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Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions
Slow pyrolysis of biomass is commonly performed in rotary kilns. The effect of the particle residence time distribution on biomass conversion is often neglected when numerically modeling such systems. But this effect might be significant under certain conditions. The data presented here are results...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633881/ https://www.ncbi.nlm.nih.gov/pubmed/34877378 http://dx.doi.org/10.1016/j.dib.2021.107603 |
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author | Pichler, Mario Haddadi, Bahram Jordan, Christian Norouzi, Hamidreza Harasek, Michael |
author_facet | Pichler, Mario Haddadi, Bahram Jordan, Christian Norouzi, Hamidreza Harasek, Michael |
author_sort | Pichler, Mario |
collection | PubMed |
description | Slow pyrolysis of biomass is commonly performed in rotary kilns. The effect of the particle residence time distribution on biomass conversion is often neglected when numerically modeling such systems. But this effect might be significant under certain conditions. The data presented here are results of numerical simulation of the biomass pyrolysis in rotary kilns under numerous operating conditions and levels of axial dispersion of biomass particles. The varied operating conditions are the kiln diameter ([Formula: see text] –1 m), the ratio of particle to kiln diameter ([Formula: see text] – [Formula: see text]), the ratio of kiln length to kiln diameter ([Formula: see text] –10), the kiln’s inclination angle ([Formula: see text] –8 [Formula: see text]), the Froude number ([Formula: see text] – [Formula: see text]), the rotational Reynolds number ([Formula: see text] – [Formula: see text]), and the Péclet number ([Formula: see text] –100). Data of 13,851 single case simulations are provided with this article. This includes the mean particle residence time, gas, bed and kiln wall temperatures, solid and gaseous species mass flows, heat fluxes, and the solid bed height over the kiln length. These comprehensive data have the potential to help in modeling, design, analysis, and optimization of rotary kilns used for the pyrolysis of biomass. The main characterization and interpretation is presented in the related main research paper by Pichler et al. (2021)[1]. |
format | Online Article Text |
id | pubmed-8633881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-86338812021-12-06 Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions Pichler, Mario Haddadi, Bahram Jordan, Christian Norouzi, Hamidreza Harasek, Michael Data Brief Data Article Slow pyrolysis of biomass is commonly performed in rotary kilns. The effect of the particle residence time distribution on biomass conversion is often neglected when numerically modeling such systems. But this effect might be significant under certain conditions. The data presented here are results of numerical simulation of the biomass pyrolysis in rotary kilns under numerous operating conditions and levels of axial dispersion of biomass particles. The varied operating conditions are the kiln diameter ([Formula: see text] –1 m), the ratio of particle to kiln diameter ([Formula: see text] – [Formula: see text]), the ratio of kiln length to kiln diameter ([Formula: see text] –10), the kiln’s inclination angle ([Formula: see text] –8 [Formula: see text]), the Froude number ([Formula: see text] – [Formula: see text]), the rotational Reynolds number ([Formula: see text] – [Formula: see text]), and the Péclet number ([Formula: see text] –100). Data of 13,851 single case simulations are provided with this article. This includes the mean particle residence time, gas, bed and kiln wall temperatures, solid and gaseous species mass flows, heat fluxes, and the solid bed height over the kiln length. These comprehensive data have the potential to help in modeling, design, analysis, and optimization of rotary kilns used for the pyrolysis of biomass. The main characterization and interpretation is presented in the related main research paper by Pichler et al. (2021)[1]. Elsevier 2021-11-23 /pmc/articles/PMC8633881/ /pubmed/34877378 http://dx.doi.org/10.1016/j.dib.2021.107603 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Pichler, Mario Haddadi, Bahram Jordan, Christian Norouzi, Hamidreza Harasek, Michael Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
title | Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
title_full | Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
title_fullStr | Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
title_full_unstemmed | Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
title_short | Dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
title_sort | dataset for the simulated biomass pyrolysis in rotary kilns with varying particle residence time distributions |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633881/ https://www.ncbi.nlm.nih.gov/pubmed/34877378 http://dx.doi.org/10.1016/j.dib.2021.107603 |
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