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Development of technological solutions to improve the quality of railway rails by improving the technology of smelting, out-of-furnace processing and continuous casting of rail electric steel.

2023· article· en· W4389150678 on OpenAlex
А. А. Уманский, A. S. Borisov, С. В. Фейлер

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFerrous Metallurgy Bulletin of Scientific Technical and Economic Information · 2023
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Materials Science
Canadian institutionsEVRAZ (Canada)
Fundersnot available
KeywordsMetallurgySmeltingSteelmakingSlag (welding)Materials scienceContinuous castingElectric arc furnace

Abstract

fetched live from OpenAlex

Based on a complex of metallographic and X-ray phase studies for the conditions of EVRAZ ZSMK, which is a leading domestic manufacturer of railway rails, the nature of characteristic defects of rails of metallurgical origin has been determined. These defects, which are the cause of rejection of rails during ultrasonic quality control in the flow of rail-block mill, are stratifications, in the localities of which accumulations of silicate, alumina and sulfide non-metallic inclusions are concentrated; at the same time, these defects in the vast majority of cases are located in the neck of the rail profiles. Analysis of contamination with non-metallic inclusions of suitable rails of the current production of EVRAZ ZSMK showed that, unlike the locations of defects in rejected rails, alumina non-metallic inclusions have an extremely low concentration, while manganese sulfides and silicate inclusions have the highest relative concentration. Based on the results obtained, technological measures were developed, pilot-industrial and implemented to improve the production technology of rail steel in the conditions of the electric steelmaking workshop of EVRAZ ZSMK. In order to reduce the concentration of oxide nonmetallic inclusions in rail steel, a new technology of ladle treatment of steel using a low-ash carburizer and calcium carbide for slag deoxidation has been developed. To reduce sulfide inclusions contamination, measures have been implemented to ensure the sulfur content in the finished steel at a level of no more than 0.008%. The optimization of the modes of electromagnetic mixing in the mold and the temperature regimes of continuous casting of steel was carried out, which also had an effect on reducing the concentration of non-metallic inclusions in continuously cast billets of rail steel and finished rails. The introduction of a set of these technological solutions and measures allowed to reduce the rejection of rails for internal defects from 7% to less than 2%

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.228
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it