Yazar "Zhang, Xiaochun" seçeneğine göre listele

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    Arsenic partitioning behavior during sludge co-combustion: Thermodynamic equilibrium simulation
    (Springer, 2019) Liu, Jingyong; Xie, Candie; Xie, Wuming; Zhang, Xiaochun; Chang, KenLin; Büyükada, Musa; Kuo, Jiahong; Evrendilek, Fatih
    Using the computation method of thermodynamic equilibrium, effects of sewage sludge (SS) co-combustion conditions and interactions with Fe2O3, SiO2, CaO and Al2O3 on migration and transformation of arsenic (As) were simulated in oxy-fuel (CO2/O-2) and air (N-2/O-2) atmospheres. Arsenic mainly existed as As(s), As-4(g), As2O5(s), As4O6(g) and AsO(g) and volatilized more easily in reducing than oxidizing atmosphere. Increased O-2 concentration slowed down the formation rate of AsO(g), thus reducing the volatilization rate of As. With the increased pressure, the conversion rate of As2O5(s) into As4O6(g) accelerated. In the multi-chemical system of SiO2, Al2O3 and CaO, As reacted with CaO and Al2O3 to form AlAsO4(s) and Ca-3(AsO4)(2)(s) which inhibited As volatilization. SiO2 prevented As from reacting with CaO to generate Ca-3(AsO4)(2)(s). Fe2O3 affected reactions between Al2O3(CaO) and As which inhibited As volatilization. In the whole SS co-combustion system, As reacted with O-2 but had a weak affinity with Cl and with no arsenic chlorides observed.
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    Co-combustion of sewage sludge and coffee grounds under increased O-2/CO2 atmospheres: Thermodynamic characteristics, kinetics and artificial neural network modeling
    (Elsevier Sci Ltd, 2018) Chen, Jiacong; Xie, Candie; Liu, Jingyong; He, Yao; Xie, Wuming; Zhang, Xiaochun; Chang, Kenlin; Büyükada, Musa; Evrendilek, Fatih
    (Co-)combustion characteristics of sewage sludge (SS), coffee grounds (CG) and their blends were quantified under increased O-2/CO2 atmosphere (21, 30, 40 and 60%) using a thermogravimetric analysis. Observed percentages of CG mass loss and its maximum were higher than those of SS. Under the same atmospheric O-2 concentration, both higher ignition and lower burnout temperatures occurred with the increased CG content. Results showed that ignition temperature and comprehensive combustion index for the blend of 60% SS-40% CG increased, whereas burnout temperature and co-combustion time decreased with the increased O-2 concentration. Artificial neural network was applied to predict mass loss percent as a function of gas mixing ratio, heating rate, and temperature, with a good agreement between the experimental and ANN-predicted values. Activation energy in response to the increased O-2 concentration was found to increase from 218.91 to 347.32 kJ.mol(-1) and from 218.34 to 340.08 kJ.mol(-1) according to the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods, respectively.
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    Co-combustion thermal conversion characteristics of textile dyeing sludge and pomelo peel using TGA and artificial neural networks
    (Elsevier Sci Ltd, 2018) Xie, Candie; Liu, Jingyong; Zhang, Xiaochun; Xie, Wuming; Sun, Jian; Chang, Kenlin; Kuo, Jiahong; Büyükada, Musa; Evrendilek, Fatih
    Co-combustion characteristics of textile dyeing sludge (TDS) and pomelo peel (PP) under O-2/N-2 and O-2/CO2 atmospheres were investigated using a thermogravimetric analysis (TGA) and artificial neural networks. 30% O-2/70% CO2 and air atmospheres led to a similar co-combustion performance. Increases in O-2 concentration and PP significantly improved the oxy-fuel co-combustion performance of TDS. Principal component analysis was applied to reduce the dimensionality of differential TGA curves and to identify the principal reactions. The interaction between TDS and PP occurred mainly at 490-600 degrees C, thus improving the process of residue co combustion. Radial basis function was found to have more reliable and robust predictions of TGA under different O-2/CO2 atmospheres than did Bayesian regularized network. Regardless of Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) methods used, the lowest mean value of apparent activation energy (155.4 kJ.mol(-1) by FWO and 153.2 kJ.mol(-1) by KAS) was obtained under the 30% O-2/70% CO2 atmosphere.
