Ternopil Ivan Pul'uj National Technical University

About: Ternopil Ivan Pul'uj National Technical University is a based out in . It is known for research contribution in the topics: Deformation (engineering) & Fracture toughness. The organization has 134 authors who have published 187 publications receiving 1019 citations.

Improvement of machine safety devices

Abstract: The article presents a development of new machine safety devices, which provide protection of operating elements from overload. Theoretical calculations have been made in order to determine the optimum design, kinematic and dynamic parameters of safety devices. A test bench has been developed and experimental investigations have been conducted in order to determine basic parameters of overload clutches.

Effect of Long Term Operation on Degradation of Material of Main Gas Pipelines

Abstract: The mechanisms of metal damage in the pipe of the main pipeline are investigated, the main reasons for their appearance are found and analysed. The main results are obtained by joint use of metallography, indentation, method for processing and analysis of digital images.

Investigation of thermophysical properties of epoxy nanocomposites

Abstract: The effect of nano-fillers (carbon carbon nanotubes) on thermophysical properties of epoxy composites is investigated. The curve showing the dependence between the heat resistance of epoxy composite and the content of nanoparticles demonstrates the optimal content of carbon carbon nanotubes, indicating the improved performance characteristics of the material with the above content of carbon carbon nanotubes. To analyze the processes of structure formation and the behavior of composites under the influence of a thermal field, the thermal coefficient of linear expansion of materials is investigated. It is established that the thermal linear expansion coefficient of materials increases with an increase in temperature within different temperature areas under study. Additionally, the thermogravimetric (TGA) and differential thermal (DTA) analysis of the materials were conducted for the investigation of nanocomposites under elevated temperatures. The maximum values of endothermic and exothermic effects ...

Investigation of the Rupture Surface of the Titanium Alloy Using Convolutional Neural Networks

Abstract: The research of fractographic images of metals is an important method that allows obtaining valuable information about the physical and mechanical properties of a metallic specimen, determining the causes of its fracture, and developing models for optimizing its properties. One of the main lines of research in this case is studying the characteristics of the dimples of viscous detachment, which are formed on the metal surface in the process of its fracture. This paper proposes a method for detecting dimples of viscous detachment on a fractographic image, which is based on using a convolutional neural network. Compared to classical image processing algorithms, the use of the neural network significantly reduces the number of parameters to be adjusted manually. In addition, when being trained, the neural network can reveal a lot more characteristic features that affect the quality of recognition in a positive way. This makes the method more versatile and accurate. We investigated 17 models of convolutional neural networks with different structures and selected the optimal variant in terms of accuracy and speed. The proposed neural network classifies image pixels into two categories: “dimple” and “edge”. A transition from a probabilistic result at the output of the neural network to an unambiguously clear classification is proposed. The results obtained using the neural network were compared to the results obtained using a previously developed algorithm based on a set of filters. It has been found that the results are very similar (more than 90% similarity), but the neural network reveals the necessary features more accurately than the previous method.