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Hierarchical Nondeterministic optimization of Curvilinearly Stiffened Panel with Multicutouts

AIAA JOURNAL 2018年第10期56卷 4180-4194页

作者： Hao, Peng Wang, Yutian Liu, Chen Wang, Bo Tian, Kuo Li, Gang Wang, Qun Jiang, Liangliang Dalian Univ Technol Dept Engn Mech State Key Lab Struct Anal Ind Equipment Dalian 116023 Liaoning Peoples R China China Acad Launch Vehicle Technol Beijing Inst Astronaut Syst Engn Beijing 100076 Peoples R China

The concept of a curvilinearly stiffened panel is promising for aerospace and aircraft structures with cutouts, since the stiffness distribution and loading path can be flexibly tailored in terms of cutouts. However, uncertainties from the manufacturing process can significantly reduce the practical load-carrying capacity of a curvilinearly stiffened panel. Traditional nondeterministic design optimization methods would suffer from a high computational burden because numerous discrete-continuous variables, in which thousands of finite element analyses are usually required, are involved. Therefore, a hierarchical nondeterministic optimization framework of a curvilinearly stiffened panel is established, containing two steps (global search and local search) and four main parts (layout design, nondeterministic design optimization, reshape layout design, and stress validation). In the first-step deterministic optimization, all variables are considered, and a rough result set will be obtained by a global search. In the second-step nondeterministic optimization, all discrete-continuous layout parameters are fixed in the initial stage, and the efficient adaptive-loop method is applied to significantly increase the computational efficiency, in which the variations of material properties and geometric dimensions are considered as uncertainties. The layout also will be reshaped to explore the potential of the load-carrying capacity. Finally, the stress constraint and crippling constraint are verified for the optimum design. An illustrative example indicates the advantage of the proposed framework not merely provides a competitive efficiency and robustness over other nondeterministic approaches but also improves the rationality of deterministic design optimization.

关键词： Material Properties Aircraft Structures Structural Weight Elastic Modulus Cumulative Distribution Function Postbuckling Analysis Finite Element Method Principal Stresses Numerical Stability optimization algorithm

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On-the-Fly Unsteady Adjoint Aerodynamic and Aeroacoustic optimization Method

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AIAA JOURNAL 2024年第12期62卷 4779-4797页

作者： Zhi, Haolin Xiao, Tianhang Qin, Ning Deng, Shuanghou Lu, Zhaoyan Nanjing Univ Aeronaut & Astronaut Coll Aerosp Engn Nanjing 210016 Peoples R China Univ Sheffield Dept Mech Engn Sheffield S1 3JD England Innovat Acad Microsatellites Shanghai 201304 Peoples R China State Key Lab High Temp Gas Dynam Beijing 100190 Peoples R China

An on-the-fly unsteady adjoint-based aerodynamic and aeroacoustic optimization methodology is presented, aiming to achieve practical engineering applications to explore high-efficiency and low-noise design for aerodynamic shapes. Firstly, a novel on-the-fly hybrid CFD-CAA approach is developed with a close integration of unsteady Reynolds-averaged Navier-Stokes equations and a fully viscous time-domain FW-H formulation. Subsequently, an adjoint-based sensitivity analysis method is proposed for unsteady aerodynamic and aeroacoustic problems with either stationary or moving boundaries, wherein a unified architecture for discrete-adjoint sensitivity analysis of both aerodynamics and aeroacoustics is achieved by integrating the on-the-fly hybrid CFD-CAA approach. The on-the-fly approach facilitates direct evaluation of partial derivatives required for solving adjoint equations, eliminating the need for explicitly preprocessing flow and adjoint variables at all time levels in a standalone adjoint CAA solver and consequently substantially reducing memory consumption. The proposed optimization methodology is implemented within an open-source suite SU2. Results show that the proposed on-the-fly adjoint methodology is capable of achieving highly accurate sensitivity derivatives while significantly reducing memory requirements by an order of magnitude, and further demonstrations of single-objective and coupled aerodynamic and aeroacoustic optimizations highlight the potential of the proposed method in exploring high-efficiency and low-noise design for aerodynamic shapes.

