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Updating for Model-Based Simulation

Updating for Model-Based Simulation
更新基于模型的仿真
批准号:
0200019
负责人:
Daniel Inman
金额:
$22.5万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-09-01 至 2006-08-31

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中文摘要
翻译
Daniel J. Inman弗吉尼亚理工大学提案编号:0200019提案标题“基于模型的仿真更新”项目摘要该研究的总体目标是开发正常和阻尼柔性结构模型更新的改进方法。预计改进将体现在算法本身、实现算法的数值方案以及评估更新方法结果的工具中。将研究的具体问题是: 使用参考基础模型方法获得物理上有意义的更新模型。 模态校正和阶次匹配。确定性和随机敏感性分析。稳健的更新和可靠性问题。通过实验验证和改进方法。智力贡献是双重的。从理论角度来看,对参考基础方法的这种修改具有明显的科学价值。 其次,所指出的每一个问题都对应于寻求基于模型的仿真的行业所面临的真正实际问题。 这些问题的解决将有助于更好地建模和理解振动系统。 更具体地说,我们相信参数参考基础方法是一种非常有前途的模型更新方法,并且通过适当的调整,它将比任何其他方法表现得更好。所提出的努力预计将通过提供准确的仿真模型的算法来影响行业,这是一个长期存在的重要问题。 其次,拟议的努力将改善代表性不足群体的研究生培训,让本科生参与研究并促进学术生涯的追求。
英文摘要
Daniel J. InmanVirginia TechProposal Number: 0200019Proposal Title "Updating for Model-Based Simulation" Project Abstract The general aim of the research is to develop improved methods of model updating for normal and damped flexible structures. The improvement is expected to be in the algorithms themselves, in the numerical schemes that will realize them, and in tools for evaluating the outcome of the updating method. Specific issues that will be investigated are: Obtaining a physically meaningful updated model using reference basis model method. Mode shape correction and order matching. Deterministic and stochastic sensitivity analysis. Robust updating and reliability issues. Method validation and improvement by experiment.The intellectual contribution is twofold. From a theoretical point of view such modification of the reference basis method has a clear scientific merit. Secondly, each one of the indicated issues corresponds to a genuine practical problem facing industries seeking model-based simulation. Solution of these will lead to better modeling and understanding of vibrating systems. To be more specific, it is our belief that the parametric reference basis method is a very promising approach to model updating and with the appropriate tuning it will perform better than any other method.The proposed effort is expected to impact industry by providing algorithms to provide accurate simulation models, a long-standing problem of importance. Secondly, the proposed effort will improve graduate training of underrepresented groups, involve undergraduates in research and promote the pursuit of academic careers.
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