Karim Khodier
University of Leoben
12 Papers
6 Citations
Karim Khodier is an academic researcher from University of Leoben. The author has contributed to research in topics: Municipal solid waste & Waste treatment. The author has an hindex of 6, co-authored 12 publications. Previous affiliations of Karim Khodier include Hong Kong Environmental Protection Department.
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Papers
Digitalisation and intelligent robotics in value chain of circular economy oriented waste management - A review
TL;DR: Systems and methods that could be used in waste treatment plants or machines in the future in order to make treatment of waste more efficient, as well as technologies that have already been successfully applied in other industrial sectors and will be relevant in the waste management sector for the future are presented.
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Real time material flow monitoring in mechanical waste processing and the relevance of fluctuations.
TL;DR: Results from the authors' own practical analyses using sensor-based technologies for monitoring material flows, an on-site investigation in a large waste treatment plant and also in a pilot-scale plant using mixed commercial waste from Austria show that the quantitative monitoring of volume and mass flow and material composition is possible.
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Sampling and analysis of coarsely shredded mixed commercial waste. Part I: procedure, particle size and sorting analysis
Karim Khodier,Sandra Antonia Viczek,Alexander Curtis,Alexia Aldrian,Paul O'Leary,Markus Lehner,Renato Sarc +6 more
TL;DR: In this paper, a sampling procedure for coarsely shredded mixed commercial waste, based on the Austrian Standard ONORM S 2127, the horizontal sampling standard DS 3077 and the theory of sampling, was established, described and examined through a replication experiment determining the relative sampling variability.
Influence of pre-screening on down-stream processing for the production of plastic enriched fractions for recycling from mixed commercial and municipal waste.
TL;DR: Results demonstrate not only that the screening of both waste streams leads to enrichment of plastics in coarse particle size ranges and transfer of contaminants, organics and minerals to fine fractions, but also that sensor-based sorting performance can be significantly enhanced due to cleaning effects on plastics.
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Sensor-based Particle Size Determination of Shredded Mixed Commercial Waste based on two-dimensional Images.
TL;DR: A model in MATLAB® is presented which extracts information about several geometric descriptors from 2D images of individual particles taken by RGB cameras of pre-shredded, solid, mixed commercial waste and processes this data in a multivariate regression model using the Partial Least Squares Regression (PLSR) to predict the particle size class of each particle according to a drum screen.
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