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Record W7115688610 · doi:10.71846/18-wcee-1840

NUMERICAL EVALUATION OF SEISMICALLY DEFICIENT RC JOINTS RETROFITTED WITH FE-SMA

2025· article· en· W7115688610 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Conference of Earthquake Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRetrofittingSeismic retrofitVulnerability (computing)HierarchyReinforced concreteFrame (networking)Vulnerability assessment

Abstract

fetched live from OpenAlex

Existing reinforced concrete (RC) structures are seismically vulnerable given their design deficiencies and inadequate structural behaviour. Ageing and increasing weather-related hazards accelerate deterioration rate in regions subjected to harsh weather conditions. Particularly, Canadian civil infrastructure is affected by all these factors which increases their vulnerability to seismic actions. RC joints devotes special interest since they are integral structural components allowing continuity and transmission of forces. Therefore, joints are required to be the strongest elements in beam-columns joints. This permits a correct ductile behaviour and/or failure sequence in a structure. Generally, in poorly detailed RC joints this criterion is achieved through passive retrofitting techniques such as externally bonded fibre-reinforced polymer (FRP). Nevertheless, passive interventions may not be as effective as active retrofitting measures. Active retrofitting techniques, like shape memory alloys (SMAs), provide restorative forces which helps to close cracks (i.e., repair existing damage). This study conducts the assessment of an old RC frame building to seismically retrofit weak RC joints by applying a strength hierarchy approach. The strength hierarchy criteria identities joints lacking structural capacity and assist in the subsequent design of the retrofitting scheme. The potential of iron-based SMAs (Fe-SMA) as an active measure is explored by seizing the thermal activated shape memory effect. This generates a self-prestressing action in the material that can be harnessed to close cracks. Numerical models are developed to evaluate the effectiveness of implementing active retrofitting techniques over passive approaches. The outcomes reported that the strength hierarchy assessment is effective to size the retrofitting configuration for weak RC joints. The proposed retrofitting techniques not only improve the strength capacity of the joints but also their deformation capacity. A better overall behaviour is attained when the active intervention is implemented. After conducting the seismic retrofitting, beams become the weakest components in a RC beam-column joint.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.222
Teacher spread0.200 · 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