Oladokun, Olagoke and Nyakuma, B. and Luing, W. S. and Oladimeji, E. and Abatan, Olubunmi G. and Ayeni, .A. O. and Agboola, Oluranti and Ayoola, A. A. and Ojewunmi, M. O. and Efeovbokhan, Vincent Enon and Olagoke-Oladokun, L. and Odunlami, O. A. (2022) Gasific: A Python Tool for Biomass Gasification Process. In: Advanced Manufacturing in Biological, Petroleum, and Nanotechnology Processing. Springer Cham, pp. 335-353. ISBN ISBN978-3-030-95819-0 Online ISBN978-3-030-95820-6
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Abstract
Biomass gasification and the production of syngas are important in the production of biohydrogen, a green fuel and an energy carrier for the fuel cell. The tool for the prediction of biohydrogen production from any biomass should be readily available to determine the viability of such biomass for gasification. The software implementing a robust gasification model is complex, proprietary, and expensive. In order to solve this problem, we developed Gasific, a software module for simple, free, and accurate biomass gasification product gas prediction. Gasific, implemented biomass gasification, stoichiometric equilibrium models, in Python and runs on a variety of platforms. We discussed the application of Gasific on biomass wastes, namely, Imperata cylindrica; the simulation shows good performance in predicting the gas composition product of gasification. The developed software and the code can be modified and applied to other scientific models and transform the models into software applications.
| Item Type: | Book Section |
|---|---|
| Subjects: | T Technology > TP Chemical technology |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
| Depositing User: | Patricia Nwokealisi |
| Date Deposited: | 27 Feb 2025 16:05 |
| Last Modified: | 27 Feb 2025 16:05 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/18843 |
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