Automated advanced calibration and optimization of thermochemical models applied to biomass gasification and pyrolysis

Bianco, N., Paul, M. C. , Brownbridge, G. P.E., Nurkowski, D., Salem, A. M., Kumar, U., Bhave, A. N. and Kraft, M. (2018) Automated advanced calibration and optimization of thermochemical models applied to biomass gasification and pyrolysis. Energy and Fuels, 32(10), pp. 10144-10153. (doi:10.1021/acs.energyfuels.8b01007)

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Abstract

This paper presents a methodology that combines physicochemical modeling with advanced statistical analysis algorithms as an efficient workflow, which is then applied to the optimization and design of biomass pyrolysis and gasification processes. The goal was to develop an automated flexible approach for the analyses and optimization of such processes. The approach presented here can also be directly applied to other biomass conversion processes and, in general, to all those processes for which a parametrized model is available. A flexible physicochemical model of the process is initially formulated. Within this model, a hierarchy of sensitive model parameters and input variables (process conditions) is identified, which are then automatically adjusted to calibrate the model and to optimize the process. Through the numerical solution of the underlying mathematical model of the process, we can understand how species concentrations and the thermodynamic conditions within the reactor evolve for the two processes studied. The flexibility offered by the ability to control any model parameter is critical in enabling optimization of both efficiency of the process as well as its emissions. It allows users to design and operate feedstock-flexible pyrolysis and gasification processes, accurately control product characteristics, and minimize the formation of unwanted byproducts (e.g., tar in biomass gasification processes) by exploiting various productivity-enhancing simulation techniques, such as parameter estimation, computational surrogate (reduced order model) generation, uncertainty propagation, and multi-response optimization.

Item Type:Articles
Additional Information:The authors would like to acknowledge funding from Innovate UK [File reference: 132362; Application number: 63389-429274; TS/N011686/1] (Energy Catalyst – Early Stage Feasibility – Round 3).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Paul, Dr Manosh and Kumar, Dr Umesh and Salem, Ahmed Morsy Mostafa
Authors: Bianco, N., Paul, M. C., Brownbridge, G. P.E., Nurkowski, D., Salem, A. M., Kumar, U., Bhave, A. N., and Kraft, M.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:Energy and Fuels
Publisher:American Chemical Society
ISSN:0887-0624
ISSN (Online):1520-5029
Copyright Holders:Copyright © 2018 American Chemical Society
First Published:First published in Energy and Fuels 32(10):10144-10153
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
721661Bio-GaTe - Advanced Biomass Gasification TechnologiesManosh PaulInnovate UK (INNOVATE)132362ENG - ENGINEERING SYSTEMS POWER & ENERGY