The Application of Waste Silica Cyclone Powder for the Protective Coating of Steel Billets

The role of a protective coating is to diminish the steel surface scaling during the reheating for hot rolling. The protective coating consists of several components, and the effect of the coating is based on the formation of the modification of Al2O3, amorphous SiO2 and FeO×Al2O3, which all exhibit low permeability to oxygen at temperature up to 1200 °C. The silica sand powder from the cyclone is a waste product in the separation of silica sand. Tests confirmed that waste cyclone powder could replace the silica flour as one of the ingredients in the protective coating. The results of the efficiency of the protective coating after the advanced application of waste cyclone powder on AISI 1059 and AISI 6150 steels are presented. The application of the coating decreased the oxidation and decarburisation of the steel surface during the reheating for hot rolling

The Application of Waste Silica Cyclone Powder for the Protective Coating of Steel Billets

The role of a protective coating is to diminish the steel surface scaling during the reheating for hot rolling. The protective coating consists of several components, and the effect of the coating is based on the formation of the modification of Al2O3, amorphous SiO2 and FeO×Al2O3, which all exhibit low permeability to oxygen at temperature up to 1200 °C. The silica sand powder from the cyclone is a waste product in the separation of silica sand. Tests confirmed that waste cyclone powder could replace the silica flour as one of the ingredients in the protective coating. The results of the efficiency of the protective coating after the advanced application of waste cyclone powder on AISI 1059 and AISI 6150 steels are presented. The application of the coating decreased the oxidation and decarburisation of the steel surface during the reheating for hot rolling

SEM, AES, WDS i korozijsko testiranje oksidnih i nitridnih zaštitnih slojeva oblikovanih toplinskom obradom nerđajućeg čelika

Protective oxide and/or nitride layers on AISI 321 stainless steel were prepared by thermal treatment in air and two controlled atmospheres in a laboratory simulation of an actual technological procedure. Samples’ surface was imaged by Scanning Electron Microscopy (SEM), elemental composition of the substrates was checked by Wavelength Dispersive Spectroscopy (WDS) and depth profiles of the samples were measured by Auger Electron Spectroscopy (AES). Since protective layer thicknesses were found to be of the order of hundreds of nanometers an attempt was made to obtain some fast averaged information about layers composition by Wavelength Dispersive Spectroscopy (WDS) with appropriately adjusted primary beam energy. Electrochemical corrosion testing was also performed on samples.Zaštitne oksidne i/ili nitridne slojeve na AISI 321 nerđajućem čeliku pripremljen toplinskom obradom materijala na zraku i u 2 kontrolirana tipa atmosfera kao laboratorijsku simulaciju stvarnog tehnološkog procesa. Slike površine uzoraka dobijene tehnikom SEM, sastav substrata metodom WDS a za profilnu analizu upotrijebljena je spektroskopija Augerovih elektrona (AES). Kako je ustanovljeno da su debljine formiranih zaštitnih slojeva reda veličine nekoliko stotina nanometara pokušalo se doći do ocjene o prosječnom sastavu unutar sloja upotrijebom tehnike WDS uz odgovarajuće odabranu energiju primarnog elektronskog snopa. Na uzorcima je provjereno i korozijsko testiranje

