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Space Debris Removal with Harpoon Assistance: Choice of Parameters and optimization

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2021年第4期44卷 767-778页

作者： Sizov, Dmitry A. Aslanov, Vladimir S. Samara Natl Res Univ Dept Theoret Mech 34 Moscovskoe Shosse Samara 443086 Russia

This paper discusses three phases of the space debris removal with harpoon assistance: capture, tether deployment, and towing. The harpoon impact momentum is used to detumble the target. Equations of motion for each phase are given in dimensionless form, which significantly reduces the number of parameters describing the system. The aim of the paper is to propose algorithms for choosing optimal parameters for the capture and tether deployment phases. This optimization provides small amplitudes of the tether and debris oscillations during towing. The numerical simulations of the removal of a spent Ariane 4 upper stage H10 confirm the correctness of the proposed mathematical models anda* optimization algorithms.

关键词： Space Debris Numerical Simulation optimization algorithm Mathematical Models Phase Diagram Total Energy Kinetic Energy Angular Motion International Space Station Space Tethers

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Example of a Pitfall in Aerodynamic Shape optimization

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AIAA JOURNAL 2018年第4期56卷 1532-1540页

作者： Destarac, Daniel Carrier, Gerald Anderson, George R. Nadarajah, Siva Poole, Daniel J. Vassberg, John C. Zingg, David W. ONERA French Aerosp Lab F-92190 Meudon France Sci & Technol Corp Moffett Field CA 94035 USA McGill Univ Montreal PQ H3A 2S6 Canada Univ Bristol Bristol BS8 1TR Avon England Boeing Co Long Beach CA 90808 USA Univ Toronto 100 Coll St Toronto ON M5S 1A1 Canada

The Applied Aerodynamics Technical Committee of AIAA launched an optimization discussion group, the Aerodynamic Design optimization Discussion Group, in 2013. One of the four benchmark test cases is based on the NACA 0012 airfoil and solutions of the Euler equations with prescribed objective function and geometric constaints. Volunteer participants were invited by ONERA-The French Aerospace Lab to submit their optimized shapes for uniform pressure drag assessment through grid convergence. The assessment required three phases. Initial investigations with a simple protocol proved insufficient and raised some questions. This led to further investigations, which showed that, for most optimized airfoils, there exists a lower drag branch and a higher drag branch in the drag (Mach number) diagram. Hysteresis was observed when performing a downward Mach number sweep and an upward Mach number sweep. For several airfoils, the design Mach number falls within the overlap range of the two branches, which indicates that two solutions may exist for the same airfoil. Two kinds of supersonic flow structure can be distinguished. One kind produces a lower drag branch and the other a higher drag branch. The jump from one branch to the other involves nonsymmetrical converged solutions. These further investigations required a final assessment, where a protocol was instituted to ensure that the lower drag branch was captured by taking advantage of the hysteresis. However, nonuniqueness may confound ana* optimization algorithm because the same set of design variables can give two different objective function values.

关键词： Aerodynamic Shape optimization NACA 0012 Supersonic Flow Hysteresis Euler Equations optimization algorithm Supersonic Wave Computational Fluid Dynamics Pressure Coefficient Finite Volume Formulation

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Waveform optimization for Transmit Beamforming With MIMO Radar Antenna Arrays

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2015年第2期63卷 543-552页

作者： Guo, Lilin Deng, Hai Himed, Braham Ma, Tan Geng, Zhe Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA Air Force Res Lab Wright Patterson AFB OH 45433 USA

For coherent MIMO radar the optimal target signal processing can be achieved for any transmitted waveforms or radiation beam pattern, making transmit beamforming through waveform design possible without degrading target detection performance. In this work, an innovative waveform optimization approach termed phase-only variable metric method (POVMM) is proposed for coherent MIMO radar waveform design to form a desired transmit beam pattern such as one with radiation nulls in certain directions. The waveform design is carried out by minimizing the radiation powers of the MIMO radar antenna in the selected directions with optimization variables constrained to the waveform phases only. The gradient function of the cost function with regard to waveform phases is analytically derived for the optimization and the POVMM is developed based on the variable metric methods with a flexible search step sizing strategy for improving optimization efficiency. The proposed approach is validated with various designs and simulations.

