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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Krolick, William C. Wang, Yi Pant, Kapil CFD Res Corp Huntsville AL 35806 USA Univ South Carolina Columbia SC 29208 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

This paper presents methods and algorithms to construct nonlinear aerodynamic reduced order models (AeroROMs) in a computationally efficient framework to significantly improve coupled aeroelastic ROM accuracy. The methods presented are carried out in two steps: (1) linear, state-space ROM system identification (SYSID);and (2) nonlinear correction term identification that is accomplished by minimizing the ROM prediction error with respect to a separate nonlinear aeroelastic training data set. Two different formulations are investigated, the first by adding nonlinear correction terms to the state and output equations in the linear state space ROM, while in the second the nonlinear correction is only added to the output equation. The key novel contributions of this paper are the use of regularization to mitigate overfitting and stabilize nonlinear aeroelastic response for enhanced model generality, and the use of a new nested optimization approach in which the nonlinear correction to the state equation is obtained through iterative optimization and the output equation correction is identified in one-shot using the least square method. This leads to salient computational acceleration over the brute-force method. The use of different nonlinear function inputs is also studied. The proposed methods and nonlinear ROMs are validated and compared against the original linear aeroelastic ROMs at multiple Mach numbers approaching the transonic regime, which demonstrates excellent accuracy and computational efficiency.

关键词： Aerodynamic Force Aeroelastic Analysis System Identification Structural Displacement Finite Element Modeling optimization algorithm CFD Simulation Support Vector Machine Nonlinear Dynamics Neural Networks

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Aircraft Wing Design Through Concurrent Thickness and Material optimization

Aircraft Wing Design Through Concurrent Thickness and Materi...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Kashanian, Kiarash Kim, Il Yong Queens Univ Dept Mech & Mat Engn Kingston ON K7L 2N8 Canada

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

Existing optimization algorithms do not allow for simultaneous thickness optimization and material selection of non-laminate shell structures. The proposed concurrent thickness and material optimization (CTMO) scheme fills this niche, with a focus on practical, industry-style problems. A complex aircraft wing model is developed and optimized through CTMO. An extensive parameter sweep is conducted for this model, generating 384 results with different designable thickness limits and masses. These results are analyzed to show overall trends in compliance based on problem constraints. Selected results are presented qualitatively to study material selection and optimized thickness. Finally, the relevance of this work to real-world engineering studies is discussed, along with some areas for future improvement of CTMO.

关键词： Aircraft Wing Design optimization algorithm Finite Element Modeling Light Sport Aircraft Topology optimization Numerical Stability Composite Laminates Material Properties Structural Load Poisson's Ratio

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System Architecture optimization: An Open Source Multidisciplinary Aircraft Jet Engine Architecting Problem

System Architecture Optimization: An Open Source Multidiscip...

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AIAA Aviation Forum and Exposition

作者： Bussemaker, J. H. De Smedtt, T. La Rocca, G. Ciampa, P. D. Nagel, B. DLR German Aerosp Ctr Inst Syst Architectures Aeronaut MDO Grp Aircraft Design & Syst Integrat Hamburg Germany Delft Univ Technol Fac Aerosp Engn Flight Performance & Prop Delft Netherlands

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Decisions regarding the system architecture are important and taken early in the design process, however suffer from large design spaces and expert bias. Systematic design space exploration techniques, like optimization, can be applied to system architecting. Realistic engineering benchmark problems are needed to enable development of optimization algorithms that can successfully solve these black-box, hierarchical, mixed-discrete, multi-objective architecture optimization problems. Such benchmark problems support the development of more capable optimization algorithms, more suitable methods for modeling system architecture design space, and educating engineers and other stakeholders on system architecture optimization in general. In this paper, an engine architecting benchmark problem is presented that exhibits all this behavior and is based on the open-source simulation tools pyCycle and OpenMDAO. Next to thermodynamic cycle analysis, the proposed benchmark problem includes modules for the estimation of engine weight, length, diameter, noise and NOx emissions. The problem is defined using modular interfaces, allowing to tune the complexity of the problem, by varying the number of design variables, objectives and constraints. The benchmark problem is validated by comparing to pyCycle example cases and existing engine performance data, and demonstrated using both a simple and a realistic problem formulation, solved using the multiobjective NSGA-II algorithm. It is shown that realistic results can be obtained, even though the design space is subject to hidden constraints due to the engine evaluation not converging for all design points.