Mehanizam oksidacije legura Fe-C-Si-Al-Zr

Mechanism of the oxidation of the thermal-resistant Fe-C-Si-Al-Zr alloys was investigated at high temperatures. For the analysis three series samples: L1, L2 and L3, had been annealed at 1100 °C, were cast. After annealing the samples were investigated on the oxide thickness increase. They were observed and analysed by optical and electron microscopes. In case of the small zirconium content in the L1 sample, the graphite lamellae and only a significant amount of zirconium carbide in the ferrite matrix have been observed. At higher zirconium content (the L2 and L3 samples) graphite lamellae and particles of ZrC have been observed. During annealing an oxidation of graphite and ZrC took place. The oxidation of ZrC into ZrO2 is direct and progressive. Evolving CO gas formed the pores around ZrO2. Under sufficient amount of the dissolved oxygen the oxidation of aluminium was taking place too. Al2O3 was precipitating in the CO-ferrite interface filling up the formed pores. Finally the interaction between ZrO2 and Al2O3 were taking place and formation the compound of ZrO2·Al2O3 retarded further oxidation.Ispitivao se mehanizam oksidacije termički otpornih legura Fe-C-Si-Al-Zr na visokim temperaturama. Za analizu su izlivena tri serijska uzorka L1, L2 i L3, i žarena na 1100 °C. Nakon žarenja uzoraka ispitivana je debljina oksidnog sloja. Promatrani su i analizirani optičkim i elektronskim mikroskopom. Kad je količina cirkonija bila mala u uzorku L1 uočene su grafitne lamele i čestice ZrC. Tijekom žarenja došlo je do oksidacije grafita i ZrC. Oksidacija ZrC u ZrO2 je vanjska i progresivna. Razvija se plin CO, koji oko ZrO2 formira pore. Kad je količina rastopljenog kisika postala dovoljno velika došlo je također do oksidacije aluminija. Al2O3 se istaložio u CO-feritnom međuprostoru i popunio postojeće pore. Konačno je došlo do interakcije između ZrO2 i Al2O3 te se stvorio spoj ZrO2·Al2O3 koji je usporio daljnju oksidaciju

Changes in Hydrogen Content During Steelmaking

Štore Steel produces steel grades for spring, forging and engineering industry applications. Steelmaking technology consists of scrap melting in Electric Arc Furnace (EAF), secondary metallurgy in Ladle Furnace (LF) and continuous casting of billets (CC). Hydrogen content during steelmaking of various steel grades and steelmaking technologies was measured. Samples of steel melt from EAF, LF and CC were collected and investigated. Sampling from Electric Arc Furnace and Ladle Furnace was carried out using vacuum pin tubes. Regular measurements of hydrogen content in steel melt were made using Hydris device. Hydrogen content results measured in tundish by Hydris device were compared with results from pin tube samples. Based on the measurement results it was established that hydrogen content during steelmaking increases. The highest values were determined in tundish during casting. Factors that influence the hydrogen content in liquid steel the most were steelmaking technology and alloying elements

Oddziaływanie kąpieli metalowej z wyłożeniem ogniotrwałym kadzi pośredniej urządzenia COS

In Štore Steel steelworks steel is casted on a three strand continuous casting machine. Lining of tundish is mainly made from a magnesia based material. Tundish cover powder is based on alumina and silica. It also contains aluminum and carbon. During casting, the composition of cover slag is constantly changing. When steel in casted in sequences the change in cover slag composition depends on the amount of CaO rich ladle slag. The composition of tundish cover slag at the end of the casting sequence lies in the area of gehlenite (2CaO•Al2O3•SiO2) in ternary phase diagram CaO•Al2O3•SiO2. The result of the reaction between melted steel, refractory material and tundish cover slag are enstatite (MgO•SiO2) and monticellite (CaO•MgO•SiO2). Merwinite (3CaO•MgO•SiO2) is formed in the end of the casting sequence because of high basicity of the gehlenite based tundish cover slag. Clogging on the inner side of submerged entry nozzles (SEN) are made of calcium aluminates (CaO•2Al2O3) and spinel (MgO, MnO)•Al2O3. Only when steel is casted in sequence composition changes in tundish cover slag and clogging occurs.W stalowni Štore Steel stal odlewana jest na trzyżyłowej maszynie COS. Wyłożenie ogniotrwałe w kadzi pośredniej tej maszyny wykonane jest głównie na bazie materiałów magnezytowych. Żużel w kadzi pośredniej tworzony jest na bazie tlenków glinu i krzemionki i zawiera również glin i węgiel. Podczas odlewania skład chemiczny żużla w kadzi pośredniej ulega ciągłym zmianom. W przypadku odlewania sekwencyjnego zmiany w składzie zależą od ilości CaO żużla kadziowego. Pod koniec sekwencji odlewania skład żużla zbliża się do obszaru fazowego gelenitu (2CaO•Al2O3•SiO2) w trójskładnikowym diagramie fazowym CaO•Al2O3•SiO2. Produktami reakcji pomiędzy ciekłą stalą, wyłożeniem ogniotrwałym i żużlem kadziowym są enstatyt (MgO• SiO2) i mon-ticzellit (CaO•MgO• SiO2. SiO2). Merwinit (3CaO• SiO2) tworzy się pod koniec sekwencji odlewania z powodu wysokiej zasadowości bazującego na gelenicie żużla w kadzi pośredniej. Zarastanie wewnętrznej powierzchni wylewów zanurzeniowych spowodowane jest tworzeniem się glinianów wapnia (CaO•2Al2O3) i spinelu (MgO, MnO)•Al2O3. Zarastanie wylewów oraz zmiana składu żużla w kadzi pośredniej występują tylko podczas odlewania sekwencyjnego

