针对国内外已有的复杂工业产品多学科设计仿真优化框架与平台在多学科模型集成能力、计算能力、协同能力方面的不足,研究和开发国产自主的新一代复杂工业产品多学科设计仿真优化框架与平台UniXDE(unified exploration and design enviro...针对国内外已有的复杂工业产品多学科设计仿真优化框架与平台在多学科模型集成能力、计算能力、协同能力方面的不足,研究和开发国产自主的新一代复杂工业产品多学科设计仿真优化框架与平台UniXDE(unified exploration and design environment)。本平台基于微服务云架构技术构建整体框架,提供低代码仿真优化流程编排、组件化CAD/CAE参数化集成接口、丰富的多学科设计优化算法库、分布式高性能优化计算引擎、可视化计算监控和报告自动生成等功能。通过白车身轻量化、船型优化、飞行器起落架性能优化等工程应用,表明UniXDE可显著提升产品综合性能和设计成功率。展开更多
Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate struct...Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate structure decomposition, which limits their practical application. The rapid expansion of data makes utilizing data to guide and improve system design indispensable in practical engineering. In this paper, a data driven uncertainty evaluation approach is proposed to support the design of complex engineered systems. The core of the approach is a data-mining based uncertainty evaluation method that predicts the uncertainty level of a specific system design by means of analyzing association relations along different system attributes and synthesizing the information entropy of the covered attribute areas, and a quantitative measure of system uncertainty can be obtained accordingly. Monte Carlo simulation is introduced to get the uncertainty extrema, and the possible data distributions under different situations is discussed in detail The uncertainty values can be normalized using the simulation results and the values can be used to evaluate different system designs. A prototype system is established, and two case studies have been carded out. The case of an inverted pendulum system validates the effectiveness of the proposed method, and the case of an oil sump design shows the practicability when two or more design plans need to be compared. This research can be used to evaluate the uncertainty of complex engineered systems completely relying on data, and is ideally suited for plan selection and performance analysis in system design.展开更多
文摘针对国内外已有的复杂工业产品多学科设计仿真优化框架与平台在多学科模型集成能力、计算能力、协同能力方面的不足,研究和开发国产自主的新一代复杂工业产品多学科设计仿真优化框架与平台UniXDE(unified exploration and design environment)。本平台基于微服务云架构技术构建整体框架,提供低代码仿真优化流程编排、组件化CAD/CAE参数化集成接口、丰富的多学科设计优化算法库、分布式高性能优化计算引擎、可视化计算监控和报告自动生成等功能。通过白车身轻量化、船型优化、飞行器起落架性能优化等工程应用,表明UniXDE可显著提升产品综合性能和设计成功率。
基金Supported by National Hi-tech Research and Development Program of China(863 Program,Grant No.2015AA042101)
文摘Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate structure decomposition, which limits their practical application. The rapid expansion of data makes utilizing data to guide and improve system design indispensable in practical engineering. In this paper, a data driven uncertainty evaluation approach is proposed to support the design of complex engineered systems. The core of the approach is a data-mining based uncertainty evaluation method that predicts the uncertainty level of a specific system design by means of analyzing association relations along different system attributes and synthesizing the information entropy of the covered attribute areas, and a quantitative measure of system uncertainty can be obtained accordingly. Monte Carlo simulation is introduced to get the uncertainty extrema, and the possible data distributions under different situations is discussed in detail The uncertainty values can be normalized using the simulation results and the values can be used to evaluate different system designs. A prototype system is established, and two case studies have been carded out. The case of an inverted pendulum system validates the effectiveness of the proposed method, and the case of an oil sump design shows the practicability when two or more design plans need to be compared. This research can be used to evaluate the uncertainty of complex engineered systems completely relying on data, and is ideally suited for plan selection and performance analysis in system design.
