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Erschienen in: Clean Technologies and Environmental Policy 6/2018

24.05.2018 | Original Paper

Selection of biomass materials for bio-oil yield: a hybrid multi-criteria decision making approach

verfasst von: Petchimuthu Madhu, Chenniappan Nithiyesh Kumar, Loganathan Anojkumar, Murugesan Matheswaran

Erschienen in: Clean Technologies and Environmental Policy | Ausgabe 6/2018

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Abstract

Determination of the proper physiochemical properties of the biomass sample for pyrolysis process is an important task. Various types of biomass are able to act as fuel with diverse properties during pyrolysis inside the reactor. Systematic mathematical approach may achieve the evaluation to determine the performance of the feed. Multi-criteria decision making approach considers the characteristic properties and qualitative criteria to assign the importance to each alternative in order to select the most suitable biomass for maximum bio-oil yield. The aim of this paper is to describe this approach for choosing the best biomass type for maximum bio-oil yield during pyrolysis. Fuzzy analytic hierarchy process based on fuzzy sets and Technique for order of preference by similarity to ideal solution was the method used to choose the best alternative among the various sources of biomass. Five biomass samples such as rice straw, sunflower shell, hard wood, wheat straw, palm shell and seven evaluation criteria such as lignin, cellulose, hemicellulose, volatile matter, fixed carbon, moisture content and ash content were focused in this study to choose the suitable biomass. The results illustrated that hard wood appears as the best choice for a biomass fuel for maximum bio-oil yield.

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Metadaten
Titel
Selection of biomass materials for bio-oil yield: a hybrid multi-criteria decision making approach
verfasst von
Petchimuthu Madhu
Chenniappan Nithiyesh Kumar
Loganathan Anojkumar
Murugesan Matheswaran
Publikationsdatum
24.05.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Clean Technologies and Environmental Policy / Ausgabe 6/2018
Print ISSN: 1618-954X
Elektronische ISSN: 1618-9558
DOI
https://doi.org/10.1007/s10098-018-1545-z

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