Mesh Sensitivity Analysis of an Entrained Flow Biomass Gasifier: a CPFD Study

EasyChair Preprint 8876

Abstract

Biomass such as agricultural waste, forestry waste, municipal solid waste, and industrial waste, are renewable energy sources that may be used to produce biofuels. Biomass gasification is an effective and promising technology for converting any biomass into valuable products that can contributes considerably to renewable energy generation. In the manufacturing industry, computer-based simulations, improving production processes while incorporating sustainable industrial strategies, are rising. In the Computational Fluid Dynamics (CFD) scientific community, the reliability of computational prediction of findings is a rising problem. Mesh independence is crucial since it may determine if the solution obtained is independent of the mesh resolution. In CFD models, there are a variety of strategies for discovering a mesh independence test. The grid resolution, general Richardson extrapolation, and rid Convergence Index (GCI) are three widely used approaches. In the grid resolution technique, the mesh size gradually increases until no meaningful performance improvement can be seen due to the larger mesh size. The present study aims to analyze the mesh independence test using the grid resolution method on an entrained flow biomass gasifier and investigate the model's sensitivity to parameters such as reactants’ inlet temperature, product gas compositions and flow rate. To achieve this goal, four different scenarios were defined employing a series of CPFD simulations using Barracuda® v21.0.1. The results confirmed that within the range of 25000 and 200000 cells, synthesis gas production decreased by almost 2 percent, which is not significant.

Keyphrases: CPFD, Entrained flow gasifier, Gasification, mesh independence test, mesh sensitivity analysis

@booklet{EasyChair:8876,
  author    = {Ramesh Timsina and Zahir Barahmand},
  title     = {Mesh Sensitivity Analysis of an Entrained Flow Biomass Gasifier: a CPFD Study},
  howpublished = {EasyChair Preprint 8876},
  year      = {EasyChair, 2022}}