CFD based reactivity parameter determination for biomass particles of multiple size ranges in high heating rate devolatilization

Niemelä, Niko; Tolvanen, Henrik; Saarinen, Teemu; Leppänen, Aino; Joronen, Tero

doi:10.1016/j.energy.2017.04.023

Cited by 13 publications

(3 citation statements)

References 21 publications

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“…Particles were considered to have obtained full devolatilization if a paper showed consistent results for particle yield fractions over time, and/or the residence time was long compared to the particle size . Data which describe the char yield for fully devolatilized particles are scarce in literature, and papers − that do not provide data on fully devolatilized particles have been omitted from the study. Likewise, papers , where the experimental conditions are outside the parameter intervals for the calibration data set are also omitted from this study.…”

Section: Methodsmentioning

confidence: 99%

Predicting Biomass Char Yield from High Heating Rate Devolatilization Using Chemometrics

2018

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This study provides a simple model for biomass char yield obtained under conditions relevant for suspension ring. Using the multivariate data analysis methods, principal component analysis (PCA) and partial least squares regression (PLS regression), an equation is presented, which predict the char yield for wood and herbaceous biomass. The model parameters are heating rate (0.1-12 •10 3 K/s), average particle size (0.13-0.93 mm), maximum temperature (873-1673 K), potassium content (from 0.02 wt% db and upwards), and char yield (1-15 wt% daf). The model is developed based on wood biomass data and subsequently expanded to include straw and other herbaceous biomass. It is validated against experimental data from the literature and in general it exhibits the same characteristics. Independent data sets of wood are predicted with an average error (RMSEP) of 0.9 wt%point daf, and straw with an RMSEP = 0.9 wt% daf for the model, when a slope/intercept correction is applied, or RMSEP = 1.1 wt% daf otherwise. To include herbaceous biomass, the model introduces a potassium cut o level at 0.53wt%db, because the catalytic eect of potassium on the devolatilization 1

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Section: Methodsmentioning

confidence: 99%

Predicting Biomass Char Yield from High Heating Rate Devolatilization Using Chemometrics

2018

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“…The heating rate has been shown to be important for both the devolatilization rate and the char yield in combustion of solid fuels. Most reported studies of biomass devolatilization under conditions representative for pulverized fuel combustion have employed drop tube furnaces or entrained flow reactors. − These studies have provided important data on devolatilization rates, as well as char yields and morphology. However, important issues are still in discussion.…”

Section: Introductionmentioning

confidence: 99%

High Heating Rate Devolatilization Kinetics of Pulverized Biomass Fuels

et al. 2018

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Devolatilization kinetics for the biomass fuels miscanthus, leached miscanthus, and KCl doped pinewood were determined at high heating rates (∼ 10 5 K • s −1), high peak temperatures (14051667 K), and short residence times (< 70 ms). The particle temperature and residence time distribution were obtained from CFD simulations. The measured devolatilization rates, formulated in terms of single rst order reactions, were signicantly faster than data reported in literature. This dierence was attributed partly to the fast heating rate/high temperature conditions of the present study, and partly to a more accurate estimate of the particle temperature. The current results indicate that neither the biomass type nor the alkali content of the biomass has a signicant impact on the devolatilization rate under the investigated conditions. The development in the particle morphology was studied by electron microscopy as each fuel underwent partial to full conversion. The char yields ranged from 0.02 (leached 1 miscanthus) to 0.11 (KCl doped pinewood), indicating that even during fast heating the biomass alkali content promotes char formation.

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“…The use of larger sand particles requires higher carrier gas velocity for efficient particle fluidisation which results in a higher rate of bio-oil productions. Niemelä et al [29] suggest that while using large scale CFD simulation, considering the whole size distribution results in more accurate devolatilisation schemes. To address the effect of the biomass size on the devolatilisation scheme, ground and sieved biomass particles with three different size ranges are considered; small (112-125 µm), medium (500-600 µm) and large (800-1000 µm) fractions.…”

Section: Introductionmentioning

confidence: 99%

A hybrid SVR-PSO model to predict a CFD-based optimised bubbling fluidised bed pyrolysis reactor

Jalalifar

Masoudi

Abbassi

et al. 2020

Energy

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CFD based reactivity parameter determination for biomass particles of multiple size ranges in high heating rate devolatilization

Cited by 13 publications

References 21 publications

Predicting Biomass Char Yield from High Heating Rate Devolatilization Using Chemometrics

Predicting Biomass Char Yield from High Heating Rate Devolatilization Using Chemometrics

High Heating Rate Devolatilization Kinetics of Pulverized Biomass Fuels

A hybrid SVR-PSO model to predict a CFD-based optimised bubbling fluidised bed pyrolysis reactor

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