(251c) Impact of Material Attributes on Mill Throughput and Performance

After removal of feedstock moisture, comminution is the most expensive operation to biomass preprocessing. To better understand and optimize this processing stage, this work investigates linking material attributes and properties of Loblolly Pine to the fundamental stress-strain relationships under controlled deconstruction and pilot-scale hammermilling performance. In this work, fundamental strength properties and probabilities and variabilities for fracture and damage events are connected to a Population Balance Model (PBM) framework. This framework uses statistical and outcome distributions to predict the size reduction performance of a mill. From these fundamental damage properties, the resulting particle size distribution and relative hold-up time in the mill are predicted based on the original particle size, size distribution and moisture content as well as operation parameters of mill speed and retention screen size. In addition, this presentation reports pilot-scale milling throughput and energy consumption trials to relate the fundamental-scale testing and prediction performance to experimental data. These relationships and framework provide an opportunity to perform a small series of reduced-order lab-scale tests to predict at-scale mill operation. This operational knowledge and informatics for data-driven biomass preprocessing is housed under the BETO-funded Feedstock Conversion and Interface Consortium to investigate feedstock variability and properties that are presenting barriers to nascent biorefineries.