Publication Cover
Ironmaking & Steelmaking
Processes, Products and Applications
Volume 50, 2023 - Issue 10: STEEL WORLD ISSUE
219
Views
0
CrossRef citations to date
0
Altmetric
Research Article

The analysis of factors affecting the alloy yield of carbon structural steel Q235 in the smelting process

, , , &
Pages 1481-1488 | Received 03 Nov 2022, Accepted 08 Mar 2023, Published online: 30 Mar 2023

References

  • Xing L, Guo J, Li X, et al. Control of TiN precipitation behavior in titanium-containing micro-alloyed steel. Mater Today Commun. 2020;25:101292.
  • Krasnyanskii M, Kats YL, Myagkov K. Statistical models of the assimilation of silicon and manganese in the ladle treatment of steel. Metallurgist. 2012;55(11):790–798.
  • Gao CK, Na HM, Song K, et al. Technologies-based potential analysis on saving energy and water of China’s iron and steel industry. Sci Total Environ. 2020;699:134225.
  • Wang Y, Karasev A, Park JH, et al. Non-metallic inclusions in different ferroalloys and their effect on the steel quality: a review. Metall Mater Trans B. 2021;52(5):2892–2925.
  • Hasanbeigi A, Price L, Chunxia Z, et al. Comparison of iron and steel production energy use and energy intensity in China and the U.S. J Clean Prod. 2014;65:108–119.
  • Kothari AK, Ranjan R, Singh RS, et al. A real-time ferroalloy model for the optimum ladle furnace treatment during the secondary steelmaking. Ironmak Steelmak. 2019;46(3):211–220.
  • Wang X, Wei Y, Shao Q. Decomposing the decoupling of CO2 emissions and economic growth in China’s iron and steel industry. Resour Conserv Recycl. 2020;152:104509.
  • Cui D, Deng Z, Liu Z. China’s non-fossil fuel CO2 emissions from industrial processes. Appl Energy. 2019;254:113537.
  • Zhou K, Yang S. Emission reduction of China׳s steel industry: progress and challenges. Renew Sust Energ Rev. 2016;61:319–327.
  • Sommerfeld M, Friedrich B. Replacing fossil carbon in the production of ferroalloys with a focus on bio-based carbon: a review. Minerals. 2021;11(11):1286.
  • Wang Z, Bao Y, Gu C. Convolutional neural network-based method for predicting oxygen content at the end point of converter. Steel Res Int. 2022;93:2200342.
  • Bizyukov PV, Giese SR. Effects of Zr, Ti, and Al additions on nonmetallic inclusions and impact toughness of cast low-alloy steel. J Mater Eng Perform. 2017;26(4):1878–1889.
  • Tsakiridis P. Aluminium salt slag characterization and utilization – a review. J Hazard Mater. 2012;217–218:1–10.
  • Pande M, Guo M, Guo X, et al. Ferroalloy quality and steel cleanliness. Ironmak Steelmak. 2010;37(7):502–511.
  • Wang Y, Karasev A, Jönsson PG. An investigation of non-metallic inclusions in different ferroalloys using electrolytic extraction. Metals (Basel). 2019;9(6):687.
  • Campbell J. Melting, remelting, and casting for clean steel. Steel Res Int. 2017;88:1600093.
  • Bublik S, Olsen JE, Loomba V, et al. A review of ferroalloy tapping models. Metall Mater Trans B. 2021;52(4):2038–2047.
  • Bi Y, Karasev A, Jönsson PG. Investigations of inclusions in ferrochromium alloys. Ironmak Steelmak. 2014;41(10):756–762.
  • Han PW, Chu SJ, Ping M, et al. Oxide inclusions in ferromanganese and its influence on the quality of clean steels. J Iron Steel Res Int. 2014;21:23–27.
  • Rick CJ, Engholm M. Ferroalloy design, ferroalloy selection and utilization optimization with particular focus on stainless steel materials. J S Afr Inst Min Metall. 2010;110(12):759–765.
  • Chernyshev S, Spirin A, Zyryanov A, et al. Implementation of steelmaker’s assistant software module in a ladle-furnace unit. Metallurgist. 2022;66(3):457–461.
  • Qi X, Jia Z, Yang Q, et al. Effects of vanadium additive on structure property and tribological performance of high chromium cast iron hardfacing metal. Surf Coat Technol. 2011;205(23–24):5510–5514.
  • Wei X, Fu D, Chen M, et al. Data mining to effect of key alloying elements on corrosion resistance of low alloy steels in Sanya seawater environment alloying elements. J Mater Sci Technol. 2021;64:222–232.
  • Erisoglu M, Calis N, Sakallioglu S. A new algorithm for initial cluster centers in k-means algorithm. Pattern Recognit Lett. 2011;32(14):1701–1705.
  • Jing J, Ke S, Li T, et al. Energy method of geophysical logging lithology based on K-means dynamic clustering analysis. Environ Technol Innov. 2021;23:101534.
  • Wright S. Path coefficients and path regressions: alternative or complementary concepts? Biometrics. 1960;16(2):189–202.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.