S
Shahab Sokhansanj
Researcher at University of British Columbia
Publications - 369
Citations - 13055
Shahab Sokhansanj is an academic researcher from University of British Columbia. The author has contributed to research in topics: Pellets & Moisture. The author has an hindex of 54, co-authored 355 publications receiving 11677 citations. Previous affiliations of Shahab Sokhansanj include University of Saskatchewan & Oak Ridge National Laboratory.
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A Constrained K-Means and Nearest Neighbor Approach for Route Optimization in the Bale Collection Problem
TL;DR: A constrained k-means algorithm and nearest neighbor approach to the BCP, which minimizes travel time and hence fuel consumption and can be incorporated into precision agricultural systems to assist in the planning of routes for loaders and bale wagons.
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Simulation and optimization of energy systems for in-bin drying of canola grain (rapeseed)
TL;DR: In this article, the authors used a validated computer simulation model and typical weather data for a prairie location in North America to investigate the use of different energy systems, including natural gas, propane, electricity, solar energy, and combined natural gas and solar energy for in-bin drying of canola.
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In-depot upgrading the quality of fuel chips for a commercial gasification plant
Ehsan Oveisi,Shahab Sokhansanj,Anthony To-Ming Lau,C. Jim Lim,Xiaotao Bi,Mahmood Ebadian,Fernando Preto,Cliff Mui,Robby Gill +8 more
TL;DR: In this article, the sensitivity of steam production rate in a commercial updraft gasifier to several critical feedstock quality attributes like moisture, ash, and particles size was quantified.
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Control Strategies for Low Temperature In-bin Drying of Barley for Feed and Malt
TL;DR: In this paper, a computer simulation model was used to investigate low-temperature in-bin drying of barley grain for feed and malt under typical weather conditions in the Canadian prairies in North America.
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Optimization of sawmill residues collection for bioenergy production
TL;DR: A combination of scenario analysis and heuristics are used to solve this stochastic vehicle routing problem for a network composed of a single depot and several sawmills, revealing an estimated daily energy savings of 6 GJ over the benchmark method.