Application of a new ash fusion test to Theodore coals

Kahraman, H.; Bos, Frans; Reifenstein, A.P.; Coin, C.

doi:10.1016/s0016-2361(98)00004-0

Cited by 18 publications

(10 citation statements)

References 2 publications

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“…23−28 Therefore, many scholars have summed up the prediction formulas for FTs based on the chemical composition of coal ash. Xu et al, 29 based on 181 kinds of coal ash samples, established the empirical formula 1 for FT. Kahraman et al 30 (2)…”

Section: Resultsmentioning

confidence: 99%

“…The research shows that the FT can reduce with increasing basic components, while it can increase with increasing acidic components; however, since the complexity of coal ash composition and the content of each component change substantially, there is an uncertain quantitative relationship between the FT and ash composition. − Therefore, many scholars have summed up the prediction formulas for FTs based on the chemical composition of coal ash. Xu et al, based on 181 kinds of coal ash samples, established the empirical formula for FT. Kahraman et al established the empirical formula for FT based on Australian coal ash samples. The samples that had 15, 25, and 35% DCLR were used to verify the prediction accuracy of the BP model and empirical formulas, and the results are shown in Figure . As shown in Figure a, the results of BP prediction are consistent with the experimental results and significantly better than the prediction of the empirical formulas, which directly verifies the credibility of the BP model.…”

Section: Resultsmentioning

confidence: 99%

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Influence of the Direct Coal Liquefaction Residue on the Fusion Characteristics of Jincheng Coal with a High Ash Fusion Temperature

Xie

2019

Energy Fuels

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Nowadays, entrained flow bed gasification technology is the foundation of the modern coal chemical industry, while its liquid slag discharge process generally requires the flow temperature (FT) of coal ash to be less than 1400 °C. To reduce the ash fusion temperature (AFT) of high AFT coal and to make full use of the direct coal liquefaction residue (DCLR), Jincheng coal (JC) with a high AFT and Shenhua DCLR with a low AFT are used to prepare blended samples. The influence of the DCLR on the AFT of JC is explored using an intelligent ash fusion point tester, ternary phase diagrams, differential scanning calorimetry (DSC), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results show that the addition of DCLR can reduce the AFT of JC effectively; when the amount of DCLR added is higher than 25%, the FT of the mixed coal ash is lower than 1400 °C, which meets the requirement of a liquid slag discharge process. The back propagation (BP) neural network prediction model based on the FT data of partial coal blending ratio experiments has a better prediction accuracy than empirical formulas. The results of DSC show that the heat capacity of blended coal ash varies significantly ranging from 1000 to 1300 °C; at the same time, the results of XRD and SEM also show that a series of chemical reactions among ash compositions of blended coal happen between 1000 and 1200 °C. The chemical reactions mainly include the decomposition of CaSO 4 into CaO and the reduction of Fe 2 O 3 into FeO. Meanwhile, CaO and FeO react with SiO 2 and Al 2 O 3 to produce a series of new calcium/iron-containing aluminosilicates (anorthite (CaAl 2 Si 2 O 8 ), fayalite (Fe 2 SiO 4 ), hercynite (FeAl 2 O 4 ), etc.), and CaO and FeO in coal ash have a significant inhibitory effect on the generation of mullite (Al 6 Si 2 O 13 ). FeO in coal ash can easily form glassy state substances and cause the sintering of coal ash. The reason for the higher AFT of JC is that its ash contains a large amount of Al 6 Si 2 O 13 at high temperatures, and the reason for the lower AFT of the DCLR is that its ash has a large amount of calcium/iron-containing aluminosilicates, especially rich in a large amount of gehlenite (Ca 2 Al 2 SiO 7 ). In addition, the calcium/ iron-containing aluminosilicates in coal ash have a certain positive synergistic effect on the reduction of FT.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Influence of the Direct Coal Liquefaction Residue on the Fusion Characteristics of Jincheng Coal with a High Ash Fusion Temperature

Xie

2019

Energy Fuels

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“…The curve is fitted by using various algorithms, including stepwise regression method [19][20][21][22], piecewise fitting method [23,24], regression analysis fitting [25], partial least squares regression [26,27], least squares regression [28].…”

Section: Linear Regression Methodsmentioning

confidence: 99%

The Use of an Improved LSSVM and Joint Normalization on Temperature Prediction of Gearbox Output Shaft in DFWT

et al. 2017

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Abstract:In the working process of Double-Fed Wind Turbines (DFWT), it is very important to monitor and predict the temperature of the high-speed output shaft of the gearbox timely and effectively. Support vector machine has more advantages in the temperature prediction of wind turbines. Least squares support vector machine is suitable for online prediction due to reducing the computational complexity of support vector machine. In order to solve the sparsity of least squares support vector machine, an improved least squares support vector machine based on pruning algorithm is proposed in this paper to predict the temperature of the high-speed output shaft of gearbox using the practical data of Double-Fed Wind Turbines. At the same time, in order to improve the prediction accuracy and to solve the problem of few links between different feature parameters in common normalization method, the paper uses the method of joint normalization to preprocess the data. The principal component analysis is used to reduce the dimension of the data. Particle swarm optimization algorithm is used to optimize the parameters of the pruning least squares support vector machine. The proposed model that is established in this paper is a new model to forecast the temperature of the high-speed output shaft. The results show that its prediction accuracy is higher than that of other algorithms.

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“…One of the main limitations of ash fusion test is that it is subjective and has poor repeatability [36]. Kahraman et al reported that the initial deformation temperature (IDT) can vary as much as 400 K when determined by two different operators [36].…”

Section: Prediction Of Slag Formationmentioning

confidence: 99%

A Critical Review of Mineral Matter Related Issues during Gasification of Coal in Fixed, Fluidized, and Entrained Flow Gasifiers

Krishnamoorthy

Pisupati

2015

Energies

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Gasification of coal is gaining more popularity due to its clean operation, and its ability to generate products for various markets. However, these technologies are not widely commercialized due to reliability and economic issues. Mineral matter in coal plays an important role in affecting the availability/reliability of a gasifier. Agglomeration in the bed, slag mobility and blockage of the syngas exit section are some of the operations related concerns in fixed-bed gasifiers, while ash deposition and sudden defluidization are the major concerns in fluidized bed gasifiers. In the case of entrained flow gasifiers, syngas cooler fouling and blockage, corrosion and erosion of refractory, and slag mobility are some of the major issues affecting the operations and the reliability of the gasifier. This review is aimed at critically examining various mineral matter related issues contributing to the operation and reliability problems in three types of generic gasifiers (fixed bed, fluidized bed and entrained flow gasifiers). Based on the review, some strategies to counter the potential mineral matter related issues are presented.

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Application of a new ash fusion test to Theodore coals

Cited by 18 publications

References 2 publications

Influence of the Direct Coal Liquefaction Residue on the Fusion Characteristics of Jincheng Coal with a High Ash Fusion Temperature

Influence of the Direct Coal Liquefaction Residue on the Fusion Characteristics of Jincheng Coal with a High Ash Fusion Temperature

The Use of an Improved LSSVM and Joint Normalization on Temperature Prediction of Gearbox Output Shaft in DFWT

A Critical Review of Mineral Matter Related Issues during Gasification of Coal in Fixed, Fluidized, and Entrained Flow Gasifiers

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