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Uncertain multidisciplinary design optimization on Next Generation Subsea Production System by Using Surrogate Model and Interval Method

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China Ocean Engineering 2021年第4期35卷 609-621页

作者： WU Jia-hao ZHEN Xing-wei LIU Gang HUANG Yi School of Naval Architecture and Ocean Engineering Dalian University of TechnologyDalian 116024China

The innovative Next Generation Subsea Production System(NextGen SPS)concept is a newly proposed petroleum development solution in ultra-deep water *** definition of NextGen SPS involves several disciplines,which makes the design process *** this paper,the definition of NextGen SPS is modeled as an uncertain multidisciplinary design optimization(MDO)*** deterministic optimization model is formulated,and three concerning disciplines—cost calculation,hydrodynamic analysis and global performance analysis are *** model technique is applied in the latter two *** optimization(CO)architecture is utilized to organize the concerning disciplines.A deterministic CO framework with two disciplinelevel optimizations is proposed *** the uncertainties of design parameters and surrogate models are incorporated by using interval method,and uncertain CO frameworks with triple loop and double loop optimization structure are established *** optimization results illustrate that,although the deterministic MDO result achieves higher reduction in objective function than the uncertain MDO result,the latter is more reliable than the former.

关键词： next generation subsea production system multidisciplinary design optimization uncertain optimization collaborative optimization surrogate model interval method

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multidisciplinary design optimization for Effectiveness-Based design in the AFRL EXPEDITE Program

Multidisciplinary Design Optimization for Effectiveness-Base...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Levy, Mason Choi, Kevin Lockheed Martin Aeronaut ADP Palmdale CA 93599 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

The EXPEDITE (EXPanded multidisciplinary design optimization (MDO) for Effectiveness Based design TEchnologies) Program is an AFRL/RQ effort to advance the state of the art of Mulidisciplinary design optimization by implementing Effectiveness Based design, wherein an air vehicle is sized not to vehicle-level metrics like Gross Weight, but to scenario effectiveness parameters. This paper's focus is on the modeling techniques used to approach this task, from the overall sizing framework to individual disciplines such as Electromagnetics and Aerodynamics, and demonstrates preliminary results with these models.

关键词： Air Force Research Laboratory multidisciplinary design optimization Aerodynamics design Technology Air Vehicle CAD System Angle of Attack High Performance Computing Landing Gear Vortices

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Constrained efficient global multidisciplinary design optimization using adaptive disciplinary surrogate enrichment

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STRUCTURAL AND multidisciplinary optimization 2024年第2期67卷 23-23页

作者： Cardoso, Ines Dubreuil, Sylvain Bartoli, Nathalie Gogu, Christian Salaun, Michel Univ Toulouse DTIS ONERA Toulouse France Univ Toulouse ICA CNRS UPSINSAISAEMines Albi 3 Rue Caroline Aigle F-31400 Toulouse France

Surrogate-based optimization has become a popular approach for solving problems with computationally expensive disciplinary solvers. Recently, the Efficient Global multidisciplinary design optimization (EGMDO) algorithm was introduced as a surrogate-based algorithm for multidisciplinary optimization, where the disciplinary solvers are replaced by Gaussian process (GP) surrogate models. A dedicated model of the resulting random objective function is then used to perform Bayesian optimization and focus the computational effort in promising areas of the design space. While its results are promising, the original EGMDO formulation does not provide a strategy for constraint handling. In this work we reformulate the original EGMDO algorithm to be able to handle both equality and inequality constraints. To do so, surrogate models of the constraint functions are first obtained. Then, the original uncertainty reduction strategy is adapted to account for the uncertainty introduced by the disciplinary GPs in both objective and constraint functions. The performance of the resulting algorithm, called Constrained-EGMDO (C-EGMDO), is then illustrated on a benchmark analytical MDO problem and on an engineering test case.

