ANN-Based Model to Predict the Viscosity of Molten Blast Furnace Slag at High Temperatures of

ANN-Based Model to Predict the Viscosity of Molten Blast Furnace Slag at High Temperatures of > 1600 K

Published:2023-06-14 Issue:3 Volume:9 Page:1020-1032
ISSN:2199-3823
Container-title:Journal of Sustainable Metallurgy
language:en
Short-container-title:J. Sustain. Metall.

Author:

Liu Qingshan,Wu Junjun^ORCID,Shao Yice,Wang Hong,Zhu Xun,Liao Qiang

Funder

Young Scientists Fund

Venture and Innovation Support Program for Chongqing Overseas Returnees

Innovative Research Group Project of the National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Metals and Alloys,Mechanics of Materials,Environmental Science (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s40831-023-00706-0.pdf

Reference84 articles.

1. Zhang H, Wang H, Zhu X et al (2013) A review of waste heat recovery technologies towards molten slag in steel industry. Appl Energy 112:956–966

2. https://worldsteel.org/steel-by-topic/statistics/world-steel-in-figures/

3. Lv Yiwen, Zhu Xun, Wang Hong, et al (2020) Centrifugal granulation and waste heat recovery technology for high temperature molten slag. China Basic Sci 28–36

4. Ding B, Zhu X, Wang H et al (2018) Numerical investigation on phase change cooling and crystallization of a molten blast furnace slag droplet. Int J Heat Mass Transf 118:471–479

5. Gao J, Feng Y, Feng D et al (2020) Solidification with crystallization behavior of molten blast furnace slag particle during the cooling process. Int J Heat Mass Transf 146:118888

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