Introduction of Simulation Learning and Optimization to Support Engineering Design

引入仿真学习和优化来支持工程设计

• 批准号: 9114475
• 负责人: Stephen C-Y. Lu
• 金额: $ 15万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-04-15 至 1994-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9114475&HistoricalAwards=false
• 关键词: Introduction; Simulation; Learning; Optimization; Support

The objective of this research is to integrate simulation, learning, and optimization to form an Adaptive and Interactive Modeling System (AIMS) to support multiple perspectives at different stages for design and concurrent engineering. Given a database of examples collected from simulations or experiments, and a set of modeling objectives and design objectives, AIMS performs multi-objective optimization at both model formation and utilization phases. By varying modeling objectives, such as speed, accuracy, and comprehensibility, AIMS can produce layered models to meet the changing needs at different stages of design. By treating different life-cycle concerns as competing design objectives, AIMS can support systematic incorporation of multiple perspectives for concurrent engineering. This research represents a significant and meaningful integration between artificial intelligence based techniques and conventional engineering methods to further advance the basic research in design automation.

本研究的目标是将仿真、学习和优化集成起来，形成自适应交互式建模系统（AIMS），以支持设计和并行工程不同阶段的多种视角。 给定从模拟或实验中收集的示例数据库以及一组建模目标和设计目标，AIMS 在模型形成和使用阶段执行多目标优化。 通过改变建模目标，例如速度、准确性和可理解性，AIMS 可以生成分层模型，以满足不同设计阶段不断变化的需求。 通过将不同的生命周期问题视为竞争的设计目标，AIMS 可以支持并行工程的多个视角的系统整合。 这项研究代表了人工智能技术与传统工程方法之间的重大且有意义的整合，以进一步推进设计自动化的基础研究。