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Record W1762239207 · doi:10.1139/l2012-090

Effects of freezing and thawing cycles on the shear resistance of concrete lift joints

2012· article· en· W1762239207 on OpenAlexafffundvenue
Félix-Antoine Martin, Patrice Rivard

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceCrackingGeotechnical engineeringShear (geology)Composite materialSurface finishStructural engineeringDirect shear testGeologyEngineering

Abstract

fetched live from OpenAlex

Previous studies have shown that 19% of dam deterioration cases are due to freezing and thawing cycles. Considering that lift joints are planes of weakness and that the mechanical properties of concrete are diminished with increasing freeze and thaw cycles, the aim of this paper is to capture the impact of these cycles on the shear resistance of lift joints. Identical concrete joint replicas were subjected to different levels of alteration prior to being sheared in accordance with the standard direct shear test method. The results found in this study showed that initially (up to 87 cycles) frost action has a positive effect on the shear resistance of lift joints due to the increase in roughness the process generates exposed surfaces of concrete joints. However, as the process continues the internal micro-cracking and loss in compressive strength of concrete is such that they offset the positive effects of the increasing roughness and a lost in shear resistance is noticeable thereafter.

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 score0.005

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.169
Teacher spread0.161 · 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

Citations16
Published2012
Admission routes3
Has abstractyes

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