| 1. |
- Zhao, Z., et al.
(författare)
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CFD simulation of soot generation during biomass gasification in a cyclone gasifier
- 2024
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Ingår i: Fuel. - : Elsevier Ltd. - 0016-2361 .- 1873-7153. ; 364
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Tidskriftsartikel (refereegranskat)abstract
- Soot generation is a challenging issue in high-temperature biomass gasification, which reduces the biomass conversion rate and leads to contamination of the reactor. To provide new means and insights to optimize gasification processes, the soot generation during biomass gasification in a cyclone reactor is studied here by establishing a novel biomass gasification and soot formation model to improve the accuracy attainable in numerical predictions of spatio-temporal soot evolution. The new method is validated by comparing it with gasification experiments in two reactor configurations. A good performance in capturing the overall soot generation and light gas yield of the current model is obtained in the simulations of an entrained flow reactor compared with experimental data. Besides, the biomass gasification behavior in this entrained flow reactor is systematically studied by reviewing the tar, precursor, and soot mass fraction evolution in the reactor under different steam/carbon ratios, gasification temperatures, and air excess ratios with the new model. Furthermore, the influence of varying air equivalence ratios, the operation temperature and the fuel moisture on the soot generation in a cyclone gasifier, as well as the ability of the proposed model to reflect such influences, are also discussed. Numerical simulations demonstrate the existence of an optimal operation condition for the cyclone gasifier in terms of the soot generation. The current work thus provides a useful tool for analyzing the mechanism of soot formation at the reactor scale.
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| 2. |
- Zhou, R., et al.
(författare)
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Maritime Disruption Impact Evaluation Using Simulation and Big Data Analytics
- 2022
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Ingår i: Proceedings - Winter Simulation Conference. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350309713 ; , s. 784-795
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Konferensbidrag (refereegranskat)abstract
- Disruptions in maritime networks may cause significant financial burden and damage to business. Recently, some international ports have been experiencing unprecedented congestions due to the COVID19 pandemic and other disruptions. It is paramount for the maritime industry to further enhance the capability to assess and predict impacts of disruptions. With more data available from industrial digitization and more advanced technologies developed for big data analytics and simulation, it is possible to build up such capability. In this study, we developed a discrete event simulation model backed with big data analytics for realistic and valid inputs to assess impacts of the Suez Canal blockage to the Port of Singapore. The simulation results reveal an interesting finding that, the blockage occurred in the Suez Canal can hardly cause significant congestion in the Port of Singapore. The work can be extended to evaluate impacts of other types of disruptions, even occurring concurrently.
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