Mathematical modelling of biomass gasification process in fixed bed reactors

doctoral thesis

• Title (croatian): Matematičko modeliranje procesa rasplinjavanja biomase u reaktorima s nepomičnim slojem
• Author: Robert Mikulandrić
• Mentor: Dražen Lončar (mentor)
• Committee member: Dubravko Majetić (predsjednik povjerenstva)
• Committee member: Dražen Lončar (član povjerenstva)
• Committee member: Luka Perković (član povjerenstva)
• Granter: University of Zagreb; Faculty of Mechanical Engineering and Naval Architecture; Zagreb
• Defense date and country: 2022-10-28, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mechanical Engineering
• Universal decimal classification (UDC): 620 - Materials testing. Power stations. Economics of energy

Abstract

The aim of the research was to develop a mathematical model that is capable to predict process parameters with reasonable speed and accuracy in different and changeable operating conditions during biomass gasification. Process parameters such as fuel and air flow rate were considered as one of the model inputs which lead to prediction of other process parameters such as syngas temperature and syngas composition. Process dynamics were modelled and simulaiton results were analysed in order to enable further development of an on-line gasification process control concept. Model was designed to predict process parameters in different and changing operating conditions. For model development purposes different equlibrium models and artificial inteligence based models were utilised and their performance was analysed. Model prediction potential was validated on measurement data from a fixed-bed type gasification facility. Developed models were able to predict process parameters such as syngas temperature with average prediction error below 10% (R2 > 0.82) and syngas composition with average prediction error below 38% (R2 > 0.42).Dynamic modelling approach with active prediction error estimation was developed to predict process parameters in variable operating conditions. Models were further used to develop a control strategy that could improve process efficiency by 25%.

Abstract (croatian)

Cilj istraživanja bio je razvoj matematičkog modela koji će predvidjeti pogonske parametre s razumnom brzinom i točnošću u različitim i promjenjivim pogonskim uvjetima tokom rasplinjavanja. Pogonski parametri poput protoka goriva i zraka uzeti su u obzir kao jedni od ulaznih parametara koji su korišteni za predviđanje pogonskih parametara kao što su temperatura i sastav sintetskog plina. Dinamika procesa je modelirana i rezultati simulacije su analizirani u svrhu budućeg razvoja regulacijskih sustava procesa rasplinjavanja. Model je u stanju predviditi pogonske parametre u različitim i promijenjivim pogonskim uvjetima. Za razvoj modela korišteni su različiti modeli temeljeni na očuvanju mase i energije kao i modeli temeljeni na umjetnoj inteligenciji te će se analizirati njihove značajke. Predikcijski potencijal modelavalidiran je na temelju mjerenih podataka prikupljenih s rasplinjača s nepomičnim slojem. Razvijeni modeli su u mogućnosti predvidjeti procesne parametre kao što je temperatura sintetskog plina s prosječnom greškom prdvuđanja ispod 10% (R2 > 0.82) te sastav sintetskog plina s greškom predviđanja ispod 38% (R2 > 0.42). Dinamični pristup modeliranju koji uključuje aktivnu analizu greške predviđanja korišten je za predviđanje pogonskih parametara u promjenjivim uvjetima. Razvijeni modeli su dalje korišteni za razvoj nove strategije vođenja postrojenja koja ima potencijal poboljšati efikasnost procesa za 25%.

• Keywords: biomass gasification numerical modelling artificial neural networks
• Keywords (croatian): rasplinjavanje biomase; numeričko modeliranje; neuronske mreže
• Language: english
• URN:NBN: urn:nbn:hr:235:800287
• Study programme: Title: Mechanical Engineering and Naval Architecture; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, područje tehničkih znanosti (doktor/doktorica znanosti, područje tehničkih znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2022-11-29 14:06:54