Collaborative Research: Multi-Accuracy Bayesian Models for Improving Property Prediction of Nanotube Buckypaper Composites
Collaborative Research: Multi-Accuracy Bayesian Models for Improving Property Prediction of Nanotube Buckypaper Composites
批准号:
1000099
负责人:
Chun Zhang
金额:
$21.98万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-08-15 至 2013-08-31
中文摘要
这项佛罗里达州立大学和德克萨斯A M大学之间的合作研究是开发多精度预测模型,可以提高布基纸基复合材料性能的预测能力。该团队将研究适当的建模策略,以整合多精度信息以及解决相关计算和设计问题的解决方案技术,以保证该方法的效率和实用性。目前,一些力学模型可用于对布基纸基复合材料进行性能预测,但由于模型的不充分性和不确定性,大多数模型的准确性较低。力学模型和实际物理实验的输出构成了一组多精度的信息源,从不同的角度反映了相同的物理性质。我们的猜想是,结合多精度的输出可以帮助提高所需的性能predictationforbukyper-based复合材料,这一新方法的成功开发将有可能实现稳定的,可重复的,和可扩展的生产过程中bukyper-based复合材料,这是最抢手的纳米材料之一,由于其性能在传统材料中找不到,并适用于广泛的应用。高性能材料研究所(HPMI)在佛罗里达州立大学,其中铅PI是附属机构,是最好的研究设施在巴克纸研发和原型生产能力方面的国家之一。预测模型是在纳米制造中实现任何过程和质量控制尝试的基石,因为只有使用这些模型,人们才能识别关键的过程变量,以便进行过程测量或进行调整,以产生预期的结果。
英文摘要
This collaborative research between Florida State University and Texas A&M University is to develop multi-accuracy predictive models that can enhance the prediction capability for bukypaper-based composite properties. The team will investigate proper modeling strategies to integrate the multi-accuracy information as well as the solution techniques that address the associated computational and design issues in order to guarantee the method's efficiency and practicality. Currently, a few mechanics models are available for making property predictions for bukypaper-based composites but most of them suffer from having low accuracy due to model inadequacy and uncertainty. The outputs from the mechanics models and actual physical experiments constitute a set of multi-accuracy information sources, reflecting the same physical properties from different perspectives. Our conjecture is that combining the multi-accuracy outputs could help enhance the desired property predication for bukypaper-based composites.The successful development of this new methodology will potentially enable stable, repeatable, and scalable production processes for bukypaper-based composites, which are one of the most sought-after nano-materials, due to its properties unfound in traditional materials and applicability to a broad array of applications. The High-Performance Material Institute (HPMI) at Florida State University, with which the lead PI is affiliated, is one of the best research facilities in the nation in terms of buckypaper R&D and prototype production capabilities. Predictive models are the cornerstones for enabling any attempts of process and quality control in nano-manufacturing because only with these models can people identify the critical process variables for taking in-process measurements, or making adjustments, in order to yield expected outcomes.
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IUCRC Phase I Georgia Institute of Technology: Center for Composite and Hybrid Materials Interfacing (CHMI)
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批准号:2052714
-
项目类别:Continuing Grant
-
资助金额:$85.0万
-
财政年份:2021
-
负责人:Chun Zhang
-
依托单位:
REU Site: Research Experience for Student Veterans in Advanced Manufacturing and EntrePreneurship (REVAMP)
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批准号:1852253
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项目类别:Standard Grant
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资助金额:$36.0万
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财政年份:2019
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负责人:Chun Zhang
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依托单位:
Planning IUCRC at Georgia Institute of Technology: Center for [Digital Composite Joining and Repair]
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批准号:1822035
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项目类别:Standard Grant
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资助金额:$1.5万
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财政年份:2018
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负责人:Chun Zhang
-
依托单位:
CPS/Synergy/Collaborative Research: Cybernizing Mechanical Structures through Integrated Sensor-Structure Fabrication
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批准号:1544595
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项目类别:Standard Grant
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资助金额:$21.5万
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财政年份:2016
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负责人:Chun Zhang
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依托单位:
REU Site: Research Experience for student Veterans in Advanced Manufacturing and entrePreneurship (REVAMP)
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批准号:1359019
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项目类别:Standard Grant
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资助金额:$35.91万
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财政年份:2014
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负责人:Chun Zhang
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依托单位:
Collaborative Research: Multi-Accuracy Bayesian Models for Improving Property Prediction of Nanotube Buckypaper Composites
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批准号:1346681
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项目类别:Standard Grant
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资助金额:$9.98万
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财政年份:2013
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负责人:Chun Zhang
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依托单位:
SGER: On-Line Fiber Preform Permeability Measurement and Its Applications to Liquid Composite Molding
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批准号:0001243
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项目类别:Standard Grant
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资助金额:$9.8万
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财政年份:2000
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负责人:Chun Zhang
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依托单位:
GOALI/Faculty and Students in Industry: Rapid Development of Computer Aided Process Planning Systems
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批准号:9510456
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项目类别:Standard Grant
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资助金额:$1.17万
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财政年份:1995
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负责人:Chun Zhang
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依托单位:
国内基金
海外基金
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