With the rise of biomass gasification and combustion, predicting pollutants in the different processes became fundamental. The challenges in this derive from the strong relationships between fluid dynamics and chemistry in fluidized beds, which are the main type of reactors used for biomass valorization. Detailed kinetic mechanisms are mandatory to investigate tar, PAH and soot formation, but their application in CFD simulations presents prohibitive computational times. This issue can be solved using equivalent reactor network (ERN) models, which allow to fix the motion field using ideal reactors interconnected in various ways where detailed kinetics can be applied. Past work on these models involves gas-phase homogeneous cases. When more than one phase is involved, segregation has been applied to study all the phenomena in a disjointed fashion. The issue here is that pursuing mathematical segregation reduces the capability to study interrelations between processes and, from a purely numerical standpoint, while it involves a lower computational cost in terms of raw CPU power convergence is slow and solution can easily diverge. This thesis aims to set the foundation for fully-coupled heterogeneous reactor network models. A fully-coupled approach can encompass better how each phenomenon influences the others. To this end, a numerical tool was developed called NetSMOKE. It is a modular framework that extends the OpenSMOKE++ libraries with capabilities to interpret and solve reactor networks. Mathematical formulation of the problem is discussed. This tool was then validated with test cases, and then used to reproduce experimental data of pilot-scale fluidized beds reactors. Good agreement was found.
Con il crescente interesse verso la gassificazione e la combustione di biomasse, predire gli inquinanti nei differenti processi è diventato fondamentale. La sfida in questo viene dalla forte interazione tra fluidodinamica e chimica in reattori a letto fluidizzato, principali reattori usati per la valorizzazione delle biomasse. Meccanismi cinetici dettagliati sono obbligatori per investigare la formazione di tar, PAH e soot, ma se accoppiati ad una simulazione CFD presentano tempi computazionali proibitivi. Questo problema può essere risolto usando modelli di rete di reattori equivalente, dove il campo di moto è fissato usando reattori ideali interconnessi in vari modi sui quali è possibile applicare meccanismi cinetici dettagliati. Lavori precedenti sui modelli a rete di reattori riguardavano principalmente sistemi omogenei gassosi. Quando più fasi erano coinvolte, si tendeva a segregare il sistema e studiare i fenomeni disaccoppiati. Il problema della segregazione è che si perdono informazioni sulle interrelazioni tra i processi, nonché i problemi numerici dovuti ad una lenta convergenza e alta probabilità di divergere nonostante il minor costo computazionale dei metodi segregati. Questo lavoro ambisce a gettare le fondamenta per modelli a rete di reattori eterogenei “fully-coupled”. Un approccio di questo tipo consente di includere meglio la competizione e le relazioni tra i vari processi. A questo scopo, è stato sviluppato un tool numerico chiamato NetSMOKE, un framework modulare che estende le librerie OpenSMOKE++ con la capacità di trattare reti di reattori. La formulazione matematica del problema e la struttura del software sono discusse. NetSMOKE è stato poi validato con casi test e applicato nella riproduzione di dati sperimentali da reattori a letto fluido pilota. I risultati ottenuti sono stati positivi.
Reactor network model of biomass combustion in fluidized beds
MENSI, MATTEO
2016/2017
Abstract
With the rise of biomass gasification and combustion, predicting pollutants in the different processes became fundamental. The challenges in this derive from the strong relationships between fluid dynamics and chemistry in fluidized beds, which are the main type of reactors used for biomass valorization. Detailed kinetic mechanisms are mandatory to investigate tar, PAH and soot formation, but their application in CFD simulations presents prohibitive computational times. This issue can be solved using equivalent reactor network (ERN) models, which allow to fix the motion field using ideal reactors interconnected in various ways where detailed kinetics can be applied. Past work on these models involves gas-phase homogeneous cases. When more than one phase is involved, segregation has been applied to study all the phenomena in a disjointed fashion. The issue here is that pursuing mathematical segregation reduces the capability to study interrelations between processes and, from a purely numerical standpoint, while it involves a lower computational cost in terms of raw CPU power convergence is slow and solution can easily diverge. This thesis aims to set the foundation for fully-coupled heterogeneous reactor network models. A fully-coupled approach can encompass better how each phenomenon influences the others. To this end, a numerical tool was developed called NetSMOKE. It is a modular framework that extends the OpenSMOKE++ libraries with capabilities to interpret and solve reactor networks. Mathematical formulation of the problem is discussed. This tool was then validated with test cases, and then used to reproduce experimental data of pilot-scale fluidized beds reactors. Good agreement was found.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/139747