关键词： Antenna array optimization algorithm phased arrays transmit beamforming waveform design

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Low-Thrust Trajectory optimization with Averaged Dynamics Using Analytical Switching Detection

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2024年第6期47卷 1135-1149页

作者： Wu, Di Cheng, Lin Gong, Shengping Baoyin, Hexi Tsinghua Univ Sch Aerosp Engn Beijing 100084 Peoples R China Beihang Univ Sch Astronaut Beihang 102206 Peoples R China

This paper presents an efficient indirect optimization method for the time- and fuel-optimal low-thrust many-revolution transfers with averaged dynamics. Compared with the previous indirect method, the proposed method involves a new set of variables and several near-optimal control laws to formulate the two-point boundary value problem based on three practical assumptions. Then, the costate transformations between two reference frames are first derived with respect to the the corresponding Eulerian angles, such that the switching function can be expressed with a six-degree polynomial function and the number of parameters used to determine the energy-optimal solutions is reduced to 6. Finally, a neural network is trained to generated the initial guesses, and the solution algorithms for solving the time- and fuel-optimal problem are formulated. Numerical simulations demonstrate that the convergence ratio of initial guesses is higher than 98%, the proposed assumptions are reasonable for guaranteeing the near optimality, and the presented method can obtain convergent solutions within tenths of a second for the Earth- and moon-centered external/interior transfers considering the shadow J2 and third-body perturbations.

关键词： Pontryagin's Maximum Principle Solar System Moons Planets algorithms and Data Structures Artificial Neural Network Boundary Element Method Numerical Simulation optimization algorithm Propellant Geostationary Transfer Orbit

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Evolution strategies for film cooling optimization

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AIAA JOURNAL 2001年第3期39卷 537-539页

作者： Müller, SD Walther, JH ETH Zentrum Swiss Fed Inst Technol Inst Computat Sci CH-8092 Zurich Switzerland

Presents a study which implemented an evolutionary algorithm in a realistic automated design cycle of turbine blade film cooling. Description of a blade cooling configuration; Blade cooling optimization; Conclusions.

关键词： Film Cooling Radial Velocity Vortex Breakdown Coolant Angle of Attack Delta Wing Ogive Cylinder Heat Transfer Charge Coupled Device optimization algorithm

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ENGINEERING CODE FOR HYPERSONIC VEHICLE optimization

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JOURNAL OF SPACECRAFT AND ROCKETS 1994年第1期31卷 150-152页

作者： THOMPSON, RA RILEY, CJ NASA Langley Research Center Hampton Virginia 23681

The integration of an approximate engineering code with an optimization routine is carried out to produce a useful engineering tool. To demonstrate the usefulness of this approach, the integrated procedure is used to calculate minimum drag and minimum heat-load nose shapes for a 5-deg conical body with a 3.2808-ft base radius. The results obtained with the integrated procedure are summarized. It is noted that extensions to more complex shapes and a greater range of design parameters require further study. (AIAA)

关键词： Hypersonic Vehicles Freestream Conditions Boundary Layer Equations Aerothermodynamic optimization Stagnation Region Perfect Gas Shock Layers Hypersonic Flows optimization algorithm Wind Tunnels

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A human-computer cooperation improved ant colony optimization for ship pipe route design

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OCEAN ENGINEERING 2018年 150卷 12-20页

作者： Wang, Yun-long Yu, Yan-yun Li, Kai Zhao, Xue-guo Guan, Guan Dalian Univ Technol Sch Naval Architecture Dalian 116024 Peoples R China

This paper presents a human-computer cooperation improved ant colony optimization (HCCIACO) algorithm for ship pipe route design (SPRD). SPRD is a conbinatorial optimization problem with various performance constraints, its hard to fmd an effective solution only by computer. Based on the human-computer cooperation theory, the HCCIACO algorithm takes full advantage of designers' expertise and experience as well as computers' calculation ability. It conbines the artificial sulotion and algorithm solution in the genetic sense of the improved ant colony optimization (IACO) algorithm so that the optimization approach for SPRD in three-dimensional space can be obtained. The improved ant colony optimization simplifies the problem by reducing the complexity in calculation and engineering to some extent. Meanwhile, it guides the algorithm to search effectively for the stable solution which satisfies the engineering requirements. in this paper, the structure and updating method of artificial solution as well as the combination mode of artificial solution and algorithm solution have been researched. Compare with the conventional mathod, HCCIACO algorithm not only improves the convergence speed, but also improves the quality of the solution. Finally, the simulation results demonstrate the feasibility and efficiency of the proposed algorithm.

