Тип публикации: статья из журнала

Год издания: 2023

Ключевые слова: induction furnace, synthetic iron, quartzite, lining, alloy smelting, heat capacity, melting furnace operation efficiency

Аннотация: First of all, the smelting equipment is the most important component of a foundry's main production process and therefore requires constant reproduction. This is ensured by timely and high-quality maintenance and repair, the cost of which is 8–12% of the total costs. The technical and economic conditions of the enterprise itself deПоказать полностьюpend on this, as the productivity of workers during production is directly related to the technical condition of the equipment and its downtime for repairs. An important factor in ensuring a melting furnace's reproduction is a replacement of the worn lining, which leads to downtime of the smelting furnace and reduces the efficiency of its operation. The amount of torque required depends directly on the compound used. The quality of the manufacturing and sintering process of the lining, which provides the necessary durability, is affected by the heat capacity of the materials used when they are affected by the melting temperature of the alloys. In the present work, using the BRUKER D8 ADVANCE diffractometer, the Shimadzu XRF-1800 spectrometer and the STA 449 F1 Jupiter synchronous thermal analyzer, we probed the changes in the heat capacity of quartzite and PKMVI-3 under the action of temperatures of 200–1550 ◦C. This technology allows the manufacture of a lining that maintains high stability during operations at 1550–1600 ◦C melting modes.

Журнал: Metals

Выпуск журнала: Т.13, №2

Номера страниц: 337

ISSN журнала: 20754701

Издатель: MDPI AG

• Kukartsev V.A. (Department of Materials Science and Materials Processing Technology, Polytechnical Institute,?Siberian Federal University)
• Kukartsev V.V. (Digital Material Science: New Materials and Technologies, Bauman Moscow State Technical University)
• Tynchenko V.S. (Information-Control Systems Department, Institute of Computer Science and Telecommunications,?Reshetnev Siberian State University of Science and Technology)
• Kurashkin S.O. (Laboratory of Biofuel Compositions, Siberian Federal University)
• Sergienko R.B. (Machine Learning Department, Gini Gmbh)
• Tynchenko S.V. (Department of Computer Science and Computer Engineering, Institute of Computer Science and Telecommunications, Reshetnev Siberian State University of Science and Technology)
• Panfilov I.A. (Department of Business Informatics and Business Process Modeling, Siberian Federal University)
• Eremeeva S.V. (Laboratory of Biofuel Compositions, Siberian Federal University)
• Panfilova T.A. (Department of Technological Machines and Equipment of Oil and Gas Complex, School of Petroleum and?Natural Gas Engineering, Siberian Federal University)

• Ядро РИНЦ (eLIBRARY.RU)