Kinetic modeling and simulation of throated downdraft gasifier

Yücel, Özgün; Hastaog̃lu, Mehmet A.

doi:10.1016/j.fuproc.2015.12.023

Cited by 51 publications

(17 citation statements)

References 27 publications

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“…Moreover, an increase in the steam-reforming reaction (R-7) also resulted in a decrease of CH4 concentration in the gas stream. The gas concentrations obtained from this study (Table 2) were slightly higher than other modelling studies [21,24,32,[51][52][53]. Previous modelling studied showed that the syngas composition generated from the throat downdraft gasifier are in the range of 13-25%mol H2, 18-38%mol CO, 8-11%mol CO2 and 1-3%mol of CH4.…”

Section: Boundary Conditions and Solution Methodsmentioning

confidence: 47%

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Optimisation of a throat downdraft gasifier for hydrogen production

Prasertcharoensuk

Hernandez²,

Bull

et al. 2018

Biomass and Bioenergy

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Gasification of coal is a well-known technology used to convert solid coal into gas (syngas). The implementation of gasification for waste and biomass still requires attention due to the difference in nature of biomass compared to coal. Although, modification to a gasifier is one of the main approaches to achieve high quality syngas production (high H2/CO ratio) and to eliminate tar formation, the effect of design of the gasifier has not been studied. Downdraft gasifiers are reported to produce relatively high quality syngas with low tar concentration compared to other designs. Therefore, in this study a 20 cm diameter throat downdraft gasifier was numerically optimised using Computational Fluid Dynamics modelling. The effect of throat diameter and the position of the air inlet nozzles above the throat on the properties of the gas and the temperature profile in the gasifier was systematically investigated and validated using experimental data. The throat diameter and the position of the air inlet nozzles had a significant effect on the properties of the gas and temperature profile. The modelling and experimental results agreed very well with less than 5% deviation. This confirms that the numerical approaches are valid and can be used in scaling up biomass gasification, reducing process development time from laboratory scales to pilot/industrial scales. The maximum concentration of H2 2 (31.2%mol) and highest H2/CO ratio (1.25) was found at a ratio of throat diameter to gasifier diameter of 0.40 and the position of the air inlet nozzles at 10 cm above the throat.

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Section: Boundary Conditions and Solution Methodsmentioning

confidence: 47%

“…Computational Fluid Dynamics (CFD) modelling has previously been used to predict the behaviour of biomass gasification to optimize operating conditions of an existing gasifier [17][18][19][20][21][22][23][24][25][26][27][28][29]. In general, only a few aspects of the gasifier design have been investigated in any one study.…”

Section: Introductionmentioning

confidence: 99%

Optimisation of a throat downdraft gasifier for hydrogen production

Prasertcharoensuk

Hernandez²,

Bull

et al. 2018

Biomass and Bioenergy

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“…Depending on the use of these resources, it is necessary to have alternative energy production routes due to the increasing environmental impacts of gas emissions . The synthesis gas produced by partial oxidation of the biomass usually comprises H 2 , CO, CO 2 , and CH 4 ; diverse pollutants such as tar (black viscous liquid) and ash occur as by‐products of gasification . The abovementioned hydrogen gas is considered as a clean energy option to reduce the dependence on petroleum and covers a huge amount of the world energy requirement .…”

Section: Introductionmentioning

confidence: 99%

“…1 The synthesis gas produced by partial oxidation of the biomass usually comprises H 2 , CO, CO 2 , and CH 4 ; diverse pollutants such as tar (black viscous liquid) and ash occur as by-products of gasification. 2 The abovementioned hydrogen gas is considered as a clean energy option to reduce the dependence on petroleum and covers a huge amount of the world energy requirement. 3,4 While natural gas is mainly used in hydrogen production, nowadays, by means of fossil fuel reforming, approximately 90% of total production is obtained.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the different artificial neural networks in prediction of biomass gasification products

2019

Self Cite

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Summary In this study, artificial neural networks (ANNs) and a nonlinear autoregressive exogenous (NARX) neural network model were employed in order to model a fixed bed downdraft gasification. The relation between the feature group and the regression performance was investigated. First, feature group consists of the equivalence ratio (ER), air flow rate (AF), and temperature distribution (T0‐T5) obtained from the fixed bed downdraft gasifiers, while the second group includes ultimate and proximate values of biomasses, ER, AF, and the reduction temperature (T0). Models constructed to predict the syngas composition (H2, CO2, CO, CH4) and calorific value. Experimental gasification data that involve 3831 data samples that belong to pinecone and wood pellet were used for training the ANNs. Different ANN architecture and NARX time series model have been constructed to examine the prediction accuracy of the models. The results of the ANN models were consistent with the experimental data (R2 > 0.99). The overall score of NARX time series networks is found to be higher than other architecture types. A successful method is proposed to reduce the number of features, and the effect of the features on the prediction capability was examined by calculating the relative importance index using the Garson's equation.

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“…On the other hand, when the gasifier is operated at temperatures below 800 °C, a kinetic model has to be applied which is known for its higher complexity and the requirement of much more parameters (Fortunato et al, 2017). Kinetic models incorporate the multi-step particle loss approach, hydrocarbon reforming and transport phenomena, and char used as the catalyst (Yucel et al, 2016). In this work, RDF gasification process for methanol production was designed and simulated in Aspen Plus environment.…”

Section: Introductionmentioning

confidence: 99%

Modelling of syngas production from municipal solid waste (MSW) for methanol synthesis

Šuhaj

Husár

Haydary

2017

Acta Chimica Slovaca

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Approximately 1 300 Gt of municipal solid waste (MSW) are produced worldwide every year. Most of it is disposed of in landfills, which is very hazardous for the environment. Up to 10 % of produced MSW are incinerated. However, incineration is not very effective and requires specific conditions for preventing emissions. Gasification and pyrolysis are more effective processes which can be used not only for heat and electricity generation but also for fuel and valuable chemicals production. MSW can be transformed into refuse-derived fuel (RDF) which has higher heat of combustion. Synthesis gas produced by RDF gasification can be utilised in methanol production. Methanol is a very lucrative chemical which can be used as renewable liquid fuel or as a reagent in organic syntheses. Gasifier design and process optimisation can be done using a reliable mathematical model. A good model can significantly decrease the number of experiments necessary for the gasification process design. In this work, equilibrium model for RDF gasification was designed in Aspen Plus environment and the flow of oxygen and steam as gasification agents were optimised to achieve the highest theoretical methanol yield. Impact of the recycle of unreacted steam and produced tar on the methanol yield was evaluated. The highest theoretical methanol yield (0.629 kg MEOH /kg RDF ) was achieved when the steam and tar recycle were switched on, the ratio between oxygen and RDF feed was 0.423 kg/kg and that between the steam and RDF feed was 0.606 kg/kg. In this case, fresh steam represented only 12 % of the total steam fed to the reactor, the rest consisted of recycled steam. Optimal gasifier temperature was 900 °C.

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Kinetic modeling and simulation of throated downdraft gasifier

Cited by 51 publications

References 27 publications

Optimisation of a throat downdraft gasifier for hydrogen production

Optimisation of a throat downdraft gasifier for hydrogen production

Comparison of the different artificial neural networks in prediction of biomass gasification products

Modelling of syngas production from municipal solid waste (MSW) for methanol synthesis

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