Zora Jančíková

The Study of Electrical Transport in Rubber Blends Filled by Single Wall Carbon Nanotubes

The paper deals with the electrical and mechanical properties of rubber blends filled by single wall carbon nanotubes (SWCNT-0,6 weight %). We have investigated the alternating current resistivity (ACR), real and imaginary part of dielectric constant,and loss factor .The addition of (SWCNT) to a rubber blend decreases ACR and increases constants ,and loss factor .

Advanced Fillers Enhancing Thermal and Mechanical Properties of Rubber Blends

In the paper we present measurements of transport physical parameters such as thermal conductivity, diffusivity and specific heat capacity and dc electrical conductivity as well as the mechanical values E*, tg δ for rubber compounds filled by different ratio of silica - carbon black fillers. From presented results it is possible to see that proper filler concentration (rubber blend - silica - carbon black) rising all thermal parameters as well as mechanical properties represented by complex Young’s modulus and so, maintains the good mechanical parameters of the blend and finally it also lowers the electrical resistance. All trends are favourable for the improvement of useful rubber blends properties.

On Experimental Thermal Analysis of Solid Materials

Abstract The paper is devoted to the presentation of a method for measurement of thermal conductivity k, specific heat capacity cp, and thermal diffusivity applying the lumped capacitance model (LCM) as a special case of Newton’s model of cooling. At the specific experimental conditions resulting from the theoretical analysis of the used model, we present a method for experimental determination of all three above mentioned thermal parameters for materials with different thermal transport properties. The input experimental data provide a cooling curve of the tested material. The evaluation of experimental data is realized by software, the fundamental features of which are presented here. The statistical analysis of experimental data was performed.

Artificial Neural Networks Application in Modal Analysis of Tires

Abstract The paper deals with the application of artificial neural networks (ANN) to tires’ own frequency (OF) prediction depending on a tire construction. Experimental data of OF were obtained by electronic speckle pattern interferometry (ESPI). A very good conformity of both experimental and predicted data sets is presented here. The presented ANN method applied to ESPI experimental data can effectively help designers to optimize dimensions of tires from the point of view of their noise.

Weibull distribution application on temperature dependence of polyurethane storage modulus

Abstract In this paper, a stiffness–temperature model based on Weibull statistics was applied to quantitatively describe changes in the storage modulus of thermoplastic polyurethane over a wide range of temperature. The variation of the storage modulus with temperature was obtained from dynamic mechanical analysis tests across transition temperatures. Both the physical and statistical parameters of the applied model were estimated in the process of parametric fitting of the model to the storage modulus versus a temperature curve by using a trust region algorithm for a robust nonlinear least squares method. Good agreement between the modeled and experimental data has been found over the entire investigated temperature range, including all observed relaxation transitions.

Artificial Neural Networks Prediction of Rubber Mechanical Properties in Aged and Nonaged State

Artificial neural networks (ANN) have been used for characterization of rubber blend mixtures ageing and for prediction of mechanical properties according to chemical composition. Strength Rm and modulus M100 have been evaluated. The ANN application was tested by statistical function RMSE (root mean square error) and R2 (coefficient of determination) which value for all predictions was higher than 0.93.

Methane Diffusion in a Porous Environment

The paper deals with modeling and simulation of methane flow through the porous environment using the CFD (Computational Fluid Dynamics) software Fluent. We compare three situations, which can occur in areas, where mining activities were closed few years ago, in this article. First case is modeling of methane flow through the rocks. Second event is situation where the thin water layer is situated at the surface. The last one is occurrence of groundwater. The article responds to the need for knowledge of natural processes in the given area and it follows our previous papers [1], [2]. Software Gambit was used for creating a geometric model of the working area, for modeling the flow of gas it was used CFD software, Fluent from ANSYS, Inc..

Artificial Neural Network Modelling of Glass Laminate Sample Shape Influence on the ESPI Modes

The present work is devoted to the applications of artificial neural networks (ANN) for material design prediction. We have investigated the dependence of the generated mode frequency as a function of a sample thickness and a sample shape of glass laminate samples by electronic speckle interferometry (ESPI). The obtained experimental results for differently shaped (thickness, canting and rounding) glass laminate samples are compared with those of ANN. The coincidence of both experimental and simulated results is very good.

The Influence of Rubber Blend Aging and Sample Homogeneity on Heat Transport Phenomena

This paper is devoted to the study of thermal transport phenomena changes caused by natural aging of rubber blends. Thermal conductivity, diffusivity and heat capacity of rubber blends were measured and compared for the same samples before and after half of a year. Samples were stored at room temperature and daily light. In the frame of our investigations there has been observed the decrease of the thermal diffusivity as well as the thermal conductivity in the interval approximately 40-50 %. The changes of specific heat capacity after sample aging were negligible. The explanation of such behaviour we can see in the sample structure degradation caused by the environmental influence.

Chosen Electrical Properties of Montmorillonite/Polyaniline Composites

The paper deals with the electrical properties of Montmorillonite (MMT)/Polyaniline (PANI) composites. These materials show specific electrical properties as relatively high anisotropic electrical conductivity, pressure dependent electrical resistance with relatively high hysteresis. Metallographic analyse as well as the Vickers micro-hardness dsof sample surfaces is presented. All these properties predetermine this material as an interesting piezoresistor.