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Application of optimisation algorithms and multibody dynamics to ground vehicle suspension design

INTERNATIONAL JOURNAL OF HEAVY VEHICLE SYSTEMS 2007年第2期14卷 158-192页

作者： He, Yuping McPhee, John Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON L1H 7K4 Canada Univ Waterloo Waterloo ON N2L 3G1 Canada

A systematic method is proposed for automating the design synthesis of ground vehicle suspensions. This method combines optimisation algorithms and numerical multibody dynamics software and considers ISO 2631 standard requirements on ride quality. The proposed method is tested and evaluated by optimising three ground vehicle models. It is recommended that stochastic global search algorithms be used with numerical multibody dynamics software in the initial design optimisation, whereas gradient-based algorithms should be used in the fine stage of fine-tuning the parameters. Results show that compared with suspension stiffness and damping coefficients or inertial property parameters, geometric parameters have a more significant effect on the ride quality.

关键词： automated design synthesis genetic algorithms GAs sequential quadratic programming SQP simplex algorithm multibody dynamics vehicles suspensions

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Aerogravity-assist maneuvers: Coupled trajectory and vehicle shape optimization

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JOURNAL OF SPACECRAFT AND ROCKETS 2007年第5期44卷 1051-1059页

作者： Armellin, Roberto Lavagna, Michele Starkey, Ryan P. Lewis, Mark J. Politecn Milan Dept Aerosp Engn I-20156 Milan Italy Univ Maryland Dept Aerosp Engn College Pk MD 20742 USA

The aerogravity-assist maneuver is proposed as a tool to improve the efficiency of the gravity assist, because due to the interaction with the planetary atmosphere, the angular deviation of the velocity vector can be definitely increased. Even though the drag reduces the spacecraft velocity, the overall A v gain could be substantial for a high-lift-to-drag vehicle. A previous study addressed the three-dimensional dynamic modeling and optimization of the maneuver, including heliocentric plane change, heating rate, and structural load analysis. A multidisciplinary study of aerogravity assist is proposed, focusing on coupled trajectory and vehicle shape optimization. A planar aerogravity assist of Mars is selected as a test case, with the aim of maximizing the vehicle heliocentric velocity and limiting the heating rate experienced during the atmospheric pass. A multiobjective approach is adopted, and a particle swarm optimization algorithm is chosen to detect the set of Pareto-optimal solutions. The study includes a further refinement of the trajectory for three significant shapes belonging to the Pareto curve. The associated optimal control problem is solved by selecting a direct-method approach. The dynamics are transcribed into a set of nonlinear constraints, and the arising nonlinear programming problem is solved through a sequential quadratic programming solver.

关键词： Trajectory Optimization Aerogravity Assist Particle Swarm Optimization sequential quadratic programming Nonlinear programming Earth Atmosphere Structural Load Aerodynamic Coefficients Aerodynamic Performance Pressure Coefficient

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Optimization of geometrically nonlinear thin shells subject to displacement and stability constraints

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AIAA JOURNAL 2007年第3期45卷 684-692页

作者： Khosravi, Peyman Sedaghati, Ramin Ganesan, Rajamohan Concordia Univ Dept Mech & Ind Engn Montreal PQ H3G 1M8 Canada

A methodology is developed for shape optimization of thin plate and shell structures undergoing large deflections subject to displacement and system stability constraints. The optimization method considers shape parameters and overall thickness of the structure as the design variables and aims to minimize the total mass of the structure subject to stability or displacement constraint. Two optimality criteria based on Karush-Kuhn-Tucker conditions are developed for mass minimization problems. Optimality criteria are combined with nonlinear corotational analysis to optimize structures with geometric nonlinearity. The method is applied to plate and shallow shell structures. The efficiency of the developed design optimization methodology is compared with that of the gradient-based method of optimization (sequential quadratic programming).

关键词： sequential quadratic programming Finite Element Solution Energy Density Beam (Structures) High Aspect Ratio Shape Optimization Spherical Shell Triangular Element Poisson's Ratio Sensitivity Analysis

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Optimization of metal-forming process via a hybrid intelligent optimization technique

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2007年第3期34卷 229-241页

作者： Li, D. Y. Peng, Y. H. Yin, J. L. Shanghai Jiao Tong Univ Sch Mech Engn Inst Knowledge Based Engn Shanghai 200240 Peoples R China

In recent years, finite element simulation has been increasingly combined with optimization techniques and applied to optimization of various metal-forming processes. The robustness and efficiency of process optimization are critical factors to obtain ideal results, especially for those complicated metal-forming processes. Gradient-based optimization algorithms are subject to mathematical restrictions of discontinuous searching space, while nongradient optimization algorithms often lead to excessive computation time. This paper presents a novel intelligent optimization approach that integrates machine learning and optimization techniques. An intelligent gradient-based optimization scheme and an intelligent response surface methodology are proposed, respectively. By machine learning based on the rough set algorithm, initial total design space can be reduced to self-continuous hypercubes as effective searching spaces. Then optimization algorithms can be implemented more effectively to find optimal design results. An extrusion forging process and a U channel roll forming process are studied as application samples and the effectiveness of the proposed approach is verified.

