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Record W4417450972 · doi:10.4028/p-eeqxf1

Enhanced Anchorage Techniques for Smooth Surfaced Nitinol-SMA Rebars

2025· article· W4417450972 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

VenueAdvances in science and technology · 2025
Typearticle
Language
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsLakehead University
Fundersnot available
KeywordsSMA*ReinforcementUltimate tensile strengthShape-memory alloyExperimental researchField (mathematics)Uniaxial tension

Abstract

fetched live from OpenAlex

Over the past decades, Shape Memory Alloys (SMAs), have revolutionized the field of seismic and structural engineering, offering their unprecedented unique properties such as superelasticity, energy dissipation, and the ability to undergo remarkable deformations and reverting to their original shape. The origins of SMA date back to the 1930s when Swedish scientist Arne Ölander initiated revolutionary research on iron alloys, exploring the distinctive characteristics of Iron-Manganese (Fe-Mn) alloy. Ever since, researchers have extensively investigated the mechanical properties of SMAs, leading to increasingly utilizing them in a wide variety of applications, including self-centering braces, structural elements, and systems frequently exposed to harsh working conditions, such as in regions susceptible to earthquakes and dynamic loading. However, a critical limitation has emerged, particularly those made of Nitinol (Nickel­­­­­­–Titanium), which possesses a smooth surface that makes it hard to implement in most structural elements, therefore anchorage systems are often required. Consequently, this smooth surface increases the possibility for slippage, therefore conventional methods to anchor steel reinforcement bars may not be applicable. A few recent studies have investigated the anchorage of SMA rebars, but there is still a big research gap. To fill this research gap, this paper presents an experimental test to evaluate the possible anchorage systems for smooth-surfaced Nitinol-SMA rebars. A total of 6 specimens were tested under uniaxial tensile loading reaching a maximum strain level up to 6%, utilizing the two different anchorage systems. The tests were conducted at a constant loading rate of 0.5 mm/min to evaluate the effectiveness of these anchorage systems. The findings show that both proposed anchorage systems are appropriate for high-deformation seismic zones since it preserved the nitinol bar to sustain up to 6% strain without showing any signs of slippage. These results provide vital insights for creating structural parts with SMA integration that are more dependable. This paper's key findings include ultimate tensile strength, force/displacement relationship, and stress/strain relationship under different constant strain. This paper highlights the need for a more thorough investigation of innovative anchorage systems suitable with SMA bars to pave the way for researchers to enable their wider application in more structural elements.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.007
Science and technology studies0.0010.006
Scholarly communication0.0000.003
Open science0.0020.000
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 head0.009
GPT teacher head0.315
Teacher spread0.306 · 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