IoT-based Mine Ventilation Control System Architecture with Digital Twin

Кычкин, А. В.; Nikolaev, A.V.

doi:10.1109/icieam48468.2020.9111995

Cited by 18 publications

(9 citation statements)

References 20 publications

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“…Makarov et al [50] introduce a three step modelling process for a manufacturing system digital twin: the development of SysML (Systems Modeling Language) diagrams, using AnyLogic as a tool for simulation modeling, and communicating with actual systems through the MES (Manufacturing Execution System). In a recent paper by Kychkin et al [51], a method for digital twin implementation based on estimation of simulation model parameters and calculation of control signals for a dynamic ventilation system of underground mines was discussed. By considering the dynamics of air distribution and changes in environmental parameters, the proposed algorithms can improve safety and energy saving in mines, in which the ventilation process consumes from 30 to 50 percent of all company electricity.…”

Section: Digital Twins For Brownfield Process Plantsmentioning

confidence: 99%

Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant

et al. 2020

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Researchers have proposed various models for assessing design alternatives for process plant retrofits. Due to the considerable engineering effort involved, no such models exist for the great majority of brownfield process plants, which have been in operation for years or decades. This article proposes a semi-automatic methodology for generating a digital twin of a brownfield plant. The methodology consists of: (1) extracting information from piping and instrumentation diagrams, (2) converting the information to a graph format, (3) applying graph algorithms to preprocess the graph, (4) generating a simulation model from the graph, (5) performing manual expert editing of the generated model, (6) configuring the calculations done by simulation model elements and (7) parameterizing the simulation model according to recent process measurements in order to obtain a digital twin. Since previous work exists for steps (1–2), this article focuses on defining the methodology for (3–5) and demonstrating it on a laboratory process. A discussion is provided for (6–7). The result of the case study was that only few manual edits needed to be made to the automatically generated simulation model. The paper is concluded with an assessment of open issues and topics of further research for this 7-step methodology.

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Section: Digital Twins For Brownfield Process Plantsmentioning

confidence: 99%

Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant

et al. 2020

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“…On the application side, Python is a universal programming language with a steadily growing community in science, which is well suited to automate processes and connect applications with each other. [8,4,5,10]. In this paper, a Python package is presented, which allows a seamless integration of the SIMULTAN data model into Python.…”

Section: Introductionmentioning

confidence: 99%

Digital Twin applications using the SIMULTAN data model and Python

Bühler

Steiner

Bednar

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Python is an open, general-purpose programming language that is used in many tools, libraries and APIs for Building Performance Simulations (BPS). Advantages of Python in the context of digital twins are the simple and powerful capabilities to generate input files, automate processes, import libraries in many languages and a large number of useful modules. However, in order to use BPS tools and libraries with real time data, a comprehensive data model is required in which all necessary data such as geometry, system engineering, databases, sensors, or simulation parameters for the different BPS are defined. Python in combination with SIMULTAN as a suitable open Building Information Modelling (BIM) data model allows an effective use of these tools and libraries to perform and automate analyses. This paper presents a Python module that integrates the SIMULTAN model in Python and enables almost seamless integration with minor adaptations to existing tools or modules. The import is achieved using simple text-based templates for the data types and their mapping in the data model. The data model, the definition of the data types and the use of this module is demonstrated by calculating the trend of the CO2 concentration in a zone of a digital twin using real time data.

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“…The volume of the incoming airflow is constantly changing, the capacity of the MMF is exceeded by 5-15% [6,7]. Considering that up to one half of the total electricity consumption at an underground mining working is spent on ventilation [8], such a method for air supply is highly energy demanding.…”

Section: Introductionmentioning

confidence: 99%

Season-oriented mine ventilation modes analysis

Nikolaev¹,

Lyalkina²,

Kychkin³

et al. 2021

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The paper presents the results of the data analysis conducted at Bereznyaki Mine-2 of Uralkali in summer and winter (during the air pre-treatment period). The findings show that when mine air heaters are operating thermal drop of ventilation pressure appears in air supply shafts. It causes "airlocks" in the shafts -a phenomenon that nearly stops the airflow in one of the shafts while increasing dramatically the airflow in the other (others) air intake shafts. As a result, mine air heaters in the shafts may stop running which provokes freezing of the mine shaft shoring.The analysis of mine ventilation modes performed in summer and winter determined the factors affecting the occurrence of "airlocks" in the air supply shafts during air pre-treatment.

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IoT-based Mine Ventilation Control System Architecture with Digital Twin

Cited by 18 publications

References 20 publications

Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant

Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant

Digital Twin applications using the SIMULTAN data model and Python

Season-oriented mine ventilation modes analysis

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