MétaCan
Menu
Back to cohort

Thermal and Structural Property Characterization of Commercially Moldable Glasses

2010· article· en· W2169586543 on OpenAlexaff
Scott W. Gaylord, Balajee Ananthasayanam, Benjamin Tincher, Laëticia Petit, Chris Cox, Ulrich Fotheringham, Paul Joseph, Kathleen Richardson

Bibliographic record

VenueJournal of the American Ceramic Society · 2010
Typearticle
Languageen
FieldMaterials Science
TopicGlass properties and applications
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsThermal expansionMaterials scienceMolding (decorative)Characterization (materials science)ThermalFinite element methodRelaxation (psychology)Glass transitionComposite materialThermomechanical analysisLens (geology)ViscosityThermodynamicsPolymerOpticsNanotechnology

Abstract

fetched live from OpenAlex

In this paper, we report the development of a kinetic model for precisely predicting glass material property response to a defined molding profile. The glass viscosity, thermal expansion, and specific heat properties for two commercial optical glasses, P‐SK57 and L‐BAL35 were measured and are reported in this paper. These data were used with the Tool–Narayanaswamy–Moynihan (TNM) model for glass structural relaxation in order to develop a thermal expansion model that simulates the glass workpiece changes through the critical cooling profile where the final workpiece shape is determined. The results show a structural relaxation model incorporated into an ABAQUS FEM code that precisely models the thermal expansion behavior acknowledging that the theory of structural relaxation is a critical element in predicting the final size and shape of a molded lens.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.162

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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

Citations25
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Ceramic SocietySame topicGlass properties and applicationsFrench-language works237,207