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Generalization of the Heat Transfer Coefficient Concept for System Simulation

机译:系统仿真中传热系数概念的推广

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Large progress has been realized in modeling conduction heat transfer problems over the past decade by the introduction of high performance compact thermal models (CTMs) mainly developed for thermal design of complicated electronic systems. The objective of this paper is to generalize these advances to convective heat transfer. A new convective CTM is proposed, which offers many advantages over the traditional approach using the heat transfer coefficient (HTC). The latter is simply a zeroth order CTM. The HTC is quite handy and simple, but with unpredictable errors. It can be suitable for hand calculations of simple systems giving rather crude estimates. For a higher precision, users have no other option than time consuming 3D simulations. For large systems, in terms of number of components, 3D simulations can be rapidly impractical. The CTM bridges the gap between both approaches going gradually from "HTC" levels (low precision and calculations time) at the zeroth order, to 3D simulation precision and computing time levels at large orders. Fortunately, like for conduction, a CTM of order of few tens quickly approaches 3D simulation precision levels, while keeping computation time significantly lower than 3D simulation. Moreover, the CTM approach solves conjugate heat transfer problems in a quite elegant way. A "black box" model, developed for fluid domain alone, can be easily combined with classical CTM conduction models to generate good precision predictions for any combination of fluid/solid domains.
机译:在过去的十年中,通过引入主要为复杂电子系统的热设计而开发的高性能紧凑型热模型(CTM),在对传导传热问题进行建模方面已经取得了巨大进展。本文的目的是概括对流传热的这些进展。提出了一种新的对流CTM,它比使用传热系数(HTC)的传统方法具有许多优势。后者只是一个零阶CTM。 HTC非常方便和简单,但存在不可预测的错误。它可能适用于简单系统的手工计算,从而给出粗略的估计。为了获得更高的精度,用户除了耗时的3D模拟外别无选择。对于大型系统,就组件数量而言,3D仿真可能不切实际。 CTM弥合了这两种方法之间的差距,这些方法逐渐从零阶的“ HTC”级别(低精度和计算时间)到大阶的3D模拟精度和计算时间级别。幸运的是,就像传导一样,几十个数量级的CTM可以迅速达到3D模拟精度水平,同时使计算时间大大低于3D模拟。此外,CTM方法以一种非常优雅的方式解决了共轭传热问题。单独为流体域开发的“黑匣子”模型可以轻松地与经典CTM传导模型组合,以对流体/固体域的任何组合生成良好的精度预测。

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