3D reconstruction and design of porous media from thin sections

摘要

Characterization and design of fluid-thermal transport through random porous sintered beds is critical for improving the performance of two-phase heat transport devices such as heat pipes. Two-dimensional imaging techniques are quite well developed and commonly employed for microstructure and material characterization. In this study, we employ 2D image data (thin sections) for measuring critical micro-structural features of commercial wicks for use in correlation-based prediction of transport properties. We employ a stochastic characterization methodology based on the two-point autocorrelation function, and compare the predicted properties such as particle and pore diameters and permeability with those from our previously published studies, in which 3D X-ray microtomography data was employed for reconstruction. Further, we implement a reconstruction technique for reconstructing a three-dimensional stochastic equivalent structure from the thin sections. These reconstructed domains are employed for predicting effective thermal conductivity, permeability and interfacial heat transfer coefficient in single-phase flow. The current computations are found to compare well with models and correlations from the literature, as well as our previous numerical studies. Finally, we propose a new parametrized model for the design of porous materials based on the nature of the two-point autocorrelation functions. Using this model, we reconstruct sample three-dimensional microstructures, and analyze the influence of various parameters on fluid-thermal properties of interest. With advances in additive manufacturing techniques, such an approach may eventually be employed to design intricate porous structures with properties tailored to specific applications.