In this study, a new generalized regression neural network model for predicting the curing characteristics of rubber blends with different contents of carbon black filler cured at various temperatures is proposed for the first time The carbon black contents in the rubber blend and cure temperature were used as input parameters, while the minimum and maximum elastic torque, scorch time, and optimal cure time, obtained from the analysis of 11 rheological cure curves registered at 10 various temperatures, were considered as output parameters of the model. A special pre-processing procedure of the experimental input and target data and the training algorithm is described. Less than 55% of the experimental data were used to significantly reduce the total number of input and target data points needed for training the model. Satisfactory agreement between the predicted and experimental data, with a maximum error in the prediction not exceeding 5%, was found. It is concluded that the generalized regression neural network is a powerful tool for intelligently modelling the curing process of rubber blends even in the case of a small dataset, and it can find a wide range of practical applications in the rubber industry.
The precise experimental estimation of mechanical properties of rubber blends can be a very costly and time-consuming process. The present work explores the possibilities of increasing its efficiency by using artificial neural networks to study the mechanical behavior of these widely used materials. A multilayer feed-forward back-propagation artificial neural network model, with a strain and the carbon black content as input parameters and stress as an output parameter, has been developed to predict the uniaxial tensile response of vulcanized natural rubber blends with different contents of carbon black in the form of engineering stress-strain curves. A novel procedure has been created for the simulation of the optimized artificial neural network model with input datasets generated by a regression model of an experimental dependence of tensile strain-at-break on the carbon black content in the investigated blends. Errors of the prediction of experimental stress-strain curves, as well as of tensile strain-at-break, tensile stress-at-break and M100 tensile modulus were estimated for all simulated stress-strain curves. The present study demonstrated that the performance of a developed neural network model to predict the stress-strain curves of rubber blends with different contents of carbon black is also exceptionally high in the case of a network that had never learned the input data, which makes it a suitable tool for extensive use in practice.
Irradiation by ionizing radiation is a specific type of controllable modification of the physical and chemical properties of a wide range of polymers, which is, in comparison to traditional chemical methods, rapid, non-polluting, simple, and relatively cheap. In the presented paper, the influence of high-energy ionizing radiation on the basic mechanical properties of the melamine resin, phenol-formaldehyde resin, and nitrile rubber blend has been studied for the first time. The mechanical properties of irradiated samples were compared to those of non-irradiated materials. It was found that radiation doses up to 150 kGy improved the mechanical properties of the tested materials in terms of a significant increase in stress at break, tensile strength, and tensile modulus at 40% strain, while decreasing the value of strain at break. At radiation doses above 150 kGy, the irradiated polymer blend is already degrading, and its tensile characteristics significantly deteriorate. An radiation dose of 150 kGy thus appears to be optimal from the viewpoint of achieving significant improvement, and the radiation treatment of the given polymeric blend by a beam of accelerated electrons is a very promising alternative to the traditional chemical mode of treatment which impacts the environment.
The presented paper deals with a study of selected rubber compounds as well as their vulcanizates with partially replaced commonly used filler by adding selected alternative fillers. Alternative fillers were mixed into rubber compounds as partial replacement of commonly used filler – carbon black. As an alternative partial replacement of common filler, we have chosen fine fractions of the waste of thermoplastics. The differences of rubber compounds were based on the amount of used alternative filler. We determined vulcanization characteristics of prepared tread compounds and physical and mechanical properties and dynamic mechanical properties of their vulcanizates. From the measured results it can be concluded that studied waste can be used in the function of filler into rubber, as partial replacement of commonly used filler.
The aim of given paper is to study selected polymers using dynamic mechanical analysis method (DMA). DMA is one of the most useful techniques for the study of the viscoelastic behaviour of thermoplastic polymers. In relation to DMA, an oscillatory stress and strain is applied to the material at specific frequencies and temperatures and based on this mentioned fact hereinbefore, the resulting changes after the loading in the material are measured. This technique allows detecting the melting temperature and the glass transition temperature of the thermoplastic materials. Furthermore, some spectroscopy techniques, such as energy dispersive X-ray spectroscopy (EDX) and infrared spectroscopy (IR), were also used for the investigation of the thermoplastics. The thermoplastics used for examination, namely polyethylene, polystyrene, polypropylene and polyethylene terephthalate, were gained from the waste of the packaging.
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