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Record W2319932683 · doi:10.14288/1.0078781

Tool-part interaction in composites processing

2009· article· en· W2319932683 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComposite materialMaterials scienceComputer science

Abstract

fetched live from OpenAlex

The ability to process composite structures with a high degree of dimensional control remains a barrier to the further implementation of composite materials in commercial applications. Poor control over final part shape can necessitate custom shimming of composite parts or remachining of tooling, resulting in excessive manufacturing costs. Mechanical interaction between the tool and part has been identified as a significant contributor to dimensional control problems yet this phenomena remains poorly understood. Tool-part interaction can often manifest itself in the warpage of initially flat laminates. In the present work an experimental study was performed to identify the effect that part geometry and process variables had on this warpage. Part geometry had a much greater influence on warpage than autoclave process pressure did, while tool surface condition was not observed to have any significant effect. A second experimental study was performed whereby a thin aluminum tool was instrumented with strain gages. The mechanical strain induced in the instrumented tool provided a means for estimating the magnitude and distribution of shear stress operative at the tool-part interface. Both sliding and sticking interface conditions were observed to occur at various times throughout the cure cycle. The interfacial shear stress increased with increasing part degree of cure. An analytical model to predict warpage was developed based on the conclusions of the instrumented tool investigation. This model agreed well with the trends in part warpage which were identified experimentally. Process induced warpage was also simulated using an existing numerical process model. The current method of accounting for tool-part interactions via an elastic shear layer was unable to correctly represent the interface behavior, however, reasonable agreement with experimental results was possible by using a sufficiently low modulus shear layer. The value assigned to the shear modulus of the part was also observed to have a significant effect on the success with which part warpage could be modelled.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.974

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 head0.008
GPT teacher head0.179
Teacher spread0.172 · 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