Zmiany zawartości wodoru w kąpieli metalowej podczas procesu stalowniczego

Štore Steel produces steel grades for spring, forging and engineering industry applications. Steelmaking technology consists of scrap melting in Electric Arc Furnace (EAF), secondary metallurgy in Ladle Furnace (LF) and continuous casting of billets (CC). Hydrogen content during steelmaking of various steel grades and steelmaking technologies was measured. Samples of steel melt from EAF, LF and CC were collected and investigated. Sampling from Electric Arc Furnace and Ladle Furnace was carried out using vacuum pin tubes. Regular measurements of hydrogen content in steel melt were made using Hydris device. Hydrogen content results measured in tundish by Hydris device were compared with results from pin tube samples. Based on the measurement results it was established that hydrogen content during steelmaking increases. The highest values were determined in tundish during casting. Factors that influence the hydrogen content in liquid steel the most were steelmaking technology and alloying elements.Stalownia Štore Steel produkuje gatunki stali sprężynowych, stali do kucia oraz stali do innych zastosowań przemysłowych. Linia technologiczna obejmuje elektryczny piec łukowy (EAF), rafinację pozapiecową w piecu kadziowym (LF) oraz maszynę do ciągłego odlewania kęsów (COS). Badaniom poddana została zmienność zawartości wodoru w stali w zależności od gatunku stali i wybranej linii technologicznej. Zgromadzono bazę danych w postaci próbek pobieranych z pieca łukowego, pieca kadziowego oraz maszyny COS. Próbki z pieca łukowego oraz pieca kadziowego pobierano za pomocą rurek próżniowych. Przeprowadzano regularnie pomiary zawartości wodoru w stali za pomocą urządzenia Hydris. Mierzoną zawartość wodoru w kadzi pośredniej za pomocą urządzenia Hydris porównywano z zawartością wodoru w próbkach pobranych za pomocą rurek próżniowych. Bazując na opisanych pomiarach stwierdzono wzrost zawartości wodoru w stali w czasie realizowanego procesu stalowniczego. Najwyższe zawartości stwierdzono w kadzi pośredniej urządzenia COS. Czynnikami mającymi największy wpływ na zawartość wodoru w ciekłej stali była zastosowana technologia wytapiania oraz pierwiastki stopowe

