The city of Ust-Kamenogorsk, East Kazakhstan region, annually has a high risk of flooding and flooding of territories caused by spring snowmelt. These extreme phenomena are one of the most dangerous natural disasters, as they cause enormous socio-economic damage to the coastal settlements of the city. In the flood zone, agricultural and residential facilities, as well as engineering and technical infrastructure facilities are indicated. In some years, the funds allocated by the local buzhet to restore the damage caused by the disaster are not enough. One of the most effective means of stopping the consequences of such natural phenomena is an early warning system. Forecasting and modeling of hydrological phenomena can be provided using new IT technologies, some of which are Geoinformation technologies (GIS technologies) based on the cartographic method. In addition to modern advanced data processing methods in the GIS environment, the article presents a water collection design for emergency protection by calculating the main influencing factors of flooding and determining specific scales of flood levels in river valleys near settlements, determining the area of reservoirs collected at a risk control point at specific flood sites, as well as analyzing the detected ers material. The prospects for the use of GIS technologies as a means of forecasting and modeling floods caused by annual floods during the spring snowmelt period are also outlined, an analysis of the real situation is carried out, and a simple design of the shore for use in extreme conditions during periods of flooding is given.

The article discusses the engineering geological conditions for the cadastral assessment of urban lands, in value terms, the calculation of the area of distribution of hazardous substances in the atmosphere from industrial and other waste sources. The method of zoning territories by pollution level and a cartogram of distribution of hazardous substances in the atmosphere by allocated territories were provided. The following factors and their influence were studied in detail: spatial planning, zoning, cost of land development, engineering and transport infrastructure, physical properties of land, environmental conditions of air, water, soil, nature of construction, nature of the settlement, wind direction. The basis of obtained quantitative, qualitative data, determination in specific territories using geoinformation systems technology (GIS) was considered. The algorithm for assessing the state of atmospheric air in real time includes the integration of the obtained data and modeling the current state of the atmosphere. The study was conducted in the city of Ust-Kamenogorsk, where there are several industrial plants, such as Kazzinc, Ulba Metallurgical Plant (UMP), Titanium Magnesium Plant (TMP). The study results and the calculated coefficients for assessing the atmospheric pollution allow us to draw individual conclusions on the territory of a zoned city. The practical value of the work is providing an algorithm for assessing the state of atmospheric air in real time using the presented results, modeling the state of atmospheric air in each point of the city and qualitative assessment of regions for environmental friendliness in the cadastral system.

This study examines the modernization of the 61-4179 TVZ passenger coach for transporting light automobiles up to 3 tons, addressing the efficiency of multifunctional rail use. The objective was to assess how additional mass–dimensional loading influences strength, load distribution, and the dynamic stability of the vehicle–track system. Finite element simulations in ANSYS Workbench 2021 R2 determined stress distribution, deformations, and safety margins, while multibody dynamics modeling in Universal Mechanism evaluated wheel–rail contact forces, carbody accelerations, and stability coefficients. Field tests on curves with radii of 350 m and 300 m at 60 km/h validated the models. Carbody accelerations were 0.65–0.68 m/s², below the 0.7 m/s² regulatory limit; wheelset attack angles remained under 0.01 rad; and derailment safety coefficients were 1.6–1.8, all meeting international standards. Uniform load distribution maintained stability and suppressed oscillations. However, critical scenarios (wheel wear, extreme flange clearance, higher speeds) produced parameters approaching threshold values. To mitigate risks, clearance adjustment per δ₀ standards, a 1:20 guard-rail inclination, and optimized crossing profiles are proposed. These measures reduced lateral dynamic forces by 12–15% and raised the strength coefficient by 1.2–1.3. The results confirm technical feasibility, operational safety, and extended service life, supporting sustainable multimodal transport development.

The purpose of this study is to extend the service life of liquid-layer furnaces through experimental evaluation of their performance. Instead of using conventional large and small aggregates, this research investigates the use of secondary refractory materials to reduce the cost of the concrete mixture. To address this problem, it was proposed to replace the traditional method of lining the furnace floor with SHB-brand fireclay bricks by a monolithic concrete structure. Considering the operational characteristics of the furnace - high temperatures up to 1000 °C and an aggressive environment producing SO₃ gaseous sulfur -sodium-infused liquid glass concrete was selected as the base. Instead of cement, liquid glass with low thermal conductivity, including amorphous-phase materials and glass-layered composite viscous substances, is recommended. A novel aspect of this research is the integration of machine learning techniques with experimental data to predict the thermal performance of concrete under high-temperature conditions. Furthermore, the study introduces the use of secondary refractory materials as a cost-effective aggregate alternative, offering a unique combination of sustainability and performance in industrial furnace applications.

This study provides an assessment of the process of sand landslide degradation of the Abay Region of the Republic of Kazakhstan and space materials (RS-Remote Sensing, GIS-Geographic Information Systems and machine learning data of the soilgrid platform, QGIS Trends). Using the technology of the Earth module and field research, the amount of landslide sand g/kg at a depth of 5 cm was determined and the SDG land degradation target, the land productivity indicator (productivity), the indicator of the impact assessment of the change in the type of surface cover (land cover), the indicator of the change in the carbon stock of soil organic matter (carbon velocity) were calculated in the machine learning module, which uses integrated research to monitor, map and quantify the threat of land degradation. The study was analyzed and obtained between 2015 and 2022 by interpreting data from machine learning images with visual, interactive interpretation. The data of dynamic reverse changes from Sandy and worn areas, in these two stages, were obtained by overlapping the database. The results of the study showed that in the proportion of years obtained, 3009.29 km2 of newly degraded land was formed, and most of the newly degraded land is the area where sand landslides occur, as is known from the quantitative data of the study, it was found that the share of sand landslide degradation of the surveyed 272 410.4 km2 area within 7 years is 4.56 % of the total area. By analyzing the results of the study, some constructive measures were proposed aimed at ecological protection of forest clusters in the North-West of Abay Region and planting new forest seedlings.

This paper investigates the thermal performance and early-age strength development of concrete cured using embedded electric heating wires (SHWPI – steel heating wire with polyethylene insulation) under winter conditions. A full-scale monolithic reinforced concrete slab was divided into four thermal zones for real-time monitoring using temperature sensors and ultrasonic testing over a 72-hour period. Experimental results were compared with thermal simulations conducted using the ELCUT software (WinConcrete module). The central zone reached a peak temperature of 35.6°C and achieved over 60% of the design strength within 48 hours, while edge zones attained only 52–56%. Actual temperature values were on average 12% lower than predicted, and strength deviations ranged from 8% to 13%. Based on this discrepancy, a correction factor of 0.08–0.13 is proposed to improve strength forecasting accuracy. The study highlights the critical role of temperature uniformity during the curing phase and demonstrates the value of integrating numerical modeling with real-time field monitoring. The findings are particularly relevant for optimizing electric curing strategies in cold climates, especially in regions with severe winters such as East Kazakhstan.