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Title: Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective

Abstract

Feedstock price and availability are key challenges for biorefinery development and biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the variability of yields of hydrolyzed sugar remained unclear. This study quantifies the uncertainties in the sugar yields from the blends of corn stover, switchgrass, and grass clippings by considering both variable and model uncertainties. The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A further investigation on xxx demonstrates that the reduction in overall uncertainty is achieved by reduced compositional uncertainties of blended feedstock. Based on these results, the optimization of blending ratios was performed with respect to three objectives: (1) probability of meeting the sugar yield target; (2) expected sugar yields; and (3) sugar yield per unit feedstock expense, while satisfying constraints of feedstock availability and cost. In conclusion, the optimization method developed in this study, is readily applied to other combinations of feedstocks, biofuels production processes, and constraints.

Authors:
ORCiD logo [1];  [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2];  [1]; ORCiD logo [1]
  1. North Carolina State Univ., Raleigh, NC (United States)
  2. Idaho National Lab. (INL), Idaho Falls, ID (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B)
OSTI Identifier:
1478497
Report Number(s):
INL/JOU-18-45606-Rev000
Journal ID: ISSN 2168-0485
Grant/Contract Number:  
AC07-05ID14517
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
ACS Sustainable Chemistry & Engineering
Additional Journal Information:
Journal Volume: 6; Journal Issue: 8; Journal ID: ISSN 2168-0485
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; blending; uncertainty analysis; Bayesian linear regression; feedstock blending; model uncertainty; Monte Carlo simulation; optimization; uncertainty quantification

Citation Formats

Ou, Longwen, Luo, Guanqun, Ray, Allison, Li, Chenlin, Hu, Hongqiang, Kelley, Stephen, and Park, Sunkyu. Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective. United States: N. p., 2018. Web. doi:10.1021/acssuschemeng.8b02150.
Ou, Longwen, Luo, Guanqun, Ray, Allison, Li, Chenlin, Hu, Hongqiang, Kelley, Stephen, & Park, Sunkyu. Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective. United States. doi:10.1021/acssuschemeng.8b02150.
Ou, Longwen, Luo, Guanqun, Ray, Allison, Li, Chenlin, Hu, Hongqiang, Kelley, Stephen, and Park, Sunkyu. Thu . "Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective". United States. doi:10.1021/acssuschemeng.8b02150. https://www.osti.gov/servlets/purl/1478497.
@article{osti_1478497,
title = {Understanding the Impacts of Biomass Blending on the Uncertainty of Hydrolyzed Sugar Yield from a Stochastic Perspective},
author = {Ou, Longwen and Luo, Guanqun and Ray, Allison and Li, Chenlin and Hu, Hongqiang and Kelley, Stephen and Park, Sunkyu},
abstractNote = {Feedstock price and availability are key challenges for biorefinery development and biomass blending has been suggested as a route to overcome these limitations. However, the impacts of feedstock blending on the variability of yields of hydrolyzed sugar remained unclear. This study quantifies the uncertainties in the sugar yields from the blends of corn stover, switchgrass, and grass clippings by considering both variable and model uncertainties. The results indicate that feedstock blending reduces the uncertainties in sugar yields and delivers feedstock of more uniform quality. A further investigation on xxx demonstrates that the reduction in overall uncertainty is achieved by reduced compositional uncertainties of blended feedstock. Based on these results, the optimization of blending ratios was performed with respect to three objectives: (1) probability of meeting the sugar yield target; (2) expected sugar yields; and (3) sugar yield per unit feedstock expense, while satisfying constraints of feedstock availability and cost. In conclusion, the optimization method developed in this study, is readily applied to other combinations of feedstocks, biofuels production processes, and constraints.},
doi = {10.1021/acssuschemeng.8b02150},
journal = {ACS Sustainable Chemistry & Engineering},
issn = {2168-0485},
number = 8,
volume = 6,
place = {United States},
year = {2018},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Figure 1 Figure 1: Workflow for uncertainty quantification.

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Works referencing / citing this record:

Editorial: Advancements in Biomass Feedstock Preprocessing: Conversion Ready Feedstocks
journal, December 2019

  • Hess, J. Richard; Ray, Allison E.; Rials, Timothy G.
  • Frontiers in Energy Research, Vol. 7
  • DOI: 10.3389/fenrg.2019.00140

Editorial: Advancements in Biomass Feedstock Preprocessing: Conversion Ready Feedstocks
journal, December 2019

  • Hess, J. Richard; Ray, Allison E.; Rials, Timothy G.
  • Frontiers in Energy Research, Vol. 7
  • DOI: 10.3389/fenrg.2019.00140

    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.