The present study compares the behavior of different sound types and their sources concerning distance. Experimental findings demonstrate a consistent reduction in noise levels with increasing distance from the sound origin, aligning with anticipated sound propagation patterns. Median noise level reductions are quantified, showing decreases from 72.7 dB at the source to 54.8 dB at a distance of 3 m. Pulsed sounds exhibit pronounced fluctuations and peaks at close distances, while steady and blended sounds maintain more uniform levels. An exponential model accurately characterizes the noise reduction phenomenon (R² = 0.8664), underscoring its applicability for construction noise control. These results offer valuable insights into sound propagation dynamics and provide a basis for developing effective noise control strategies.

Hidden waterlogging of subsurface soils may develop without clear external signs, while still deteriorating the hydro-physical state of foundation soils. This proof-of-concept study demonstrates a compact monitoring and interpretation workflow for identifying such zones through moisture profiling and subsequent engineering interpretation using the liquidity index (${\mathrm{I}}_{\mathrm{L}}$) for cohesive soils and the saturation ratio (${\mathrm{S}}_{\mathrm{r}}$) for non-cohesive soils. The developed prototype comprises a modular immersion probe, Arduino-based transmitter and receiver units, 433 MHz ASK wireless communication, and data logging. Using geotechnical survey data from a representative site in Astana, a baseline hydro-physical state and an intentionally constructed synthetic risk-waterlogging scenario were analyzed through vertical profiles and horizontal interpolation maps. Under the baseline state, moisture content varied mainly from about 6 to 23%, while most ${\mathrm{I}}_{\mathrm{L}}$ and ${\mathrm{S}}_{\mathrm{r}}$ values remained within the normal zone. In the synthetic scenario, the response was much stronger in cohesive soils, where ${\mathrm{I}}_{\mathrm{L}}$ increased from about −0.55 to 1.8, whereas ${\mathrm{S}}_{\mathrm{r}}$ in non-cohesive soils changed only slightly. The Welch’s t-test indicated significant scenario-related changes for ${\mathrm{I}}_{\mathrm{L}}$ (p-value of 1.095 × 10⁻¹⁹) but not for ${\mathrm{S}}_{\mathrm{r}}$ (p-value of 0.147). The results show the methodological potential of the proposed workflow for engineeringly interpretable zoning of hidden waterlogging; however, site-specific calibration, metrological characterization, and field validation are still required before practical deployment.

This study examined the physical-mechanical properties of steel fiber reinforced concrete with different fiber orientations and vibration times. The concrete mixtures contained crushed stone, sand, Portland cement, Rheobuild 181A plasticizer, and 5 cm steel fibers with 2% reinforcement. Using steel fibers from worn ropes from Innotech LLP (Almaty, Kazakhstan) increased the average strength of concrete and improved its ductility, allowing for plastic failure instead of brittle failure. Joint mixing of steel fiber-reinforced concrete with randomly oriented fibers made from used cables increased the mean value of flexural strength. The concrete mixtures with a vibration time of 9 seconds showed the highest flexural strength, which was 2.1 times higher than that of concrete samples without fiber. These findings demonstrate the potential of steel fiber reinforcement to improve the mechanical properties of concrete, especially in applications requiring flexural strength.

Waterlogging, a consequence of rising groundwater levels exacerbated by climate change and urbanization, poses a mounting challenge. This review provides an in-depth exploration of contemporary waterlogging risk management strategies, spotlighting the pivotal role of geographic information systems (GIS) and associated technologies. The introduction underscores the problem's gravity, citing its intricate nature and adverse effects on urban settings. The article covers diverse risk mitigation approaches like vertical and horizontal drainage, automated monitoring, and artificial surface elevation. The focal point is on GIS's transformative impact, delving into recent research demonstrating its efficacy in hazard mapping, exposure assessment, vulnerability analysis, and crafting risk management plans. Noteworthy is the use of Landsat 8-9 and Sentinel 1 satellite imagery for monitoring and modeling waterlogging effects. Conclusions stress the integration of multi-criteria analysis and GIS for precise risk mapping. The article advocates for innovative techniques like three-dimensional visualization in GIS and enhanced forecasting methods. It underscores the importance of technological advancements for bolstering urban resilience against waterlogging in various scenarios. Future directions involve refining forecasting techniques in a changing climate, integrating artificial intelligence and machine learning for more accurate predictions, and leveraging 3D visualization in GIS for detailed representations. The piece also highlights the potential of IoT-based automated monitoring systems in providing real-time information for proactive responses to potential waterlogging threats.