrid fuzzy control scheme to improve the performance of tilting trains using a nulling-based tilt strategy. Two multi-objective genetic algorithm tuning methods (MOGA and NSGAII) were employed to opitimise both the fuzzy output membership functions and the controller parameters. The objective functions incorporated the tilt response and roll gyroscope signals for the deterministic (curved track) profile, and lateral acceleration for the stochastic (straight track) profile. Simulation results discuss the effectiveness of using the presented techniques for tuning the fuzzy control scheme via multiple objectives. The proposed scheme is compared with the conventional nulling-tilt approach and a manually tuned fuzzy controller.

关键词： railway dynamics tilt intelligent control tilting trains fuzzy control multi objective genetic algorithm

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Tilt control design for high-speed trains: a study on multi-objective tuning approaches

Tilt control design for high-speed trains: a study on multi-...

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20th Symposium of the International-Association-for-Vehicle-System-Dynamics

作者： Zamzuri, Hairi Zolotas, Argyrios C. Goodall, Roger M. Univ Loughborough Dept Elect & Elect Engn Loughborough Leics England Univ Teknol Malaysia Coll Sci & Technol Kuala Lumpur Malaysia

ISBN: (纸本)9780415486026

关键词： railway dynamics tilt intelligent control tilting trains fuzzy control multi objective genetic algorithm

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Comparing the N-branch genetic algorithm and the multi-objective genetic algorithm

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AIAA JOURNAL 2004年第7期42卷 1495-1500页

作者： Martin, ET Hassan, RA Crossley, WA Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA

An investigation using four test cases compared performance of aselection-based and a ranking fitness-based GA approach on different types of three-objectiveproblems. For these problems, both approaches reasonably approximate the Pareto set. Results of thesimple constrained and 10-bar truss problems suggest that the N-branch GA is better suited tosolving constrained problems. The adjacent minima problem results favor the MOGA ***'s speed reducer is both highly constrained and has two similar objectives, and it is notclear which approach is preferred here. The MOGA finds more evenly distributed points on the Paretofront than the N-branch GA; however, the N-branch GA finds better solutions near the extremes of thePareto set where constraints are active. Based on the investigations, it is difficult to make adefinitive choice for the preferred MOGA approach. Like many aspects of the GA, the choice appearsproblem dependent. It seems that the N-branch tournament GA is preferred for three-objectiveproblems with solutions that have numerous active conslraints. The MOGA appears preferred forproblems in which two or more objectives are adjacent in the design space. However, for manyengineering problems, it may not be known whether two or more objectives are adjacent a priori. Thesuccess of the N-branch tournament GA demonstrates that a selection-based method can generatemulti-objective solutions that are comparable to those generated by a nondominance ranking method.

关键词： multi objective genetic algorithm Trusses Radiative Transfer Chemical Kinetics Premixed Flame Hydrocarbon Fuels Young's Modulus Astronautics Aeronautics Material Properties

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Airfoil shape optimization for transonic flows of Bethe-Zel'dovich- Thompson fluids

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AIAA JOURNAL 2007年第6期45卷 1303-1316页

作者： Congedo, P. M. Corre, C. Cirmella, P. Univ Lecce Dept Engn Innovat I-73100 Lecce Italy Ecole Natl Super Arts & Metiers SINUMEF Lab F-75013 Paris France

High-performance airfoils for transonic flows of Bethe-Zel'dovich-Thompson fluids are constructed using a robust and efficient Euler How solver coupled with a multi-objective genetic algorithm. Bethe-Zel'dovich-Thompson fluids are characterized by negative values of the fundamental derivative of gasdynamics for a range of temperatures and pressures in the vapor phase, which leads to nonclassical gasdynamic behaviors such as the disintegration of compression shocks. Using Bethe-Zel'dovich-Thompson gases as working fluids may result in low drag exerted on airfoils operating at high transonic speeds, due to a substantial increase in the airfoil critical Mach number. This advantage can be further improved by a proper design of the airfoil shape, also leading to the enlargement of the airfoil operation range within which Bethe-Zel'dovich-Thompson effects are significant. Such a result is of particular interest in view of the exploitation of Bethe-Zel'dovich-Thompson fluids for the development of high-efficiency turbomachinery.

关键词： Supercritical Flow Symmetric Airfoil Shape Optimization Drag Divergence Mach Number Reynolds Averaged Navier Stokes multi objective genetic algorithm Transonic Speed Turbomachinery Lift to Drag Ratio Aerodynamic Performance

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multi-objective pareto concurrent subspace optimization for multidisciplinary design

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AIAA JOURNAL 2007年第8期45卷 1894-1906页

作者： Galuski, J. Bloebaum, C. L. Ind Technol Res Inst Mech & Syst Res Labs Hsinchu 310 Taiwan SUNY Buffalo Dept Mech & Aerosp Engn Buffalo NY 14260 USA

Most real-world design problems are complex and multidisciplinary, with almost always more than one objective (cost) function to be extremized simultaneously. The primary goal of this research is to develop a framework to enable multi-objective optimization of multidisciplinary design applications, wherein each discipline is able to retain substantial autonomous control during the process. To achieve this end, we have extended the capability of the concurrent subspace optimization method to handle multi-objective optimization problems in a multidisciplinary design optimization context. Although the conventional concurrent subspace optimization approach is easily able to deal with multi-objective optimization problems by applying the weighted sum approach, the main disadvantage is that the weighted sum cannot capture Pareto points on any nonconvex part of the Pareto frontier. Moreover, an aggregate objective function simply cannot reflect the true spirit of the concurrent subspace optimization method, which was developed to allow groups of specialists to independently have more control over their own design criteria and goals, even while maintaining system level coordination. In this paper, the multi-objective Pareto concurrent subspace optimization method is proposed in which each discipline has substantial control over its own objective function during the design process, while still ensuring responsibility for constraint satisfaction in coupled subspaces. The proposed approach is particularly useful given the realities of geographical distribution, computational platform variation, and dependence upon legacy codes within individual disciplines that so predominates the design of large-scale products such as aircraft and automobiles. As part of the multi-objective Pareto concurrent subspace optimization method developed here, it is demonstrated that the endpoints of the Pareto frontier can be easily identified, together with an ability to generate Pareto points with

关键词： Pareto Optimality MDO Concurrent Subspace Optimization Method multi objective genetic algorithm Sensitivity Analysis Optimization algorithm Lagrange multipliers Aircraft Design NASA Langley Research Center Evolutionary algorithm

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Aerodynamic optimization of a morphing airfoil using energy as an objective

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AIAA JOURNAL 2007年第9期45卷 2113-2124页

作者： Namgoong, Howoong Crossley, William A. Lyrintzis, Anastasios S. Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA

Recent advances in materials science and actuation technologies have raised interest in morphing aircraft that can significantly change shape during flight. The research discussed in this paper focuses upon the shape design of morphing airfoil sections. In the efforts herein, the relative strain energy needed to change from one airfoil shape to another is presented as an additional design objective along with a drag design objective, while constraints are enforced on lift. Solving the resulting multi-objective problem generates a range of morphing airfoil designs that represent the best tradeoffs between aerodynamic performance and morphing energy requirements. From the multi-objective solutions, a designer can select a set of airfoil shapes with a low relative strain energy that requires a small actuation cost and with improved aerodynamic performance at the design conditions.

关键词： Morphing Airfoil Aerodynamic Performance Aerodynamic Configurations XFoil Boundary Layer Transition multi objective genetic algorithm Shape Functions Actuation Mechanisms Newton's Method Mission Adaptive Wings

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