Thermogravimetric analysis of the co-combustion of eucalyptus residues and paper mill sludge

Cai, Zexiang; Ma, Xiaoqian; Fang, Shiwen; Yu, Zhaosheng; Lin, Yan

doi:10.1016/j.applthermaleng.2016.06.088

Cited by 52 publications

(10 citation statements)

References 32 publications

(38 reference statements)

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“…Combustion characteristics of samples are described by the following parameters: The ignite index D i

D_{normali} = \frac{{false(normald w / normald τ false)}_{\max}}{T_{normali} \cdot T_{normalp}}

The (d w /d τ ) max is the maximum reaction rate of combustion in formula (1); it could be denoted by DTG max , %·min −1 ; T i and T p are corresponding to the ignition and peak temperatures, respectively, K, which are determined by the TG/DTG method The comprehensive combustive characteristic index S

S = \frac{{(d w / d τ)}_{\max} {(d w / d τ)}_{normalmean}}{{T_{i}}^{2} T_{normalf}}

…”

Section: Resultsmentioning

confidence: 99%

Investigation on the Explosion and Combustion of Various Carbon–Starch Blended Dust

et al. 2020

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The effect of different carbon allotropes on the explosion and combustion of potato‐starch dust is preliminarily investigated by modified Hartmann tube and cone calorimeter (CC), using expandable graphite (EG), naturally flaky graphite, vermicular graphite, and carbon black as the dust suppressants, respectively. The results show that the maximum explosion pressure (Pmax) decreases from 0.66 to 0.39 MPa and the peak heat release rate reduces from 31.45 to13.64 kW·m−2 for the EG‐starch blended dust, due to the physically shielding effect of the fluffy and charring layer. It clarifies that the combustion of starch is mainly governed by Zhuralev–Lesokin–Tempelman 3D diffusion calculated by the modified Coats–Redfern integral method; the carbonaceous materials block the pyrolysis and migration of volatiles, leading to a decrease in DTGmax. It establishes a comprehensive method to evaluate the explosion and combustion of organic combustible dust, combining the CC with combustion kinetics effectively.

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“…Combustion characteristics of samples are described by the following parameters: The ignite index D i

D_{normali} = \frac{{false(normald w / normald τ false)}_{\max}}{T_{normali} \cdot T_{normalp}}

S = \frac{{(d w / d τ)}_{\max} {(d w / d τ)}_{normalmean}}{{T_{i}}^{2} T_{normalf}}

…”

Section: Resultsmentioning

confidence: 99%

Investigation on the Explosion and Combustion of Various Carbon–Starch Blended Dust

et al. 2020

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“…Ignition and burnout performance of the blended fuel can be revealed by the integrated combustion index. The higher the S, the better the overall combustion performance, which is defined as:

S = {(dω / dτ)}_{\max} {(dω / dτ)}_{mean} / T_{i}^{2} T_{h}

where (dω/dτ) max is the burning rate corresponding to the maximum weight‐loss ratio on the differential thermal gravity (DTG) curve, and (dω/dτ) mean is the average burning rate.…”

Section: Resultsmentioning

confidence: 99%

“…Ignition and burnout performance of the blended fuel can be revealed by the integrated combustion index. The higher the S, the better the overall combustion performance, which is defined as 27 :…”

Section: Derivation Of Parametersmentioning

confidence: 99%

Experimental investigation on co-combustion kinetics and gas emission law of sewage sludge-bituminous coal

Yang

et al. 2018

Int J Energy Res

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Summary The kinetic mechanism of the co‐combustion of sewage sludge (SS) and bituminous coal (BC) is studied. The separate combustion process of the SS can be divided into four stages, as follows: moisture precipitation, volatile precipitation, non‐volatile substance precipitation, and fixed carbon burnout. During the co‐combustion of the mixture, SS and BC maintained their respective combustion properties. The SS can significantly improve the ignition and combustion performance of BC. Through Fourier transform infrared spectroscopy analysis, we found that the main combustible component in the SS is the volatile organic matter, and the main emission product is CO2. These results provide a theoretical basis for the new technology of combined power generation of SS energy recycling.

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“…The result of the calculation → IP tr value is listed in Table 7. During the process of modeling all nine naphtha with Kumar model optimized by an error correction chaos algorithm [21], naphtha (1) to (3) are strikingly different from naphtha (4) to (9). The MRE after optimization is less than 0.1% in naphtha (1) to (3) compared with which in naphtha (4) to (9).…”

Section: Case Backgrounds and Conditionsmentioning

confidence: 97%

“…Ethylene is an important olefinic hydrocarbon in the petrochemical industry, while pyrolysis is the major available industrial process exists for the production of olefins yet although some research has been performed on catalytic cracking for the production of such materials [1][2][3][4][5][6][7]. Traditionally, the feedstock used is petroleum fraction, although some reports say biomass fuel have been used to produce such materials, the industrialization is limited [8][9][10][11][12]. The modern ethylene plant usually has a yield of billions of pounds (about million tons) per year, in which even a trace of deviation in simulation may have significant influence on the economy and environment [13,14].…”

Section: Introductionmentioning

confidence: 99%

Thermal Cracking Furnace Optimal Modeling Based on Enriched Kumar Model by Free-Radical Reactions

2020

Processes

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The Kumar model as a molecular model has achieved successful application. However, only 22 reactions limit its veracity and adaptability for feedstocks. A series of models with different degrees of integration of the free radical model and the molecular model has been proposed to enhance feedstock adaptability and simulation accuracy. An improved search engine algorithm, namely Improved PageRank (IPR), is provided and applied to calculate the importance of substances in Kumar model to screen the free-radical reaction network for efficient model selection. A methodology of optimal structure and model parameters chosen is applied to the target to improve the adaptability of the material and the accuracy of the model. Then, two cases with different feedstocks are demonstrated with industrial data to verify the correctness of the proposed approach and its wide feedstock adaptability. The proposed model demonstrates good performance: (1) The mean relative errors (MRE) of the K-R (Kumar and free-radical) model have reached an order of magnitude less than 0.1% compared with 5% in the Kumar model. Further, (2) the K-R model can be implemented to model some feedstocks which Kumar model can’t simulate successfully. The K-R model can be applied in simulation of extensive feedstocks with high accuracy.

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Thermogravimetric analysis of the co-combustion of eucalyptus residues and paper mill sludge

Cited by 52 publications

References 32 publications

Investigation on the Explosion and Combustion of Various Carbon–Starch Blended Dust

Investigation on the Explosion and Combustion of Various Carbon–Starch Blended Dust

Experimental investigation on co-combustion kinetics and gas emission law of sewage sludge-bituminous coal

Thermal Cracking Furnace Optimal Modeling Based on Enriched Kumar Model by Free-Radical Reactions

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