关键词： metal forming finite element simulation rough set algorithm sequential quadratic programming response surface methodology

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Black-box structural optimization of a mechanical component

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COMPUTERS & INDUSTRIAL ENGINEERING 2007年第3期53卷 514-530页

作者： Calvel, Sonia Mongeau, Marcel Univ Toulouse 1 CNRS LAAS F-31077 Toulouse 4 France Technoctr Renault F-78288 Guyancourt France

The aim of this paper is twofold. First, we wish to bring to the attention of the Industrial Engineering community a challenging industrial problem, black-box structural design, which cannot currently be satisfactorily addressed by professional software for topology optimization. The constraint functions considered here are non-linear and implicit, their evaluation requires the resolution of a computation-intensive finite-element analysis performed by a black-box commercial structural mechanics software such as MSC/Nastran. We present here a brief overview of topology optimization methods. Secondly, we propose a practical topology design heuristic methodology for handling such problems, which includes a new interpolation scheme for the fictive-material SIMP model. We present 3D computational experiments on a car component for Renault using a state-of-the-art public-domain nonlinear optimization software to drive the overall optimization process. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： structural optimization topology optimization sequential quadratic programming fictive material model automotive industry heuristics

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Three-dimensional ascent trajectory optimization for stratospheric airship platforms in the jet stream

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2007年第5期30卷 1341-1352页

作者： Lee, Sangjong Bang, Hyochoong Korea Aerosp Res Inst Air Vehicle Syst Dept Div Aircraft Taejon 305333 South Korea Korea Adv Inst Sci & Technol Div Aerosp Engn Taejon 305701 South Korea

Full three-dimensional optimal-ascent trajectory design is addressed for a stratospheric airship platform, considering real jet stream and flight constraints. The target airship's equations of motion are first constructed by including wind effects and its inherent features such as added mass and buoyancy effects. For realistic trajectory optimization, additional necessary modeling of the jet stream, aerodynamic force, and thrust are established based on a flight test, wind-tunnel test, and meteorological observation data. In addition, detailed path constraints such as the target airship's performance and local airspace are also accounted for. The sequential quadratic programming approach is employed as a numerical solver for both minimum flight time and minimum-energy performance indices. The solutions obtained satisfy all of the constraints and are largely affected by the jet stream of high wind speed. From the optimization results, the minimum flight time trajectory is recommended due to the low flight performance of the airship in contrast to its huge size and heavy weight.

关键词： Stratospheric Airship Trajectory Optimization Jet Stream Aerodynamic Coefficients Flight Testing Airspace sequential quadratic programming Buoyancy Effects Wind Tunnel Tests Flight Performance

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Object library of algorithms for dynamic optimization problems: Benchmarking SQP and nonlinear interior point methods

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2007年第4期17卷 515-537页

作者： Blaszczyk, Jacek Karbowski, Andrzej Malinowski, Krzysztof Warsaw Univ Technol Fac Elect & Informat Technol Inst Control & Computat Engn PL-00665 Warsaw Poland Res & Acad Comp Network NASK PL-02796 Warsaw Poland

The main purpose of this paper is to describe the design, implementation and possibilities of our object-oriented library of algorithms for dynamic optimization problems. We briefly present library classes for the formulation and manipulation of dynamic optimization problems, and give a general survey of solver classes for unconstrained and constrained optimization. We also demonstrate methods of derivative evaluation that we used, in particular automatic differentiation. Further, we briefly formulate and characterize the class of problems solved by our optimization classes. The solution of dynamic optimization problems with general constraints is performed by transformation into structured large-scale nonlinear programming problems and applying methods for nonlinear optimization. Two main algorithms of solvers for constrained dynamic optimization are presented in detail: the sequential quadratic programming (SQP) exploring the multistage structure of the dynamic optimization problem during the solution of a sequence of quadratic subproblems, and the nonlinear interior-point method implemented in a general-purpose large-scale optimizer IPOPT. At the end, we include a typical numerical example of the application of the constrained solvers to a large-scale discrete-time optimal control problem and we use the performance profiles methodology to compare the efficiency and robustness of different solvers or different options of the same solver. In conclusions, we summarize our experience gathered during the library development.