关键词： optimization algorithm Computational Fluid Dynamics Overall Sound Pressure Level Aerodynamic Shape optimization Aerodynamic Performance Discrete Adjoint Solvers Unsteady Aerodynamics Gradient-Based Design optimization Multidisciplinary Design optimization Computational Aeroacoustics

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Implementation of a New Solar-Powered Street Lighting System: optimization and Technical-Economic Analysis Using Artificial Intelligence

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IEEE ACCESS 2024年 12卷 46657-46667页

作者： Belloni, Elisa Massaccesi, Andrea Moscatiello, Cristina Martirano, Luigi Univ Perugia Dept Engn I-06132 Perugia Italy Sapienza Univ Rome Dept Elect Engn I-00185 Rome Italy

Public lighting system represents a key role in the energy transition process, considering the high electricity consumptions related to this sector. The integration of renewables could be suitable for this application and many solutions of solar-based lamps for street lighting are spreading. In this research work, a specific application of a PV-integrated lighting system was installed in the center of Italy along a footpath and monitored for several months, both in terms of electricity parameters and lighting behavior. It is equipped with monocrystalline photovoltaic cells, a lithium-based battery, and a LED lamp. The measured data allow the development of ana* optimization algorithm in Python program for the correct management of the solar streetlamp and the forecasting of electricity consumptions for different boundary conditions (e.g. Italian geographical position). The energy taken from grid in a year is very low with respect to a traditional lamp not powered by renewables: only 43-46% in central-northern regions and 35% in south region. Data are also used to study the possible substitution of all the traditional lamppost of the walkway with the novel proposed system. A technical-economic analysis is carried out to analyze the effectiveness of this solution not only in terms of electricity consumptions reduction, but also costs savings. The suitability of the investment and the payback time depend on Italian national price of electricity and initial cost of the solar lamp. The results can be applied to similar case studies in Italy to save electricity consumptions and reduce CO2 emissions.

关键词： Lighting Batteries Electricity Green products Voltage control Renewable energy sources Pedestrians Artificial intelligence Energy consumption optimization methods Photovoltaic systems Energy storage Technology management Economics electricity consumptions LED optimization algorithm photovoltaic (PV) storage streetlamp technical-economic analysis

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Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes

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AEROSPACE SCIENCE AND TECHNOLOGY 2017年 64卷 52-62页

作者： Song, Lu-Kai Fei, Cheng-Wei Wen, Jie Bai, Guang-Chen Beihang Univ Sch Energy & Power Engn Beijing 100191 Peoples R China Hongkong Polytechn Univ Dept Mech Engn Kowloon Hong Kong Peoples R China

To make multi-objective reliability-based design optimization (MORBDO) more effective for complex structure with multi-failure modes and multi-physics coupling, multiple response surface method (MRSM)-based artificial neural network (ANN) (ANN-MRSM) and dynamic multi-objective particle swarm optimization (DMOPSO) algorithm are proposed based on MRSM and MOPSO algorithm. The mathematical model of ANN-MRSM is established by using artificial neural network to fit the multiple response surface function. The DMOPSO algorithm is proposed by designing dynamic inertia weight and dynamic learning factors. The proposed approach is verified by the MORBDO of turbine blisk deformation and stress with respect to fluid-thermal-structure interaction from probabilistic analysis. The optimization design results show that the proposed approach has the promising potentials to improve computational efficiency with acceptable computational precision for the MORBDO of turbine blisk deformation and stress. Moreover, Pareto front curve and a set of viable design values of turbine blisk are obtained for the high-reliability high-performance design of turbine blisk. The presented efforts provide an effective approach for MORBDO of complex structures, and enrich mechanical reliability design theory as well. (C) 2017 Elsevier Masson SAS. All rights reserved.

