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Record W2996943853 · doi:10.1088/1361-665x/ab6694

Robust lightweight multifunctional thermally tailored lattices

2019· article· en· W2996943853 on OpenAlex
Marina M. Toropova, Craig A. Steeves

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

VenueSmart Materials and Structures · 2019
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of TorontoSystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsMaterials scienceComputer scienceDistributed computing

Abstract

fetched live from OpenAlex

Abstract This paper presents conceptual designs for lightweight lattices that are able to connect two materials with differing coefficients of thermal expansion without generating thermal expansion mismatch stresses during temperature excursions. The lattices operate passively at ambient conditions to accommodate large variations of temperature and to provide constant separation, independent of temperature, between the substrate materials. When pin-connected, the lattices are free from thermal mismatch stresses both internally and at their connections with the substrates. However, previous configurations of these lattices are highly sensitive to small perturbations in geometry, as would be associated with thermal expansion or manufacturing imperfections, and hence must be designed giving consideration to such phenomena. Hence, sensitivity analysis must be a factor in the design process. To show that such sensitivity analyses can be carried out using theoretical approaches, experimental results are presented that are in accord with the theoretical calculations. Several examples are given to demonstrate strategies for reducing lattice sensitivity to geometric imperfections for different combinations of material and geometry. More importantly, novel alternative designs for lattices using simpler configurations, which are less sensitive to small perturbations, are explained. These alternative lattices employ less complicated geometry and, in some cases, require only one material, but offer less adaptibility in the situations to which they are applicable.

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 categoriesInsufficient payload (model declined to judge)
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 score0.563
Threshold uncertainty score0.998

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)0.0030.000

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 head0.006
GPT teacher head0.180
Teacher spread0.173 · 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