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Record W2780396533 · doi:10.22065/jsce.2017.92721.1264

بررسی آزمایشگاهی و عددی رفتار ستون های مختلط نیمه مدفون تحت بار محوری

2019· article· fa· W2780396533 on OpenAlexaboutno aff
مهدی عبادی جامخانه, محمد علی کافی, علی خیرالدین

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languagefa
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

In current international practice, composite construction is gaining importance in industrial buildings and in particular in high-rise buildings. Partially encased composite (PEC) columns are one of the recent developments in composite column. Using composite columns have several advantages such as an increased speed of erection compared to reinforced concrete (RC) columns, a more cost-effective design, smaller cross-section dimensions for similar axial resistance, and a better resistance to fire and local buckling than for steel only columns in compare with traditional RC or steel only columns. One of the proper sections for columns is a cross-sectional shape that can be used in these columns. In this paper, experimental and numerical studies are carried out on three PEC columns under pure compression load. The main difference between the specimens is in the reinforcement details of the concrete. Parameters studied in numerical work, details of reinforcement, failure mode, width to thickness ratio of steel flange and distance and transverse link diameter. The results are presented in the form of axial load-displacement curves. Also, the values of experimental work were compared with the relations between the two European and Canadian regulations, which indicated that the Canadian code was conservative. The results were developed in a numerical section after validation with a laboratory specimens and the load-bearing capacity and deformation were evaluated. The evident buckling pattern in the specimens was the kind of rupture of the welds of the links and the local buckling of the flange plate between the two links. Also, the bigger interval between the two links caused an early local buckling in the specimen.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.013

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 head0.174
GPT teacher head0.523
Teacher spread0.350 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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