关键词： Aircrafts Afterburner Thermodynamic Cycles optimization algorithm Black Box Space Exploration Thrust Specific Fuel Consumption Turbofan Engines Airframes Model Based System Engineering

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Active Manifold and Model Reduction for Multidisciplinary Analysis and optimization

Active Manifold and Model Reduction for Multidisciplinary An...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Boncoraglio, Gabriele Farhat, Charbel Stanford Univ Dept Aeronaut & Astronaut Durand BldgRoom 2242 Stanford CA 94305 USA Stanford Univ Dept Aeronaut & Astronaut Aircraft Struct Durand BldgRoom 257 Stanford CA 94305 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

A computational framework is proposed for efficiently solving multidisciplinary analysis and optimization (MDAO) problems in a relatively high-dimensional design space. It relies on the appropriate blend of linear and nonlinear projection-based model order reduction to accelerate analysis and optimization;and on a new concept of nonlinear active manifold (AM) to mitigate the curse of dimensionality during the training of projection-based reduced-order models (PROMs). The method of AM relies on the nonlinear concept of a deep convolutional autoencoder for dimensionality reduction: it is proposed as a superior alternative to the concept of an active subspace whose capabilities are limited by the capabilities of an affine approximation. The proposed computational framework also blends the concept of a global PROM as a surrogate model of a discretized nonlinear partial differential equation (PDE)based behavior function with that of a database of local, linear PROMs for approximating, wherever appropriate, a linear PDE-based behavior function. Adaptive parameter sampling is performed for training the global, nonlinear PROM as well as for populating the database of local, linear PROMs. The proposed computational framework is demonstrated for the solution of an MDAO problem formulated for a flexible instance of NASA's Common Research Model, where the objective function pertains to aerodynamics in the transonic regime, the constraint relates to flutter, and the design space contains 58 structural and aerodynamic shape design variables. The obtained numerical results illustrate the potential of the AM method for addressing the curse of dimensionality. They also demonstrate the feasibility of the computational framework for realistic MDA Oproblems and highlight its potential for reducing solution time.

关键词： Model Order Reduction Aerodynamic Configurations Computational Fluid Dynamics Fuselages Computational Structural Dynamics Greedy algorithm Structural Modeling Damping Ratio optimization algorithm Sweep Angle

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Multi-Working Point Performance optimization of Variable Cycle Engine Based on Ensemble Radial Basis Function Neural Network

Multi-Working Point Performance Optimization of Variable Cyc...

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AIAA Propulsion and Energy Forum / IEEE Electric Aircraft Technologies Symposium (EATS)

作者： Ye, Yifan Wang, Zhanxue Zhang, Xiaobo Northwestern Polytech Univ Sch Power & Energy Xian 710129 Shaanxi Peoples R China

ISBN: (数字)9781624106118

ISBN: (纸本)9781624106118

This paper proposed a multi-working point performance optimization algorithm based on the radial basis function neural network (RBFNN) for a variable cycle engine. The ensemble RBFNN is used to replace the engine performance simulation model during the optimization process to improve the optimization efficiency. Also, an enhanced multi-objective differential evolution algorithm is proposed to improve the Pareto solutions quality and convergence rate. Finally, a sample for three working points performance optimization of a double-bypass variable cycle engine is presented. This work optimizes a series of variable cycle engine design parameters and adjusting schedules, which consider high takeoff thrust and low cruise fuel consumption.

关键词： Neural Networks Variable Cycle Engines optimization algorithm Fuel Consumption Numerical Modeling High Pressure Turbine Bypass Ratio Particle Swarm optimization Air Flow Rate Compressor Surge

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Application and effect evaluation of BIM technology in seismic design of high-rise buildings

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INFRASTRUCTURE ASSET MANAGEMENT 2025年

作者： Hu, Yunpeng Henan Univ Urban Construct Sch Management Pingdingshan Peoples R China

This paper discusses the application of Building Information Modelling (BIM) technology in the seismic design of high-rise buildings, focusing on digital modelling based on BIM, seismic performance optimisation algorithm, structural analysis and seismic load simulation, and data-driven performance evaluation methods. Through the construction and optimisation of the BIM model, not only is the design accuracy improved, but the intelligent and dynamic optimisation of the design process is also realized, especially in the application of seismic performance prediction and structural optimisation. The material utilisation rate of 23.5% shows a high resource utilisation efficiency, while 87% of the building structures meet the design seismic standards. When considering different optimisation schemes, a 54.8% improvement in seismic performance was recorded. However, a 12.9% increase in cost affected the final decision. The optimized scheme exhibited a 68.4% improvement in seismic stability, while a 91% shortened construction period, indicating that the optimized design improved performance and significantly improved in time. A good balance is achieved between the 34.7% increase in seismic effect and the 77.2% cost saving, indicating the critical role of BIM technology in optimisation design.

关键词： BIM technologies high-rise buildings optimization algorithm seismic design

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Design optimization Studies of Partially Superconducting Machines based on NASA's High Efficiency Megawatt Motor

Design Optimization Studies of Partially Superconducting Mac...