关键词： Multi-objective reliability-based design optimization Multi-failure modes Multiple response surface method Artificial neural network Dynamic multi-objective particle swarm optimization algorithm

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STRUCTURAL SIZING BY GENERALIZED, MULTILEVEL optimization

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AIAA JOURNAL 1987年第1期25卷 139-145页

作者： SOBIESZCZANSKISOBIESKI, J JAMES, BB RILEY, MF KENTRON INT INC DIV AEROSP TECHNOLADV COMP METHODS UNITHAMPTONVA

Developments of a general multilevel optimization capability and results for a three-level structural optimization are described. The latter is considered a major stage in the method development because the addition of more levels beyond three does not introduce any new qualitative elements. Therefore, a three-level implementation is, qualitatively, the equivalent to a multilevel implementation. The method partitions a structure into a number of substructuring levels where each substructure corresponds to a subsystem. The method is illustrated by a portal framework that decomposes into individual beams. Each beam is a box that can be further decomposed into stiffened plates. Consequently, substructuring for this example spans three levels: the bottom level of finite elements representing the plates, an intermediate level of beams treated as substructures, and the top level for the assembled structure. This example is an extension of a previously presented case that was limited to two levels. © 1987 American Institute of Aeronautics and Astronautics, Inc., All rights reserved.

关键词： Finite Element Analysis Structural optimization Engineer's Beam Theory optimization algorithm Sensitivity Analysis Aerospace Technology Distributed Computing Black Box Structural Sensitivity Analysis NASA Langley Research Center

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Research on the route optimization for fresh air processing of air handling unit in spacecraft launching site

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APPLIED THERMAL ENGINEERING 2015年 86卷 292-300页

作者： Yang, Yongli Jiang, Pengcheng Cong, Hua Feng, Fuzhou Zhang, Hongxing Acad Armored Forces Engn Dept Mech Engn Beijing 100072 Peoples R China Taiyuan Satellite Launch Ctr Taiyuan 036304 Peoples R China

The existing control methods for Air handling units (AHUs) in spacecraft launching site (SLS) are comparatively dated, the air processing routes are usually arbitrarily determined in line with experience, which fails to cope with the coupling and function redundancy of air condition system and the diversity of outdoor environment, therefore resulting in tremendous energy waste. This paper proposes a new route optimization strategy for fresh air processing-Firstly analyzing the possibly processing routes for fresh air based on psychrometric chart, then proposing ana* optimization algorithm AFSA-GA to optimize the possibly processing routes, eventually obtaining the best route that requires the least energy consumption. By adopting the strategy proposed to optimize air processing route for High-Temperature and High-Humidity working conditions, it can be proved that the proposed strategy can decrease considerable amount of energy consumption, and the proposeda* optimization algorithm AFSA-GA has the advantages of faster convergence speed and avoiding premature. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： AHU Fresh air processing Psychrometric chart Route optimization optimization algorithm

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A novel atom search optimization for dispersion coefficient estimation in groundwater

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2019年 91卷 601-610页

作者： Zhao, Weiguo Wang, Liying Zhang, Zhenxing Hebei Univ Engn Sch Water Conservancy & Hydropower Handan 056021 Hebei Peoples R China Univ Illinois Illinois State Water Survey Prairie Res Inst Champaign IL 61820 USA

A new type of meta-heuristic global optimization methodology based on atom dynamics is introduced. The proposed Atom Search optimization (ASO) approach is a population-based iterative heuristic globala* optimization algorithm for dealing with a diverse set of optimization problems. ASO mathematically models and mimics the atomic motion model in nature, where atoms interact with each other through interaction forces resulting form Lennard-Jones potential and constraint forces resulting from bond length potential, the algorithm is simple and easy to implement. ASO is applied to a dispersion coefficient estimation problem, the experimental results demonstrate that ASO can outperform other well-known approaches such as Particle Swarm optimization (PSO), Genetic algorithm (GA) and Bacterial Foraging optimization (BFO) and that ASO is competitive to its competitors for parameter estimation problems. The source codes of ASO are available at https://***/matlabcentral/fileexchange/67011-atom-search-optimization-aso-algorithm?s_tid=srchtitle. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Heuristic algorithm optimization algorithm Dispersion coefficient Parameter estimation Global optimization Metaheuristic Atom search optimization

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MULTIOBJECTIVE optimization OF LARGE-SCALE STRUCTURES

