Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator
The commercial COCO simulation program was used to mimic the experimental slow pyrolysis process of five different biomasses based on thermodynamic consideration. The program generated the optimum set of reaction kinetic parameters and reaction stoichiometric numbers that best described the experime...
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sg-ntu-dr.10356-1438112020-09-26T21:58:10Z Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator Tangsathitkulchai, Chaiyot Punsuwan, Natthaya Weerachanchai, Piyarat Nanyang Environment and Water Research Institute Science::General Biomass Pyrolysis Cassava Pulp Residue The commercial COCO simulation program was used to mimic the experimental slow pyrolysis process of five different biomasses based on thermodynamic consideration. The program generated the optimum set of reaction kinetic parameters and reaction stoichiometric numbers that best described the experimental yields of solid, liquid and gas products. It was found that the simulation scheme could predict the product yields over the temperature range from 300 to 800 °C with reasonable accuracy of less than 10% average error. An attempt was made to generalize the biomass pyrolysis behavior by dividing the five biomasses into two groups based on the single-peak and two-peak characteristics of the DTG (derivative thermogravimetry) curves. It was found that this approximate approach was able to predict the product yields reasonably well. The proposed simulation method was extended to the analysis of slow pyrolysis results derived from previous investigations. The results obtained showed that the prediction errors of product yields were relatively large, being 12.3%, 10.6%, and 27.5% for the solid, liquid, and gas products, respectively, possibly caused by differing pyrolysis conditions from those used in the simulation. The prediction of gas product compositions by the simulation program was reasonably satisfactory, but was less accurate for predicting the compositions of liquid products analyzed in forms of hydrocarbons, aromatics and oxygenated fractions. In addition, information on the kinetics of thermal decomposition of biomass in terms of the variation of fractional conversion with time was also derived as a function of temperature and biomass type. Published version The financial support of this work was provided by The Research and Development Fund, Suranaree University of Technology, and is gratefully acknowledged. 2020-09-24T08:38:43Z 2020-09-24T08:38:43Z 2019 Journal Article Tangsathitkulchai, C., Punsuwan, N., & Weerachanchai, P. (2019). Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator. Processes, 7(11), 775-. doi:10.3390/pr7110775 2227-9717 https://hdl.handle.net/10356/143811 10.3390/pr7110775 11 7 en Processes © 2019 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/). application/pdf |
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Science::General Biomass Pyrolysis Cassava Pulp Residue Tangsathitkulchai, Chaiyot Punsuwan, Natthaya Weerachanchai, Piyarat Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator |
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The commercial COCO simulation program was used to mimic the experimental slow pyrolysis process of five different biomasses based on thermodynamic consideration. The program generated the optimum set of reaction kinetic parameters and reaction stoichiometric numbers that best described the experimental yields of solid, liquid and gas products. It was found that the simulation scheme could predict the product yields over the temperature range from 300 to 800 °C with reasonable accuracy of less than 10% average error. An attempt was made to generalize the biomass pyrolysis behavior by dividing the five biomasses into two groups based on the single-peak and two-peak characteristics of the DTG (derivative thermogravimetry) curves. It was found that this approximate approach was able to predict the product yields reasonably well. The proposed simulation method was extended to the analysis of slow pyrolysis results derived from previous investigations. The results obtained showed that the prediction errors of product yields were relatively large, being 12.3%, 10.6%, and 27.5% for the solid, liquid, and gas products, respectively, possibly caused by differing pyrolysis conditions from those used in the simulation. The prediction of gas product compositions by the simulation program was reasonably satisfactory, but was less accurate for predicting the compositions of liquid products analyzed in forms of hydrocarbons, aromatics and oxygenated fractions. In addition, information on the kinetics of thermal decomposition of biomass in terms of the variation of fractional conversion with time was also derived as a function of temperature and biomass type. |
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Nanyang Environment and Water Research Institute |
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Nanyang Environment and Water Research Institute Tangsathitkulchai, Chaiyot Punsuwan, Natthaya Weerachanchai, Piyarat |
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Article |
author |
Tangsathitkulchai, Chaiyot Punsuwan, Natthaya Weerachanchai, Piyarat |
author_sort |
Tangsathitkulchai, Chaiyot |
title |
Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator |
title_short |
Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator |
title_full |
Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator |
title_fullStr |
Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator |
title_full_unstemmed |
Simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram COCO simulator |
title_sort |
simulation of batch slow pyrolysis of biomass materials using the process-flow-diagram coco simulator |
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2020 |
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https://hdl.handle.net/10356/143811 |
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1681056455701037056 |