关键词： Ship pipe route design optimization algorithm Human-computer cooperation Artificial solution algorithm solution Ant colony algorithm

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Machine Learning-Driven APPs Recommendation for Energy optimization in Green Communication and Networking for Connected and Autonomous Vehicles

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

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IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING 2022年第3期6卷 1543-1552页

作者： Xu, Yueshen Lin, Junwei Gao, Honghao Li, Rui Jiang, Zhiping Yin, Yuyu Wu, Yinchen Xidian Univ Sch Comp Sci & Technol Xian 710126 Peoples R China Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China Gachon Univ Coll Future Ind Seongnam 461701 Gyeonggi Do South Korea Hangzhou Dianzi Univ Coll Comp Hangzhou 310018 Peoples R China

With the rapid development of connected and autonomous vehicles (CAVs), a large number of mobile and edge applications (APPs) have been developed and deployed through green communication and networking technology. The problem of high energy consumption during APPs usage becomes serious and in this paper, we propose to optimize energy usage through effective APPs recommendation. Traditional recommendation methods have been developed for years, such as collaborative filtering and latent factor models. But those methods are not designed for APPs recommendation and only focus on the use of historical records. We find that there are hidden relationships in the content and context of APPs in green communication and networking. In this paper, we develop a holistic APPs recommendation framework for CAVs in green communication and networking. The developed framework is driven by machine learning, where we propose two joint matrix factorization models and hidden relationship mining method. The machine learning-driven models can leverage the neglected information and learn latent features in APPs recommendation for CAVs. We used a real-word mobile and edge APPs dataset, performed sufficient experiments and compared our framework with well-known methods. Experimental results show that our framework produces the best performance in all test cases.

关键词： Machine learning algorithms optimization Computational modeling Computer science User experience Mobile applications Collaboration Green communication and networking connected and autonomous vehicles APPs recommendation machine learning optimization algorithm

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Performance Enhancement of Global optimization-Based Gas Turbine Fault Diagnosis Systems

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JOURNAL OF PROPULSION AND POWER 2016年第1期32卷 214-224页

作者： Mohammadi, Ehsan Montazeri-Gh, Morteza Iran Univ Sci & Technol Sch Mech Engn Syst Simulat & Control Lab Tehran *** Iran

Fault detection and identification of gas turbines is a crucial process for providing engine safe operation and decreasing the maintenance costs. In studies conducted in the field of global optimization-based gas turbine fault diagnosis, the genetic algorithm as the most well-known evolutionarya* optimization algorithm is usually employed to identify the engine health parameters. However, because of the evolutionary and stochastic nature of this algorithm, the genetic-algorithm-based diagnosis usually suffers from computational burden and reliability. To mitigate this problem, in the present work, a comparative study has been performed on the global optimization-based gas turbine fault diagnosis, and it is shown that an innovative hybrida* optimization algorithm as a fault detection and identification system can significantly enhance the performance of the conventional optimization-based diagnosis systems, even in the presence of measurement noise. The results obtained indicate that the fault detection and identification system based on the hybrid invasive weed optimization/particle swarma* optimization algorithm outperforms all the examined diagnosis systems (i.e., the genetic-algorithm-based, particle-swarm-optimization-based, and invasive weed-optimization-based fault detection and identification system) in terms of accuracy, reliability, and especially computational cost. The results demonstrate that the genetic-algorithm-based fault detection and identification system showed the weakest performance among all the examined diagnosis systems.

关键词： Gas Turbine Particle Swarm optimization optimization algorithm Fault Detection Genetic algorithm Axial Compressors Artificial Neural Network Bayesian Belief Networks Influence Coefficients Gas Path Analysis

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MODE TRACKING ISSUES IN STRUCTURAL optimization

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AIAA JOURNAL 1995年第10期33卷 1926-1933页

作者： ELDRED, MS VENKAYYA, VB ANDERSON, WJ UNIV MICHIGAN ANN ARBORMI 48109 USA AEROFLIGHTDYNAM DIRECTORATEWRIGHT PATTERSON AFBOH 45433

Within the context of optimization of the structural dynamics properties of finite element models, methodology is developed for the tracking of eigenpairs through changes in the structural eigenvalue problem. The goal is to eliminate difficulties caused by ''mode switching'' (i.e., frequency crossing), Out of several candidate methods, two methods for mode tracking are successful. The first method, the higher order eigenpair perturbation algorithm, is based on a perturbation expansion of the eigenproblem. It iteratively computes changes in the eigenpairs due to parameter perturbations with the important feature of maintaining the correspondence between the baseline and perturbed eigenpairs. The second method is a cross-orthogonality check method, which uses mass orthogonality to reestablish correspondence after a standard reanalysis. Modified eigenpair extraction routines (Lanezos, subspace iteration, inverse power) were unsuccessful in tracking modes. Applications of mode tracking technology that are presented are frequency-constrained optimization and optimization with mode shape constraints. Each application procedure is outlined and examples are given. Recommendations are made based on method efficiency and robustness in the example problems.

关键词： Structural optimization Finite Element Modeling Structural Dynamics Wing Box Nonlinear Programming Free Vibrations Singular Value Decomposition Aeroelastic Analysis Track algorithm optimization algorithm

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