Application of the Luikov’s Model in the Moisture Content Measurement of Solid Materials by the Drying Method
Based on the weighing of samples before and after drying, the drying in oven method is widely used to measure the moisture content in solid materials. Time and temperature are some of the most important conditions for the application of this method, which frequently are unknown and must be determine...
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Published in: | International journal of thermophysics Vol. 40; no. 1; pp. 1 - 12 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
New York
Springer US
2019
Springer Nature B.V |
Subjects: | |
Online Access: | Get full text |
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Summary: | Based on the weighing of samples before and after drying, the drying in oven method is widely used to measure the moisture content in solid materials. Time and temperature are some of the most important conditions for the application of this method, which frequently are unknown and must be determined experimentally or by another method. However, it is known that experimental processes are time-consuming and require excessive amounts of energy. A less expensive and faster option is the use of mathematical models to describe the heat and moisture transfer in the drying process, where several models apply. The Luikov’s model is one of the most accepted of them since it has a wide application in the calculation of drying curves of solid materials. This model consists in a coupled system of nonlinear partial differential equations which is derived from thermodynamics principles of irreversible processes, laws of energy and mass conservation and also the diffusion of heat and mass law. The solution to the Luikov’s model for the one-dimensional case was obtained using a method proposed by Lui et al., applied to several solid materials. In this paper, the drying curves for red brick and wood are presented and compared with those obtained experimentally. Finally, the drying curves were used to determine the sample’s moisture content and the corresponding uncertainty was estimated as well. |
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ISSN: | 0195-928X 1572-9567 |
DOI: | 10.1007/s10765-018-2461-5 |