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25th AIAA/CEAS Aeroacoustics Conference

作者： Palma, Giorgio Centracchio, Francesco Burghignoli, Lorenzo Iemma, Umberto Cioffi, Ilaria Roma Tre Univ Dept Engn Via Vito Volterra 62 I-00146 Rome Italy

ISBN: (数字)9781624105883

ISBN: (纸本)9781624105883

Space-coiling metamaterials that exploit the generalized Snell's law are suitable for the subwavelength manipulation of acoustic waves, leading to extraordinary refraction and reflection properties. Typically, space-coiling metasurfaces are characterized by a narrow operating range in frequency due to the intrinsic connection between the design wavelength and the characteristic dimensions of the metasurface. The main goal of the present work is to design a broadband and modular metasurface based on space-coiling cells by extending the range of frequency where the effective metabehaviour is achieved through numerical optimization. The metasurface module is composed by eight different unit cells, each introducing a tailored phase shift in the field, that can be combined side by side to produce the desired acoustic effect. The design parameters of each cell are selected as the result of an optimization process that minimizes the dependency on the operating frequency of the metabehaviour, keeping the overall thickness below a quarter of the design wavelength. Preliminary results are obtained for a benchmark problem.

关键词： Numerical optimization Acoustic Metamaterial Refraction Index Particle Swarm optimization Finite Element Method Electromagnetic Field optimization algorithm Acoustic Simulation Comsol Multiphysics Genetic algorithm

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Acoustic Cloaking in Flows by Topology optimization Method 25

Acoustic Cloaking in Flows by Topology Optimization Method

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25th AIAA/CEAS Aeroacoustics Conference

作者： Ma, Zhengyu Huang, Xun Peking Univ Dept Aeronaut & Astronaut Beijing 100871 Peoples R China Peking Univ State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China

ISBN: (数字)9781624105883

ISBN: (纸本)9781624105883

In this Letter, we propose an acoustic cloak design in the presence of background mean flow by using topology optimization, which would enable the associated fabrication of the cloaking design. In particular, one kind of isotropic material, that is, aluminum, is considered in this work. A density-based topology optimization method is utilized, along with the gradient-based moving asymptotic algorithm, which is based on the derivative information from the simulation studies that are calculated using a finite element solver. This Letter first introduces the whole design method, then numerically demonstrates the corresponding performance, which shall constitute the main contribution of the present work. The proposed method could find applications in future silent vehicle designs.

关键词： Topology optimization Inviscid Fluid Acoustic Scattering Frequency Domain Conservation of Mass Bernoulli's Equation Streamlines Stochastic optimization optimization algorithm Numerical Simulation

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optimization of 3D Curved Fiber Steered Shells

Optimization of 3D Curved Fiber Steered Shells

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： van Zanten, F. J. Pupo, C. Barazanchy, D. van Tooren, M. Univ South Carolina Columbia SC 29208 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

In this paper a framework to optimize a Variable Stiffness (VS) laminate is altered such that it can be used to optimize curved laminates for strength. The framework uses a secondary mesh to discretize the continuous fiber angle in steered laminates. Extending the framework is achieved by moving the secondary mesh elements into a 2D environment. After discussion the methodology to achieve this, the results for a tensile panel, a buckling panel, a shear panel and a panel with holes loaded in tension will be presented. The paper aims to show that a previously existing framework can be adapted to optimize 3D curved fiber steered shells for strength.

关键词： Finite Element Analysis Abaqus Python Industrial Applications optimization algorithm Aerospace Industry Allowable Stress Computing

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Airfoil optimization Using Far-Field Analysis of the Drag Force

Airfoil Optimization Using Far-Field Analysis of the Drag Fo...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Morales, Elisa Quagliarella, Domenico Tognaccini, Renato CIRA Ctr Italiano Ric Aerosp Fluid Mech Dept I-81043 Capua Italy Univ Napoli Federico II Dept Ind Engn I-80125 Naples Italy

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

Far-field analysis for drag prediction and decomposition is here explored and applied to aerodynamic shape design problems. The work aims at illustrating how the far-field approach may allow substantial reductions of the computational effort required by a shape design task. The advantage of this method, in comparison with classical near-field methods, is illustrated both in the classical field of deterministic design optimization and in the robust shape design context. In particular, the approach is shown by optimizing the wave drag of a NACA 0012 airfoil in transonic flow conditions at zero angle of attack. Both the deterministic and the robust stochastic approach have been used, and the obtained results are here reported. © 2019 by Xin Ning. Published by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Symmetric Airfoil Aerodynamic Shape optimization Angle of Attack Compressible Flow Computational Fluid Dynamics Pressure Coefficient optimization algorithm Viscosity Python Computing

