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Record W1977855611 · doi:10.1088/0964-1726/21/1/013001

A review on structural enhancement and repair using piezoelectric materials and shape memory alloys

2011· review· en· W1977855611 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

VenueSmart Materials and Structures · 2011
Typereview
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPiezoelectricityShape-memory alloyMaterials scienceStructural materialProperty (philosophy)Mechanical engineeringStructural engineeringComputer scienceComposite materialEngineering

Abstract

fetched live from OpenAlex

In the past two decades, the active and controllable mechanical properties of piezoelectric materials and shape memory alloys have been widely employed in structural enhancement and repair with remarkable and interesting research findings. This article is designed to introduce and review these research findings. The active electromechanical property of piezoelectric materials is presented first. The research findings on both structural stability enhancement of engineering structures and repair of cracked/notched and delaminated structures under static and dynamic loadings via the piezoelectric materials follow. The active thermo-mechanical property of shape memory alloys and their applications in structural enhancement and repair are also briefly presented. Limitations of the current studies and recommended future endeavors are summarized as well. This review sums up different methodologies and designs in structural enhancement and repair using piezoelectric materials and shape memory alloys to promote new applications in the area.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
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 head0.027
GPT teacher head0.264
Teacher spread0.237 · 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