Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass
The prediction of phase transformation of biomass ashes is challenging due to the highly variable composition of these fuels as well as the complex processes accompanying phase transformations. The AFT (Ash Fusion Temperature) model was performed in Statistica 13.1 software. This model was divided i...
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| Format: | Article |
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MDPI AG
2020-12-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/24/6543 |
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| author | Joanna Wnorowska Waldemar Gądek Sylwester Kalisz |
| author_facet | Joanna Wnorowska Waldemar Gądek Sylwester Kalisz |
| author_sort | Joanna Wnorowska |
| collection | DOAJ |
| description | The prediction of phase transformation of biomass ashes is challenging due to the highly variable composition of these fuels as well as the complex processes accompanying phase transformations. The AFT (Ash Fusion Temperature) model was performed in Statistica 13.1 software. This model was divided into three separate submodels, which were designed to predict the characteristic ash melting temperatures for raw and modified biomass. It is based on the chemical composition of fuel and ash as obtained using ash analysis standards. For the discussed models, several coefficients describing multiple regression parameters are presented. The AFT model discussed in this article is suitable for predicting ash fusion temperatures for biomass and allows for the prediction of the temperature with an average error of <±70.05 °C for IDT; <±51.98 °C for HT; <±47.52 °C for FT for raw biomass. For some of the additionally tested biomass, a value higher than the average difference between the measured temperature and the designated model was observed (<90 °C). Moreover, morphological analyses of the structure SEM-EDS for ash samples with and without additive were performed. |
| first_indexed | 2024-03-10T14:08:36Z |
| format | Article |
| id | doaj.art-304c4166c5ff44a88407983fe6d498aa |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T14:08:36Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-304c4166c5ff44a88407983fe6d498aa2023-11-21T00:22:56ZengMDPI AGEnergies1996-10732020-12-011324654310.3390/en13246543Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped BiomassJoanna Wnorowska0Waldemar Gądek1Sylwester Kalisz2Department of Power Engineering and Turbomachinery, Faculty of Energy and Environmental Engineering, Silesian University of Technology, 44-100 Gliwice, PolandDepartment of Power Engineering and Turbomachinery, Faculty of Energy and Environmental Engineering, Silesian University of Technology, 44-100 Gliwice, PolandDepartment of Power Engineering and Turbomachinery, Faculty of Energy and Environmental Engineering, Silesian University of Technology, 44-100 Gliwice, PolandThe prediction of phase transformation of biomass ashes is challenging due to the highly variable composition of these fuels as well as the complex processes accompanying phase transformations. The AFT (Ash Fusion Temperature) model was performed in Statistica 13.1 software. This model was divided into three separate submodels, which were designed to predict the characteristic ash melting temperatures for raw and modified biomass. It is based on the chemical composition of fuel and ash as obtained using ash analysis standards. For the discussed models, several coefficients describing multiple regression parameters are presented. The AFT model discussed in this article is suitable for predicting ash fusion temperatures for biomass and allows for the prediction of the temperature with an average error of <±70.05 °C for IDT; <±51.98 °C for HT; <±47.52 °C for FT for raw biomass. For some of the additionally tested biomass, a value higher than the average difference between the measured temperature and the designated model was observed (<90 °C). Moreover, morphological analyses of the structure SEM-EDS for ash samples with and without additive were performed.https://www.mdpi.com/1996-1073/13/24/6543ash fusion temperature (AFT)biomass combustionfuel additivesAFT statistic modelprediction of ash temperature |
| spellingShingle | Joanna Wnorowska Waldemar Gądek Sylwester Kalisz Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass Energies ash fusion temperature (AFT) biomass combustion fuel additives AFT statistic model prediction of ash temperature |
| title | Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass |
| title_full | Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass |
| title_fullStr | Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass |
| title_full_unstemmed | Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass |
| title_short | Statistical Model for Prediction of Ash Fusion Temperatures from Additive Doped Biomass |
| title_sort | statistical model for prediction of ash fusion temperatures from additive doped biomass |
| topic | ash fusion temperature (AFT) biomass combustion fuel additives AFT statistic model prediction of ash temperature |
| url | https://www.mdpi.com/1996-1073/13/24/6543 |
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