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Using Python to characterize the structure of wood


The energy-intensive nature of the mechanical pulping production process (disassembling wood chips into their constituent fibres to make pulp) has resulted in a great deal of work in the area of energy reduction strategies for the process. Prior-to-pulping wood chip compression processes fit this bill exactly and have been shown to reduce the energy consumed by the process as a whole by up to 15%, but are less than fully understood in their mechanism of action. This talk will cover the development of the computational and experimental tools that have been developed to characterize wood chips, and, ultimately, better understand the mechanics of the chip-compression process as a whole. Specifically: the development of an image analysis (via OpenCV)/model fitting (via scikit-learn) data analysis pipeline has allowed for a quantitative assessment of the micro-structure of wood.


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