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.

a b s t r a c tAs forecasted by the International Energy Agency Energy Technology Perspectives baseline scenario, the largest increment in LDV (light-duty vehicles) stock, travel demand and transport sector energy consumption will take place in the developing world. In the developing countries where the import of used vehicles is allowed, a considerable portion of the LDV stock increment will be realized with used vehicles.In this paper, the analytical framework for assessment of climate change mitigation potential of transport sector in developing countries is adapted in order to incorporate the expected vehicle fleet increase with used vehicles. The evaluation of appropriate mitigation strategies is performed using the GHG Costing Model (GACMO), which compares each mitigation option with the BAU (business-as-usual) option and determines its environmental effectiveness (t CO 2 reduced) and economic effectiveness (US$/ t CO 2 reduced).The adapted analytical framework is applied on the case of transport sector of Macedonia, evaluating appropriate options inline with five mitigation strategies: improvement of vehicle fleet, introduction of low carbon fuels, improvement of travel behaviour, advancement of vehicle equipment and improvement of driver behaviour. The resulting marginal cost curve for the year 2020 indicates a total achievable reduction of 22% with respect to BAU GHG transport sector emissions, with bulk of it at relatively high specific costs of around 90 US$/t CO 2 .

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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.