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Title: Flow Behavior of Particulate Pine Forest Residues and Corn Stover: A Comparison of Experiments and Simulations

Abstract

Feeding and handling problems have been recognized as a major contributor to low production of renewable cellulosic ethanol in the US, which achieved only 7% of nameplate capacity in 2016. In this work we compare the flow behavior of pine forest residues and corn stover at various particle sizes and moisture contents in instrumented pilot-scale hopper tests and instrumented shear testers to continuum finite element method (FEM) and discrete element method (DEM) models. The shear testers include a Schulze ring shear tester, a custom large Peschl-style tester, and a modified Johanson direct shear tester. In addition to measurements of normal force and torque, the shear testers are also instrumented with arrays of pressure transducers. Modeling approaches include a Drucker-Prager model, a micropolar hypoelasticity model, and DEM simulations employing non-spherical, deformable particles. Results from physical experiments indicate that continuum elastoplastic models, such as Drucker-Prager models, do not account for the full complexity of biomass flow, and that more advanced rheological models are better able to predict nuances of the flow behavior, especially the compressive stress field.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1]
  1. Idaho National Laboratory
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1498072
Report Number(s):
INL/CON-18-51869-Rev000
DOE Contract Number:  
AC07-05ID14517
Resource Type:
Conference
Resource Relation:
Conference: AIChE 2018, Pittsburgh, PA, 10/28/2018 - 11/03/2018
Country of Publication:
United States
Language:
English
Subject:
09 - BIOMASS FUELS; flowability; particle technology; shear strength

Citation Formats

Westover, Tyler L, Huang, Hai, Xia, Yidong, Klinger, Jordan L, and Jin,. Flow Behavior of Particulate Pine Forest Residues and Corn Stover: A Comparison of Experiments and Simulations. United States: N. p., 2018. Web.
Westover, Tyler L, Huang, Hai, Xia, Yidong, Klinger, Jordan L, & Jin,. Flow Behavior of Particulate Pine Forest Residues and Corn Stover: A Comparison of Experiments and Simulations. United States.
Westover, Tyler L, Huang, Hai, Xia, Yidong, Klinger, Jordan L, and Jin,. Mon . "Flow Behavior of Particulate Pine Forest Residues and Corn Stover: A Comparison of Experiments and Simulations". United States. https://www.osti.gov/servlets/purl/1498072.
@article{osti_1498072,
title = {Flow Behavior of Particulate Pine Forest Residues and Corn Stover: A Comparison of Experiments and Simulations},
author = {Westover, Tyler L and Huang, Hai and Xia, Yidong and Klinger, Jordan L and Jin,},
abstractNote = {Feeding and handling problems have been recognized as a major contributor to low production of renewable cellulosic ethanol in the US, which achieved only 7% of nameplate capacity in 2016. In this work we compare the flow behavior of pine forest residues and corn stover at various particle sizes and moisture contents in instrumented pilot-scale hopper tests and instrumented shear testers to continuum finite element method (FEM) and discrete element method (DEM) models. The shear testers include a Schulze ring shear tester, a custom large Peschl-style tester, and a modified Johanson direct shear tester. In addition to measurements of normal force and torque, the shear testers are also instrumented with arrays of pressure transducers. Modeling approaches include a Drucker-Prager model, a micropolar hypoelasticity model, and DEM simulations employing non-spherical, deformable particles. Results from physical experiments indicate that continuum elastoplastic models, such as Drucker-Prager models, do not account for the full complexity of biomass flow, and that more advanced rheological models are better able to predict nuances of the flow behavior, especially the compressive stress field.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {10}
}

Conference:
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