This paper presents methodological investigations performed in research activities in the field of Multi-disciplinary Design and Optimization (MDO) for overall aircraft design in the EU funded research project AGILE (2015–2018). In the AGILE project a team of 19 industrial, research and academic partners from Europe, Canada and Russia are working together to develop the next generation of MDO environment that targets significant reductions in aircraft development costs and time to market, leading to cheaper and greener aircraft. The paper introduces the AGILE project structure and describes the achievements of the 1st year that led to a reference distributed MDO system. A focus is then made on different novel optimization techniques studied during the 2nd year, all aiming at easing the optimization of complex workflows that are characterized by a high number of discipline interdependencies and a large number of design variables in the context of multi-level processes and multi-partner collaborative engineering projects. Three optimization strategies are introduced and validated for a conventional aircraft. First, a multi-objective technique based on Nash Games and Genetic Algorithm is used on a wing design problem. Then a zoom is made on the nacelle design where a surrogate-based optimizer is used to solve a mono-objective problem. Finally a robust approach is adopted to study the effects of uncertainty in parameters on the nacelle design process. These new capabilities have been integrated in the AGILE collaborative framework that in the future will be used to study and optimize novel unconventional aircraft configurations.

中文翻译：

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使用 AGILE 协作 MDO 框架增强优化能力，并应用到机翼和机舱设计

本文介绍了在欧盟资助的研究项目 AGILE（2015-2018 年）中，针对整体飞机设计的多学科设计和优化 (MDO) 领域的研究活动中进行的方法论调查。在 AGILE 项目中，来自欧洲、加拿大和俄罗斯的 19 个工业、研究和学术合作伙伴正在共同开发下一代 MDO 环境，旨在显着降低飞机开发成本和上市时间，从而生产更便宜、更环保的飞机. 本文介绍了 AGILE 项目结构，并描述了第一年导致参考分布式 MDO 系统的成就。然后将重点放在第二年研究的不同新颖优化技术上，所有这些都旨在简化复杂工作流程的优化，这些工作流程的特点是在多层次流程和多合作伙伴协作工程项目的背景下具有大量学科相互依赖性和大量设计变量。针对传统飞机引入并验证了三种优化策略。首先，基于纳什博弈和遗传算法的多目标技术被用于机翼设计问题。然后对机舱设计进行缩放，其中使用基于代理的优化器来解决单目标问题。最后，采用稳健的方法来研究参数不确定性对机舱设计过程的影响。