关键词： multidisciplinary design optimization Global optimization Surrogate models Constraint handling

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multidisciplinary design optimization of Reusable Launch Vehicles for Different Propellants and Objectives

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JOURNAL OF SPACECRAFT AND ROCKETS 2021年第4期58卷 1017-1029页

作者： Dresia, Kai Jentzsch, Simon Waxenegger-Wilfing, Guenther Santos Hahn, Robson Dos Deeken, Jan Oschwald, Michael Mota, Fabio German Aerosp Ctr DLR Inst Space Propuls D-74239 Hardthausen Germany Rhein Westfal TH Aachen Inst Jet Prop & Turbomachinery D-52062 Aachen Germany Fed Univ ABC Dept Aerosp Engn Sao Paulo Brazil DLR Inst Space Prop Head Rocket Prop Dept German Aerosp Ctr D-74239 Hardthausen Germany

Identifying the optimal design of a new launch vehicle is most important because design decisions made in the early development phase limit the later performance of the vehicles and determine the associated costs. Reusing the first stage via retropropulsive landing increases the complexity even more. Therefore, an optimization framework for partially reusable launch vehicles is developed, which enables multidisciplinary design studies. The framework contains suitable mass estimates of all essential subsystems and a routine to calculate the needed propellant for the ascent and landing maneuvers. For design optimization, the framework can be coupled with a genetic algorithm. The overall goal was to reveal the implications of different propellant combinations and objective functions on the optimal design of the launcher for various mission scenarios. The results show that the optimization objective influences the most suitable propellant choice and the overall launcher design, concerning staging, weight, size, and rocket engine parameters. In terms of gross lift-off weight, liquid hydrogen seems to be favorable. When optimizing for a minimum structural mass or an expendable structural mass, hydrocarbon-based solutions show better results. Finally, launch vehicles using a hydrocarbon fuel in the first stage and liquid hydrogen in the upper stage are an appealing alternative, combining the benefits of both fuels.

关键词： Launch Vehicle Configurations Propellant multidisciplinary design optimization Genetic Algorithm Reusable Rocket Engine Hydrocarbon Fuels Rocket Performance Geostationary Transfer Orbit Thrust to Weight Ratio Chamber Pressure

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multidisciplinary design optimization of distributed energy generation systems: The trade-offs between life cycle environmental and economic impacts

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APPLIED ENERGY 2021年 284卷 116197-116197页

作者： Yan, Junchen Broesicke, Osvaldo A. Tong, Xin Wang, Dong Li, Duo Crittenden, John C. Georgia Inst Technol Brook Byers Inst Sustainable Syst Sch Civil & Environm Engn 828 West Peachtree StSuite 320 Atlanta GA 30332 USA Rice Univ Nanosyst Engn Ctr Nanotechnol Enabled Water Treat 6100 Main St Houston TX 77005 USA

Distributed energy systems (DES) are the focus of increasing attention because they have the potential to enhance the sustainability performance of energy generation. Previous DES researches evaluated various distributed energy technologies and systems from different aspects. However, there is still a research gap to evaluate and compare the multiple technology combinations and sizes for finding optimal energy solutions under various scenarios. This study aims to determine the best combination of technologies and their corresponding sizes for DES for various building types and climate zones in terms of life cycle environmental and economic impact. We developed parametric models (which considers dynamic hour by hour energy demand) for six commercially available distributed energy technologies and simulated the performance of them under various conditions. Then, we used a novel approach - multidisciplinary design optimization (MDO) to examine the billions of options (e.g., technologies, sizes, climate zone, Etc.) and identified the Pareto front with the optimal environmental and economic impact. According to MDO simulations, the microturbine-solar PVs-lithium ion battery and solid oxide fuel cells-solar PVs-lithium ion battery are two optimal combinations of technologies for three commercial building types for five climate zones. The DES can primarily reduce the environmental impact compared to conventional centralized energy production (CCEP) by 16-61% in all scenarios. However, the life cycle cost of DES is higher than CCEP, especially for SOFC-based DES. The microturbine-based DES is more cost-competitive and economical (about 65%, 32%, and 64% lower than SOFC-based DES for the small, medium, and large office, respectively).

