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CC BY-NC-ND V4.0, Open Access
Journal article
Stochastic simulation and optimization of mobile chipping economics in processing and transport of forest biomass from residues
Silva Fennica., Vol.47(5)
2013
Handle:
https://hdl.handle.net/2376/5938
Abstract
We analyzed the economics of mobile chipping and transport of biomass from forest residues for energy purposes under uncertainty. A discrete-event simulation model was developed and utilized to quantify the impacts of controllable and environmental variables on productivity in order to determine the most cost effective transportation options under steep terrain conditions. Truck-chipper interactions were analyzed to show their effect on truck and chipper standing time. A costing model was developed to account for operating and standing time cost (for the chipper and trucks). The model used information from time studies of each activity in the productive cycle and spatial-temporal information obtained from geographic information system (GIS) devices, and tracking analysis of machine and truck movements. The model was validated in field operations, and proved to be accurate in providing the expected productivity. A cost distribution was elaborated to support operational decisions of forest managers, landowners and risk-averse contractors. Different scenarios were developed to illustrate the economic effects due to changes in road characteristics such as in-highway transport distance, in-forest internal road distance and pile to trailer chipper traveling distances.
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Details
- Title
- Stochastic simulation and optimization of mobile chipping economics in processing and transport of forest biomass from residues
- Creators
- Rene Zamora-Cristales (Author)Kevin Boston (Author)John Sessions (Author)Glen Murphy (Author)
- Publication Details
- Silva Fennica., Vol.47(5)
- Academic Unit
- Peer-Reviewed Publications, Northwest Advanced Renewables Alliance
- Identifiers
- 99900502007101842
- Copyright
- Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International ; https://creativecommons.org/licenses/by-nc-nd/4.0/
- Language
- English
- Resource Type
- Journal article