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    Influence of catalysts on co-combustion of sewage sludge and water hyacinth blends as determined by TG-MS analysis
    (Elsevier Sci Ltd, 2018) Huang, Limao; Xie, Candie; Liu, Jingyong; Zhang, Xiaochun; Chang, KenLin; Kuo, Jiahong; Sun, Jian; Büyükada, Musa; Evrendilek, Fatih
    Effects of the three metal carbonates (K2CO3, Na2CO3, and MgCO3) were quantified on catalytic co-combustion of the sewage sludge and water hyacinth (SW) blend using a thermogravimetric-mass spectrometric (TG-MS) analysis and kinetics modeling. The main dominating steps of the catalysts were the organic volatile matter release and combustion stage. Weighted mean values of activation energy (E-m) were estimated at 181.18 KJ . mol(-1), 199.76 KJ . mol(-1), 138.76 KJ . mol(-1), and 177.88 KJ . mol(-1) for SW, SW + 5% K2CO3, SW + 5% Na2CO3, and SW+ 5% MgCO3, respectively. The lowest E-m occurred with SW+ 5% Na(2)CO3. Overall, catalyst effect on co-combustion appeared to be negligible as indicated by Gibbs free energy (Delta G). The normalized intensities of SW+ MgCO3 were strongest. The addition of Na2CO3 and MgCO3 to SW increased flue gases emissions (CO2, NO2, SO2, HCN, and NH3) of SW, whereas the addition of K2CO3 to SW reduced flue gases emissions from the entire combustion process.
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    Kinetics, thermodynamics, gas evolution and empirical optimization of (co-) combustion performances of spent mushroom substrate and textile dyeing sludge
    (Elsevier Sci Ltd, 2019) Huang, Jianli; Liu, Jingyong; Kuo, Jiahong; Xie, Wuming; Zhang, Xiaochun; Büyükada, Musa; Evrendilek, Fatih
    Spent mushroom substrate (SMS) and textile dyeing sludge (TDS) were (co-)combusted in changing heating rates, blend ratios and temperature. The increased blend ratio improved the ignition, burnout and comprehensive combustion indices. A comparison of theoretical and experimental thermogravimetric curves pointed to significant interactions between 350 and 600 degrees C. High content of Fe2O3 in TDS ash may act as catalysis at a high temperature. Ignition activation energy was lower for TDS than SMS due to its low thermal stability. 40% SMS appeared to be the optimal blend ratio that significantly decreased the activation energy, as was verified by the response surface methodology. D3 model best described the (co-)combustions. SMS led to more NO and NO2 emissions at about 300 degrees C and less HCN emission than did TDS. The addition of 40% SMS to TDS lowered SO2 emission. The co-combustion of TDS and SMS appeared to enhance energy generation and emission reduction.
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    Kinetics, thermodynamics, gas evolution and empirical optimization of cattle manure combustion in air and oxy-fuel atmospheres
    (Pergamon-Elsevier Science Ltd, 2019) Zhang, Junhui; Liu, Jingyong; Evrendilek, Fatih; Xie, Wuming; Kuo, Jiahong; Zhang, Xiaochun; Büyükada, Musa
    Thermogravimetric (TG) and TG-Fourier transform infrared (FTIR) analyses were performed to quantify the comparative performances of cattle manure combustion in air (N-2/O-2) and oxy-fuel (CO2/O-2) atmospheres at four heating rates. Out of the distributed activation energy model, Flynn-Wall-Ozawa (FWO), Friedman and Starink methods (R-2 >= 0.86), the FWO method on average led to the highest R-2 value with the lowest activation energy. On average, the combustion in the oxy-fuel atmosphere had the lowest activation energy (180.6 kJ/mol) with the highest R-2 value (0.9812). Our TG-FTIR results showed that CO2 was the major gas evolution of the cattle manure combustion. Interaction effects of atmosphere type by heating rate on the multiple responses of remaining mass, derivative TG, and differential scanning calorimetry were found to be significant (p < 0.001). The joint optimization of the three responses was achieved at 424.6 degrees C in the air atmosphere at the heating rate of 40 K/min.
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    TG-FTIR and Py-GC/MS analyses of pyrolysis behaviors and products of cattle manure in CO2 and N-2 atmospheres: Kinetic, thermodynamic, and machine-learning models
    (Pergamon-Elsevier Science Ltd, 2019) Zhang, Junhui; Liu, Jingyong; Evrendilek, Fatih; Zhang, Xiaochun; Büyükada, Musa
    The increased amounts of manure have become an issue of environmental management due to the rapid growth of livestock industry. This study quantified the pyrolytic performance and gaseous products of cattle manure using (derivative) thermogravimetric ((D)TG), Fourier transform infrared spectrometry (FTIR) and pyrolysis-gas chromatography and mass spectrometry (Py-GC/MS) analyses. The pyrolysis process of cattle manure was determined to occur in three stages, with the main reaction in the range of 161-600 degrees C. The N-2 atmosphere was found to be more favorable for the release of volatiles according to a higher comprehensive pyrolysis index in the range of 30 - 600 degrees C. The lower activation energies were shown to be required in the CO2 than N-2 atmosphere. Random forests algorithm outperformed multiple linear regression, gradient boosting machine, and artificial neural networks for the prediction of mass loss due to the cattle manure pyrolysis. The main gaseous products were CO2, phenol (23.23%), and furans (12.98%). The theoretical and practical guidance for the energy and resource utilization of cattle manure was provided by this study.