This paper deals with the application of inverse concepts to the drying of bodies that undergo changes in their dimensions. Simultaneous estimation is performed of moisture diffusivity, together with the thermal conductivity, heat capacity, density, and phase conversion factor of a drying body, as well as the heat and mass transfer coefficients and the relative humidity of drying air. This was accomplished by using only temperature measurements. A mathematical model of the drying process of shrinking bodies has been developed where the moisture content and temperature fields in the drying body are expressed by a system of two coupled partial differential equations. The shrinkage effect was incorporated through the experimentally obtained changes of the specific volume of the drying body in an experimental convective dryer. The proposed method was applied to the process of drying potatoes. For the estimation of the unknown parameters, the transient readings of a single temperature sensor located in the midplane of the potato slice, exposed to convective drying, have been used. The Levenberg–Marquardt method and a hybrid optimization method of minimization of the least-squares norm are used to solve the present parameter estimation problem. Analyses of the sensitivity coefficients and of the determinant of the information matrix are presented as well.
This paper deals with the application of inverse approaches to estimation of drying body parameters. Simultaneous estimation of the thermo physical properties of a drying body as well as the heat and mass transfer coefficients, by using only temperature measurements, is analyzed. A mathematical model of the drying process has been developed, where the moisture content and temperature fields in the drying body are expressed by a system of two coupled partial differential equations. For the estimation of the unknown parameters, the transient readings of a single temperature sensor located in an infinite flat plate, exposed to convective drying, have been used. The Levenberg-Marquardt method and a hybrid optimization method of minimization of the least-squares norm are used to solve the present parameter estimation problem. An analysis of the influence of the drying air velocity, drying air temperature, drying body dimension, and drying time on the thermophysical properties estimation, that enables the design of the proper experiments by using the so-called D-optimum criterion was conducted. In order to perform this analysis, the sensitivity coefficients and the sensitivity matrix determinant were calculated for the characteristic drying regimes and the drying body dimensions.
In this article, the conjugate gradient method with adjoint problem is applied for the identification of the heat and mass transfer coefficients at the surface of drying capillary-porous bodies. The unknown functions are supposed to vary in time and along the surface open to the surrounding environment. The inverse problem is solved by considering either the heat or the mass transfer coefficients as unknown, as well as by considering simultaneously both functions as unknown. The effects of temperature and moisture content measurements on the inverse analysis are examined. A comparison of different versions of the conjugate gradient method is also presented as applied to the inverse problem under study.
The inverse problem of using temperature measurements to estimate the moisture content and temperature-dependent moisture diffusivity together with the heat and mass transfer coefficients is analyzed in this paper. In the convective drying practice, usually the mass transfer Biot number is very high and the heat transfer Biot number is very small. This leads to a very small temperature sensitivity coefficient with respect to the mass transfer coefficient when compared to the temperature sensitivity coefficient with respect to the heat transfer coefficient. Under these conditions the relative error of the estimated mass transfer coefficient is high. To overcome this problem, in this paper the mass transfer coefficient is related to the heat transfer coefficient through the analogy between the heat and mass transfer processes in the boundary layer. The resulting parameter estimation problem is then solved by using a hybrid constrained optimization algorithm OPTRAN.
This paper deals with the estimation of the moisture diffusivity, together with other thermophysical properties, as well as the heat and mass transfer coefficients of a convective drying body, on the basis of single thermocouple temperature measurements by using an inverse approach. Potato and apple slices have been chosen as representative drying bodies with significant shrinkage effects. A mathematical model of the drying process of shrinking bodies has been applied. The Levenberg-Marquardt method and a hybrid optimization method of minimization of a resulting least-squares norm were used to solve the present inverse problem. The experiments have been conducted on the experimental setup that is designed to simulate an industrial convective dryer. An analysis of the influence of the drying air speed, temperature and relative humidity, drying body dimensions, and drying time on the estimation of the unknown parameters enables the design of appropriate experiments that have been conducted as well. The estimated moisture diffusivities are compared with the results published by other authors. The experimental transient temperature and moisture content changes during the drying are compared with numerical solutions.
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