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作 者:铁鸣[1] 张星[1] 许靖尧 徐聪[1] Tie Ming;Zhang Xing;Xu Jingyao;Xu Cong(Science and Technology on Space Physics Laboratory,Beijing Institute of Nearspace Vehicles System Engineering,Beijing 100076,China)
机构地区:[1]北京临近空间飞行器系统工程研究所空间物理重点实验室,北京100076
出 处:《新型工业化》2024年第1期57-66,共10页The Journal of New Industrialization
基 金:国家自然科学基金“高超声速飞行器转捩高维数据高效辨识与智能CFD预报方法”(61773068)。
摘 要:新一代航天复杂装备的发展,亟须改变传统研制模式,提升总体设计水平,缩短研制周期,降低试验成本。同时,我国航天装备研制过程积累的大数据资源没有形成有效的知识积累与重用手段,并且多专业强耦合的总体设计研制流程信息化程度低,导致专业内部和专业之间协同不高效,难以驱动装备总体方案设计实现敏捷、高效、最优。因此,如何建设智慧研发体系成为当前航天总体设计面向数字化、智能化融合发展的主要焦点问题。本文介绍了航天装备总体设计的智慧研发模式,分析了难点与需求,提出了实施途径、模型体系、研制流程和支撑平台架构,以研制流程高效可控、数据智能学习、知识驱动设计、系统耦合验证为构建思路,用于指导建设新一代航天装备总体设计的智能化、协同化研发环境,支撑产品自主研发能力和产品研发活动规范高效地开展,指导设计持续改进,推动航天装备数字化研制。The development of complex aerospace equipment urgently requires changing the traditional R&D(research and development)mode,in order to upgrade the integrated design level,shorten the development cycle as well as reduce test costs.In addition,the big data resources from the historical development of aerospace equipment have not formed an effective means of knowledge accumulation and reuse.Furthermore,the strongly coupled multidisciplinary integrated design process leads to inefficient collaboration within and between disciplines and makes it difficult to achieve agile,efficient,and optimal development procedure.Therefore,how to build a smart R&D system has become a main focus problem of the integration of digitization and intelligence in the current aerospace engineering.This paper introduces an intelligent R&D model for the integrated design of aerospace equipment,analyses the difficulties and requirements,and presents the smart development process,system,and platform architecture.The presented intelligent development model can be capable of building an intelligent and collaborative R&D environment for aerospace design,so as to achieve the efficient knowledge-driven development process as well as improve digitization and collaboration of the development process.
分 类 号:V57[航空宇航科学与技术—航空宇航推进理论与工程] F407.67[经济管理—产业经济]
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