课题基金 / 基金详情

Collaborative Research: Computational Foundations for Learning, Verifying, and Applying Model Simplification Rules

Collaborative Research: Computational Foundations for Learning, Verifying, and Applying Model Simplification Rules
协作研究:学习、验证和应用模型简化规则的计算基础
批准号:
1161474
负责人:
Krishnan Suresh
金额:
$23.87万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-07-01 至 2016-06-30

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中文摘要
翻译
该奖项的目标是开发基于特征的计算机辅助设计模型的简化,特别是加速和自动化下游有限元分析。特别是,这项研究将为从人类专家进行的演示中学习保守的特征抑制规则创建算法基础。将正式描述简化对模拟精度的影响,并将利用这一理解在计算机辅助设计模型中创建稳健的特征抑制算法。研究成果将被纳入研究生和本科生课程。这项研究最终将产生一个框架,用于自动学习、验证和应用可由人类专家审计的上下文相关模型简化规则,并部署用于自动执行模型简化任务。如果成功,该研究将显著加快模型简化速度,并增强工程分析工具在设计过程中的自动化使用。潜在的应用包括热交换器、飞机结构和半导体设备的设计。计划的研究和教育整合活动和推广活动将使研究生、本科生和高中生熟悉在具有挑战性的工程设计项目中使用模型简化技术。该项目还将提高实践工程师对自动化模型简化在复杂工程设计项目中的潜在用途的认识。参与该项目的学生还将参加威斯康星大学校园的獾夏令营和工程博览会活动,以及马里兰大学的马里兰日活动,以增进公众对科学和技术的了解。
英文摘要
The objective of this award is to develop feature-based simplification of computer-aided-design models, specifically to accelerate and automate downstream finite-element-analysis. In particular, the research will create algorithmic foundations for learning conservative feature suppression rules from demonstrations performed by human experts. The effect of simplification on simulation accuracy will be formally characterized and this understanding will be used to create robust algorithms for feature suppression within computer-aided design models. Research findings will be integrated into graduate and undergraduate curriculum. The research will ultimately lead to a framework to automatically learn, validate, and apply context dependent model simplification rules that can be audited by human experts, and deployed to automate the model simplification task.If successful, the research will significantly speed up model simplification, and enhance the automated use of engineering analysis tools in the design process. Potential applications include design of heat exchangers, aircraft structures, and semi-conductor equipment. The planned research and education integration activities and outreach activities will familiarize graduate, undergraduate, and high school students with the use of model simplification technologies in challenging engineering design projects. This project will also increase awareness among practicing engineers about the potential usage of automated model simplification in complex engineering design projects. Students working on this project will also participate in Badger Camp and Engineering Expo events at the University of Wisconsin campus and Maryland Day at the University of Maryland to enhance the public understanding of the science and technology.
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Predicting the Benefits of Topology Optimization
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 项目类别:
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Generalization of Non-Uniform Rational Bezier Splines: Theory and Applications
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  • 项目类别:
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  • 资助金额:
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Using Topology Optimization to Reduce Support Structures in Additive Manufacturing
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 依托单位:
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