关键词： Distributed energy systems multidisciplinary design optimization Renewable energy Parametric modelling Life cycle assessment Life cycle cost

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Improved Augmented Lagrangian Relaxation-Assisted Analytical Target Cascading for multidisciplinary design optimization

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Journal of Mechanical design 2025年第8期147卷 081701页

作者： Zhou, Xiaowei Li, Wei School of Mechanical Engineering Hefei University of Technology Hefei 230009 China

Analytical target cascading (ATC) is an optimization strategy designed for multilevel and multidisciplinary design optimization (MDO) problems. Its core aim is to enhance the overall convergence of the system by reducing the inconsistency between different levels. In previous studies, although the augmented Lagrangian relaxation method can achieve rapid and accurate positioning of the optimal solution, it is highly sensitive to the penalty parameters, which can easily cause instability in numerical calculation. In contrast, the Lagrangian duality theory effectively reduces the numerical instability by adaptively adjusting the parameters, but this method is at the expense of increasing the computational time and the number of iterations. This study proposes an analytical target cascading combined with the Maclaurin series method (ATC-MAC), which aims to reduce parameter sensitivity and accelerate convergence to the optimal solution. The method uses the Maclaurin series to approximate the cross terms in the augmented Lagrangian function to reduce its interference with the main function. Meanwhile, the step size updating strategy is optimized by combining the duality theory and the multiplier method. Through the application in three numerical cases and one engineering case, the effectiveness and practicability of the ATC-MAC method are verified.

关键词： design automation design optimization Modal assurance criterion design optimization Lagrangian duality Computer programming augmented Lagrangian relaxation Relaxation (Physics) multidisciplinary design optimization analytical target cascading

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Coupled-analysis assisted gradient-enhanced kriging method for global multidisciplinary design optimization

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ENGINEERING optimization 2021年第6期53卷 1081-1100页

作者： Chen, Xu Wang, Peng Dong, Huachao Zhao, Xiaozhe Xue, Deyi Northwestern Polytech Univ Sch Marine Sci & Technol Xian Peoples R China Univ Calgary Dept Mech & Mfg Engn Calgary AB Canada

A coupled-analysis assisted gradient-enhanced kriging (CAGEK) method is introduced to improve the quality and efficiency in solving global multidisciplinary design optimization (MDO) problems when multiple disciplines are coupled and expensive computations are required to evaluate these disciplines. In this method, the multidisciplinary feasible architecture is employed to effectively obtain the values of coupled variables. The CAGEK method is an adaptive metamodelling-based optimization method with the gradient-enhanced kriging (GEK) model as the metamodel for improving optimization efficiency by using fewer data samples. A coupled analysis approach is used to calculate the gradient efficiently for the GEK model. Besides, a multiple-point infill method is used to obtain new samples at each optimization iteration considering convergence rate and global optimization capability. The CAGEK method is compared with three traditional methods using four MDO problems to demonstrate its effectiveness.

关键词： multidisciplinary design optimization coupled analysis gradient-enhanced kriging global optimization

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multidisciplinary design optimization of Low-Boom Supersonic Aircraft with Mission Constraints

Multidisciplinary Design Optimization of Low-Boom Supersonic...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Li, Wu Geiselhart, Karl NASA Langley Res Ctr Aeronaut Syst Anal Branch Hampton VA 23681 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