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AIAA JOURNAL 1993年第7期31卷 1329-1337页

作者： GRANDHI, RV BHARATRAM, G VENKAYYA, VB USAF FLIGHT DYNAM DIRECTORATEANAL & OPTIMIZAT BRANCHWRIGHT PATTERSON AFBOH 45433

This paper presents a multiobjectivea* optimization algorithm based on generalized compound scaling techniques. The algorithm handles any number of objective functions, similar to handling behavior constraints. This technique generates a partial Pareto set while solving the optimization problem. A reliability-based decision criterion is used for selecting the best compromise design. The example cases considered in this work include various disciplines in airframe structures, such as stress, displacement, and frequency with hundreds of design variables and constraints. This paper also discusses the concept of Pareto-optimal solutions in the context of a multiobjective structural optimization problem and the commonly used methods of generating Pareto-optimal solutions.

关键词： Structural optimization optimization algorithm Airframes Poisson's Ratio Trusses Normal Stress Structural Weight Probability Distribution Functions Computer Aided Design Material Properties

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New optimization Strategy for Design of Active Twist Rotor

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AIAA JOURNAL 2015年第2期53卷 436-448页

作者： Kumar, Devesh Cesnik, Carlos E. S. Univ Michigan Dept Aerosp Engn Ann Arbor MI 48105 USA

This paper presents the development of a mixed-variable optimization framework for the aeroelastic analysis and design of active twist rotors. Proper tailoring of the blade properties can lead to the maximization of the active twist and the control authority for vibration reduction under operating conditions. Thus, using mathematical optimization, the cross-sectional layout is designed using continuous and discrete design variables for an active composite rotor blade to maximize the dynamic active twist while satisfying a series of constraints on blade cross-section parameters, stiffness, and strength. The optimization framework developed includes the Intelligent Cross-Section Generator as the cross-section and mesh generator, University of Michigan/Variational Asymptotic Beam Sectional analysis code for active cross-sectional analysis, and Rotorcraft Comprehensive Analysis Software for aeroelastic analysis of the active twist rotor blade. The optimization problem is solved using a surrogate-based approach in combination with the Efficient Globala* optimization algorithm. In this paper, the results with mixed design variables are obtained with three different techniques and are compared with the results obtained using continuous design variables.

关键词： Rotor Blades Aeroelastic Stability Twisted Rotor Blade Rotorcrafts Mathematical optimization optimization algorithm Finite Element Analysis Aerodynamic Characteristics Surrogate Model Genetic algorithm

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NM-MF: Non-Myopic Multifidelity Framework for Constrained Multi-Regime Aerodynamic optimization

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AIAA JOURNAL 2023年第3期61卷 1270-1280页

作者： Di Fiore, Francesco Mainini, Laura Politecn Torino Dept Mech & Aerosp Engn I-10129 Turin Italy

The exploration and trade-off analysis of different aerodynamic design configurations requires solving optimization problems. The major bottleneck to assess the optimal design is the large number of time-consuming evaluations of high-fidelity computational fluid dynamics (CFD) models, necessary to capture the non-linear phenomena and discontinuities that occur at higher Mach number regimes. To address this limitation, we introduce an original non-myopic multifidelity Bayesian framework aimed at including expensive high-fidelity CFD simulations for the optimization of the aerodynamic design. Our scheme proposes a novel two-step lookahead policy to maximize the improvement of the solution quality considering the rewards of future steps, and combines it with utility functions informed by the fluid dynamic regime and the information extracted from data, to wisely select the aerodynamic model to interrogate. We validate the proposed framework for the case of a constrained drag coefficient optimization problem of a NACA 0012 airfoil, and compare the results to other popular multifidelity and single-fidelity optimization frameworks. The results suggest that our strategy outperforms the other approaches, allowing to significantly reduce the drag coefficient through a principled selection of limited evaluations of the high-fidelity CFD model.

关键词： Aerodynamic Coefficients Computational Fluid Dynamics Bayesian optimization Compressible Fluid optimization algorithm Multidisciplinary Design optimization Aerodynamic Design Transonic Aerodynamics Derivative Free optimization

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