MétaCan
Menu
Back to cohort
Record W4386426029 · doi:10.5151/2594-5327-39890

CAMPAIGN LIFE ASSESSMENT AND EXTENSION OF MELT SHOP CRANES

2023· article· en· W4386426029 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

VenueABM Proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Failure Analysis and Simulation
Canadian institutionsQueen's UniversityMcMaster UniversityHatch (Canada)
Fundersnot available
KeywordsScrapDamagesWork (physics)EngineeringLife extensionRoot causeForensic engineeringReliability engineeringMechanical engineering

Abstract

fetched live from OpenAlex

PDF | Operators of equipment critical to plant operations commonly require Fitness-For-Service (FFS) assessments to determine necessary measures for continued operation. This paper presents the work performed on by Hatch on several melt shop cranes which supports operations at Gerdau’s integrated steel plant at Ouro Branco in Minas Gerais State, Brazil. Some of these cranes have shown signs of structural damage including cracking and local deformations to girders and trolley structures. Hatch was requested to perform a structural FFS assessment of some of the critical cranes which included two primary Hot Metal Charging cranes, a BOF slag crane and a Scrap Metal Charging crane. Root Cause Analysis (RCA) and subsequent FFS assessments were performed, which included fatigue assessments to aid in the identification of cracking mechanisms for the observed damages to the crane structure. This work led to the development of a range of practical options for mitigation and monitoring tailored to address the observed damages. These options included short-term local repairs and monitoring strategies that could be completed with minimum interruptions to overall production. This work also proposed possible long-term repairs, reinforcements, and local platework replacements to extend the operational life until a replacement crane is procured and installed. To date, many of the interventions have been successfully implemented, allowing for reliable continued operation of these cranes, resulting major benefits to the melt shop facility.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.267

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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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