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AIAA Propulsion and Energy Forum / IEEE Electric Aircraft Technologies Symposium (EATS)

作者： Tallerico, Thomas F. Anderson, Aaron D. Scheidler, Justin J. NASA Glenn Res Ctr Rotating & Drive Syst Branch Cleveland OH 44135 USA NASA Glenn Res Ctr Diagnost & Electromagnet Branch Cleveland OH 44135 USA

ISBN: (数字)9781624106118

ISBN: (纸本)9781624106118

Single aisle class electric aircraft require high power density and efficient megawatt-scale electric machines to be competitive with their traditional turbofan counterparts. Superconducting machines are seen as a key enabling technology for achieving the electric motor power density and efficiency needed by these aircraft. NASA's High Efficiency Megawatt Motor (HEMM) is a partially superconducting machine being developed at NASA Glenn Research Center as a technology demonstration of a practical near-term superconducting machine. HEMM is being developed to meet the requirements of the generators on NASA's STARC-ABL reference aircraft. HEMM is expected to achieve greater than 16 kW/kg electromagnetic specific power and greater than 98% efficiency at a nominal operating condition of IA MW and 6800 RPM. In this paper, a design optimization algorithm for partially superconducting machines based on HEMM's technologies is used to explore the possible performance of HEMM technology at other machine power levels and operating conditions. The design optimization algorithm is detailed in full, and results for achievable geared and direct drive machine performance are presented.

关键词： High Efficiency Megawatt Motor Hybrid Electric Aircraft optimization algorithm NASA Glenn Research Center Turbofan Finite Element Analysis Superconductor Thermal Performance Biot Savart Law Eddy Current

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Enhanced Flexible algorithm for the optimization of Slot Filling Factors in Electrical Machines

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ENERGIES 2020年第5期13卷

作者： Dietz, Armin Di Tommaso, Antonino Oscar Marignetti, Fabrizio Miceli, Rosario Nevoloso, Claudio Tech Hsch Nurnberg Inst ELSYS D-90489 Nurnberg Germany Univ Palermo Dipartimento Ingn Viale Sci I-90128 Palermo Italy Univ Cassino & South Lazio Dept Elect & Informat Engn DIEI Via G Di Biasio 43 I-03043 Cassino Italy

The continuous development in the field of industrial automation and electric mobility has led to the need for more efficient electrical machines with a high power density. The improvement of electrical machines' slot filling factors is one of the measures to satisfy these requirements. In recent years, this topic has aroused greater interest in the industrial sector, since the evolution of the winding technological manufacturing processes allows an economically sustainable realization of ordered winding arrangements, rather than random ones. Moreover, the manufacture of electrical machines' windings must be preceded by an accurate design phase in which it is possible to evaluate the maximum slot filling factor obtainable for a given wire shape and for its dimensions. For this purpose, this paper presents an algorithmic approach for the evaluation of maximum slot filling factors in electrical machines under an ideal geometric premise. In particular, this algorithm has a greater degree of flexibility with respect to the algorithm approaches found in the literature, since the study has been extended to round, rectangular and hexagonal wire sections. Furthermore, the slot filling factor calculation was carried out both for standard and non-standard slots. The algorithmic approach proposed can be considered as an additional useful tool for the fast design of electrical machine windings.

关键词： electrical motors sot filling factor optimization algorithm windings magnetic wire filling factor optimization

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Path Synthesis optimization Model of Planar Five-Bar Metamorphic Mechanism 14th

Path Synthesis Optimization Model of Planar Five-Bar Metamor...

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14th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Yao, Xinyuan Wang, Xingdong Sun, Wei Bai, Haoke Wuhan Univ Sci & Technol Sch Mech Automat Wuhan Peoples R China

ISBN: (纸本)9783030890926;9783030890919

The path synthesis of metamorphic mechanism is an essential problem in kinematics. This paper develops a new optimization model for planar five-bar metamorphic mechanism with two sub-configurations. As different configurations may produce large differences in the target points, the utilization of two configurations can help to preserve good results and avoid bad results. Comparative study between metamorphic mechanism and the models using one sub-configuration shows that trajectory of metamorphic mechanism by the proposed model is closer to the target point. In addition, an example demonstrates the comprehensive capabilities of metamorphic mechanisms in the face of trajectories with change mutation points. This optimization model has potential reference value for the optimization of other metamorphic mechanisms.

关键词： Metamorphic mechanism Path synthesis optimization algorithm Kinematics Five-bar mechanism

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Conjunction Time and Collision Probability Calculation Based on Bayesian optimization

Conjunction Time and Collision Probability Calculation Based...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Jia, Bin Xing, Ming Aptiv Agoura Hills CA 91301 USA Univ Missouri Dept Mech & Aerosp Engn Columbia MO 65211 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

Collision probability calculation is critical to space situational awareness or space traffic management. To determine the collision probability, the conjunction time is required first. In this paper, the continuous representation of the polynomial chaos is used to describe the uncertainty of space objects along with time. Based on this representation, the Bayesian optimization is employed to find the conjunction time and then the collision probability. The polynomial chaos representation and Bayesian optimization do not require Gaussian assumption and are computationally more efficient than the Monte Carlo sampling-based method to calculate collision probability and time. The effect of the order of polynomial chaos as well as the sampling period is also analyzed. Two numerical experiments are used to show the effectiveness of the proposed algorithm.

关键词： Bayesian optimization Space Situational Awareness Space Traffic Management Numerical Integration Monte Carlo Method Probability Density Functions Graphics Processing Unit optimization algorithm Maximum Likelihood Estimation Aerospace Engineering

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