A generic input–output approach in developing and optimizing an Aspen plus steam-gasification model for biomass

Zaman, Sk Arafat; Ghosh, Sudip

doi:10.1016/j.biortech.2021.125412

Cited by 44 publications

(10 citation statements)

References 41 publications

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“…The values of

and

were between 0 and 100%. A value of more than 90% means the model is accurate [ 30 , 32 ]. Further evidence for a good model is provided by the less than 0.2 difference between

and

[ 32 ].…”

Section: Methodsmentioning

confidence: 99%

Microwave-assisted pyrolysis of pine sawdust: Process modelling, performance optimization and economic evaluation for bioenergy recovery

Makepa

Chihobo

Ruziwa

et al. 2023

Heliyon

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“…The values of

and

were between 0 and 100%. A value of more than 90% means the model is accurate [ 30 , 32 ]. Further evidence for a good model is provided by the less than 0.2 difference between

and

[ 32 ].…”

Section: Methodsmentioning

confidence: 99%

Microwave-assisted pyrolysis of pine sawdust: Process modelling, performance optimization and economic evaluation for bioenergy recovery

Makepa

Chihobo

Ruziwa

et al. 2023

Heliyon

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“…Model development in the present study is performed using Aspen Plus simulation software. Aspen Plus is the most widely used simulation tool to simulate the gasification process of the different types of solid fuels. − …”

Section: Methodsmentioning

confidence: 99%

“…Generally, the process of coal gasification in a downdraft fixed-bed gasifier is described by dividing the overall process into different reaction zones. The typical reactions occurring in different zones of the gasifier are given in Table . − The process flowsheet of the coal gasification process in a downdraft fixed-bed gasifier using air as an oxidant is shown in Figure . The details of unit operations and Aspen Plus blocks are given in Table S1 in the Supporting Information file.…”

Section: Methodsmentioning

confidence: 99%

“…Determining the best optimal condition depends on the dimensionless desirability value, which ranges from 0 to 1. The d value is 0 for unacceptable responses and 1 for desirable responses. , The optimization is performed to target the H 2 /CO molar ratio value to 1, along with maximizing CGE (%) and CCE (%). The inbuilt optimizer tool in Minitab statistical software has been employed to achieve the best operational conditions of the current process.…”

Section: Methodsmentioning

confidence: 99%

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High-Ash Low-Rank Coal Gasification: Process Modeling and Multiobjective Optimization

2022

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The diversification of coal for its sustainable utilization in producing liquid transportation fuel is inevitable in countries with huge coal reserves. Gasification has been contemplated as one of the most promising thermochemical routes to convert coal into high-quality syngas, which can be utilized to produce liquid hydrocarbons through catalytic Fischer−Tropsch (F-T) synthesis. Liquid transportation fuel production through coal gasification could help deal with environmental challenges and renewable energy development. The present study aims to develop an equilibrium model of a downdraft fixed-bed gasifier using Aspen Plus simulator to predict the syngas compositions obtained from the gasification of high-ash low-rank coal at different operating conditions. Air is used as a gasifying agent in the present study. The model validation is done using published experimental and simulation results from previous investigations. The sensitivity analysis is done to observe the influence of the major operating parameters, such as equivalence ratio (ER), gasification temperature, and moisture content (MC), on the performance of the CL-RMC concerning syngas generation. The gasification performance of CL-RMC is analyzed by defining various performance parameters such as syngas composition, hydrogento-carbon monoxide (H 2 /CO), molar ratio, syngas yield (Y Syngas ), the lower heating value of syngas (LHV Syngas ), cold gas efficiency (CGE), and carbon conversion efficiency (CCE). The combined effects of the major operating parameters are studied through the response surface methodology (RSM) using the design of experiments. The optimized condition of the major operational parameters is determined for a target value of a H 2 /CO molar ratio of 1 and the maximum CGE and CCE using the multiobjective optimization approach. The high-degree accurate regression model equations were generated for the H 2 /CO molar ratio, CGE, and CCE using the variance analysis (ANOVA) tool. The optimal conditions of the major operating parameters, i.e., ER, gasification temperature, MC for the H 2 /CO molar ratio of 1, and the maximum CGE and CCE, are found to be 0.5, 655 °C, and 16.36 wt %, respectively. The corresponding optimal values of CGE and CCE are obtained as 22 and 16.36%, respectively, with a cumulative composite desirability value of 0.7348. The findings of the present investigation can be decisive for future developmental projects in countries concerning the utilization of high-ash low-rank coal in liquid fuel production through the gasification route.

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“…The optimum combination of this parameters is crucial in developing a sustainable utilization of biomass resources through gasification process. In a recent work, it was found that the optimum temperature range is from 780 °C to 790 °C and the equivalence ratio is approximately 0.7 for biomass gasification using steam as oxidizing agent [4].…”

Section: Introductionmentioning

confidence: 99%

Analytical and numerical modelling of biomass gasification in downdraft gasifiers

Moretti

Arpino

Cortellessa

et al. 2022

J. Phys.: Conf. Ser.

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The ever-growing energy demand and environmental pollution level have pushed research interest toward the development of new promising technologies to utilize bioenergy sustainably. In this scenario, biomass gasification has been regarded as a promising renewable energy resource that, if efficiently exploited, can contribute to the reduction of dependency on fossil fuel and CO2 emissions from the power sector. Nevertheless, exploitation of biomass gasification still requires to overcome technological and logistical issues. In this work, the authors propose a general thermodynamic model able to predict the steady operating conditions of biomass gasification. Assuming thermodynamic equilibrium, the model is able to predict temperature, mass flow rate and composition of produced syngas. Moreover, a numerical model of the biomass gasification system has been developed by using the commercial software Aspen Plus. It is a steady-state zero-dimensional equilibrium model, based on the mass and energy balances, assuming the Gibbs free energy minimization. Aspen Plus allows building models of customized operative units using the Fortran code. In order to assure the performance of both analytical and Aspen Plus models, numerical results are compared with experimental data available in the scientific literature for downdraft gasifiers.

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A generic input–output approach in developing and optimizing an Aspen plus steam-gasification model for biomass

Cited by 44 publications

References 41 publications

Microwave-assisted pyrolysis of pine sawdust: Process modelling, performance optimization and economic evaluation for bioenergy recovery

Microwave-assisted pyrolysis of pine sawdust: Process modelling, performance optimization and economic evaluation for bioenergy recovery

High-Ash Low-Rank Coal Gasification: Process Modeling and Multiobjective Optimization

Analytical and numerical modelling of biomass gasification in downdraft gasifiers

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