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Wyszukujesz frazę "Alsafasfeh, Ashraf" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
The Behavior of Jordanian Oil Shale during Combustion Process from the El-Lajjun Deposit
Autorzy:
Gougazeh, Mousa
Alsaqoor, Sameh
Borowski, Gabriel
Alsafasfeh, Ashraf
Hdaib, Ismail I.
Powiązania:
https://bibliotekanauki.pl/articles/2173323.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
El-Lajjun oil shale
combustion
X-ray diffraction
thermogravimetric
fourier transform infrared spectroscopy
X-ray fluorescence
Opis:
The results of X-ray diffraction, thermogravimetric and FTIR spectroscopy analyses of mineral composition indicated that the El-Lajjun oil shale is principally composed of calcite, quartz with minor amounts of kaolinite), gypsum, and apatite. The obtained oil shale ash products at 830 °C and 1030 °C are dominated by lime, quartz, anhydrite, portlandite, gehlenite, and amorphous phases. The TGA weight loss curves clearly indicate that it occurred in the temperature range from 310 to 650 °C. The decomposition of oil shale carbonates was detected above 750°C. The functional groups in the organic material of oil shale are dominated by the aliphatic hydrocarbons, the semi-ash of which had diverse structures of polycyclic aromatic hydrocarbons. The most intensive of combustion occurred in the temperature range of 400–750 °C. In this temperature range, about 75 wt.% was accounted for the total mass loss.
Źródło:
Journal of Ecological Engineering; 2022, 23, 8; 133--140
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of flotation efficiency of phosphate minerals in mine tailings using polymeric depressants : experiments and machine learning
Autorzy:
Alsafasfeh, Ashraf
Alagha, Lana
Alzidaneen, Ala
Nadendla, Venkata Sriram Siddhardh
Powiązania:
https://bibliotekanauki.pl/articles/2146912.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
phosphate tailing
froth flotation
polymers
chitosan
artificial neural networks
Opis:
In this study, direct froth flotation experiments were conducted on silicate-rich phosphate tailing samples. The average grade of P2O5 in the flotation feed was 21.6% as determined using a combination of spectroscopic techniques including X-ray powder diffraction (XRD), mineral liberation analysis (MLA), and scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS). Two polymers were selected to promote the depression of silicates and enhance the flotation of phosphates: in-house synthesized hybrid polyacrylamide (Hy-PAM) and chitosan. Flotation efficiency of phosphates was evaluated at different flotation conditions including depressant type, depressant dosage, pH, and the flotation time. Results indicated that the optimum flotation efficiency of phosphate minerals (84.6% recovery at 28.6% grade of P2O5) was obtained when Hy-PAM was utilized at the studied range of pH and flotation time. All datasets produced from the flotation experiments were integrated within the framework of machine learning (ML) using artificial neural networks (ANNs). The ANN platform was trained, validated, and successfully employed to predict the process outcomes in relation to the pulp and reagents characteristics, which in turn were used to determine the optimum values of process variables. Coefficient of determination (R2), mean absolute error (MAE), and root-mean-square error (RMSE) were used as model indicators. Optimization results showed that the peak flotation performance could be achieved at higher dosages of both polymers. However, lower pH and shorter flotation time for Hy-PAM, and higher pH and longer flotation time for chitosan, were predicted to give the optimum process efficiency.
Źródło:
Physicochemical Problems of Mineral Processing; 2022, 58, 4; art. no. 150477
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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