I.K. Beisembetov, T.T. Bekibayev, U.K. Zhapbasbayev, B.K. Kenzhaliyev, H. Retnawati, G.I. Ramazanova
The Astrakhan-Mangyshlak main water pipeline is important for water supply to the population and industrial enterprises of the Atyrau and Mangyshlak regions. Digitalization of the water pipeline is carried out to create a database of the SmartTranWater software package. The database is created to model and optimize the water supply system and determine energy-saving modes of operation of pumping units and volumes of water transportation. The database consists of digital profiles of working sections of the main water pipeline, identification of parameters of the linear part of sections, and creation of digital objects at the water pipeline stations. Regression analysis of the machine learning method was used to identify the initial data. The following initial data were updated: profiles of sections, location of water pumping stations in the main water pipeline, characteristics of pumps, hydraulic parameters of pipelines, nodes of sections, water withdrawals, and looping of pipelines. For each section, a linear pipeline part was built with the introduction of pipe elevations depending on the kilometrage. All pipeline nodes were taken as three object types: section nodes, withdrawal nodes, and pipe-looping nodes. Pumping units in stations are stored as a station-related objects, which are linked by rotor type and electric motor type. For each operating pumping unit, depending on the pumping mode and the pumped water, the values of the created heads and power consumption were determined. © 2023, National Academy of Sciences of the Republic of Kazakhstan. All rights reserved.
Satbayev University, Almaty, Kazakhstan; Institute of Metallurgy and Ore Beneficiation, Almaty, Kazakhstan; Universitas Negeri Yogyakarta (Yogyakarta State University), Yogyakarta, Indonesia
