Applying the Random Forest Method to Improve Burner Efficiency
Fuel power plants are one of the main sources of pollutant emissions, so special attention should be paid to improving the efficiency of the fuel combustion process. The mathematical modeling of processes in the combustion chamber makes it possible to reliably predict and find the best dynamic chara...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/12/2143 |
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| author | Vladislav Kovalnogov Ruslan Fedorov Vladimir Klyachkin Dmitry Generalov Yulia Kuvayskova Sergey Busygin |
| author_facet | Vladislav Kovalnogov Ruslan Fedorov Vladimir Klyachkin Dmitry Generalov Yulia Kuvayskova Sergey Busygin |
| author_sort | Vladislav Kovalnogov |
| collection | DOAJ |
| description | Fuel power plants are one of the main sources of pollutant emissions, so special attention should be paid to improving the efficiency of the fuel combustion process. The mathematical modeling of processes in the combustion chamber makes it possible to reliably predict and find the best dynamic characteristics of the operation of a power plant, in order to quantify the emission of harmful substances, as well as the environmental and technical and economic efficiency of various regime control actions and measures, and the use of new types of composite fuels. The main purpose of this article is to illustrate how machine learning methods can play an important role in modeling and predicting the performance and control of the combustion process. The paper proposes a mathematical model of an unsteady turbulent combustion process, presents a model of a combustion chamber with a combined burner, and performs a numerical study using the STAR-CCM+ multidisciplinary platform. The influence of various input indicators on the efficiency of burner devices, which is evaluated by several parameters at the output, is investigated. In this case, three possible states of the burners are assumed: optimal, satisfactory and unsatisfactory. |
| first_indexed | 2024-03-09T23:07:47Z |
| format | Article |
| id | doaj.art-5e3061cbb32f4c5bb154718516ea0459 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T23:07:47Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-5e3061cbb32f4c5bb154718516ea04592023-11-23T17:50:23ZengMDPI AGMathematics2227-73902022-06-011012214310.3390/math10122143Applying the Random Forest Method to Improve Burner EfficiencyVladislav Kovalnogov0Ruslan Fedorov1Vladimir Klyachkin2Dmitry Generalov3Yulia Kuvayskova4Sergey Busygin5Laboratory of Inter-Disciplinary Problems in Clean Energy Production, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, RussiaLaboratory of Inter-Disciplinary Problems in Clean Energy Production, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, RussiaLaboratory of Inter-Disciplinary Problems in Clean Energy Production, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, RussiaLaboratory of Inter-Disciplinary Problems in Clean Energy Production, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, RussiaLaboratory of Inter-Disciplinary Problems in Clean Energy Production, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, RussiaLaboratory of Inter-Disciplinary Problems in Clean Energy Production, Ulyanovsk State Technical University, 32 Severny Venetz Street, 432027 Ulyanovsk, RussiaFuel power plants are one of the main sources of pollutant emissions, so special attention should be paid to improving the efficiency of the fuel combustion process. The mathematical modeling of processes in the combustion chamber makes it possible to reliably predict and find the best dynamic characteristics of the operation of a power plant, in order to quantify the emission of harmful substances, as well as the environmental and technical and economic efficiency of various regime control actions and measures, and the use of new types of composite fuels. The main purpose of this article is to illustrate how machine learning methods can play an important role in modeling and predicting the performance and control of the combustion process. The paper proposes a mathematical model of an unsteady turbulent combustion process, presents a model of a combustion chamber with a combined burner, and performs a numerical study using the STAR-CCM+ multidisciplinary platform. The influence of various input indicators on the efficiency of burner devices, which is evaluated by several parameters at the output, is investigated. In this case, three possible states of the burners are assumed: optimal, satisfactory and unsatisfactory.https://www.mdpi.com/2227-7390/10/12/2143mathematical modelingcombustionemissioncombustion chambersburnersmulticlass classification |
| spellingShingle | Vladislav Kovalnogov Ruslan Fedorov Vladimir Klyachkin Dmitry Generalov Yulia Kuvayskova Sergey Busygin Applying the Random Forest Method to Improve Burner Efficiency Mathematics mathematical modeling combustion emission combustion chambers burners multiclass classification |
| title | Applying the Random Forest Method to Improve Burner Efficiency |
| title_full | Applying the Random Forest Method to Improve Burner Efficiency |
| title_fullStr | Applying the Random Forest Method to Improve Burner Efficiency |
| title_full_unstemmed | Applying the Random Forest Method to Improve Burner Efficiency |
| title_short | Applying the Random Forest Method to Improve Burner Efficiency |
| title_sort | applying the random forest method to improve burner efficiency |
| topic | mathematical modeling combustion emission combustion chambers burners multiclass classification |
| url | https://www.mdpi.com/2227-7390/10/12/2143 |
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