Zobrazeno 1 - 10 of 15 pro vyhledávání: '"Ondřej ZIMNÝ"'
1
Akademický článek
On rheological properties of environmentally friendly inorganic systems and their modeling by artificial neural networks
Autor: Lenka Řeháčková, Vlastimil Novák, Silvie Rosypalová, Milan Heger, Ondřej Zimný, Dalibor Matýsek, Sára Leinweberová, Dalibor Novák
Publikováno v: Journal of Materials Research and Technology, Vol 22, Iss , Pp 1410-1422 (2023)
This work aims to investigate the rheological properties, namely dependence of dynamic viscosity on temperature, chemical composition, and shear rate, of environmentally friendly inorganic systems using a high-temperature rotational viscometer up to
Externí odkaz: https://doaj.org/article/bfadb75675744ed0b37f468de35b9fe4
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2
Akademický článek
Application of Artificial Neural Networks and Regression for Analysis Of Chemical Steel Reheating
Autor: Jan MORÁVKA, Zora JANČÍKOVÁ, Ondřej ZIMNÝ
Publikováno v: Transactions of the VŠB-Technical University of Ostrava, Mechanical Series, Vol 55, Iss 2 (2009)
Metallurgical processes belong to complex physical-chemical processes theoretically described by means of multidimensional generally nonlinear dynamic systems with different transfer lags in their structure. Before realization of these systems contro
Externí odkaz: https://doaj.org/article/9ad572fc842b4b809c109764e5bdbe62
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6
Optimizing the model of heating the material in the reheating furnace in metallurgy
Autor: Špička, I., Heger, M., Ondřej Zimný, Jančíková, Z., Tykva, T.
Publikováno v: Metalurgija, Vol 55, Iss 4, Pp 719-722 (2016)
Metalurgija
Volume 55
Issue 4
Scopus-Elsevier
The optimal operation of reheating furnaces in the metallurgical industry is subject to regularities in the work of the furnace. In practice, however, one cannot avoid downtime to some extent, which causes the deterioration of economic indicators in
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::99d4edee9b75416874ebb2d65a803332
http://hrcak.srce.hr/file/232019
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7
Prediction of metal corrosion by neural networks
Autor: Jančíková, Z., Ondřej Zimný, Koštial, P.
Publikováno v: Metalurgija, Vol 52, Iss 3, Pp 379-381 (2013)
Scopus-Elsevier
Metalurgija
Volume 52
Issue 3
The contribution deals with the use of artifi cial neural networks for prediction of steel atmospheric corrosion. Atmospheric corrosion of metal materials exposed under atmospheric conditions depends on various factors such as local temperature, rela
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d104b214f16ef7854b5e5da0ddf48e2f
http://hdl.handle.net/10084/96188
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