2023
DOI: 10.3390/w15122289
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Modeling of Distributed Control System for Network of Mineral Water Wells

Abstract: The article is devoted to solving the problem of designing a distributed control system for a network of production wells on the example of mineral water deposits in the Caucasus Mineral Waters region, Russia. The purpose was to determine the set of parameters of the control system to ensure technologically effective and safe operating modes of mineral water deposits. A mathematical model of the deposit was developed taking into account the given configuration and production rate of the network of the wells. T… Show more

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Cited by 51 publications
(28 citation statements)
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References 42 publications
(46 reference statements)
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“…One of the additional risks arising from the production of aluminum is the risk of pollution of water resources, including deep-seated pollution. The modeling of such risks, as well as the movement of aquifers, can be found in [54].…”
Section: Discussionmentioning
confidence: 99%
“…One of the additional risks arising from the production of aluminum is the risk of pollution of water resources, including deep-seated pollution. The modeling of such risks, as well as the movement of aquifers, can be found in [54].…”
Section: Discussionmentioning
confidence: 99%
“…and made a detailed description of the process of electrolysis occurring in the cell. However, this mathematical model has a number of disadvantages associated with a rather large discretization of the model 14 . In order to increase the accuracy of calculations of electromagnetic fields of electrolyzers, Chinese scientists 15 propose to use a genetic neural network.…”
Section: Methodsmentioning
confidence: 99%
“…and made a detailed description of the process of electrolysis occurring in the cell. However, this mathematical model has a number of disadvantages associated with a rather large discretization of the model [37]. In order to increase the accuracy of calculations of electromagnetic fields of electrolyzers, Chinese scientists [11] propose to use a genetic neural network.…”
Section: The State Of Knowledge Of the Problemmentioning
confidence: 99%