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Multiscale Concurrent optimization Towards Additively Manufactured Structures

Multiscale Concurrent Optimization Towards Additively Manufa...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Murphy, Ryan Imediegwu, Chikwesiri Hewson, Robert Santer, Matthew Muir, Martin J. Imperial Coll London Dept Aeronaut London SW7 2AZ England Airbus Cent R&T Bristol Avon England

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

This work establishes a robust concurrent multiscale optimization framework which facilitates the precise functional-grading of mechanical properties within structures, over two scales. The novelty lies in the concurrent nature of the response surface which connects the small-scale geometry to the large-scale domain. A concurrent implementation enables an efficient application of computational resources, such that a large number of design variables can be used without a significant computational penalty. This framework also takes advantage of the process flexibility and precision of additive manufacturing techniques to ensure that all optimized structures are manufacturable and suitable for an aerospace based application. A compliance minimization case is compared against a standard topologya* optimization algorithm, resulting in superior functional values and demonstrates the efficacy of the presented approach. A further application of this framework is highlighted through a target deformation case, where a complex deformation field is obtained through simple loading conditions. Results from both of the example problems indicate that this framework has potential within the field of adaptive structures, to inspire a new generation of multifunctional designs.

关键词： Mechanical Properties Adaptive Structures optimization algorithm Topology optimization Cantilever Material Properties Structural optimization Shear Stress Finite Element Analysis Dirichlet Boundary Condition

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Prediction of abrasion resistance characteristics of sintered aggregates from coal gangue and feldspar powder based on optimized BP-ANN neural network

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Construction and Building Materials 2025年 487卷

作者： Wei Deng Rui Xiong Haoyu Wang Youjie Zong Yanping Sheng Bowen Guan Mingfeng Chang School of Materials Science and Engineering Chang’an University Xi’an 710061 China School of Civil Engineering University of Nottingham Nottingham NG1 4BU England

Developing new high-quality utilization pathways for coal gangue is crucial for precise absorption. The abrasion resistance of coal gangue-feldspar powder sintered aggregates (GFAA) is evaluated using Vickers hardness and crystallinity as indicators. The impact of sintering conditions on the physical properties and crystallization process of GFAA is investigated through correlation matrices and principal component analysis. A backpropagation artificial neural network (BP-ANN) predictive model with a topology of 6–7–1 is designed and optimized using PSO (Particle Swarm optimization) and GA (Genetic algorithm) to enhance the accuracy of a multi-index evaluation model. The results indicate that optimizing raw material proportions and increasing sintering temperatures significantly enhance the performance of GFAA. Additionally, the incorporation of fluxing components is shown to accelerate the depolymerization of the glass network structure and reduce the system's liquid-phase viscosity, with GFAA exhibiting Vickers hardness significantly greater than that of natural aggregates. High accuracy is demonstrated by both the BP-ANN and its optimized models; the models optimized using PSO and GA result in reductions in RMSE of 19.43 % and 15.31 % for Vickers hardness predictions and 26.30 % and 28.07 % for crystallinity predictions, respectively, thereby showcasing superior accuracy and generalization ability. Consequently, the high predictive accuracy of the optimized models provides valuable guidance for the design of mixed proportions of high abrasion-resistant aggregates developed from solid waste.

关键词： Artificial aggregate Machine learning optimization algorithm Abrasion resistance Liquid viscosity

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Properties Calculator and optimization for Drop-in Alternative Jet Fuel Blends

Properties Calculator and Optimization for Drop-in Alternati...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Floral, Giacomo Kosir, Shane Behnke, Lily Stachler, Robert Heyne, Joshua Zabarnick, Steven Gupta, Mohan Univ Dayton Res Inst Energy Technol & Mat Div 300 Coll Pk Dayton OH 45429 USA Univ Dayton Mech & Aero Engn 300 Coll Pk Dayton OH 45429 USA US DOE Bioenergy Technol Off Detail FAA DOT 1000 Independence Ave SW Washington DC 20585 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

A predictive computational tool to determine the optimum blending ratios for a potential certifiable mixture of conventional and alternative fuel is proposed. Hydrocarbons blending rules were implemented for several properties including density, viscosity, flash point, aromatic concentration, net heat of combustion and derived cetane number (DCN). The ASTM methods D1655 and D7566 with the recent findings of the National Jet Fuel Combustion Program were used to impose limitations for the candidate blends. Results were calculated for a Jet-A/FT-SPK (Syntroleum GTL), Jet-A/HEFA-SPK (Sasol IPK), Jet-A/Gevo ATJ Jet-A/LanzaTech ETJ and Jet-A/Farnesane blends, and are in agreement with the certified ratios. For the Jet-A/Gevo ATJ blend, the major limiting property was the derived cetane number whereas for Jet-A/Farnesane the viscosity limited the fraction of Farnesane to 22 % by vol. For all other fuel blends, the limiting property appeared to be the aromatic concentrations, confining the alternative fraction to values slightly above 50%. An optimization code was also developed to predict optimum jet fuel compositions that maximize energy density and specific energy. A total of 58 hydrocarbon species typically found in jet fuels were combined to obtain optimum solutions.

