EFFICIENT DESULFURIZATION IN O<sub>2</sub>/CO<sub>2</sub>COMBUSTION: DEPENDENCE ON COMBUSTION CONDITIONS AND SORBENT PROPERTIES

Líu, Hao; Yao, Hong; Yuan, Xing; Xu, Xin; Fan, Yibo; Ando, Takashi; Okazaki, Ken

doi:10.1080/00986445.2011.633288

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…In addition, extreme weather events already account for 91% of all major disasters and 77% of recorded economic losses from natural disasters [5]. To avoid this situation, greenhouse gas emissions-mainly produced by the combustion of fossil fuels-must be dramatically reduced in the coming years [6][7][8]. In the same direction, the European Union (EU) has planned a linear reduction factor of 2.2% for CO 2 emissions over the next decade (i.e., 2021-2030) [9].…”

Section: Introductionmentioning

confidence: 99%

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

et al. 2020

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In this paper, response surface methodology (RSM) designs and an artificial neural network (ANN) are used to obtain the optimal conditions for the oxy-combustion of a corn–rape blend. The ignition temperature (Te) and burnout index (Df) were selected as the responses to be optimised, while the CO2/O2 molar ratio, the total flow, and the proportion of rape in the blend were chosen as the influencing factors. For the RSM designs, complete, Box–Behnken, and central composite designs were performed to assess the experimental results. By applying the RSM, it was found that the principal effects of the three factors were statistically significant to compute both responses. Only the interactions of the factors on Df were successfully described by the Box–Behnken model, while the complete design model was adequate to describe such interactions on both responses. The central composite design was found to be inadequate to describe the factor interactions. Nevertheless, the three methods predicted the optimal conditions properly, due to the cancellation of net positive and negative errors in the mathematical adjustment. The ANN presented the highest regression coefficient of all methods tested and needed only 20 experiments to reach the best predictions, compared with the 32 experiments needed by the best RSM method. Hence, the ANN was found to be the most efficient model, in terms of good prediction ability and a low resource requirement. Finally, the optimum point was found to be a CO2/O2 molar ratio of 3.3, a total flow of 108 mL/min, and 61% of rape in the biomass blend.

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Section: Introductionmentioning

confidence: 99%

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

et al. 2020

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“…The characteristics of combustion, heat transfer, burnout, pollutants, and slagging under oxy‐fuel combustion (Oxy) conditions are very different from those under air combustion (Air) conditions. Many scholars have studied the coal combustion and pollutant emission characteristics of oxy‐fuel boilers . However, there has been little information about the deposition characteristics of ash .…”

Section: Introductionmentioning

confidence: 99%

“…Many scholars have studied the coal combustion and pollutant emission characteristics of oxy-fuel boilers. [6][7][8][9][10][11][12][13][14][15][16] However, there has been little information about the deposition characteristics of ash. 17,18 Coal contains a certain amount of inorganic material.…”

Section: Introductionmentioning

confidence: 99%

Experimental study of ash formation under O₂/CO₂ combustion

Zhang

Liao

et al. 2019

Greenhouse Gases

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Oxy‐fuel combustion technology has been recognized as the most promising technology for controlling CO2 emission in coal‐fired boilers. The slagging characteristics of oxy‐fuel combustion (O2/CO2) are very different from those of air combustion (O2/N2). In this paper, an ash sample collection of Shenhua coal with high Ca and Fe content was carried out in a muffle furnace and a tubular furnace under different conditions. The ash melting point, X‐ray diffraction (XRD) and scanning electron microscopy (SEM) were used for characterization. The characteristics of Shenhua coal ash slagging in different atmospheres were studied, and the mineral transformation trend was obtained. It was concluded that the melting point of the ash samples under oxy‐fuel combustion was lower than that under an air atmosphere, and the slagging tendency was enhanced under conditions of high oxygen combustion. Under oxy‐fuel combustion, CaCO3 was found. This did not occur under an air atmosphere. The atmosphere has no obvious effect on the crystal minerals of Fe. The decrease in high melting point oxide, the formation of carbonate, and the increase in glass state and sulfate under an oxy‐fuel atmosphere all make the ash melting point lower than under an air atmosphere. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

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Comparative Energy and Emission Analysis of Oxy-Combustion and Conventional Air Combustion

2021

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EFFICIENT DESULFURIZATION IN O₂/CO₂COMBUSTION: DEPENDENCE ON COMBUSTION CONDITIONS AND SORBENT PROPERTIES

Cited by 3 publications

References 34 publications

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

Experimental study of ash formation under O₂/CO₂ combustion

Comparative Energy and Emission Analysis of Oxy-Combustion and Conventional Air Combustion

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EFFICIENT DESULFURIZATION IN O2/CO2COMBUSTION: DEPENDENCE ON COMBUSTION CONDITIONS AND SORBENT PROPERTIES

Cited by 3 publications

References 34 publications

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

A Comparison between Several Response Surface Methodology Designs and a Neural Network Model to Optimise the Oxidation Conditions of a Lignocellulosic Blend

Experimental study of ash formation under O2/CO2 combustion

Comparative Energy and Emission Analysis of Oxy-Combustion and Conventional Air Combustion

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EFFICIENT DESULFURIZATION IN O₂/CO₂COMBUSTION: DEPENDENCE ON COMBUSTION CONDITIONS AND SORBENT PROPERTIES

Experimental study of ash formation under O₂/CO₂ combustion