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Multi-disciplinary and multi-objective optimization of an over-wing-nacelle aircraft concept

机译:过翼式机舱飞机概念的多学科和多目标优化

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In this paper, a multi-disciplinary and multi-objective optimization (MDO-MOO) of a baseline over-wing-nacelle (OWN) concept design is presented. The present study extends the previous works, which considered only aerodynamic optimization, to include structural and mission design parameters. The competing objectives of minimum empty weight and minimum fuel weight for a design mission are considered in the multi-objective formulation as well as the single-objective problem of minimizing takeoff gross weight, one of many compromises possible for the multi-objective problem. An integrated computational environment has been implemented. High-fidelity analyses for the structural and aeroelastic assessment, together with middle-fidelity analyses for aerodynamic, mission, and performance analyses are performed. A complex multi-disciplinary analysis framework is proposed, to account for the interdisciplinary interaction and to provide a consistent computational framework. Optimization results with a Multi-objective Genetic Algorithm (MOGA) show Pareto frontiers accounting for structural, aeroelastic, and mission design constraints. The disciplines coupling is quantified, in terms of constraints, design variables influences, and possible trade-offs among the objectives.
机译:在本文中,提出了基线上限翼型(自身)概念设计的多学科和多目标优化(MDO-Moo)。本研究扩展了以前的作品,其仅考虑空气动力学优化,包括结构和任务设计参数。在多目标配方中考虑了设计任务的最小空体重和最小燃料重量的竞争目标,以及最小化起飞毛重的单个客观问题,对于多目标问题的许多妥协之一。已经实施了集成的计算环境。进行结构和空气弹性评估的高保真分析,以及用于空气动力学,使命和性能分析的中间保真分析。提出了一个复杂的多学科分析框架,以解释跨学科互动并提供一致的计算框架。具有多目标遗传算法(MOGA)的优化结果显示帕累托前沿占结构,空气弹性和任务设计约束的核对。在限制方面,对学科耦合进行量化,设计变量影响,以及目标之间可能的权衡。

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