关键词： Jet Fuel Heat of Combustion Flash Point Kinematic Viscosity Alternative Fuels Energy Density Crude Oil Aviation Fuel optimization algorithm Commercial Aviation

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optimization of serrations for broadband trailing-edge noise reduction using an analytical model 25

Optimization of serrations for broadband trailing-edge noise...

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25th AIAA/CEAS Aeroacoustics Conference

作者： Kholodov, Pavel Moreau, Stephane Univ Sherbrooke Dept Mech Engn Sherbrooke PQ J1K 2R1 Canada

ISBN: (数字)9781624105883

ISBN: (纸本)9781624105883

The design space exploration and numerical optimization techniques are used to predict the optimum configuration of airfoil trailing-edge serrations for the purpose of broadband noise reduction. The nested optimization concept is applied to find the optimum shape of the serrations. Ayton's analytical model is used to compute the trailing-edge noise from the Controlled Diffusion airfoil. The results suggest that the optimum serrations geometry is a combination of sharp and slitted shapes such as chopped-peak, double-wavelength and sawtooth v-slitted serrations. The maximum noise reduction has a non-linear dependency on the global wavelength and depth of the serrations for any given shape. Additional parameters may be necessary to study the practical application limit for the found shapes.

关键词： Sound Pressure Level Aircraft Wings Airfoil Space Exploration Numerical optimization optimization algorithm Aerodynamic Performance Power Spectral Density Boundary Layer Thickness Airfoil Chord

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Aerodynamic Design optimization and Shape Exploration using Generative Adversarial Networks

Aerodynamic Design Optimization and Shape Exploration using ...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Chen, Wei Chiu, Kevin Fuge, Mark D. Univ Maryland Dept Mech Engn College Pk MD 20742 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

Global optimization of aerodynamic shapes requires a large number of expensive CFD simulations because of the high dimensionality of the design space. One means to combat that problem is to reduce the dimension of the design space-for example, by constructing low dimensional parametric functions (such as PARSEC and others)-and then optimizing over those parameters instead. Such approaches require first a parametric function that compactly describes useful variation in airfoil shape-a non-trivial and error-prone task. In contrast, we propose to use a deep generative model of aerodynamic designs (specifically airfoils) that reduces the dimensionality of the optimization problem by learning from shape variations in the UIUC airfoil database. We show that our data-driven model both (1) learns realistic and compact airfoil shape representations and (2) empirically accelerates optimization convergence by over an order of magnitude.

关键词： Aerodynamic Shape optimization Generative Adversarial Network Airfoil Databases Computational Fluid Dynamics Simulation XFoil Newton's Method Lift to Drag Ratio Particle Swarm optimization optimization algorithm Bayesian optimization

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Towards Aerodynamic Shape optimization of Unsteady Turbulent Flows

Towards Aerodynamic Shape Optimization of Unsteady Turbulent...

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AIAA Science and Technology (SciTech) Forum and Exposition

作者： Ashley, Anthony Creant, Jared Hicken, Jason Rensselaer Polytech Inst Dept Mech Nucl Engn Aerosp Troy NY 12181 USA

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

optimization is an important phase of modern engineering design, and gradient-based optimization methods are especially effective for design problems involving a large number of design variables, such as aerodynamic shape optimization. However, if the system of interest exhibits chaotic dynamics and the quantity of interest is a long-time average, for example, drag in a turbulent flow, conventional sensitivity analysis methods will fail to provide useful gradients and gradient-based optimization becomes infeasible. Progress has been made in the sensitivity analysis of chaotic systems, but most proposed methods are computationally expensive. We propose a new method of stabilizing the tangent-sensitivity equations by introducing a minimal perturbation to the linearized equations. The goal is to eliminate linear instabilities in the sensitivity equations, while ensuring useful gradients are obtained. We implement the tangent sensitivity method on a model chaotic problem, demonstrate the effectiveness of our stabilizations, and validate the gradient information obtained from the stabilized tangent sensitivity. Finally, we describe how the method of stabilization can easily be adapted to the sensitivity analysis of large-scale computational fluid dynamics problems.

关键词： Aerodynamic Shape optimization Unsteady Turbulent Flow Sensitivity Analysis Computational Fluid Dynamics Navier Stokes Simulation Runge Kutta Methods optimization algorithm Euler Equations Shear Layers Galerkin Finite Element Method

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