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Process Window for Friction Stir Lap Welding of Aluminum Alloy 6061

2014· article· en· W2045812462 on OpenAlexaff
Simon Larose, Maxime Guérin, Priti Wanjara

Bibliographic record

VenueMaterials science forum · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceFriction stir weldingWeldabilityWeldingMetallurgyProcess windowAlloyMicrostructureAlonizingAluminiumElectric resistance weldingComposite material

Abstract

fetched live from OpenAlex

Precipitation-hardenable 6xxx series aluminum alloys are incorporated in many structural components with due consideration of their good combination of properties including a relatively high strength, outstanding extrudability and excellent corrosion resistance. Accordingly, AA6061 has been identified as a very good candidate material for structural lightweighting of transportation vehicles. However, the weldability of aluminum alloy (AA) 6061 by means of conventional technologies such as GMAW and GTAW methods is limited by sensitivity to solidification cracking. In this respect, friction stir welding (FSW) presents a tremendous potential for assembly of aluminum structures for the transportation industry due to the low heat involved that can mitigate crack formation and, thus, translate into improved mechanical performance of the assembly. In this work, FSW of 3.18 mm thick AA6061-T6 sheets in the lap joint configuration was investigated. This configuration is considered to be more challenging for assembly by FSW than the butt joint type due to the orientation of the interface with respect to the welding tools and the necessity to break the oxide layer on two aluminium alloy planar surfaces. Weld trials were performed to examine the influence of the FSW tool geometry and process parameters on the welding defects, microstructure, hardness and bend performance. Unacceptable material expulsion and/or significant thinning in one of the two overlapped sheets were produced under most conditions. A set of FSW tool geometries leading to a viable process operational window under which the risk of defects could be mitigated and/or eliminated was identified in this study.

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 score0.199
Threshold uncertainty score0.488

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 head0.008
GPT teacher head0.254
Teacher spread0.246 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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