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Record W2805056836 · doi:10.3151/jact.16.210

Impact of Drying on Structural Performance of Reinforced Concrete Shear Walls

2018· article· en· W2805056836 on OpenAlexfundno aff
Hiroshi Sasano, Ippei Maruyama, Akihiro Nakamura, Yoshihito Yamamoto, Masaomi Teshigawara

Bibliographic record

VenueJournal of Advanced Concrete Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
FundersPartenariat Canadien Contre Le Cancer
KeywordsMaterials scienceShrinkageComposite materialShear wallStiffnessTrussReinforcementShear strength (soil)Compressive strengthShear (geology)Ultimate tensile strengthStructural engineeringGeology

Abstract

fetched live from OpenAlex

The aim of this study is to experimentally investigate the effect of drying on a shear wall, and to clarify the mechanism of the changes in the structural performance due to drying. Two sufficiently hydrated wall specimens are prepared. Then, one is loaded without drying, while the other is tested after sufficient drying until the shrinkage of concrete reaches an equi-librium state. The results show a reduction in the initial stiffness and little change in the ultimate shear strength in the dry specimen, in spite of an increase in the compressive strength. Reproduction numerical analysis using Rigid Body Spring-network Model (RBSM) coupled with a truss network model for moisture transport is conducted, and an ac-ceptable agreement is confirmed in the ultimate strength and the crack patterns. From the numerical results, it is revealed that two factors are balanced in the ultimate shear strength after drying in this experiment: 1) an increase in the com-pressive strength due to aging (material scale), and 2) a strength reduction due to lateral strain, which is evaluated using the formula suggested by Vecchio and Collins (1986) (member scale). This indicates that the wall reinforcement ratio and concrete shrinkage have the influence on the ultimate strength through increasing/decreasing the number of cracks and the crack width.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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 head0.005
GPT teacher head0.239
Teacher spread0.233 · 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

Citations49
Published2018
Admission routes1
Has abstractyes

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