Insight into Theories of Heat and Mass Transfer at the Solid−Fluid Interface Using Direct Numerical Simulation and Large Eddy Simulation

• Published in: Industrial & engineering chemistry research 2007-12, Vol.46 (25), p.8525-8557
• Main Authors: Mathpati, C. S, Joshi, J. B
• Format: Article
• Language: English
• Subjects: Applied sciences; Chemical engineering; Exact sciences and technology; Heat and mass transfer. Packings, plates
• ISSN: 0888-5885; 1520-5045
• DOI: 10.1021/ie061633a

Solid−fluid heat-transfer coefficients have an important role in the design of chemical processing equipment. The major resistance to heat transfer lies in a region very close to the wall, where experimental measurements are very difficult. The validity and accuracy of the models developed for the estimation of the heat- and mass-transfer coefficient still do not have general applicability for the entire range of Reynolds and Prandtl numbers, because of the limited knowledge of near-wall turbulence. There have been two approaches for such model development:  one is an analytical approach, which considers the momentum, mass, and heat transfer to be analogous in nature and the understanding of one of these processes can be used to predict the other two; the other approach is heuristic, based on the visualization of the behavior of the coherent structures in the near-wall region. The continuous movement of fluid elements to and away from the wall (coherent structures) affects the transport phenomena. The models for the quantification of this behavior have been developed for the estimation of heat- and mass-transfer rates in the literature. However, both these approaches contain parameters fitted empirically to obtain good agreement with the experimental heat- and mass-transfer data. These models must be tested for their formulation and empirical constants on the basis of accurate solutions of governing equations of heat, mass, and momentum transfer. This is possible using direct numerical simulation (DNS) and large eddy simulation (LES), which can accurately predict the near-wall flow pattern. An attempt has been made to exploit the ability of DNS and LES to develop insight into hitherto used models, based on analogies and/or heuristic arguments.