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Multi-Disciplinary and Multi-Objective optimization Method Based on Machine Learning

AIAA JOURNAL 2024年第2期62卷 691-707页

作者： Dai, Jiahua Liu, Peiqing Li, Ling Qu, Qiulin Niu, Tongzhi Beihang Univ Sch Aeronaut Sci & Engn Beijing 100191 Peoples R China Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China

The optimization of aircraft is a typical multidisciplinary and multi-objective problem. To solve this problem, the difficulty lies not only in the high cost of discipline performance evaluation but also in the complex coupling relationship between different disciplines. To improve the optimization efficiency, a new optimization method is proposed, including two new algorithms: conditional generative adversarial nets with vector similarity (VS-CGAN) and distributed single-step deep reinforcement learning with transfer learning (TL-DSDRL). For low-cost disciplines, VS-CGAN learns the relationship between variables and objectives through presampling to compress the variable domains. The cosine function is used to evaluate the similarity between the random noise and generated variables to avoid mode collapse. For high-cost disciplines, TL-DSDRL improves optimization efficiency through pretraining. The newly designed reward function and multi-agent cooperation mechanism enhance the multi-objective search ability of reinforcement learning.

关键词： Reinforcement Learning optimization algorithm Aerodynamic Performance Mean Aerodynamic Chord Generative Adversarial Network Aerodynamic optimization Take off and Landing Reynolds Averaged Navier Stokes

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Quantitative Recognition of Granary Heat Source Using Quantum-Behaved Particle Swarm optimization Method

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JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER 2020年第3期34卷 498-503页

作者： Wang, Kun Liu, Juan Kong, Songtao Cai, Ping Xu, Hongmei Wan, Shibin Chongqing Univ Sci & Technol Coll Mech & Power Engn Chongqing 401331 Peoples R China Chongqing Med & Pharmaceut Coll Higher Educ Res Inst Chongqing 401331 Peoples R China Chongqing Univ Technol Sch Elect & Elect Engn Chongqing 400054 Peoples R China

On the basis of the inverse heat transfer methodology, the quantitative recognition of heat source parameters (location and intensity) in granary is studied using the finite element method and the quantum-behaved particle swarm optimization (QPSO) method. For the quantitative recognition problem of heat source parameters, a recognition system based on QPSO is established: the fitness function of QPSO is constructed according to the offsets between the measuring temperatures and calculating temperatures in granary, and the heat source parameters are obtained by optimizing the fitness function. The influence of heat source intensity, number of measuring points, measurement error, and initial guess value on the recognition results is studied through experiments, and compared with Levenberg-Marquardt method. The results show that the QPSO method in this paper can obviously weaken the influence of the number of measurement points and the initial guess on the recognition results and is able to ameliorate the anti-interference ability to the measurement errors.

关键词： Particle Swarm optimization Convective Heat Transfer Coefficient FEM Inverse Heat Conduction Thermal Conductivity Conjugate Gradient Method Artificial Neural Network Nondestructive Testing optimization algorithm Electron Beam Welding

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optimization of Nonlinear Lateral Characteristic of Lifting-Body Type Reentry Vehicle

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JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION 2009年第3期6卷 239-255页

作者： Jeong, Shinkyu Suzuki, Kunihiro Obayashi, Shigeru Kurita, Mitsuru Tohoku Univ Inst Fluid Sci Aoba Ku Sendai Miyagi 9808577 Japan Japan Aerosp Explorat Agcy Inst Aerosp Technol Tokyo 1828622 Japan

The nonlinear lateral characteristics of a lifting-body type reentry vehicle were improved by applying efficient optimization techniques to determine the optimum configuration. First, the causes for the nonlinear lateral characteristics were investigated by computational fluid dynamics analysis. The results indicated that fins mounted on the Japan Aerospace Exploration Agency's baseline lifting-body configuration cause unsymmetrical development of vortices and result in nonlinear lateral characteristics. An efficienta* optimization algorithm, called efficient global optimization for multiobjective problems, was adopted to improve these nonlinear lateral characteristics. Efficient global optimization for multiobjective problems predicts potential optimum solutions based on the probability estimated by the Kriging model. The computational time for optimization was markedly reduced owing to use of the Kriging model. Further investigations were also performed to determine the effects of the upswept upper-aft and swept-back fin angles. The results indicated that the swept-back fin angle is an important factor controlling the lateral characteristics of the lifting-body type reentry vehicle.