design of low-boom supersonic aircraft is heavily dictated by aircraft volume and lift distributions. These unique design characteristics make it a challenge to enforce mission requirements ( such as static margins and trim requirements) during design optimization. This low-boom design challenge is resolved by using reversed equivalent area targets for low-fidelity low-boom design and a decomposition method for multidisciplinary design optimization (MDO). The corresponding low-boom MDO problem includes aircraft mission constraints for cruise ranges, cruise speeds, trim margin for low-boom cruise, static margins for takeoff/cruise/landing, tail rotation angles for trim at takeoff/landing, takeoff/landing field lengths, and approach velocity, as well as volume constraints for cabin and main landing gear packaging. The decomposition method is developed to optimally resolve the conflicts between the low-boom design objective and other design constraints. The decomposition method is successfully applied to design a low-boom supersonic configuration that carries 40 passengers, has low-boom cruise of Mach 1.6 with range >= 2,500 nm, and can also cruise at Mach 1.8 with range >= 3,600 nm. The generated configuration satisfies all specified mission constraints and has the potential to achieve a low-boom ground noise level below 75 PLdB.

关键词： Supersonic Aircraft multidisciplinary design optimization Aircraft Configurations Aerodynamic Performance Aerodynamic Center Takeoff and Landing Computational Fluid Dynamics Flight optimization System Wing Planforms Cruise Altitude

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Enabling large-scale multidisciplinary design optimization through adjoint sensitivity analysis

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STRUCTURAL AND multidisciplinary optimization 2021年第5期64卷 2959-2974页

作者： Martins, Joaquim R. R. A. Kennedy, Graeme J. Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA Georgia Inst Technol Sch Aerosp Engn Atlanta GA USA

This paper is written to honor Raphael T. Haftka's seminal contributions to multidisciplinary design optimization. We focus on those contributions that directly impacted our research, namely: the adjoint method for computing derivatives, wing aerostructural design optimization, and architectures for multidisciplinary design optimization. For each of these topics, we describe Haftka's contributions, how they impacted our research, and examples of what they enabled us to do. The overarching theme of the contributions and developments described in this paper is the efficient computation of derivatives, which, together with gradient-based optimizers, enables the optimization with respect to large numbers of design variables, even when using costly high-fidelity models.

关键词： multidisciplinary design optimization Sensitivity analysis Adjoint method Structural optimization Aerodynamic shape optimization Aircraft design

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A multidisciplinary design optimization for conceptual design of hybrid-electric aircraft

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STRUCTURAL AND multidisciplinary optimization 2021年第6期64卷 3505-3526页

作者： Silva, Higor L. Resende, Gustavo J. Neto, Roberto M. C. Carvalho, Andre R. D. Gil, Alexandre A. Cruz, Mateus A. A. Guimaraes, Thiago A. M. Fed Univ Uberlandia UFU Dept Mech Engn Campus Santa Monica Uberlandia MG Brazil Aeronaut Inst Technol ITA Dept Sci & Aerosp Technol Sao Jose Dos Campos Brazil

Aircraft design has become increasingly complex since it depends on technological advances and integration between modern engineering systems. These systems are multidisciplinary, i.e., any process or division of any aircraft design produces effects in all others, making the definition of each parameter a significant challenge. In this context, this work presents a general multidisciplinary design optimization method for the conceptual design of general aviation and hybrid-electric aircraft. The framework uses efficient computational methods comprising modules of engineering that include aerodynamics, flight mechanics, structures, and performance, and the integration of all of them. The aerodynamic package relies on a Nonlinear Vortex Lattice Method solver, while the flight mechanics package is based on an analytical procedure with minimal dependence on historical data. Moreover, the structural module adopts an analytical sizing approach using boom idealization, and the performance of the aircraft is computed based on energy and power required to accomplish a specific mission. The objective functions are to minimize the fuel consumption and to minimize the takeoff weight. The Pareto-optimal front encompasses aircraft with different propulsive architectures: turboelectric, hybrid electric, and fully electric. The degrees of hybridization defined by the optimization and the mission requirements chosen in this study directly affect the final weight breakdown of the aircraft, which is related to the sizing of the wings, propulsive system, and horizontal and vertical tails.

关键词： Aircraft design Hybrid-electric aircraft multidisciplinary design optimization General aviation aircraft

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