2025/04/08 by Ilgar Aliyev, Aliyev, Ilgar
Engineering · Materials Science · #49M20 #93A30 #93C95 #C.3 #FOS: Mathematics #G.1.6 #I.2.8 #Material Properties and Failure Mechanisms #Optimization and Control (math.OC) #Structural Integrity and Reliability Analysis #Water Systems and Optimization
paper · pdf · doi:10.48550/arxiv.2504.06420
openalex publication_date 2025/04/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The study explores technological schemes and control methods for reconstructing parallel gas pipeline systems under non-stationary conditions. It focuses on improving safety, reliability, and efficiency by automating valve control and integrating IoT-based monitoring. Automated shut-off valves are designed to detect sudden pressure drops and block leaks instantly. These valves utilize pressure drop rates and valve position sensors to detect and isolate leaks. Wireless pressure sensors and real-time monitoring systems enable remote control of gas flow. Mathematical modeling is employed to analyze pressure variations along damaged sections in order to determine optimal valve placement and activation timing. Machine learning algorithms in the control center are used to predict and verify leak locations based on sensor data. To ensure uninterrupted gas supply in the event of an accident, the study develops an empirical formula for determining the location of connecting pipes activated between parallel pipelines, based on real-time pressure data. The aim of this research is to reduce gas leaks and environmental hazards, ensure continuous gas supply during emergencies, enhance decision-making through automated systems, minimize gas losses, and reduce maintenance costs.