The Implementation of Neural Networks for Polymer Mold Surface Evaluation.

This paper presents the measurement and evaluation of the surfaces of molds produced using additive technologies. This is an emerging trend in mold production. The surfaces of such molds must be treated, usually using laser-based alternative machining methods. Regular evaluation is necessary because of the gradually deteriorating quality of the mold surface. However, owing to the difficulty in scanning the original surface of the injection mold, it is necessary to perform surface replication. Therefore, this study aims to describe the production of surface replicas for in-house developed polymer molds together with the determination of suitable descriptive parameters, the method of comparing variances, and the mean values for the surface evaluation. Overall, this study presents a new summary of the evaluation process of replicas of the surfaces of polymer molds. The nonlinear regression methodology provides the corresponding functional dependencies between the relevant parameters. The statistical significance of a neural network with two hidden layers based on the principle of Rosenblatt's perceptron has been proposed and verified. Additionally, machine learning was utilized to better compare the original surface and its replica.

Study into the Fire and Explosion Characteristics of Polymer Powders Used in Engineering Production Technologies.

Polymers and their processing by engineering production technologies (injection, molding or additive manufacturing) are increasingly being used. Polymers used in engineering production technologies are constantly being developed and their properties are being improved. Granulometry, X-ray, FTIR and TGA were used to characterize polymer samples. Determination of the fire parameters of powder samples of polyamide (PA) 12, polypropylene, and ultra-high molecular weight (UHMW) polyethylene is the subject of the current article. An explosive atmosphere can be created by the powder form of these polymer materials, and introduction of preventive safeguards to ensure safety is required for their use. Although the fire parameters of these basic types of polymers are available in databases (e.g., GESTIS-DustEx), our results showed that one of the samples used (polypropylene) was not flammable and thus is safe for use in terms of explosiveness. Two samples were flammable and explosive. The lower explosive limit was 30 g·m-3 (PA12) and 60 g·m-3 (UHMW polyethylene). The maximum explosion pressure of the samples was 6.47 (UHMW polyethylene) and 6.76 bar (PA12). The explosion constant, Kst, of the samples was 116.6 bar·m·s-1 (PA12) and 97.1 bar·m·s-1 (UHMW polyethylene). Therefore, when using polymers in production technologies, it is necessary to know their fire parameters, and to design effective explosion prevention (e.g., ventilation, explosive-proof material, etc.) measures for flammable and explosive polymers.

Solving the Issue of Discriminant Roughness of Heterogeneous Surfaces Using Elements of Artificial Intelligence.

This work deals with investigative methods used for evaluation of the surface quality of selected metallic materials' cutting plane that was created by CO2 and fiber laser machining. The surface quality expressed by Rz and Ra roughness parameters is examined depending on the sample material and the machining technology. The next part deals with the use of neural networks in the evaluation of measured data. In the last part, the measured data were statistically evaluated. Based on the conclusions of this analysis, the possibilities of using neural networks to determine the material of a given sample while knowing the roughness parameters were evaluated. The main goal of the presented paper is to demonstrate a solution capable of finding characteristic roughness values for heterogeneous surfaces. These surfaces are common in scientific as well as technical practice, and measuring their quality is challenging. This difficulty lies mainly in the fact that it is not possible to express their quality by a single statistical parameter. Thus, this paper's main aim is to demonstrate solutions using the cluster analysis methods and the hidden layer, solving the problem of discriminant and dividing the heterogeneous surface into individual zones that have characteristic parameters.

Study of Carbon Black Types in SBR Rubber: Mechanical and Vibration Damping Properties.

Styrene-butadiene rubber mixtures with four types of carbon black were studied in this paper. The mechanical properties, including the ability to damp mechanical vibration, were investigated, along with dynamical mechanical analysis (DMA). It has been found that carbon black types N 110 and N 330, having the largest specific surface area and the smallest particle diameter, provide a good stiffening effect. These particles have significant interactions between the rubber, resulting in good reinforcement. On the other hand, the carbon black N 990 type has a lower reinforcing effect and improved vibration damping properties at higher excitation frequencies due to higher dissipation of mechanical energy into heat under dynamic loading. The effect of the number of loading cycles on vibration damping properties of the rubber composites was also investigated in this study. It can be concluded that the abovementioned properties of the investigated rubber composites correspond to physical-mechanical properties of the applied carbon black types.

Biocompatible Polymer Materials with Antimicrobial Properties for Preparation of Stents.

Biodegradable polymers are promising materials for use in medical applications such as stents. Their properties are comparable to commercially available resistant metal and polymeric stents, which have several major problems, such as stent migration and stent clogging due to microbial biofilm. Consequently, conventional stents have to be removed operatively from the patient's body, which presents a number of complications and can also endanger the patient's life. Biodegradable stents disintegrate into basic substances that decompose in the human body, and no surgery is required. This review focuses on the specific use of stents in the human body, the problems of microbial biofilm, and possibilities of preventing microbial growth by modifying polymers with antimicrobial agents.

Structure Analysis of Montmorillonite Intercalated with Cetylpyridinium and Cetyltrimethylammonium: Molecular Simulations and XRD Analysis.

Molecular mechanics and molecular dynamics simulations combined with X-ray powder diffraction were used in structure investigation of montmorillonite intercalated with cetylpyridinium (CP) and cethyltrimethylammonium (CTA) cations. Molecular modeling revealed the interlayer structure and differences in intercalation behavior of CP and CTA cations in montmorillonite. The experimental and calculated values of basal spacing were in good agreement for both intercalates: in the case of CP-montmorillonite d(exp)=20.59 Å, d(calc)=20.60 Å; for CTA-montmorillonite d(exp)=18.00 Å and d(calc)=18.10 Å. CTA-montmorillonite exhibits significantly higher total sublimation energy and higher host-guest interaction energy than the CP-montmorillonite. The main difference between both intercalates is in charge distribution on the host layers and guest species. The charge transfer from the guest species to the host layer is higher in CTA-montmorillonite than in CP-montmorillonite, and consequently the charge polarization between the host and guest layers is much higher in CTA-montmorillonite. This leads to much stronger host-guest electrostatic interaction in the case of CTA-montmorillonite. Copyright 2001 Academic Press.