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The finite difference approximation is applied to estimate the moisture-dependent diffusion coefficient by utilizing test data of isothermal moisture desorption in northern red oak (Quercus rubra). The test data contain moisture distributions at discrete locations across the thickness of specimens, which coincides with the radial direction of northern red oak, and at various stages of drying. The results show that both the effective diffusion coefficient and the finite difference method closely follow the trends of diffusion equation. Due to its simplicity, the proposed finite difference approximation can be applied to estimate moisture-dependent diffusion coefficient from non-reproducible test data, and thereby may be generalized to accommodate more involved diffusion models.Copyright © 2013 Elsevier B.V. All rights reserved.

This project focuses on the identification of underground fuel level in a basement using wireless PIR (passive infrared) sensor networks. An automatic algorithm based on the depth contour map of the buried objects is implemented to locate the underground fuel level. In the whole operation process, the real-time monitoring data is recorded and analyzed during the excitation, and the detecting data are archived after the sensor decay. This project is the first attempt to apply infrared detector in to PRT (Passive... d2c66b5586