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Multicriteria design optimization of integrated three-dimensional supersonic inlets

JOURNAL OF PROPULSION AND POWER 2003年第3期19卷 456-463页

作者： Gaiddon, A Knight, DD MBDA France Computat Fluid Dynam Team F-92320 Chatillon France Rutgers State Univ Dept Mech & Aerosp Engn Piscataway NJ 08854 USA

Automated optimization by means of numerical simulation is a very promising technique now mainly used for research studies. However, its application in an industrial context is not very common. optimization of a supersonic inlet is presented in the context of the development of an actual airbreathing missile. The automated optimization loop is described in detail. The aerodynamic evaluation tool (the computational fluid dynamics software 2ES3D) is described, and its validation on realistic cases is presented. The use of the optimization loop on a realistic and complex problem is compared with classical methodology for inlet design. The results are very promising in terms of design cycle time and cost reduction.

关键词： Supersonic Inlets Aerodynamic Design Aerodynamic Performance Numerical Simulation Airbreathing Missiles Cost Reduction Multi Objective Genetic algorithm Ramjet Engines Wind Tunnel Tests optimization algorithm

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APPROXIMATION IN NONHIERARCHIC SYSTEM optimization

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AIAA JOURNAL 1994年第1期32卷 198-205页

作者： RENAUD, JE GABRIELE, GA RENSSELAER POLYTECH INST DEPT MECH ENGN AERONAUT ENGN & MECHTROYNY 12180

This paper reports on the effectiveness of a nonhierarchic systema* optimization algorithm in application to complex coupled systems problems. A second-order nonhierarchic systema* optimization algorithm developed in earlier studies is modified in this study to provide for individual constraint/state modeling. A cumulative constraint formulation was used in previous implementation studies. The test problems in this study are each complex coupled systems. Complex coupled systems require an iterative solution strategy to evaluate system states. Nonhierarchic algorithm development is driven by these types of problems, and their study is imperative. The algorithm successfully optimizes each of the complex coupled systems. A significant reduction in the number of system analyses required for optimization is observed as compared with conventional optimization using the generalized reduced-gradient method.

关键词： Iterative Solution algorithms and Applications optimization algorithm Gradient Method Heat Sinks Multidisciplinary Design optimization Electronic Component Thermal Analysis Artificial Neural Network Nonlinear Programming

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Improved simulated annealing search for structural optimization

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AIAA JOURNAL 2000年第10期38卷 1965-1973页

作者： Moh, JS Chiang, DY Natl Cheng Kung Univ Inst Aeronaut & Astronaut Tainan 701 Taiwan

Ana* optimization algorithm based on simulated annealing is proposed, in which the domain of the search is successively reduced based on a probability concept until the stopping criteria are satisfied. By introducing the ideas of probability cumulative distribution function and stable energy, the selection of initial temperature and equilibrium criterion in the process of simulated annealing becomes easy and effective. Numerical studies using a set of standard test functions and an example or a 10-bar truss show that the approach is effective and robust in solving both functional and structural optimization problems.

关键词： Structural optimization Annealing Techniques Probability Distribution Functions Trusses optimization algorithm Genetic algorithm Augmented Lagrangian Method Computing Facilities Boltzmann Constant

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Novel Range Wise optimization of the Exponential Bounds on the Gaussian Q Function and its Applications in Communications Theory

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IEEE LATIN AMERICA TRANSACTIONS 2023年第12期21卷 1237-1246页

作者： Powari, Aditya Anand, Garv Sadhwani, Dharmendra Univ Manchester Dept Elect & Elect Engn Manchester M13 9PL England IITRAM Dept Elect & Comp Sci Engn Ahmadabad 380026 India

This paper presents a novel and highly effective method for improving the accuracy of approximations for the Gaussian Q function. By rigorously optimizing the coefficients of the approximations using the interior point optimization technique, significantly tighter bounds are achieved with simplicity intact. The proposed approach, which is applicable to a wide range of scenarios, focuses on enhancing the simple exponential bounds proposed in the literature. Through a comprehensive analysis based on the relative error, the superiority of the optimized coefficients compared to the existing bounds and approximations available in the open literature is demonstrated. Moreover, an insight into the generic applicability of the optimized coefficients is provided, which exhibits excellent performance in terms of the absolute error as well. The Gaussian Q function plays a crucial role in evaluating the performance of diverse wireless communication systems under various challenging fading distributions. Therefore, the proposed research significantly contributes to advancing the accuracy of the approximations of the Gaussian Q function, enabling improved error performance for coherent digital modulation techniques. The findings presented herein offer valuable contributions to the state-of-the-art and set a new standard for accuracy in the work related to Gaussian Q function approximations.

