Biomass Fast Pyrolysis: Experimental Analysis and Modeling Approach † (original) (raw)
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Fast pyrolysis of biomass: A review of relevant aspects. Part I: Parametric study
Recent years have witnessed a growing interest in developing biofuels from biomass by thermochemical processes like fast pyrolysis as a promising alternative to supply ever-growing energy consumption. However, the fast pyrolysis process is complex, involving changes in phase, mass, energy, and momentum transport phenomena which are all strongly coupled with the reaction rate. Despite many studies in the area, there is no agreement in the literature regarding the reaction mechanisms. Furthermore, no detailed universally applicable phenomenological models have been proposed to describe the main physical and chemical processes occurring within a particle of biomass. This has led to difficulties in reactor design and pilot industrial scale operation, stunting the popularization of the technology. This paper reviews relevant topics to help researchers gain a better understanding of how to address the modeling of biomass pyrolysis.
Experimental and Modelling Studies of Biomass Pyrolysis
Chinese Journal of Chemical Engineering, 2012
The analysis on the feedstock pyrolysis characteristic and the impacts of process parameters on pyrolysis outcomes can assist in the designing, operating and optimizing pyrolysis processes. This work aims to utilize both experimental and modelling approaches to perform the analysis on three biomass feedstocks wood sawdust, bamboo shred and Jatropha Curcas seed cake residue, and to provide insights for the design and operation of pyrolysis processes. For the experimental part, the study investigated the effect of heating rate, final pyrolysis temperature and sample size on pyrolysis using common thermal analysis techniques. For the modelling part, a transient mathematical model that integrates the feedstock characteristic from the experimental study was used to simulate the pyrolysis progress of selected biomass feedstock particles for reactor scenarios. The model composes of several sub-models that describe pyrolysis kinetic and heat flow, particle heat transfer, particle shrinking and reactor operation. With better understanding of the effects of process conditions and feedstock characteristics on pyrolysis through both experimental and modelling studies, this work discusses on the considerations of and interrelation between feedstock size, pyrolysis energy usage, processing time and product quality for the design and operation of pyrolysis processes.
Pyrolysis of thick biomass particles: Experimental and kinetic modelling
Chemical Engineering Transactions, 2013
The aim of this work is to analyze some new experimental data of pyrolysis of thick woody biomass particles with the help of a general and comprehensive mathematical model. This multiphase and multiscale problem involves strong interactions between chemical kinetics, both in the solid and in the gas phase, and heat/mass transfer phenomena. Detailed experimental measurements have been obtained in an original lab scale reactor. This setup is designed to measure the products yielded along the pyrolysis of a single biomass (beech) particle as well as the temperature profiles into the sample. Experiments are carried out with pyrolysis temperatures ranging between 723 K and 1073 K. Lower-temperature pyrolysis data for poplar from a second reactor are also presented. These results constitute a very useful data set to tune and validate a predictive multistep kinetic model of biomass pyrolysis (Ranzi et al. 2008) and to analyse and discuss the relative effect of different phenomena. The thermal behavior of the pyrolysis process is particularly highlighted.
In this study, kinetic parameters of fast and slow pyrolysis is compared. For fast pyrolysis, cylindrical wood pieces of 20 mm diameter and 50 mm length is pyrolysed in a tube furnace at temperatures ranging from 300oC to 500oC. Solid, liquid and gas products are collected and the yields are calculated. For slow pyrolysis, thermogravimetric analysis (TGA) is used using sawdust from the same biomass. Using the experimental data from two different methods the kinetic parameters are calculated such as activation energy and pre-exponential factor for the two different pyrolysis methods. For fast pyrolysis the parameters are found to be E = 32.5 kJ/mol and A = 35/min and for slow pyrolysis Es = 50.48 kJ/mol and As = 3179.86/min. The large difference between the values show that kinetic studies and modelling work using thermogravimetric analysis data is not suitable for commercial scale simulation. Also, the pre-exponential value for fast pyrolysis shows that the kinetic equation used from flash pyrolysis is not exactly suitable for this situation. Therefore, it is recommended that more studies on the kinetic parameters of fast pyrolysis of thermally thick biomass need to be done.
