The key for sodium-rich coal utilization in entrained flow gasifier: The role of sodium on slag viscosity-temperature behavior at high temperatures

Chen, Xiao; Kong, Lingxue; Bai, Jin; Dai, Xin; Li, Huaizhu; Bai, Zongqing; Li, Wen

doi:10.1016/j.apenergy.2017.10.020

Cited by 85 publications

(20 citation statements)

References 51 publications

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“…Slag viscosity is determined by the slag composition and temperature. It has previously been shown that the viscosity increased with the increasing content of SiO 2 [36], while alkali decreased the viscosity [37]. Predicting the slag viscosity was, however, out of the scope of the current paper.…”

Section: Bottom Ashmentioning

confidence: 86%

Oxygen-Blown Gasification of Pulp Mill Bark Residues for Synthetic Fuel Production

2021

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Synthetic fuel production via gasification of residual biomass streams from the pulp and paper industry can be an opportunity for the mills to enable improved resource utilization and at the same time reduce the production of excess heat. This paper summarizes initial oxygen-blown gasification experiments with two bark residues from a European pulp and paper mill, i.e., a softwood bark and a hardwood bark. The gasification process was characterized by measuring syngas yields and process efficiency to find optimum operating conditions. In addition, impurities in the syngas and ash behavior were characterized. Maximum yields of CO and H2 were obtained from softwood bark and amounted to approximately 29 and 15 mol/kg fuel, respectively. Optimum cold gas efficiency was achieved at an oxygen stoichiometric ratio of λ = 0.40 and was approximately 76% and 70% for softwood bark and hardwood bark, respectively. Increased λ had a reducing effect on pollutants in the syngas, e.g., higher hydrocarbons, NH3, HCl, and soot. The situation for sulfur species was more complex. Evaluation of the bark ashes indicated that slag formation could start already from 800 °C. Furthermore, a non-intrusive laser diagnostics technique gave rapid feedback on the millisecond scale. Measured syngas temperature and water content were in good agreement with the applied reference methods.

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Section: Bottom Ashmentioning

confidence: 86%

Oxygen-Blown Gasification of Pulp Mill Bark Residues for Synthetic Fuel Production

2021

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“…If the ash was naturally formed, it contained all the components listed in the table. The artificially prepared samples were meant to match the compounds of hazardous waste or to simulate slags with additions of fluxing agents [7,21,44]. In order to investigate the influence of a specific or several components on the viscosity, and make the measurement easier, samples with less components were often artificially prepared to simplify the ash system [18,25,49].…”

Section: Model Development For the Classification Of Slagsmentioning

confidence: 99%

Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Lin

Dai

et al. 2020

Energies

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Molten gasification is considered as a promising technology for the processing and safe disposal of hazardous wastes. During this process, the organic components are completely converted while the hazardous materials are safely embedded in slag via the fusion-solidification-vitrification transformation. Ideally, the slag should be glassy with low viscosity to ensure the effective immobilization and steady discharge of hazardous materials. However, it is very difficult to predict the characteristics of slag using existing empirical equations or conventional mathematical methods, due to the complex non-linear relationship among the phase transformation, vitrification transition and chemical composition of slag. Equipped with a strong nonlinear mapping ability, an artificial neural network may be able to predict the properties of slags if a large amount of data is available for training. In this work, over 10,000 experimental data points were used to train and develop a slag classification model (glassy vs. non-glassy) based on a neural network. The optimal structure of the neural network was figured out and validated. The results suggest that the classification accuracy for the independent test samples reached 93.3%. Using 1 and 0 as model inputs to represent mildly reducing and inert atmospheres, a double hidden layer structure in the neural network enabled the accurate classification of slags under various atmospheres. Furthermore, the neural network for the prediction of glassy slag viscosity was optimized; it featured a double hidden layer structure. Under a mildly reducing atmosphere, the absolute error from the independent test data was generally within 4 Pa·s. By adding a gas atmosphere into the input of the neural network using a simple normalization method, a multi-atmosphere slag viscosity prediction model was developed. Said model is much more accurate than its counterpart that does not consider the effect of the atmosphere. In summary, the artificial neural network proved to be an effective approach to predicting the slag properties under different atmospheres. The data-driven models developed in this work are expected to facilitate the commercial deployment of molten gasification technology.

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“…Consequently, the liquid slag is discharged through the down pipe into the water-cooled pool of the quench chamber to form gasification residue slag. 6 For the stable operation and long-term running of opposed multiburner CWS gasification, it is very critical that the mineral matters in coal melt and successfully flew out of the gasifier as liquid slag. Therefore, the melting properties of coal ash and the slag characteristics such as viscosity and flow behavior under high temperature, as well as the char-slag transition, are necessary and significant for further research.…”

Section: Introductionmentioning

confidence: 99%

Understanding the slag transformation behaviors during entrained‐flow gasification based on comparative analysis of slag properties

Wang

Bao

et al. 2021

Asia-Pacific J Chem Eng

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In this work, four slag samples were collected from the OMB CWS gasification, and the mineral behavior and morphology were studied to explore the formation mechanism of blockage slag. Results showed that amorphous phase is dominant in all slag samples, which was mainly glassy substances rich in low-temperature eutectic of iron. The precipitation of metallic iron and the crystals of SiC, calcite, and quartz were found in slags which were taken from the bottom of the combustion chamber (S-b). The quench slag collected from stable operation conditions (S-s) had a low content of quartz crystalline. While slag from the down pipe of the quench chamber (S-b) and bulk slag from the water-cooled pool (S-p) had observed the precipitation of crystals. Comparing to S-s, carbon matters in S-b had a higher order degree of carbon structure. By comparing the slag sample obtained during stable operation (S-s) with slag blocking occurs (S-b, S-d, S-p), it is found that the blockage of the OMB CWS gasifier was strongly related to unreacted residual carbon and the high content of sodium and iron in coal. They will interact with each other and form small number of crystals and most of the amorphous material.

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The key for sodium-rich coal utilization in entrained flow gasifier: The role of sodium on slag viscosity-temperature behavior at high temperatures

Cited by 85 publications

References 51 publications

Oxygen-Blown Gasification of Pulp Mill Bark Residues for Synthetic Fuel Production

Oxygen-Blown Gasification of Pulp Mill Bark Residues for Synthetic Fuel Production

Prediction of Slag Characteristics Based on Artificial Neural Network for Molten Gasification of Hazardous Wastes

Understanding the slag transformation behaviors during entrained‐flow gasification based on comparative analysis of slag properties

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