关键词： Reentry Vehicles Lifting Body Kriging Model Vortices CFD Analysis Japan Aerospace Exploration Agency optimization algorithm Angle of Attack Surface Modeling Aerodynamic Characteristics

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Flight Performance optimization of a Multilift Rotorcraft Formation

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JOURNAL OF AIRCRAFT 2017年第4期54卷 1521-1538页

作者： Enciu, J. Horn, J. F. Penn State Univ Dept Aerosp Engn University Pk PA 16802 USA

A numeric optimization is performed for maximizing the cruise performance of a multilift rotorcraft system. The optimization process locates the optimal relative positions of the formation rotorcraft. The optimization problem is formulated as a constrained nonlinear programming problem. Constraints on the distances between the formation rotorcraft are imposed in order to maintain safe separation distances. It is shown that, for every airspeed, an optimal formation geometry can be found that minimizes the rotorcraft power required. An optimization analysis for subsequent airspeeds yields an optimal recommended airspeed that is close to the "bucket" airspeed of the unloaded rotorcraft. The cable length is shown to have a secondary influence on optimization results. The improvement in the resulting multilift mission performance is demonstrated using a nonlinear simulation of the system. It is shown that the operational efficiency of the system can be significantly increased by adopting the optimization results.

关键词： Rotorcrafts True Airspeed Numerical optimization Flight Performance UH 60 Black Hawk Helicopter Aerodynamic Performance Aerodynamic Characteristics Heading Angle Angle of Sideslip optimization algorithm

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Variable-Fidelity optimization of Film-Cooling Hole Arrangements Considering Conjugate Heat Transfer

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JOURNAL OF PROPULSION AND POWER 2018年第5期34卷 1140-1151页

作者： Kim, Yoonki Lee, Sanga Yee, Kwanjung Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 08826 South Korea Seoul Natl Univ Dept Mech & Aerosp Engn Inst Adv Aerosp Technol Seoul 08826 South Korea

In spite of its crucial importance, conjugate heat transfer has been ignored in most film-hole-array optimization studies due to the burdensome associated with added complexity and computational requirements. To cope with this issue and to consider the conduction cooling effects, the hierarchical kriging model was applied to optimize the film-cooling hole array on a high-pressure turbine nozzle. The hierarchical kriging model used in this study consists of three levels and was constructed effectively using both adiabatic-condition-based analyses and conjugate-heat-transfer analyses. The expected-improvement-based efficient globala* optimization algorithm was coupled with the hierarchical kriging model to improve the efficiency of the whole optimization process. As a result, the required computation time to obtain the optimum solution was markedly reduced to a quarter compared to the time without the hierarchical kriging model, and the viability of the method for highly nonlinear and time-consuming problems was proved. Additionally, the conjugate-heat-transfer-based optimum film-hole array showed that it has improved the overall cooling effectiveness and could have a different shape compared to the array obtained under the adiabatic wall condition. The detailed causes of the resultant hole arrangement were thoroughly examined with respect to both the external and internal cooling aspects.

关键词： Conjugate Heat Transfer Analysis Film Cooling Kriging Model Turbine Inlet Temperature Adiabatic Conditions Wall Temperature optimization algorithm Coolant Aerodynamic Properties Nozzle Geometry

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A new trisection method for solving Lipschitz bi-objective optimization problems

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MATHEMATICS AND COMPUTERS IN SIMULATION 2021年 190卷 1186-1205页

作者： Naffeti, Bechir Ammar, Hamadi Carthage Univ Natl Sch Adv Sci & Technol Borj Cedria LR16ES08 Tunis Tunisia Carthage Univ Fac Sci Bizerte Bizerte Tunisia Carthage Univ Fac Econ & Management Nabeul Nabeul Tunisia

In this paper, we develop a branch and bounds algorithm to solve bound-construction bi-objective optimization problem. The proposed algorithm allows to determine an approximation of the Pareto optimal solutions sets in both spaces: decisions and objectives ones. By running alpha-dense space filling curves, we convert a multidimensional bi-objective optimization problem into a one-dimensional one. Hence it gets possible the implementation of the proposed algorithm when objectives depend on more than one decision variable. The proposed algorithm was applied on an engineering problem to find the working space of a robotic manipulator and the obtained results are promising. (C) 2021 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词： optimization algorithm Bi-objective optimization Branch and bounds Trisection methods Lipschitz functions Pareto front Alienor technical

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Airfoil shape design and optimization using multifidelity analysis and embedded inverse design

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AIAA JOURNAL 2006年第9期44卷 2051-2060页

作者： Barrett, Thomas R. Bressloff, Neil W. Keane, Andy J. Univ Southampton Sch Engn Sci Southampton SO17 1BJ Hants England

Design optimization using high-fidelity computational fluid dynamics simulations is becoming increasingly popular, sustaining the desire to make these methods more computationally efficient. A reduction in problem dimensions as a result of improved parameterization techniques is a common contributor to this efficiency. The focus of this paper is on the high-fidelity aerodynamic design of airfoil shapes. A multifidelity design search method is presented which uses a parameterization of the airfoil pressure distribution followed by inverse design, giving a reduction in the number of design variables used in optimization. Although an expensive analysis code is used in evaluating airfoil performance, computational cost is reduced by using a low-fidelity code in the inverse design process. This method is run side by side with a method which is considered to be a current benchmark in design optimization. The two methods are described in detail, and their relative performance is compared and discussed. The newly presented method is found to converge towards the optimum design significantly more quickly than the benchmark method, providing designs with greater performance for a given computational expense.

