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Reactor network analysis of biomass gasification in fluidized beds

Başlık çevirisi mevcut değil.

  1. Tez No: 711852
  2. Yazar: LEON LONİ BERKEL
  3. Danışmanlar: PROF. ALESSANDRO STAGNİ, PROF. TİZİANO FARAVELLİ
  4. Tez Türü: Yüksek Lisans
  5. Konular: Metalurji Mühendisliği, Metallurgical Engineering
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2021
  8. Dil: İngilizce
  9. Üniversite: Polıtecnıco Dı Mılano
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Belirtilmemiş.
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: Belirtilmemiş.

Özet

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Özet (Çeviri)

With the increasing environmental concerns, utilization of clean energy sources and reduction of pollutants have become a vital issue. Due to its high availability and integrability to existing infrastructure, biomass is an important alternative that can be used in gasification and combustion units. However, predictive modelling of these reactors is challenging due to various phenomena occurring simultaneously at different scales. CFD simulations are employed for predicting main gas species, but pollutant predictions require detailed kinetic mechanisms and application of these mechanisms in CFD simulations become usually unfeasible due to required computation times. Equivalent reactor network models are a viable option in these cases. With this approach, reactor networks are created by using simple reactor models and directing the flow between each reactor. The fluid dynamics are simplified, but detailed chemical kinetic mechanisms can be used with much more feasible computation times, allowing also the prediction of pollutants. In this work, an efficient reactor network solver, NetSMOKE, was developed in C++, which is capable of managing networks with both solid and gas reactors. The developed solver was compared with other solvers and its improvements were analysed and discussed. Model equations of units were reviewed, and various network solution strategies were examined. NetSMOKE was found to be fast with improved functionality and flexibility over the previous reactor network solvers. Finally, reactor network analysis was done on some case studies in which fluidized bed reactors were used for biomass gasification. Networks were created by either utilizing CFD data or using fluidization models, and then solved with NetSMOKE. In some cases, good agreement between experimental data and simulation results were observed, while in others, significant differences were present. Effects of various parameters on reactor network model were also discussed.

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