Systematic Study on Large‐Size Alarm Inclusions in U75V Heavy Rail Steel Using Industrial CT and Interfacial Reaction Analysis

The formation of large‐sized alarm inclusions during production of heavy rail steel severely impairs its service performance. Using industrial CT and electrolytic extraction, these inclusions in U75V steel were identified as exogenous Al 2 O 3 –SiO 2 –CaO–MgO system containing MgO·Al 2 O 3 spinel, often exceeding 3000 μm in length. Erosion of MgO‐based refractory by the tundish‐covering flux significantly increased the MgO content of the covering flux, leading to the formation of high‑MgO and spinel‑type inclusions. They reacted with the submerged entry nozzle coating and were subsequently scoured off by steel flow, thereby forming alarm inclusions. The effects of flux and refractory compositions on erosion were simulated, and the results demonstrated that appropriately increasing the MgO content in the covering flux or enhancing the purity of the refractory effectively mitigated erosion. Consequently, the increase of MgO content in flux was suppressed, resulting in Al 2 O 3 –SiO 2 –CaO–MgO inclusions with lower MgO content. Thermodynamic calculations indicated that when the MgO content in inclusions was reduced to 7.6%, the spinel formation was prevented. Upon further reduction to 4.6%, only liquid inclusions attached to the nozzle surface. This study demonstrates that controlling erosion behavior in the tundish is of practical significance for reducing the formation of large‐sized alarm inclusions in heavy rail steel.

Authors

Institutions

Publication Details

Journal
steel research international
Published
2026-08-18
DOI
https://doi.org/10.1002/srin.70649
Primary Topic
Metallurgical Processes and Thermodynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systematic Study on Large‐Size Alarm Inclusions in U75V Heavy Rail Steel Using Industrial CT and Interfacial Reaction Analysis

Chengsong Liu, Yaowu Wei, Yong Wang, Ruigang Guo et al.
steel research international
Metallurgical Processes and Thermodynamics
article

Systematic Study on Large‐Size Alarm Inclusions in U75V Heavy Rail Steel Using Industrial CT and Interfacial Reaction Analysis

Chengsong Liu, Yaowu Wei, Yong Wang, Ruigang Guo, Hongwei Ni, Hua Zhang, Hongguang Li, Kun Bai
article en

Abstract

The formation of large‐sized alarm inclusions during production of heavy rail steel severely impairs its service performance. Using industrial CT and electrolytic extraction, these inclusions in U75V steel were identified as exogenous Al 2 O 3 –SiO 2 –CaO–MgO system containing MgO·Al 2 O 3 spinel, often exceeding 3000 μm in length. Erosion of MgO‐based refractory by the tundish‐covering flux significantly increased the MgO content of the covering flux, leading to the formation of high‑MgO and spinel‑type inclusions. They reacted with the submerged entry nozzle coating and were subsequently scoured off by steel flow, thereby forming alarm inclusions. The effects of flux and refractory compositions on erosion were simulated, and the results demonstrated that appropriately increasing the MgO content in the covering flux or enhancing the purity of the refractory effectively mitigated erosion. Consequently, the increase of MgO content in flux was suppressed, resulting in Al 2 O 3 –SiO 2 –CaO–MgO inclusions with lower MgO content. Thermodynamic calculations indicated that when the MgO content in inclusions was reduced to 7.6%, the spinel formation was prevented. Upon further reduction to 4.6%, only liquid inclusions attached to the nozzle surface. This study demonstrates that controlling erosion behavior in the tundish is of practical significance for reducing the formation of large‐sized alarm inclusions in heavy rail steel.

steel research international
Kunming University of Science and Technology (CN), Naval University of Engineering (CN), Panzhihua University (CN), Wuhan University of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 18%
Metallurgical Processes and Thermodynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.