Gilmar Guimaraes

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

Thermal properties estimation of polymers using only one Active Surface

This work describes an experimental technique for obtaining, simultaneously, the thermal diffusivity and thermal conductivity of polymer materials. This technique uses experimental data from only one of the sample surfaces. It means functions using experimental and calculated temperature are defined. An objective function representing the eigenvalue phase angle is used to determine thermal diffusivity, while a least square error function is used for the thermal conductivity estimation. The sequential unconstrained optimization technique BFGS is used to calculate the search direction. In each case the golden section method is used in a one-dimensional search, followed by a polynomial approximation. A comparison with the flash method and the guarded hot plate method gives a deviation of 2.97 % and 0.63 % for thermal diffusivity and thermal conductivity, respectively, for a Polychloroethylene (PVC) sample. An uncertainty analysis is also presented.

A correlation function for thermal properties estimation applied to a large thickness sample with a single surface sensor

This article describes an experimental technique to measure simultaneously the thermal diffusivity and thermal conductivity of nonmetallic materials. The method is applied to a large thickness sample and uses a single temperature sensor located at the heating surface of a perspex sample. In addition the golden section optimization technique is used with parameter estimation for minimizing two different objective functions. Each of the thermal properties is estimated in a different way. The diffusivity estimation uses a correlation function estimator between heat flux and temperature while a square function error of experimental and estimated temperatures is the objective function used for determining the conductivity. A comparison with the guarded hot plate method indicates a deviation of 2.1% of the thermal conductivity. An error analysis for both properties is also presented.

Dynamic observers based on Green's functions applied to 3D inverse thermal models

This work develops a new procedure for the use of dynamic observers in inverse heat conduction problem (IHCP). The dynamic observer state technique, used here, is developed to solve not only a one-dimensional but also a three-dimensional heat transfer problem. The IHCP is represented by a classical inverse definition, that is, an unknown heat flux heat is imposed at a front surface of a sample. The heat flux is then estimated by using the dynamic observer techniques and temperature data from a sensor located at the sample far from the heat source. The novelty is the new procedure to obtain the heat transfer function of the system. In this work, this function is derived using Greens function concept instead of taking Laplace transform of a spatially discretized system, as is usual. This procedure allows a great flexibility to the observer technique and represents an easy way to solve multidimensional heat conduction problem. Tests have shown excellent results.

Analyses of Effects of Cutting Parameters on Cutting Edge Temperature Using Inverse Heat Conduction Technique

During machining energy is transformed into heat due to plastic deformation of the workpiece surface and friction between tool and workpiece. High temperatures are generated in the region of the cutting edge, which have a very important influence on wear rate of the cutting tool and on tool life. This work proposes the estimation of heat flux at the chip-tool interface using inverse techniques. Factors which influence the temperature distribution at the AISI M32C high speed steel tool rake face during machining of a ABNT 12L14 steel workpiece were also investigated. The temperature distribution was predicted using finite volume elements. A transient 3D numerical code using irregular and nonstaggered mesh was developed to solve the nonlinear heat diffusion equation. To validate the software, experimental tests were made. The inverse problem was solved using the function specification method. Heat fluxes at the tool-workpiece interface were estimated using inverse problems techniques and experimental temperatures. Tests were performed to study the effect of cutting parameters on cutting edge temperature. The results were compared with those of the tool-work thermocouple technique and a fair agreement was obtained.

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.

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.

Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts

The use of fiber reinforced materials such as randomly-oriented strands has grown in recent years, especially for manufacturing of aerospace composite structures. This growth is mainly due to their advantageous properties: they are lighter and more resistant to corrosion when compared to metals and are more easily shaped than continuous fiber composites. The resistance and stiffness of these materials are directly related to their fiber orientation. Thus, efficient approaches to assess their fiber orientation are in demand. In this paper, a non-destructive evaluation method is applied to assess the fiber orientation on laminates reinforced with randomly-oriented strands. More specifically, a method called pulsed thermal ellipsometry combined with an artificial neural network, a machine learning technique, is used in order to estimate the fiber orientation on the surface of inspected parts. Results showed that the method can be potentially used to inspect large areas with good accuracy and speed.

INFLUENCE OF TOOL HOLDER MATERIAL ON INTERFACIAL, INSERT AND TOOL HOLDER TEMPERATURES DURING TURNING OPERATION OF GRAY IRON

Usually studies related to machining temperature consider a system comprised of workpiece, chip and cutting tool, the effect of tool holder material is not taken in account. However, due to its physical properties, the tool holder material, usually carbon steel, has effect in the dissipation of the heat generated. This work studies the effect of the tool holder material on the temperature distribution during the turning operation of gray iron using cemented carbide cutting tool and without cutting fluid. Five tool holders were manufactured from materials with different heat conductivity: carbon steel, stainless steel, titanium, copper and bronze. Temperatures in eight different positions in the tool holder and cutting insert were measured. The average temperature at the chip tool interface was also measured using the tool-work thermocouple method. The results showed that the measured chip tool interface temperature was less affected by the tool holder material, although the temperature distribution at the cutting tool is highly affected.Copyright

Thermographic Computational Analyses of a 3D Model of a Scanned Breast

Breast cancer is the most common type of cancer among women. Cancer cells are characterized by having a higher metabolic activity and superior vascularization when compared to healthy cells. The internal heat generated by tumors travels to the skin surface where an infrared camera is capable of detecting small temperatures variations on the dermal surface. Breast cancer diagnosis using only thermal images is still not accepted by the medical community which makes necessary another exam to confirm the disease. This work presents a methodology which allows identification of breast cancer using only simulated thermal images. Experiments are performed in a three-dimensional breast geometry obtained with a 3D digital scanning. The procedure starts with the 3D scanning of a model of a real female breast using a “Picza LPX-600RE 3D Laser Scanner” to generate the breast virtual geometry. This virtual 3D model is then used to simulate the heat transfer phenomena using Finite Element Model (FEM). The simulated thermal images of the breast surface are obtained via the FEM model. Based on the temperature difference of a healthy breast and a breast with cancer it is possible to identify the presence of a tumor by analyzing the biggest thermal amplitudes. Results obtained with the FEM model indicate that it is possible to identify breast cancer using only infrared images.