Journal
FUEL
Volume 278, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.fuel.2020.118251
Keywords
Eulerian; CFD; Biomass; Fouling; Combustion
Categories
Funding
- project 'Fouling en Superficies de Transferencia de Calor: Mitigacion y/o Regeneracion. Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Convocatoria 2017, 2018-2020' [ENE2017-87855-R]
- Ministry of Economy, Industry and Competitiveness (Spain) [BES-2016-076785]
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Driven by a society that is becoming more aware of the environment over the recent decades, biomass use has increased on both the domestic and industrial scales. In addition, the ease of the use of biomass as a transition fuel in non-renewable solid fuel installations has contributed to this rising trend. Nevertheless, the use of biomass presents serious operational problems, especially in facilities not designed for biomass combustion or in cases of low-quality biomass. To manage these issues, CFD codes have become a powerful tool that provides valuable data on the phenomena involved inside facilities. Previous works of the authors examine the fouling phenomenon through a deeply optimized Euler-Lagrange framework; nevertheless, the computational effort is still high and not suitable for highly parallelised environments. Due to the physical limitations, the IT industry research on the core density inside each die is evolving faster than that on the individual core performance. Therefore, parallelisation has become of great relevance when coding. This work begins a new line of research on the study of the phenomenon of fouling in biomass combustion systems; however, this study is developed entirely in an Eulerian framework, guaranteeing a greater performance. The new full Eulerian-fouling model is based on the 3D-EBITCOM (3D Eulerian Biomass Transient Combustion Model) from the University of Vigo. The initial results are compared against experimental and previous modelling data obtained in an experimental burner, and they show an overall lower computational effort and better response in most scenarios.
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