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Welding with High Power Fiber Laser API5L-X100 Pipeline Steel

2010· article· en· W2013270155 on OpenAlexaboutno aff
R.M. Miranda, L. Quintino, Stewart Williams, D. Yapp

Bibliographic record

VenueMaterials science forum · 2010
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsnot available
Fundersnot available
KeywordsWeldingWeldabilityMaterials scienceLaser beam weldingDuctility (Earth science)MetallurgyPipeline transportFlash weldingToughnessElectric resistance weldingElectrogas weldingCrackingHeat-affected zoneGas metal arc weldingComposite materialMechanical engineeringEngineeringCreep

Abstract

fetched live from OpenAlex

The increasing length of oil and gas transportation pipelines, associated with their construction and operating costs, has lead to the development of new steel grades with higher performance. The API 5L- X100 is a new high strength steel for pipeline applications which enables the use of thinner walled pipes, lighter to transport and easier to handle on site, allowing greater operating pressures and reducing overall costs. However, this steel grade has limited ductility. Since advantages largely surpass disadvantages, these materials are being seen adequate for earthquake risk areas and low temperature environment as in the Arctic region. X100 grade is already used in northern Canada and is planed for Japan Sub Sea. Automatic metal arc welding on site is the most common method of welding onshore pipelines in steel grades X65, X70 and X80. The use of high strength steels requires the development of new welding procedures with narrow specifications and the X100 steel has limited weldability. Research is needed to develop appropriate welding procedures, avoiding typical metallurgical problems like cold cracking and toughness reduction in the weld area and to achieve high productivity and economical feasibility. This paper presents results on API X100 steel grade welded by high power fiber lasers. Since these lasers are quite new in the market, an analysis of the laser source, as well as the beam/material interaction is made. The welds produced were investigated for both macro- and microstructural analysis and mechanical properties, contributing to a better understanding of the transformations induced in this material by the thermal cycle associated with laser welding.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
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 score0.013
Threshold uncertainty score0.999

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)0.0020.000

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 head0.004
GPT teacher head0.207
Teacher spread0.202 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2010
Admission routes1
Has abstractyes

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