关键词： dynamic optimization large-scale optimization sequential quadratic programming nonlinear interior-point methods object-oriented numerical computations automatic differentiation performance data analysis

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Multidisciplinary design optimization of a zero-emission vehicle chassis considering crashworthiness and hydroformability

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2007年第D5期221卷 511-526页

作者： Cristello, Nick Kim, Il Yong Queens Univ Dept Mech & Mat Engn Kingston ON K7L 3N6 Canada

This research used multidisciplinary design optimization to optimize the ladder frame chassis of a zero-emission vehicle by simultaneously considering three objective functions: (a) chassis mass, (b) deceleration during collision, and (c) manufacturability of a part in hydroforming. Additionally, design constraints were placed on torsional and bending stiffness, maximum von-Mises stress, and the natural frequency in torsion and bending. Optimization was completed in a three-phase approach: phase one used a simplified chassis model to conduct topology optimization with genetic algorithms;phase two was conducted to determine an optimum cross-sectional type and shape;and phase three incorporated results from phases one and two, into a high-fidelity, three-dimensional chassis model, for gradient-based optimization. Results from all phases of the design optimization indicated that improvements could be made over the baseline configuration. Through examination of Pareto frontiers in phase three, distinct trade-offs were identified between all objective functions: a 5 per cent reduction in chassis mass was required to maximize hydroformability;to minimize mass required a 90 per cent increase in deceleration;and minimization of deceleration required an 18 per cent decrease in hydroformability. Tri-objective optimization was used to generate a three-dimensional Pareto frontier 'surface' to show the impact of one objective function on all others simultaneously.

关键词： multidisciplinary design optimization zero-emission vehicle light weight crashworthiness hydroformability genetic algorithms sequential quadratic programming Pareto frontier chassis

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Heliocentric solar sail orbit transfers with locally optimal control laws

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JOURNAL OF SPACECRAFT AND ROCKETS 2007年第1期44卷 273-276页

作者： Macdonald, Malcolm McInnes, Colin R. Dachwald, Bernd Univ Glasgow Glasgow G12 8QQ Lanark Scotland Univ Strathclyde Glasgow G1 1XJ Lanark Scotland German Aerosp Ctr DLR D-51170 Cologne Germany

A previous (planetocentric) method of assessing the relative importance oforbit elements during solar sail transfers called accessibility and deficit, A~nD, blending has beenevolved, allowing rapid generation of heliocentric trajectories by blending locally optimal controllaws. An Earth-Mercury trajectory was presented to demonstrate the capability of A~nD blending whenattempting to find planet-to-planet transfer trajectories. It was found that the A~nD generatedtrajectory duration was within 1% of the sequential quadratic programming, SQP, generatedtrajectory. Thus, A~nD blending can provide a very good rapid assessment of such a mission scenario,or provide an excellent initial guess for further optimization as part of a detailed missionanalysis. The A~nD blending method has also been demonstrated for generation of sail trajectories to200 AU, where it was repeatedly shown that A~nD generated trajectories were very similar induration to the transfer time found using an evolutionary neurocontroller, which is expected to benear global optimal. Furthermore, the A~nD generated trajectories were consistently more efficientthan SQP generated trajectories. A~nD blending has been shown to be able to optimize a solar sailtrajectory using a nonideal sail force model. The A~nD blending results clearly demonstrate that anonideal sail will require a characteristic acceleration of approximately 1.5 mm · s~(-1) to reach200 AU in 25 years, assuming no optical surface degradation.

关键词： Solar Electric Propulsion Trajectory Optimization sequential quadratic programming Earth Perihelion Solar System Propulsion System Sample Return Missions Space Environment Osculating Orbit

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Computation of the empirical likelihood ratio from censored data

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2007年第11-12期77卷 1103-1112页

作者： Chen, Kun Zhou, Mai Univ Kentucky Dept Stat Lexington KY 40506 USA Bayer Pharmaceut W Haven West Haven CT 06516 USA

The empirical likelihood ratio method is a general nonparametric inference procedure that has many desirable properties. Recently, the procedure has been generalized to several settings including testing of weighted means with right-censored data. However, the computation of the empirical likelihood ratio with censored data and other complex settings is often nontrivial. We propose to use a sequential quadratic programming (SQP) method to solve the computational problem. We introduce several auxiliary variables so that the computation of SQP is greatly simplified. Examples of the computation with null hypothesis concerning the weighted mean are presented for right- and interval-censored data.

关键词： sequential quadratic programming maximization constraints Wilks' theorem

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