Modeling of heterogeneous chemical reactions caused in pyrolysis of biomass particles
Advanced Powder Technology, 2007
Pyrolysis of woody biomass was studied experimentally with the aim of investigating heat transfer and heterogeneous chemical reactions. In rapid pyrolysis, two different pyrolysis rates were obtained, with different reactions taking place depending on the temperature (a process producing gas and a process producing tar + water). However, the temperature at the transit stage between the two steps for gas differs from the temperature for tar + water. The fact means that there are two processes for gas generation. The experimental results obtained for slow pyrolysis showed that the average temperature in the biomass layer increased slowly as compared with the change in the set temperature. This tendency does not vary over a mean particle size range of 1.1 < D p,50 (mean particle size) < 11 mm. Numerical simulation of heat transfer in a tubular reactor, without considering chemical enthalpy, was carried out. Comparison of the calculated results with the experimental heat flow rates in the biomass layer revealed two endothermic regions and two exothermic regions. The flow rate of gas generated in the reaction showed two peaks at the exothermic regions. Thus, it was concluded that heat transfer by pyrolysis consists of many processes. Furthermore, we propose a new mechanism representing the heterogeneous chemical reactions involved in pyrolysis, which is divided into four processes: (i) evaporation of water, (ii) decomposition of cellulose, (iii) decomposition of generated tar and (iv) decomposition of lignin.
Analytical Investigations of Kinetic and Heat Transfer in Slow Pyrolysis of a Biomass Particle
The utilization of biomass for heat and power generation has aroused the interest of most researchers especially those of energy .In converting solid fuel to a usable form of energy, pyrolysis plays an integral role. Understanding this very important phenomenon in the thermochemical conversion processes and representing it with appropriate mathematical models is vital in the design of pyrolysis reactors and biomass gasifiers. Therefore, this study presents analytical solutions to the kinetic and the heat transfer equations that describe the slow pyrolysis of a biomass particle. The effects of Biot number, temperature and residence time on biomass particle decomposition were studied. The results from the proposed analytical models are in good agreement with the reported experimental results. The developed analytical solutions to the heat transfer equations which have been stated to be “analytically involved” showed average percentage error and standard deviations 0.439 and 0.103 from the experimental results respectively as compared with previous model in literature which gives average percentage error and standard deviations 0.75 and 0.106 from the experimental results respectively. This work is of great importance in the design of some pyrolysis reactors/units and in the optimal design of the biomass gasifiers.
The utilization of biomass for heat and power generation has aroused the interest of most researchers especially those of energy .In converting solid fuel to a usable form of energy, pyrolysis plays an integral role. Understanding this very important phenomenon in the thermochemical conversion processes and representing it with appropriate mathematical models is vital in the design of pyrolysis reactors and biomass gasifiers. Therefore, this study presents analytical solutions to the kinetic and the heat transfer equations that describe the slow pyrolysis of a biomass particle. The effects of Biot number, temperature and residence time on biomass particle decomposition were studied. The results from the proposed analytical models are in good agreement with the reported experimental results. The developed analytical solutions to the heat transfer equations which have been stated to be " analytically involved " showed average percentage error and standard deviations 0.439 and 0.103 from the experimental results respectively as compared with previous model in literature which gives average percentage error and standard deviations 0.75 and 0.106 from the experimental results respectively. This work is of great importance in the design of some pyrolysis reactors/units and in the optimal design of the biomass gasifiers.
Mathematical Theory and Modeling, 2013
A better understanding of biomass pyrolysis process at various thermal regimes is fundamental to the optimization of biomass thermochemical conversion processes. In this research work, the behaviour of biomass pyrolysis in thermally thin regime was numerically investigated at different heating rates (1, 5, 10 and 20 K/s). A kinetic model, consisting of five ordinary differential equations, was used to simulate the pyrolysis process. The model equations were coupled and simultaneously solved by using fourth-order Runge-Kutta method. The concentrations of the biomass sample (Maple wood) and product species per time were simulated. Findings revealed that tar yield increased with increase in heating rate. Char yield, however, decreased with increase in heating rate. Results also showed that the extent of secondary reactions, which influenced gas yield concentration, is a function of residence time and temperature. This model can be adopted for any biomass material when the kinetic parameters of the material are known.