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Wyświetlanie 1-2 z 2
Tytuł:
Recovery of Fe and V via selective reduction–magnetic separation of vanadium-titanium magnetite concentrate
Autorzy:
Liu, Liwei
Li, Guofeng
Zhao, Libing
Li, Jinpeng
Li, Yanfeng
Powiązania:
https://bibliotekanauki.pl/articles/2146847.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
vanadium-titanium magnetite concentrate
selective reduction
magnetic separation
Fe separation
V separation
Opis:
With the aim of separating Fe and V, a vanadium-titanium magnetite concentrate was selectively reduced, followed by magnetic separation. The processes accompanying reduction of the vanadium-titanium magnetite concentrate were investigated using thermodynamic simulation, experiments, scanning electron microscopy, and electron probe microanalysis. Appropriate reduction conditions and controlling the amount of CaCO3 promoted the reduction of Fe-containing minerals to metallic Fe. V was released from magnetite, ilmenite, and titanomagnetite, and was inhibited to reduce to metallic V, leading to V enrichment in the non-magnetic products in the form of oxides. Moreover, the Fe particles wrapped the slag phase when the amount of CaCO3 exceeded 8%, which is unfavourable for the magnetic separation of Fe and V. Magnetic products with an Fe content of 87.19%, Fe recovery of 82.62%, V content of 0.09% and non-magnetic products with a V content of 1.00% and a V recovery of 85.49% were obtained when the vanadium-titanium magnetite concentrate was reduced for 100 min at 1623 K with a C/O molar ratio of 2.5 and 8% CaCO3, followed by separating at a magnetic field strength of 85 mT.
Źródło:
Physicochemical Problems of Mineral Processing; 2022, 58, 1; 50--62
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Damage identification of bridge structure model based on empirical mode decomposition algorithm and Autoregressive Integrated Moving Average procedure
Autorzy:
Lu, Weijia
Dong, Jiafan
Pan, Yuhehg
Li, Guoya
Guo, Jinpeng
Powiązania:
https://bibliotekanauki.pl/articles/2174099.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Opis:
Time series models have been used to extract damage features in the measured structural response. In order to better extract the sensitive features in the signal and detect structural damage, this paper proposes a damage identification method that combines empirical mode decomposition (EMD) and Autoregressive Integrated Moving Average (ARIMA) models. EMD decomposes nonlinear and non-stationary signals into different intrinsic mode functions (IMFs) according to frequency. IMF reduces the complexity of the signal and makes it easier to extract damage-sensitive features (DSF). The ARIMA model is used to extract damage sensitive features in IMF signals. The damage sensitive characteristic value of each node is used to analyze the location and damage degree of the damaged structure of the bridge. Considering that there are usually multiple failures in the actual engineering structure, this paper focuses on analysing the location and damage degree of multi-damaged bridge structures. A 6-meter-long multi-destructive steel-whole vibration experiment proved the state of the method. Meanwhile, the other two damage identification methods are compared. The results demonstrate that the DSF can effectively identify the damage location of the structure, and the accuracy rate has increased by 22.98% and 18.4% on average respectively.
Źródło:
Archives of Civil Engineering; 2022, 68, 4; 653--667
1230-2945
Pojawia się w:
Archives of Civil Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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