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Fast and Reversible Bistable Hygroscopic Actuators for Architectural Applications Based on Plant Movement Strategies

2022· article· en· W4312237263 on OpenAlexaff
Emily Chen, Glenn Lu, Lyric Barnik, David Correa

Bibliographic record

VenueeCAADe proceedings · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBistabilityActuatorMovement (music)Computer scienceControl engineeringArchitectural engineeringMaterials scienceEngineeringPhysicsArtificial intelligenceAcousticsOptoelectronics

Abstract

fetched live from OpenAlex

Plant movement is of great inspiration for the development of actuators in architectural applications. Since plants lack muscles, they have developed unique hygroscopic mechanisms that use specialized tissue to generate movement in response to stimuli such as touch, light, temperature, or gravity. Most research in architecture has been focused on the stress-induced bending that can be achieved with a bilayer structure – particularly using wood composites and bi-metals. The speed of these mechanisms is mostly limited by the rules of bilayers, as described by Timoshenko, and the speed of moisture/heat diffusion. This paper presents methods to use bistable mechanisms, and their elastic instability, to enable rapid movements of “snap-through” buckling that can greatly improve the speed of transformation. The research covers biomimetic studies on the Mimosa pudica, Oxalis triangularis, and the Maranta leuconeura to develop hygroscopic mechanisms whose kinematic actuation can be amplified through the integration of a bi- stable system. The presented mechanisms make it possible to significantly increase the speed of response of the hygroscopically driven mechanism while maintaining the ability to operate over several reversible cycles. Calibration of the mechanism to specific relative humidity conditions is presented together with some initial prototypes with the potential for manual override strategies. It is the aim of this combined approach that the actuation mechanisms are better able to match users’ expectations of fast shape-change actuation in relation to environmental changes.

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)0.000
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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Same venueeCAADe proceedingsSame topicAdvanced Materials and MechanicsFrench-language works237,207