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Fenske, George

Publications and source records attributed to Fenske, George.

Improving knife milling performance for biomass preprocessing by using advanced blade materials

Mechanical preprocessing of biomass, including size reduction, is a crucial step in converting biomass into biofuel. However, feedstock inevitably contains abrasive intrinsic and extrinsic inorganics that may cause excessive tool wear in preprocessing. Here, this work demonstrates that performance of a knife mill can be significantly improved by applying a more wear-resistant blade material. A series of full-scale knife mill tests were performed for size reduction of forest residue using blades of tungsten carbide (WC–Co), iron-borided tool steel, and diamond-like carbon (DLC) coated tool steel. Blade material loss was quantified in correlation to the amount of feedstock processed and wear mechanisms were investigated via worn surface characterization. While the thin DLC coating was removed quickly, the WC-Co and iron-borided blades improved the tool life by 8X and 3X compared with the M2 tool steel blades (baseline), respectively. The in-situ throughput and power consumption measurements provided additional insights. The WC-Co and iron-borided blades had ~3X higher throughput than the baseline blades by the end of the test with lower normalized power consumption. The experimental results were then used as input for a techno-economic analysis, which suggested that the more wear resistant blades could cut the knife milling cost by $2–3 per ton of biomass processed with downtime reduced by 65–85%.

36 MATERIALS SCIENCE↗

Analysis of Cutter Blade Wear in Rotary Shear Mills

Following development of an analytical abrasive wear model to predict wear of components in a rotary shear mill, the team used a finite element analysis (FEA) approach to calculate forces and loads acting on particles responsible for abrasive wear. The analytical model related critical rotary shear process parameters (shear geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness and elastic modulus) that enabled us to model the wear of shear cutters in a rotary shear milling system developed by Forest Concepts. With proper knowledge of the forces acting between abrasive particles and cutter components built into it, the model can accurately predict wear of the cutters and provides a quality by design (QbD) approach to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches. During this reporting period, researchers at Oak Ridge National Laboratory applied an FEA package to simulate the local stresses and forces between an abrasive silica particle and two rotary shear cutters as the distance between the cutters decreases. The output of the FEA was used to provide more accurate projections of the loads applied to the particles in the analytical wear model. Comparison of the FEA force calculations are in good agreement with the loads assumed in the analytical predictions.

36 MATERIALS SCIENCE↗