Energy recovery from biomass by gasification technology has attracted significant interest because it satisfies a key requirement of environmental sustainability by producing near zero emissions. Though it is not a new technology, studies on its integrated process simulation and analysis are limited, in particular for municipal solid waste (MSW) gasification. This paper develops an integrated fixed bed gasifier model of biomass gasification using the Advanced System for Process ENngineering (Aspen) Plus software for its performance analysis. A computational model was developed on the basis of Gibbs free energy minimization. The model is validated with experimental data of MSW and food waste gasification available in the literature. A reasonable agreement between measured and predicted syngas composition was found. Using the validated model, the effects of operating conditions, namely air-fuel ratio and gasifier temperature, on syngas production are studied. Performance analyses have been done for four different feedstocks, namely wood, coffee bean husks, green wastes and MSWs. The ultimate and proximate analysis data for each feedstock was used for model development. It was found that operating parameters have a significant influence on syngas composition. An air-fuel ratio of 0.3 and gasifier temperature of 700 °C provides optimum performance for a fixed bed gasifier for MSWs, wood wastes, green wastes and coffee bean husks. The developed model can be useful for gasification of other biomasses (e.g., food wastes, rice husks, poultry wastes and sugarcane bagasse) to predict the syngas composition. Therefore, the study provides an integrated gasification model which can be used for different biomass feedstocks.

Gasification is a thermo-chemical process to convert carbon-based products such as biomass and coal into a gas mixture known as synthetic gas or syngas. Various types of gasification methods exist, and fluidized bed gasification is one of them which is considered more efficient than others as fuel is fluidized in oxygen, steam or air. This paper presents an experimental and numerical investigation of fluidized bed gasification of solid waste (SW) (wood). The experimental measurement of syngas composition was done using a pilot scale gasifier. A numerical model was developed using Advanced System for Process ENgineering (Aspen) Plus software. Several Aspen Plus reactor blocks were used along with user defined FORTRAN and Excel code. The model was validated with experimental results. The study found very similar performance between simulation and experimental results, with a maximum variation of 3%. The validated model was used to study the effect of air-fuel and steam-fuel ratio on syngas composition. The model will be useful to predict the various operating parameters of a pilot scale SW gasification plant, such as temperature, pressure, air-fuel ratio and steam-fuel ratio. Therefore, the model can assist researchers, professionals and industries to identify optimized conditions for SW gasification.

A new stormwater quality improvement device called ‘Green Gully’ has been designed and developed in this study with the aim of reusing stormwater for irrigating trees and other plants. The main purpose of the Green Gully is to collect road runoff/stormwater, make it suitable for irrigation and provide an automated network system for watering roadside plants and irrigational areas. This paper presents the design and development of Green Gully along with experimental and computational investigations of the performance of Green Gully. Performance (in the form of efficiency, i.e. the percentage of water flow through the gully grate) was experimentally determined using a gully model in the laboratory first, then a three-dimensional numerical model was developed and simulated to predict the efficiency of Green Gully as a function of flow rate. Computational fluid dynamics code FLUENT was used for the simulation. GAMBIT was used for geometry creation and mesh generation. Experimental and simulation results are discussed and compared in this paper. The predicted efficiency was compared with the laboratory measured efficiency. It was found that the simulated results are in good agreement with the experimental results.