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Technical Challenges in Narrow-Gap Root Pass Welding during Tandem and Hybrid Laser-Arc Welding of a Thick Martensitic Stainless Steel

2016· article· en· W2550679910 on OpenAlexafffund
Fatemeh Mirakhorli, X. Cao, Xuan-Tan Pham, Priti Wanjara, J. L. Fihey

Bibliographic record

VenueMaterials science forum · 2016
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsNational Research Council CanadaÉcole de Technologie Supérieure
FundersNational Research Council Canada
KeywordsMaterials scienceWeldingLaser beam weldingMetallurgyGroove (engineering)Martensitic stainless steelMartensiteArc weldingComposite materialMicrostructure

Abstract

fetched live from OpenAlex

As part of a collaborative program to develop advanced manufacturing processes for next-generation hydraulic turbines, this study investigated the technological challenges for joining 25-mm thick martensitic stainless steel (MSS) plates using tandem and hybrid laser-arc welding. Although candidate materials for the intended application typically include wrought AISI 415 and cast CA6NM, a martensitic 410 stainless steel (SS) was especially selected in this study due to its greater crack sensitivity. A narrow-gap groove was designed to minimize the amount of 410NiMo filler metal required to fill the groove using a multi-pass single-sided welding technique. All the welding trials were performed using a 5.2 kW fiber laser. The root-pass quality was characterized in terms of weld bead geometry, defects and microstructure. The main technical challenges observed for the root pass were lack of penetration, lack of fusion and cracking, as detailed in this work.

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)0.001
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 score0.015
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.019
GPT teacher head0.235
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

Classification

machine, unvalidated

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

The models applied no category: nothing in the taxonomy fit this work.
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

Citations9
Published2016
Admission routes2
Has abstractyes

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