关键词： NASA Airfoil Computational Fluid Dynamics Simulation Aerodynamic Shape optimization Aerodynamic Efficiency Airfoil Geometry Flow Conditions Reynolds Averaged Navier Stokes optimization algorithm Shape Functions Singular Value Decomposition

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MAINTAINING THE POSITIVE DEFINITENESS OF THE MATRICES IN REDUCED SECANT METHODS FOR EQUALITY CONSTRAINED optimization

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MATHEMATICAL PROGRAMMING 1991年第1期50卷 1-28页

作者： GILBERT, JC 1. International Institute for Applied Systems Analysis A-2361 Laxenburg Austria

We propose an algorithm for minimizing a function f on R(n) in the presence of m equality constraints c that locally is a reduced secant method. The local method is globalized using a nondifferentiable augmented Lagrangian whose decrease is obtained by both a longitudinal search that decreases mainly f and a transversal search that decreases mainly parallel-to c. Our main objective is to show that the longitudinal path can be designed to maintain the positive definiteness of the reduced matrices by means of the positivity of gamma-k(T)delta-k, where gamma-k is the change in the reduced gradient and delta-k is the reduced longitudinal displacement.

关键词： AUGMENTED LAGRANGIAN CONSTRAINED optimization EXACT PENALTY FUNCTION GLOBAL CONVERGENCE optimization algorithm REDUCED SECANT METHOD SUPERLINEAR CONVERGENCE WOLFE STEP-SIZE SELECTION

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Mimicking the collective intelligence of human groups as an optimization tool for complex problems

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CHAOS SOLITONS & FRACTALS 2018年 110卷 259-266页

作者： De Vincenzo, Ilario Massari, Giovanni F. Giannoccaro, Ilaria Carbone, Giuseppe Grigolini, Paolo Politecn Bari Dept Mech Math & Management Vle Japigia 182 I-70126 Bari Italy UOS Bari CNR Inst Photon & Nanotechnol Phys Dept M Merlin Via Amendola 173 I-70126 Bari Italy Imperial Coll London Dept Mech Engn South Kensington Campus London SW7 2AZ England Univ North Texas Ctr Nonlinear Sci POB 311427 Denton TX 76203 USA

A large number ofa* optimization algorithms have been developed by researchers to solve a variety of complex problems in operations management area. We present a novela* optimization algorithm belonging to the class of swarm intelligence optimization methods. The algorithm mimics the decision making process of human groups and exploits the dynamics of such a process as a tool for complex combinatorial problems. In order to achieve this aim, we employ a properly modified version of a recently published decision making model [ 64,65], to model how humans in a group modify their opinions driven by self-interest and consensus seeking. The dynamics of such a system is governed by three parameters: (i) the reduced temperature beta J, (ii) the self-confidence of each agent beta', (iii) the cognitive level 0 <= p <= 1 of each agent. Depending on the value of the aforementioned parameters a critical phase transition may occur, which triggers the emergence of a superior collective intelligence of the population. Our algorithm exploits such peculiar state of the system to propose a novel tool for discrete combinatorial optimization problems. The benchmark suite consists of the NK-Kauffman complex landscape, with various sizes and complexities, which is chosen as an exemplar case of classical NP-complete optimization problem. A comparison with genetic algorithms (GA), simulated annealing (SA) as well as with a multiagent version of SA is presented in terms of efficacy in finding optimal solutions. In all cases our method outperforms the others, particularly in presence of limited knowledge of the agent. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： optimization algorithm Artificial intelligence Collaborative decisions Decision making Group decision Social interactions Complexity Markov chains

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Gradient-Based optimization Method for Experimental Modal Parameter Estimation with Finite Element Model

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AIAA JOURNAL 2024年第9期62卷 3544-3558页

作者： Xu, Zhaoyi Zheng, Gangtie Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China

This paper presents a novel gradient-baseda* optimization algorithm for improving the accuracy of experimentally estimated modal parameters with the assistance of finite element models. Initially, we recast the discrete vibration response equation into a matrix form and formulate the parameter estimation problem in modal analysis as an optimization problem. Then the problem is solved with a gradient-based iterative algorithm, which explicitly exhibits the closed form of gradients used in optimization. Initial values for this iteration are parameters derived from finite element models, since every important engineering structure should be analyzed with a finite element model before it is constructed. Subsequently, the performance of this algorithm is validated by both pure numerical experiments, which simulate the physical world, and experiments using real measurement data gathered by sensors in the real physical world. The algorithm's performance is further enhanced by incorporating gradient clipping and an adaptive iteration threshold. As a comparison, a discussion on classical least-squares time-domain method for the problem is provided. For practical applications, the Shi-Tomasi corner detection and Lucas-Kanade optical flow methods are deployed to detect corner points from videos taken during the vibration of a structure and track the motion of these points in the videos.

关键词： optimization algorithm Finite Element Modeling Acceleration Sensors Operational Modal Analysis algorithms and Data Structures Corner Detection Mechanical and Structural Vibrations Beam (Structures) Applied Mathematics Signal Processing

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