Low-Dimensional Models for Turbulent Heat Transfer in Flexible Cylinder Arrays
Low-Dimensional Models for Turbulent Heat Transfer in Flexible Cylinder Arrays
批准号:
9903346
负责人:
Morteza Gharib
金额:
$9.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1999
资助国家:
美国
项目状态:
已结题
起止时间:
1999-09-15 至 2001-05-31
中文摘要
摘要建议编号:CTS 9903346首席调查员:M.Gharib本奖项与奖项9901732一起,是为了支持对管束周围的流动和热传递的调查。来自管束的湍流换热强烈地依赖于所采用的特定几何构型,并且在很大程度上受管子可能受到的流动诱发振动的影响。特别是,最近高强度材料的使用产生了更多细长的结构,更容易受到振动的影响。现有的用于预测换热和流致振动的模型是半经验的,即使是最复杂的模型也严重依赖于难以测量的与时间相关的系数。在这项工作中,提出了一个模型,该模型显示了柔性圆柱体阵列中湍流换热的一些复杂性,但在简化的设置下。来自实验和直接数值模拟研究的证据表明,尽管这类耦合系统很复杂,但它们表现出低维,并且可以使用基于近似惯性流形理论的动力系统技术有效地建模,所用的非线性Galerkin模型是基于层次化模式的非线性Galerkin模型,该模型是从数值和实验数据库中提取的。这些模型,除了总力系数和Nusselt数之外,还提供了速度和温度场的详细时空描述。实验和数值数据库将使用DPIV/T测量和在以前的NSF拨款中开发的动态光谱模拟,以一个代表性的Peclet数获得。更具体地说,这笔续期赠款的目标有两个:第一,开发新的实验和模拟工具,使一般流动/热结构相互作用问题能够在时间和空间上获得高分辨率。第二,构造简化的动力学模型,保持完整系统的时空复杂性,并准确地预测感兴趣的平均和起伏的量。
英文摘要
ABSTRACT Proposal Number: CTS 9903346 Principal Investigator: M. Gharib This award, in conjunction with award 9901732, is to support an investigation into the flow around and the heat transfer from tube banks. Turbulent heat transfer from tube banks depends strongly on the specific geometric configuration employed, and is influenced substantially by the flow-induced vibrations that the tubes may be subject to. In particular, the recent use of high strength materials has produced more slender structures, which are more susceptible to vibration. Existing models for predicting heat transfer and flow-induced vibrations are semi-empirical and even the most sophisticated ones depend critically on time-dependent coefficients, which are difficult to measure. In this work a model is proposed that exhibit some of the complexity of turbulent heat transfer in flexible cylinder arrays but in a simplified setting. Evidence from experimental and direct numerical simulation studies has shown that despite their complexity this type of coupled systems exhibit low-dimensionality and can be modeled effectively using dynamical systems techniques motivated by the theory of approximate inertial manifolds using nonlinear Galerkin models based on hierarchical modes extracted from numerical and experimental data bases using the ``method of snapshots". These models, in addition to the overall force coefficients and Nusselt number, provide detailed spatio-temporal description of the velocity and temperature fields. The experimental and numerical data bases will be obtained at one representative value of Peclet number using DPIV/T measurements and dynamic spectral simulations developed in a previous NSF grant. More specifically, the objective of this renewal grant is two-fold: First, to develop new experimental and simulation tools that will enable high temporal and spatial resolution of general flow/heat-structure interaction problems. Second, to construct reduced dynamical models that retain the spatio-temporal complexity of the full systems and predict accurately the mean and fluctuating quantities of interest.
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依托单位:
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依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: