Valério Luiz Borges

Identification of temperature-dependent thermal properties of solid materials

This work proposes an experimental technique for the simultaneous estimation of temperature-dependent thermal diffusivity, α, and thermal conductivity, λ, of insulation materials. The thermal model used considers a transient one-dimensional heat transfer problem. The determination of these properties is done by using the principle of the Mixed technique. In this technique two objective functions are defined, one in the frequency domain and the other in the time domain. The objective function in the frequency domain is based on the square difference between experimental and calculated values of the phase angle, while the other objective function is the least square error function of experimental and calculated signals of temperature. The properties α and λ are obtained by using an experimental apparatus that basically consists of a Polyvinyl Chloride (PVC) sample exposed to different temperatures inside an oven. The temperature inside the oven is controlled by a PID temperature controller. The properties α and λ were estimated for 7 (seven) points of average temperature in a range from 20 oC to 66 oC. The properties were determined with an additional heating of approximately 4.5 K on the frontal surface. Analyses of sensitivity, sensors location and sample dimensions were also made. Keywords : thermal properties estimation, heat conduction, optimization, experimental methods

Experimental determination of thermal conductivity and diffusivity using a partially heated surface method without heat flux transducer

This study presents a new experimental technique to obtain the thermal conductivity of conductor and non-conductor materials of small dimensions. As usual, the thermal conductivity estimation involves a thermal model with a known heat flux input. The main contribution of this study is the use of inverse techniques to estimate the heat flux input instead of measuring with heat transducers. It can be observed that the presence of transducers represents an additional experimental limitation for small samples. Besides the experimental difficulties, the smaller the transducer dimensions the more difficult it is to obtain the calibration curves due to the low sensitivity. The procedure proposed here is based on the following steps: (i) development of experimental apparatus and thermal model considering a heat flux input in part of the sample surface while the remaining surfaces are kept isolated; (ii) estimation of a dimensionless heat flux, Ф(t), proportional to the heat flux input using inverse techniques; (iii) estimation of thermal diffusivity; (iv) comparison between this heat flux, Ф(t), with the total heat flux supplied by the heating element P/S 1 to estimate the thermal conductivity of the sample.

Instrumentação térmica aplicada ao processo de produção de carvão vegetal em fornos de alvenaria

This work proposes the thermal analysis of rectangular brick kilns which has an individual capacity to produce 30 tons of charcoal for carbonization cycle. The objective of this work was to measure the temperature from thermocouples located in different sites in the kilns and to establish a relationship between temperature and charcoal production. In this sense, the thermal instrumentation predicted the installation of 22 PT100 thermocouples in each kiln. These sensors were connected to a mother boarder that emits the signal to a computer by an electronic circuit and a wireless net. The temperatures were stored in a supervisory system which presented the measured data in form of graphs and tables. Such information can be used to guide and to assist the carbonizing agent during the whole stages of the charcoal production. This measurement procedure with a statistical analysis represents an important tool to reduce the time of drying, pyrolysis and cooling. It can also minimize the losses and increase the thermal efficiency of the production process.

A dynamic thermal identification method applied to conductor and nonconductor materials

A method for determining simultaneously the thermal diffusivity, α, and the thermal conductivity, λ, of conductor and nonconductor materials is presented. The precise knowledge of these properties is especially important in heat transfer problems such as heat generation, cooling behavior in machining processes, or in developing of new materials. Additional difficulties can appear in the determination of α and λ of conductor materials. Problems of low sensitivity due to the small temperature gradient, heat loss in one-dimensional (1D) experiments, and thermal contact resistance can be cited. In this sense, a transient three-dimensional (3D) thermal model is developed. A minimization of an objective function based on the square difference between experimental and numerical phase angle in the frequency domain is used to determine α. Another objective function, a least square error function of measured and calculated temperatures, is used to obtain λ. One novelty of this technique is the use of a 3D thermal model that allows the optimizing of the experimental apparatus choosing optimal sensor locations. Three different materials are investigated in this work: a AISI304 stainless steel sample and two samples of polymers (polythene and polyvinyl chloride (PVC)). The estimation results for both conductor and nonconductor sample have shown good agreement with literature.

Computational and Mathematical Model with Phase Change and Metal Addition Applied to GMAW

This work presents a 3D computational/mathematical model to solve the heat diffusion equation with phase change, considering metal addition, complex geometry, and thermal properties varying with temperature. The finite volume method was used and the computational code was implemented in C

Dynamic Observer Method Based on Modified Green’s Functions for Robust and More Stable Inverse Algorithms

This work presents a modified procedure to use the concept of dynamic observers based on Green’s functions to solve inverse problems. The original method can be divided in two distinct steps: i) obtaining a transfer function model GH and; ii) obtaining heat transfer functions GQ and GN and building an identification algorithm. The transfer function model, GH , is obtained from the equivalent dynamic systems theory using Green’s functions. The modification presented here proposes two different improvements in the original technique: i) A different method of obtaining the transfer function model, GH , using analytical functions instead of numerical procedures, and ii) Definition of a new concept of GH to allow the use of more than one response temperature. Obtaining the heat transfer functions represents an important role in the observer method and is crucial to allow the technique to be directly applied to two or three-dimensional heat conduction problems. The idea of defining the new GH function is to improve the robustness and stability of the algorithm. A new dynamic equivalent system for the thermal model is then defined in order to allow the use of two or more temperature measurements. Heat transfer function, GH can be obtained numerically or analytically using Green’s function method. The great advantage of deriving GH analytically is to simplify the procedure and minimize the estimative errors.Copyright