Wpływ modyfikacji wtrąceń niemetalicznych na zarastanie wylewów zanurzeniowych

During the secondary refining of high strength steel in a ladle furnace aluminum is used for the melt deoxidation. Aluminates inclusions are modified with a calcium silicon injection in a melt. On the basis of the binary diagram CaO-Al203 solid and liquid calcium aluminates with different composition and shape are formed after calcium treatment. During the calcium silicon injection manganese sulphide is also modified and CaS or (Ca, Mn)S is formed and wrapped around calcium aluminates. Because of rising of calcium bubbles during the calcium silicon injection a powerful melt stirring occurs. This enables inclusion coagulation and a reaction with a slag. Additionally, the MgOźAl203 spinels are formed. Clogging of a tundish nozzle may occur during continuous casting of steel billets. Scull which forms on the nozzle's inner wall consists of spinel, calcium aluminates with various composition and calcium manganese sulphide.W czasie rafinacji pozapiecowej stali o podwyższonej wytrzymałści, jako odtleniacz stosowane jest w piecu kadziowym aluminium. Wtrącenia w postaci tlenków glinu modyfikowane są w tym procesie poprzez wprowadzanie do kąpieli CaSi. Na podstawie analizy układu fazowego CaO-Al2O3 można przewidzieć tworzenie się zróżnicowanych kształtem wtrąceń o składzie stałych lub ciekłych glinianów wapnia. W czasie modyfikacji przemianom podlegają również siarczki manganu tworząc wtrącenia typu CaS oraz (Ca, Mn)S otaczające gliniany wapnia. Z uwagi na wzrost objętości tworzących się w czasie wprowadzania CaSi pęcherzy gazowego wapnia, w procesie zachodzi intensywne mieszanie kąpieli metalowej. Zjawisko to umożliwia koagulację wtrąceń niemetalicznych oraz ich rekcję z żużlem. Dodatkowo zachodzi rónież tworzenie spinelu typu MgOźAl2O3 W procesie ciągłego odlewania kęsów może zachodzić proces zarastania wylewów zanurzeniowych kadzi pośredniej. Narosty, które tworzą się na wewnętrznej ściance wylewu zanurzeniowego zawierają w składzie chemicznym spinel MgOźAl2O3, gliniany wapnia oraz (Ca, Mn)S

Oxide and nitride protective layers formed on stainless steel by thermal treatment: SEM, AES, WDS and corrosion measurements

Protective oxide and/or nitride layers on AISI 321 stainless steel were prepared by thermal treatment in air and two controlled atmospheres in a laboratory simulation of an actual technological procedure. Samples’ surface was imaged by Scanning Electron Microscopy (SEM), elemental composition of the substrates was checked by Wavelength Dispersive Spectroscopy (WDS) and depth profiles of the samples were measured by Auger Electron Spectroscopy (AES). Since protective layer thicknesses were found to be of the order of hundreds of nanometers an attempt was made to obtain some fast averaged information about layers composition by Wavelength Dispersive Spectroscopy (WDS) with appropriately adjusted primary beam energy. Electrochemical corrosion testing was also performed on samples

Modelowanie hartowności stali z wykorzystaniem sztucznych sieci neuronowych

The objective of the research that has been presented was to model the effect of differences in chemical composition within one steel grade on hardenability, with a very broad and heterogeneous database used for studying hardness predictions. This article presents the second part of research conducted with neural networks. In the previous article [1] the most influential parameters were defined along with their weights and on the basis of these results, an improved model for predicting hardenability was developed. These developed neural networks were applied to model predictions of hardenability for three steel grades VCNMO150, CT270 and 42CrMoS4. The results proved that the correlation between the chemical composition differences within a chosen steel grade and the hardness changes can be modeled. If the database is big enough, predictions would be accurate and of high quality. But for a less comprehensive database, the differences in hardness predictions for various chemical compositions of the steel grade concernedwere observable.Celem zaprezentowanych poprzednio badań było modelowanie wpływu składu chemicznego wybranego gatunku stali na hartowność. Modelowanie przeprowadzono z wykorzystaniem rozbudowanej bazy danych zawierającej informacje o składzie chemicznym próbek stali oraz wynikach prób hartowności. W artykule przedstawiono drugą część badań przeprowadzonych z wykorzystaniem sieci neuronowych. W poprzedniej pracy [1] określono parametry modelu oraz ich współczynniki wagowe. Na podstawie uzyskanych wyników opracowano ulepszony model do predykcji hartowności stali. Utworzone sieci neuronowe wykorzystano do predykcji hartowności trzech wybranych gatunków stali: VCNM0150, CT270 oraz 42CrMoS4. Otrzymane wyniki wskazują na możliwość modelowania zależności pomiędzy składem chemicznym, a hartownością w ramach danego gatunku stali. Wykorzystanie do uczenia sieci neuronowej wystarczająco dużej liczby rekordów dotyczących wybranego gatunku stali powoduje, że otrzymywane wyniki charakteryzują się dobrą dokładnością. W przypadku mniej wy- czerpującego zbioru danych wykorzystywanego do nauki sieci, otrzymywane wyniki charakteryzuje większy błąd prognozy