VOL 98, No. 3 (2025)

This work examines the main regularities in the formation of cement stone structure and the relationship between the properties of concrete mixes with various fillers and highly compressed materials obtained through the hyperpressing method. The objective of the study is to develop an efficient technology for producing construction materials using local, including non-standard raw materials and industrial waste, which is important both from an environmental and economic perspective. The experiment investigates the use of semi-dry pressing and hyperpressing to form concrete mixes with improved performance characteristics. It is assumed that during the pressing process, especially under hyperpressing conditions (pressures above 40 MPa), intensive interaction occurs between particles forming macroparticles, which contributes to a stronger cement stone structure. The involvement of Van der Waals forces and valence bonds between filler particles and hydrated clinker minerals, as well as molecular interactions, is considered the key mechanism for enhancing the strength and durability of the material. An important aspect is the use of low-plasticity clays, overburden rocks, and industrial waste, which significantly reduces production costs and improves environmental sustainability. The study also emphasizes that the hyperpressing technology helps reduce the technological cycle time, lowers specific energy consumption, and improves economic efficiency, making this technology promising for the production of environmentally friendly construction materials. The work contributes to the development of new methods for using secondary and local materials in construction, opening up new opportunities for improving the efficiency and sustainability of construction materials production.

The article presents the successful project of the BDTR-500 robot, designed for diagnosing cracks in pipes with a silicate-enameled coating. Key achievements of the system include the use of GPS navigation and positioning methods that ensure precise location determination and rapid identification of emergency zones. New algorithms based on artificial intelligence and machine learning facilitate autonomous robot movement and high-quality data processing. High-megapixel cameras with a smart lighting system allow for effective visualization of defects, while the intelligent energy management system increases the operational time in autonomous mode. Real-time data processing ensures rapid localization and elimination of damages, while built-in sensors enhance image stability on uneven surfaces. The robot can detect cracks as small as 0.1 meters. The project results confirm the high efficiency of the BDTR-500 in diagnostics, opening new opportunities for the application of technologies in monitoring the condition of pipelines and in other challenging operating environments.