search query: @supervisor Järvinen, Mika / total: 28
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| Author: | Saqlain, Muhammad |
| Title: | Process modeling of supercritical water gasification equipment based on pure water for design of continuous feeding system |
| Publication type: | Master's thesis |
| Publication year: | 2015 |
| Pages: | [13] + 107 Language: eng |
| Department/School: | Kemian tekniikan korkeakoulu |
| Main subject: | Biorefineries (KM3005) |
| Supervisor: | Järvinen, Mika |
| Instructor: | de Blasio, Cataldo ; Magdeldin Abdelwahed, Mohamed |
| Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201509184378 |
| Location: | P1 Ark Aalto 3066 | Archive |
| Keywords: | supercritical water gasification process modeling supercritical water SCWG system Åbo Akademi |
| Abstract (eng): | Supercritical water gasification has great potential to address important problems associated with wet biomass handling and provides a mean for high conversion of biomass to fuel gases such as hydrogen and methane. However, the process is limited to lab scale due to the challenges related to demand for heat and power at high process conditions, complicated process kinetics, salt corrosion and plugging, and wet biomass feed handling. In order to address these issues, better understanding of the continuous process dynamics is required within the supercritical water medium. This research focuses on understanding and modelling a pure water based supercritical water gasification system available at Åbo Akademi University in Turku, Finland. This research studies a system response in semi-batch configuration with water as the only process medium. The results from the process model have shown to fit well with the experimental results and the model findings and conclusions will be used in the design of a continuous feed system. The study has also identified several potential areas of improvement in the current system. The process model developed will form the basis to understand the process kinetics at the given equipment for a real biomass feed. |
| ED: | 2015-09-27 |
INSSI record number: 52095
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