• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Øvrige samlinger
  • Publikasjoner fra CRIStin - NTNU
  • View Item
  •   Home
  • Øvrige samlinger
  • Publikasjoner fra CRIStin - NTNU
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Modeling and Simulation of a Waste Tire to Liquefied Synthetic Natural Gas (SNG) Plant

Rammohan Subramanian, Avinash Shankar; Kim, Donghoi; Adams, Thomas; Gundersen, Truls
Chapter
Published version
View/Open
Rammohan Subramanian (Locked)
URI
http://hdl.handle.net/11250/2637357
Date
2019
Metadata
Show full item record
Collections
  • Institutt for energi og prosessteknikk [2622]
  • Publikasjoner fra CRIStin - NTNU [19694]
Original version
10.1016/B978-0-12-818597-1.50063-1
Abstract
Thermochemical conversion of solid wastes through gasification offers the dual benefit of production of high-value fuels from the recovered energy and environmentally friendly waste disposal. Waste tires in particular may be a suitable feedstock for gasification as a result of their high energy content (LHV of ~ 34 MJ/kg, higher than coal), high volatile matter, and low ash content. Rotary kilns for steam gasification are a promising and technologically mature option to handle such difficult solid wastes that have a wider range of compositions, particle sizes, and moisture contents. In this paper, we propose a novel process for production of liquefied synthetic natural gas (SNG) and electricity from waste tires through the syngas route. We use experimental data available in the open literature to represent the complex steam gasification unit operation and use modeling and simulation techniques for the other units to evaluate the technological feasibility and thermodynamic performance of the proposed process. The process has an energy efficiency of 57.1%LHV and as such shows promise as an alternative for recovery of energy and material from waste. However, further technoeconomic and life cycle analyses are required prior to process optimization in order to improve performance.
Publisher
Elsevier

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit