Co-combustion thermal conversion characteristics of textile dyeing sludge and pomelo peel using TGA and artificial neural networks

Xie, Candie; Liu, Jingyong; Zhang, Xiaochun; Xie, Wei; Sun, Jian; Chang, Ken-Lin; Kuo, Jia‐Hong; Xie, Wenhao; Liu, Chao; Sun, Shuiyu; Büyükada, Musa; Evrendilek, Fatih

doi:10.1016/j.apenergy.2017.12.084

Cited by 142 publications

(21 citation statements)

References 50 publications

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“…Wang et al [11] indicated that a synergistic effect between straw and sludge in fixed-bed reactors was present, and concluded that the most optimal blend was formed when 60% sludge was added. Further, Xie et al [12] revealed that synergy occurred at high temperatures when 90% sludge was blended with pomelo peel. This is consistent with the results of Huang et al [13], who used sludge and a mushroom matrix for co-combustion and their results found that the synergy was most pronounced at 350-600°C during co-firing.…”

Section: Introductionmentioning

confidence: 99%

Synergistic effects of co‐combustion of sewage sludge and corn stalk and the resulting gas emission characteristics

Guo

Han

Wang

et al. 2020

IET Renewable Power Generation

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Increasing discharge of sewage sludge is a threat to the ecological environment, and sludge treatment via combustion is the most feasible alternative. However, the low calorific value and high-water content of raw sludge results in poor firing performance and increases the risk of environmental pollution. Recently, co-combustion has emerged as a more environment-friendly technology. Herein, the combustion behaviours of sewage sludge, corn stalk and their mixture at four heating rates were studied via thermogravimetric experiments. Results yielded the division of weight loss into three stages for corn stalk: dehydration, combustion of volatiles and combustion of fixed carbon; four stages were identified for sewage sludge and the mixture of sludge and stalk: dehydration, combustion of volatiles, combustion of fixed carbon and thermal decomposition of a small amount of minerals. Synergistic analyses found that with a 60% blending ratio of sewage sludge, interaction between the components in the high-temperature range was greatly promoted. Gas emission characteristics showed that CO 2 was the main product during (co-)combustion, while the NO x emissions at low (or high) temperatures for the blend were higher (or lower) than the theoretical values. Temperature had little effect on H 2 S emissions, though it significantly affected SO 2 emissions during co-combustion. V CS gas emissions when CS is burned SS E 60% actual amounts of released gas with sludge blending ratios of 60% SS C 60% theoretical amounts of released gas with sludge blending ratios of 60%

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Section: Introductionmentioning

confidence: 99%

Synergistic effects of co‐combustion of sewage sludge and corn stalk and the resulting gas emission characteristics

Guo

Han

Wang

et al. 2020

IET Renewable Power Generation

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“…After training using the experimental data from the TGA, the optimal ANN model provided a good agreement between the experimental and predicted values. Xie et al 141 compared the performance of RBF and BPNNs on the prediction of TG curves of oxy-co-combustion of textile dyeing sludge and pomelo peel, with the mixing ratio, heating rates, combustion atmosphere and temperature as the inputs and mass loss percent as the output. The results indicated that BPNNs gave a better prediction than that of RBF neural networks 141 .…”

Section: Machine Learning In Oxyfuel and Chemical-looping Combustionmentioning

confidence: 99%

“…Xie et al 141 compared the performance of RBF and BPNNs on the prediction of TG curves of oxy-co-combustion of textile dyeing sludge and pomelo peel, with the mixing ratio, heating rates, combustion atmosphere and temperature as the inputs and mass loss percent as the output. The results indicated that BPNNs gave a better prediction than that of RBF neural networks 141 . Govindan et al 142 used trained ANNs, using TGA to predict the sample mass loss percentage of oxy-fuel combustion of calcined pet coke, with the predictions obtained from the model showing a high degree of accuracy, with a coefficient of determination (R 2 ) of 0.99.…”

Section: Machine Learning In Oxyfuel and Chemical-looping Combustionmentioning

confidence: 99%

Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – a state-of-the-art review

Yan

Borhani

Subraveti

et al. 2021

Energy Environ. Sci.

130

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“…Furthermore, to evaluate the combustion performance of the raw samples and the hydrochars, the comprehensive combustion index (CCI) and combustion stability index (CSI) were calculated using Eqs. ( 5) and ( 6), respectively [3,[27][28][29].…”

Section: Thermal Analysismentioning

confidence: 99%

Upgrading the fuel properties of hydrochar by co-hydrothermal carbonisation of dairy manure and Japanese larch (Larix kaempferi): product characterisation, thermal behaviour, kinetics and thermodynamic properties

Aliyu

Iwabuchi

Itoh³

2021

Biomass Conv. Bioref.

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This study investigated co-hydrothermal carbonisation (co-HTC) of dairy manure (DM) and wood shavings from Larix kaempferi, commonly known as the Japanese larch (JL) to enhance the fuel properties of the resulting hydrochar. The JL was mixed with the DM at 25, 50 and 75 wt.% ratios. Co-HTC was conducted at 260 °C for 20 min. The resulting hydrochars were characterised based on the physicochemical properties and the thermal behaviour. Results showed that the hydrochar solid biofuel properties improved as the ratio of JL was increased. The produced hydrochars were in the region of lignite and closed to the region of the coal with increased fixed carbon, carbon contents and lowered H/C and O/C ratios. Hydrochar with ash content of 7.2 ± 0.5% was obtained at 75 wt.% JL. In addition, the HHV of hydrochar increased remarkably to 26.4 ± 0.02 MJ/kg as the mass ratio of the JL was increased. The surface morphology of the hydrochars were altered and became distinct while the specific surface area (SSA) and the total pore volume (TPV) of the hydrochars increased at increasing the mass ratio of the JL. The surface functional groups were also altered by the co-HTC process. A decline in the combustion performance was observed after the HTC process but improved at 75 wt.% JL after the co-HTC process. The kinetic analysis also revealed that the activation energy decreased after the HTC process but increased to a higher value at 50 wt.% JL after the co-HTC process. Therefore, hydrochar production by co-HTC of DM and JL has proved to be an effective and promising solid biofuel source. Graphical abstract

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Co-combustion thermal conversion characteristics of textile dyeing sludge and pomelo peel using TGA and artificial neural networks

Cited by 142 publications

References 50 publications

Synergistic effects of co‐combustion of sewage sludge and corn stalk and the resulting gas emission characteristics

Synergistic effects of co‐combustion of sewage sludge and corn stalk and the resulting gas emission characteristics

Harnessing the power of machine learning for carbon capture, utilisation, and storage (CCUS) – a state-of-the-art review

Upgrading the fuel properties of hydrochar by co-hydrothermal carbonisation of dairy manure and Japanese larch (Larix kaempferi): product characterisation, thermal behaviour, kinetics and thermodynamic properties

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