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Influence of Weld Simulation on the Microstructure and Fatigue Strength of 2195 Aluminum-Lithium Alloy

2000· article· en· W2109390371 on OpenAlexaff
M.C. Chaturvedi, Da Chen

Bibliographic record

VenueMaterials science forum · 2000
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsToronto Metropolitan UniversityUniversity of Manitoba
Fundersnot available
KeywordsMaterials scienceAlloyMicrostructureMetallurgyWeldingUltimate tensile strengthGrain boundaryCrackingGrain sizeComposite material

Abstract

fetched live from OpenAlex

Microstructure, tensile and fatigue properties of 2195 Al-Li alloy in the T8 temper (as-received alloy) and after weld simulation in Gleeble 1500 to temperatures of 550°C and 600°C were studied. The microstructure of the alloy consisted of a pancake shaped grains with the major strengthening precipitates of T 1 phase. The weld simulation resulted in the dissolution of T 1 phase and the formation of G-P zones, δ' particles and dislocations. The higher simulation temperature enhanced the microstructural modification and resulted in larger grain size, more grain boundary precipitates and microcracks or voids. The weld simulation gave rise to a significant decrease in the yield and fatigue strength due to the absence of T 1 phase and other microstructural modifications. Fatigue cracks in the base alloy were observed to initiate generally from the specimen surface, and at the interior defects in the weld simulated specimens, especially after the 600°C simulation. Fatigue striations were typical features observed in the base alloy, while cleavage-like cracking occurred in the alloy after weld simulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations0
Published2000
Admission routes1
Has abstractyes

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