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Dynamic Modeling with Experimental Calibration for the Syngas Production from Biomass Fixed-bed Gasification
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  • Xin He,
  • Qiang Hu,
  • Haiping Yang,
  • Christine Annette Shoemaker,
  • Chi-Hwa Wang
Xin He
National University of Singapore

Corresponding Author:[email protected]

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Qiang Hu
National University of Singapore
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Haiping Yang
Huazhong University of Science and Technology
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Christine Annette Shoemaker
National University of Singapore
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Chi-Hwa Wang
National University of Singapore
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In this paper, a dynamic biomass gasification model was developed based on the hybrid peripheral fragmentation and shrinking-core (HPFS) model. To improve the accuracy of syngas generation transient prediction, the chemical kinetic model was trained using global surrogate optimization techniques. The pre-exponential factors of kinetic reactions are calibrated under non-catalytic conditions, employing experimental transient data of syngas generation rate and compositions under different temperatures and gasifying agents. The DYCORS and GOMORS were employed as the numerical solvers for finding the global optimum solution of the pre-exponential factors. The calibrated kinetic models based on both single-objective and multi-objective approaches have been validated by experimental data in four different biomass gasification scenarios. The calibrated kinetic model shows an over 95% decrease in terms of integrated squared error (ISE)-based model mismatch when compared to the original kinetic model.
27 Sep 2020Submitted to AIChE Journal
18 Oct 2020Submission Checks Completed
18 Oct 2020Assigned to Editor
19 Oct 2020Reviewer(s) Assigned
10 Jan 2021Editorial Decision: Revise Major
26 Feb 20211st Revision Received
02 Mar 2021Assigned to Editor
02 Mar 2021Submission Checks Completed
08 Mar 2021Reviewer(s) Assigned
20 Apr 2021Editorial Decision: Revise Minor
26 Apr 20212nd Revision Received
02 May 2021Submission Checks Completed
02 May 2021Assigned to Editor
03 May 2021Reviewer(s) Assigned
28 Jun 2021Editorial Decision: Accept