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Title: An energy-limited model of algal biofuel production: Toward the next generation of advanced biofuels

Abstract

Algal biofuels are increasingly important as a source of renewable energy. The absence of reliable thermodynamic and other property data, and the large amount of kinetic data that would normally be required have created a major barrier to simulation. Additionally, the absence of a generally accepted flowsheet for biofuel production means that detailed simulation of the wrong approach is a real possibility. This model of algal biofuel production estimates the necessary data and places it into a heuristic model using a commercial simulator that back-calculates the process structure required. Furthermore, complex kinetics can be obviated for now by putting the simulator into energy limitation and forcing it to solve for the missing design variables, such as bioreactor surface area, productivity, and oil content. The model does not attempt to prescribe a particular approach, but provides a guide towards a sound engineering approach to this challenging and important problem.

Authors:
 [1];  [1];  [2];  [2]
  1. Pan Pacific Technologies, Adelaide SA (Australia)
  2. Univ. of Pennsylvania, Philadelphia, PA (United States). Dept. of Chemical and Biomolecular Engineering
Publication Date:
Research Org.:
Pan Pacific Technologies, Adelaide (Australia)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1096792
Report Number(s):
DOE-DANF-0003046-FF3
Journal ID: ISSN 0001-1541
Grant/Contract Number:  
EE0003046
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
AIChE Journal
Additional Journal Information:
Journal Volume: 59; Journal Issue: 12; Journal ID: ISSN 0001-1541
Publisher:
American Institute of Chemical Engineers
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; algal biofuel; process systems engineering; model; energy-limited

Citation Formats

Dunlop, Eric H., Coaldrake, A. Kimi, Silva, Cory S., and Seider, Warren D. An energy-limited model of algal biofuel production: Toward the next generation of advanced biofuels. United States: N. p., 2013. Web. doi:10.1002/aic.14251.
Dunlop, Eric H., Coaldrake, A. Kimi, Silva, Cory S., & Seider, Warren D. An energy-limited model of algal biofuel production: Toward the next generation of advanced biofuels. United States. https://doi.org/10.1002/aic.14251
Dunlop, Eric H., Coaldrake, A. Kimi, Silva, Cory S., and Seider, Warren D. 2013. "An energy-limited model of algal biofuel production: Toward the next generation of advanced biofuels". United States. https://doi.org/10.1002/aic.14251. https://www.osti.gov/servlets/purl/1096792.
@article{osti_1096792,
title = {An energy-limited model of algal biofuel production: Toward the next generation of advanced biofuels},
author = {Dunlop, Eric H. and Coaldrake, A. Kimi and Silva, Cory S. and Seider, Warren D.},
abstractNote = {Algal biofuels are increasingly important as a source of renewable energy. The absence of reliable thermodynamic and other property data, and the large amount of kinetic data that would normally be required have created a major barrier to simulation. Additionally, the absence of a generally accepted flowsheet for biofuel production means that detailed simulation of the wrong approach is a real possibility. This model of algal biofuel production estimates the necessary data and places it into a heuristic model using a commercial simulator that back-calculates the process structure required. Furthermore, complex kinetics can be obviated for now by putting the simulator into energy limitation and forcing it to solve for the missing design variables, such as bioreactor surface area, productivity, and oil content. The model does not attempt to prescribe a particular approach, but provides a guide towards a sound engineering approach to this challenging and important problem.},
doi = {10.1002/aic.14251},
url = {https://www.osti.gov/biblio/1096792}, journal = {AIChE Journal},
issn = {0001-1541},
number = 12,
volume = 59,
place = {United States},
year = {Tue Oct 22 00:00:00 EDT 2013},
month = {Tue Oct 22 00:00:00 EDT 2013}
}

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Cited by: 11 works
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Works referenced in this record:

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