关键词： optimization algorithm Gaussian Q function Wireless communication systems Performance evaluation approximate computing Digital modulation techniques Fading channels Bit-error rate Symbol-error rate

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IMPROVED COORDINATION IN NONHIERARCHIC SYSTEM optimization

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AIAA JOURNAL 1993年第12期31卷 2367-2373页

作者： RENAUD, JE GABRIELE, GA RENSSELAER POLYTECH INST DEPT MECH ENGN AERONATU ENGN & MECHTROYNY 12180

An improved coordination procedure for the optimization of nonhierarchic systems by decomposition into reduced subspaces is presented. A subspace coordination procedure based on sequential global approximation is extended to include second-order information. This second-order global approximation is formed using information obtained during subspace optimizations. The use of second-order information in the coordination procedure results in improved convergence for nonhierarchic system optimization as compared with the authors' earlier studies using a first-order coordination procedure. The same objective function and cumulative constraints are imposed at each subspace. Nonlocal functions are approximated at the subspaces using global sensitivities. The method optimizes subspace problems concurrently, allowing for parallel processing. Following each sequence of concurrent subspace optimizations, a second-order approximation of the global problem is formed using design data accumulated during the subspace optimizations. The solution of the global approximation problem is used as the starting point for subsequent subspace optimizations in an iterative solution procedure.

关键词： Iterative Solution Taylor Series Multidisciplinary Design optimization algorithm Performance Aeronautical Engineering optimization algorithm Control optimization Structural Dynamics Manufacturing Cost

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optimization of the Event-Driven Emergency Load-Shedding Considering Transient Security and Stability Constraints

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IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第4期32卷 2581-2592页

作者： Xu, Xin Zhang, Hengxu Li, Changgang Liu, Yutian Li, Wei Terzija, Vladimir Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Nanjing Automat Res Inst Nanjing 21003 Jiangsu Peoples R China Univ Manchester Sch Elect & Elect Engn Manchester M13 9PL Lancs England

Emergency control is an important measure for prevention of power system blackouts. This paper presents a new event-driven emergency load-shedding scheme that minimizes load shedding while meeting constraints on transient angle stability, voltage/frequency deviation security, and availability of load to be shed at any bus. The evaluation of these constraints is based on time domain trajectories provided by numerical simulations. The optimal event-driven load-shedding (OEDLS) model was created to minimize the total load-shedding cost. By analyzing the characteristics of the optimal solution of this model, a trajectory sensitivity based solution approach is presented. It linearizes the nonlinear OEDLS model through trajectory sensitivity and iteratively converges to the optimal solution. To accelerate the problem solving process, a parallel computation scheme is implemented for obtaining the trajectory sensitivities. The validity of the proposed algorithm and parallel computation scheme was tested and verified using two different power systems.

关键词： Angle stability frequency security load-shedding optimization algorithm parallel computation trajectory sensitivity voltage security

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Artificial Neural Network Based Particle Swarm optimization for Microgrid Optimal Energy Scheduling

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IEEE TRANSACTIONS ON POWER ELECTRONICS 2021年第11期36卷 12151-12157页

作者： Abdolrasol, Maher G. M. Mohamed, Ramizi Hannan, M. A. Al-Shetwi, Ali Q. Mansor, M. Blaabjerg, Frede Univ Kebangsaan Malaysia Bangi 43600 Malaysia Univ Tenaga Nas Dept Elect Power Engn Kajang 43000 Malaysia Fahad Bin Sultan Univ Tabuk 47721 Saudi Arabia Univ Tenaga Nas Kajang 43000 Malaysia Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

This letter proposes an enhancement for artificial neural network (ANN) using particle swarm optimization (PSO) to manage renewable energy resources (RESs) in a virtual power plant (VPP) system. This letter highlights the comparison of the ANN-based binary particle swarm optimization (BPSO) algorithm with the original BPSO algorithm. The comparison has been made upon searching the optimal value of the number of nodes in the hidden layers and the learning rate. These parameter values are used in ANN training for microgrid (MG) optimal energy scheduling. The proposed approach has been tested in the VPP system covering MGs involving RESs to minimize the power and giving priority to sustainable resources to participate instead of buying power from the utility grid. This model is tested using real load demand recorded for 24 h in Perlis state, the northern part of Malaysia. Besides, real weather condition data are recorded by Tenaga Nasional Berhad Research solar energy meteorology for a 1-h average (e.g., solar irradiation, wind speed, battery status data, and fuel level). The results show that ANN-PSO gives precise decision compared with BPSO algorithm, which in turn prove that the enhancement for the neural net reaches the optimum level of energy scheduling.

