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Title: Dynamic modelling of updraft gasifiers: Incidence of feedstock quality and operational variables in the transient model structure
Authors: Narvaez-Cueva, Ricardo A.
Blanchard, Richard E.
Chulde, Diego
Guerron, G.
Dixon, Roger
Issue Date: 2017
Publisher: © American Society of Mechanical Engineers (ASME)
Citation: NARVAEZ-CUEVA, R.A. ...et al., 2017. Dynamic modelling of updraft gasifiers: Incidence of feedstock quality and operational variables in the transient model structure. Presented at the 2017 Dynamic Systems and Control Conference (DSCC2017), Tysons Corner, Virginia, USA, October 11-13th.
Series/Report no.: DSCC2017;5142
Abstract: This paper describes the definition of the transient model structure for an updraft gasifier and the input variables related to the process and the feedstock quality with the most significant influence on the dynamic models and the transient behaviour. For such purpose, a set of open-loop dynamics experiments were carried out in the gasifier. Moreover, the output variables performance was recorded together with the composition analysis of the municipal solid waste batch (MSW). The output and operational variables record was used as base information for performing regressions of transient models with the purpose of determining the model type choice that achieves the largest occurrence frequency of fitting percentage figures above 50%. In addition, the dataset of regression parameters is analysed through feature selection in order to establish the influence of feedstock quality parameters and independent dynamic operational variables in dynamic changes. The model structure selection determined that underdamped, second order with one zero transfer function (P2ZU) is the most accurate case for updraft gasifiers. Regarding the influence of feedstock-related information, feature selection results show that ultimate composition is the group of quality parameters with the most significant influence on transient behaviour. Results also show that recirculation flow rate is the operational variable whose effect in the output variables is the most likely to be predicted and potentially controlled. The results for this variable show that 64.3% of the performed regressions achieved a fitting percentage value above 50%.
Description: This paper is in closed access.
Sponsor: Authors thank the Secretary of Higher Education, Science, Technology and Innovation of Ecuador (SENESCYT) due to its significant contribution as sponsor of the research project “MODELO CINÉTICO E IMPLEMENTACIÓN DE REACTOR PILOTO PARA COGASIFICACIÓN DE RESIDUOS SÓLIDOS Y CARBÓN VEGETAL PARA PRODUCCIÓN DE COMBUSTIBLES” under the grant agreement 20140122 CI.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/27180
Publisher Link: http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=2663603&resultClick=3
Appears in Collections:Closed Access (Mechanical, Electrical and Manufacturing Engineering)

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