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Transformative Calibration Method for Prediction of Surface Heat Flux

Transformative Calibration Method for Prediction of Surface Heat Flux
预测表面热通量的变换校准方法
批准号:
1234419
负责人:
Jay Frankel
金额:
$24.99万
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:
2012-08-15 至 2016-07-31

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中文摘要
翻译
cbet -1234419 (5): J.I. Frankel和M. keyhani田纳西大学诺克斯维尔分校(UTK)提出了一种基于深度温度测量预测地表热通量的变动性校准方法。为了减轻传感器直接暴露在恶劣环境中,通常有必要对测试件的内部位置进行仪器测量。提出了一种基于物理和数学推导的校准框架,用于研究航空航天应用中出现的各种加热条件。这项研究以互补的方式整合了分析和实验活动,以验证在大温度范围和各种加热情景下的逆预测科学。校准概念大大减少了系统误差,因为它不需要探针位置、探针特性和热物理性质的规范。完整的系统特性固有地包含在结果校准方程中。由于存在病态,提出了一种新的正则化方法来稳定数值预测。不适定问题对所收集数据中的噪声高度敏感。这种新的本地-未来时间方法利用校准方程的行为来提取最优预测。这种独特的特性可能是新的校准公式的结果。对导出的校准方程的实验验证将使用由UTK维护的电热夹层设备或高功率激光设备进行。多维和多区域几何;而且,各向同性和正交异性材料样品将被研究,因为它们在航空航天科学中与高超声速飞行器的外皮和高超声速燃烧室表面相关的热保护系统中具有重要意义。本研究的重点是开发能够利用深度温度数据准确预测材料表面热通量的方法,以进行材料评估和定位相变。该项目将通过基于生成校准方程的综合分析和实验方法,为逆问题提供新的见解。这与将实验数据作为估计地表条件的数值方法的输入的传统学说形成了对比。因此,所提出的概念可以扩展到影响物理和工程许多领域的问题或领域,包括火灾和燃烧科学;金属铸造,晶体生长和焊接科学。此外,几个欧洲机构将参与整个计划,表明这种方法对未来高速航空航天研究的优点和意义。
英文摘要
CBET-1234419PI(s): J.I. Frankel and M. KeyhaniUniversity of Tennessee-Knoxville (UTK)A transformative calibration methodology is proposed for predicting the surface heat flux based on in-depth temperature measurements. Instrumenting interior locations of a test article is often necessary in order to alleviate the sensor's direct exposure to a hostile environment. A physics based and mathematically derived calibration framework is proposed for studying a variety of heating conditions that appear in aerospace applications. This investigation integrates analytical and experimental activities in a complementary manner for verifying the science of inverse prediction over a large temperature range and under various heating scenarios. The calibration concept substantially reduces systematic errors since it does not require the specification of the probe position, probe characteristics, and thermophysical properties. Full system characterization is inherently contained in the resulting calibration equations. Being ill posed, a new regularization method is proposed for stabilizing the numerical predictions. Ill-posed problems are highly sensitive to noise in the collected data. This new, local-future time approach exploits the behavior of the calibration equation for extracting an optimal prediction. This unique characteristic may be a consequence of the novel calibration formulation. Experimental verification of the derived calibration equations will be performed using either an electrically heated sandwich facility or high-powered laser facility that are both maintained at UTK. Multidimensional and multi-regional geometries; and, isotropic and orthotropic material samples will be studied owing to their importance in the aerospace sciences for thermal protections systems associated with external skins of hypersonic vehicles and surfaces in hypersonic combustors. This research is focused on developing methodologies that can use in-depth temperature data to accurately predict the surface heat flux for material evaluation and locating transition. This project will provide new insight into inverse problems through an integrated analytical and experimental approach based on producing calibration equations. This contrasts the conventional doctrine that views experimental data as input to a numerical method for estimating the surface conditions. Hence, the proposed concept can be expanded to a large class or arena of problems affecting many areas of physics and engineering including fire and combustion sciences; metal casting, crystal growth, and welding sciences. Additionally, several European institutions will be involved in the overall plan indicating the merit and significance of the approach to future high-speed aerospace studies.
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New Paradigms for Inverse Heat Conduction Problems: Creative analytics and experiments utilizing advanced technologies
  • 批准号:
    2031808
  • 项目类别:
    Standard Grant
  • 资助金额:
    $11.05万
  • 财政年份:
    2020
  • 负责人:
    Jay Frankel
  • 依托单位:
New Paradigms for Inverse Heat Conduction Problems: Creative analytics and experiments utilizing advanced technologies
  • 批准号:
    1703442
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.23万
  • 财政年份:
    2017
  • 负责人:
    Jay Frankel
  • 依托单位:
EAGER: Application of Calibration Convolution Integrals to Diffusion Transport
  • 批准号:
    1153476
  • 项目类别:
    Standard Grant
  • 资助金额:
    $2.9万
  • 财政年份:
    2011
  • 负责人:
    Jay Frankel
  • 依托单位:
EAGER: Experimental Verification of a Transformative Calibration Method
  • 批准号:
    1137625
  • 项目类别:
    Standard Grant
  • 资助金额:
    $4.85万
  • 财政年份:
    2011
  • 负责人:
    Jay Frankel
  • 依托单位:
海外基金