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An Experimental Study on the Interaction of Thermal Loading and Mechanical Loading in Membrane Structures

2009· article· en· W1877931214 on OpenAlexaffabout
X. Wang, Wanping Zheng, Yan‐Ru Hu

Bibliographic record

VenueStrain · 2009
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsControllabilityThermalMaterials scienceMembraneDistortion (music)Tension (geology)Structural engineeringCeramicSurface (topology)Composite materialMechanical engineeringEngineeringGeometryChemistryCompression (physics)PhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract: Maintenance of membrane structures geometry is crucial for them to be utilised in some space missions, including membrane antennae being developed at the Canadian Space Agency. In the harsh space environment, thermal loading and mechanical loading both can cause the distortion of membrane surfaces. Their effects on surface distortion will interact with each other. In order to properly design active control system, the interaction needs to be well understood. An experimental setup is designed for this purpose. A square membrane is subjected to mechanical loading provided by corner tension forces and thermal loading provided by a ceramic heater. Surface profile of the membrane is measured using the photogrammetry technique. In cases of symmetric thermal loading and asymmetric thermal loading, different mechanical loading cases are evaluated in terms of mitigating surface distortions. Some results are compared and explained using numerical results. Finally, the controllability of membrane structures is discussed using the results from these experiments.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.270
Teacher spread0.254 · 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 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
Published2009
Admission routes2
Has abstractyes

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