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
项目编号:CTS 9903346首席研究员:M. Gharib该奖项与奖项9901732一起,用于支持对管库周围流动和传热的研究。管组的湍流传热在很大程度上取决于所采用的特定几何结构,并且在很大程度上受管组可能遭受的流激振动的影响。特别是,最近使用的高强度材料产生了更细长的结构,更容易受到振动。现有的预测传热和流动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时间相关系数。在这项工作中,提出了一个模型,展示了一些复杂的湍流传热在柔性圆柱阵列,但在一个简化的设置。来自实验和直接数值模拟研究的证据表明,尽管它们很复杂,但这种类型的耦合系统表现出低维性,并且可以使用由近似惯性流形理论驱动的动力系统技术有效地建模,该技术使用基于分层模式的非线性伽辽金模型,该模型使用“快照方法”从数值和实验数据库中提取。这些模型除了整体力系数和努塞尔数外,还提供了速度场和温度场的详细时空描述。实验和数值数据库将利用DPIV/T测量和动态光谱模拟获得Peclet数的一个代表性值。更具体地说,这笔续期拨款的目标是双重的:首先,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的时间和空间分辨率更高。其次,构建简化的动态模型,保留整个系统的时空复杂性,并准确预测感兴趣的平均和波动量。
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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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: