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Record W4386898527 · doi:10.1016/j.cscm.2023.e02499

Investigation of reinforcing steel rebar manufactured from local scrap at various finishing rolling temperature

2023· article· en· W4386898527 on OpenAlex

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

VenueCase Studies in Construction Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicConstruction Engineering and Safety
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceRebarUltimate tensile strengthMetallurgyCementitePearliteComposite materialScrapToughnessTemperingMicrostructureAustenite

Abstract

fetched live from OpenAlex

The mechanical properties of structural steel rebar are a very important factor for durable, sustainable, and resilient design of reinforced concrete structures. In developing countries, steel rebars are often manufactured from unsegregated steel scrap using manual rolling mill, which affects the quality of the final manufactured product and raises several concerns. Various earlier studies have been conducted on controlling the quality of steel rebar in various countries, yet quality issues of steel rebar are still pending in local industry. Therefore, this study aims to explore the mechanical properties of steel rebar manufactured with steel scrap having various chemical composition at different finishing rolling temperatures (FRT). Steel rebars were manufactured at an industrial kiln using various carbon contents (0.25%, 0.27% and 0.30%), replicating full-scale scenarios. Specimens for each type of steel were manufactured at FRT of 640⁰C, 680⁰C, 720⁰C, 760⁰C and 800⁰C. Various tests including tension, bending, hardness and microstructural examination were performed on the manufactured steel rebars. It was observed that by increasing the FRT, the average grain size in the steel rebar increased, leading to a decrease of the ultimate tensile strength, yield strength, and hardness. Conversely, the elongation and modulus of toughness increased with the increase in the average grain size due to a decrease in total grain boundary area owing to lower resistance to dislocation motion. By increasing the carbon content, inter-lamellar spacing between cementite strips in pearlite decreased, which increased the hardness, ultimate tensile strength, and yield strength, whereas the elongation and modulus of toughness decreased. The weight per unit length, yield, and ultimate strengths of the tested rebars satisfied the ASTM A615 limits. This study educates the local rolling mills stakeholders about possible causes of variations in mechanical properties of locally manufactured steel rebar and suggests solutions towards proper monitoring and mitigating harmful effects. The main findings of this study highlight that the manufacturing of rebars from scrap at various FRT affects the stress-strain behavior of steel rebar and its overall structural stability. Moreover, microstructural analysis assists in understanding the role of FRT on yield and ultimate strengths of rebars due to changes in the average grain size.

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)0.000
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 score0.456
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.024
GPT teacher head0.241
Teacher spread0.216 · 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