Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2022

Идентификатор DOI: 10.3390/ma15031220

Ключевые слова: alphaset system, cold-hardening mixture, foundry production, reclaimed product, sand grain micro-specimen

Аннотация: The spent liquid glass mixture, which is widely used in foundries as a binder after knock-ing out of moldings, contains pieces of different sizes and strengths, and there is a strong silicate film on the sand grains themselves. The proposed regeneration plants, which provide for the re-moval of the silicate film by scrubbing, have low productivity and lead to abrasion of the grains themselves. For this reason, the knocked-out mixture is taken to the dump. As a result of the study of the state of the spent liquid glass mixture in the dump, it was found that, in the spent mixture that had lain for 8–10 years, under prolonged exposure to atmospheric precipitation at plus and minus temperatures, part of the silicate film dissolves and almost all monolithic pieces are de-stroyed. Further use of hydraulic regeneration allows us to reduce the film thickness and thereby reduce the percentage of liquid glass from 5–5.5% to 0.8–1.2%. This made it possible to select the composition of the molding sand for an automatic line, using the AlpHaset-process, which consists of 22–29% of liquid glass mixture from a dump, 65–72% of liquid glass, 5.5% of liquid glass, and a hardener in the amount of 0.55%. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Журнал: Materials

Выпуск журнала: Vol. 15, Is. 3

Номера страниц: 1220

ISSN журнала: 19961944

Издатель: MDPI

• Kukartsev Viktor Alekseevich (Siberian Fed Univ, Polytechn Inst, Dept Mat Sci & Mat Proc Technol, Krasnoyarsk 660041, Russia)
• Kukartsev Vladislav Viktorovich (Siberian Fed Univ, Inst Space & Informat Technol, Dept Informat, Krasnoyarsk 660041, Russia; Reshetnev Siberian State Univ Sci & Technol, Inst Engn & Econ, Dept Informat Econ Syst, Krasnoyarsk 660037, Russia)
• Tynchenko Vadim Sergeevich (Reshetnev Siberian State Univ Sci & Technol, Inst Comp Sci & Telecommun, Informat Control Syst Dept, Krasnoyarsk 660037, Russia; Siberian Fed Univ, Sch Petr & Nat Gas, Dept Technol Machines & Equipment Oil & Gas Compl, Krasnoyarsk 660041, Russia; Bauman Moscow State Tech Univ, Digital Mat Sci New Mat & Technol, Moscow 105005, Russia)
• Bukhtoyarov Vladimir Viktorovich (Siberian Fed Univ, Sch Petr & Nat Gas, Dept Technol Machines & Equipment Oil & Gas Compl, Krasnoyarsk 660041, Russia; Reshetnev Siberian State Univ Sci & Technol, Dept Informat Technol Secur, Krasnoyarsk 660037, Russia)
• Tynchenko Valeriya Valerievna (Siberian Fed Univ, Inst Space & Informat Technol, Dept Informat, Krasnoyarsk 660041, Russia; Reshetnev Siberian State Univ Sci & Technol, Inst Comp Sci & Telecommun, Dept Comp Sci & Comp Engn, Krasnoyarsk 660037, Russia)
• Sergienko Roman Borisovich (Gini GmbH, Machine Learning Dept, D-80339 Munich, Germany)
• Bashmur Kirill Aleksandrovich (Siberian Fed Univ, Sch Petr & Nat Gas, Dept Technol Machines & Equipment Oil & Gas Compl, Krasnoyarsk 660041, Russia)
• Lysyannikov Aleksey Vasilyevich (Siberian Fed Univ, Sch Petr & Nat Gas Engn, Dept Avit Fuels & Lubricants, Krasnoyarsk 660041, Russia)

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