关键词： Training Microgrids Optimal scheduling Meteorology Job shop scheduling Search problems Schedules Artificial neural network (ANN) energy management (EM) microgrid (MG) optimization algorithm scheduling

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Novel Moving Isosurface Threshold Technique for optimization of Structures Under Dynamic Loading

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AIAA JOURNAL 2017年第2期55卷 638-651页

作者： Munk, David J. Vio, Gareth A. Steven, Grant P. Univ Sydney Sch Aeronaut Mech & Mechatron Engn Sydney NSW 2006 Australia

The optimum design of structures with frequency constraints is of great importance in the aeronautical industry. To avoid severe vibration, it is necessary to shift the fundamental frequency of the structure away from the frequency range of the dynamic loading. This paper develops a novel topology optimization method for optimizing the frequency of structures, expanded from the moving isosurface threshold technique. optimizations for maximizing a chosen frequency and maximizing the gap between two frequencies are presented. The results of thea* optimization algorithm are compared with the state-of-the-art in frequency topology optimization. The optimized frequency of the final topology is verified by experimental analysis. The results show that the novel topologya* optimization algorithm presented in this paper is promising. The method is shown to have good convergence to optimal topologies compared with current techniques. Furthermore, the algorithm produces comparable topologies to the current state-of-the-art. The algorithm is applied to a practical engineering problem for a complete design cycle.

关键词： optimization algorithm Topology optimization Elastic Modulus Finite Element Formulation Material Properties Accelerometer Aspect Ratio Structural Members Structural Modeling Vibration Amplitude

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Research on the optimization mechanism of loading path in hydroforming process

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2018年第9-12期94卷 4125-4137页

作者： Feng, Ying-ying Luo, Zong-an Su, Hai-long Wu, Qing-lin Northeastern Univ State Key Lab Rolling & Automat Shenyang 110819 Liaoning Peoples R China

In this paper, the optimization mechanism of loading path in hydroforming process is researched. Firstly, the geometric model of an X-shaped tube is established by using 3D drawing software UG;the DYNAFORM software is used to simulate the forming performance of the X tube under different loading paths. The backward displacement is taken as the main factor of the loading path, and the loading path is presented in the form of three factor graphs;it can show the relationship of the main factors of the loading path visually, accurately, and precisely, which are axial feed, internal pressure, and back displacement. Secondly, the orthogonal test method is used to select the optimal loading path, and the back propagation (BP) neural network based on genetic algorithm is used to optimize the loading path of X tubes. Through synthetic consideration of the interrelation of the minimum wall thickness, the maximum wall thickness, the height of branch, and the contact area between branch tube and back punch, the average performance index function is established in the BP neural network control algorithm to optimize the learning efficiency and shorten the calculation time. Finally, verified by experiment, the optimization method of loading path for X tube hydroforming process could control the precision error of results between the simulation and the experiment within 5%, and has high accuracy and good feasibility.

关键词： Tube hydroforming Loading path optimization algorithm Average performance index function

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High-to-Low Initial Sample Ratio of Hierarchical Kriging for Film Hole Array optimization

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JOURNAL OF PROPULSION AND POWER 2018年第1期34卷 108-115页

作者： Kim, Yoonki Lee, Sanga Yee, Kwanjung Rhee, Dong-Ho Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 151742 South Korea Seoul Natl Univ Dept Mech & Aerosp Engn Inst Adv Aerosp Technol Seoul 151742 South Korea Korea Aerosp Res Inst Aeronaut Res & Dev Head Off Daejeon 305333 South Korea

This study aims at proving the existence of the optimal number of high initial sample for time-efficient optimization and demonstrating that the reliable optimization results can be guaranteed when the hierarchical kriging model is used as a surrogate model. The hierarchical kriging model is one sort of variable-fidelity modeling, which mimics the general tendency of a model based on the low-fidelity information and calibrates the accuracy of the model with the high-fidelity information. There, however, have been still several ambiguities to be clarified for practical utilization of hierarchical kriging model. For clarifying these, the film-cooling hole arrangement is selected as an optimization target. The optimization is progressed with the expected-improvement-based efficient globala* optimization algorithm coupled with the hierarchical kriging model. The fidelity in this paper is classified by mesh density: 2 million and 8 million grid system. According to this overall optimization process, case studies are conducted with respect to the number of high initial samples. As a result, the reliable optimization results are obtained regardless of different numbers of high initial samples, and approximately 40% time reduction can be obtained.

关键词： Kriging Model Richardson Extrapolation optimization algorithm Turbine Inlet Temperature Universal Gas Constant Reynolds Averaged Navier Stokes Mass Flow Rate CFD Adiabatic Conditions Rotor Aerodynamics

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