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Record W4306752008 · doi:10.22214/ijraset.2022.47049

Inelastic Behaviour and Strength of Steel Beam-Columns with Applied Torsion

2022· article· en· W4306752008 on OpenAlexaboutno aff
Nitin Kumar

Bibliographic record

VenueInternational Journal for Research in Applied Science and Engineering Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTorsion (gastropod)EurocodeStructural engineeringNonlinear systemBeam (structure)Materials scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract: This dissertation presents the outcome of an experimental and theoretical study o f the inelastic behavior and strength of steel beam-columns with applied torsion. Although the international steel design specifications contain interaction relations for biaxially loaded beam-columns, the influence of applied torsion on such members has been completely ignored in the past. A series of hollow square section steel members are tested using an apparatus specially designed to apply torsion in the presence of an axial load and biaxial bending. The theoretical analysis involves formulation of a system of materially nonlinear differential equations and their solution based on a finite integral formulation. The predicted member response agreed quite well with the experiments. A set of new yield limit and strength interaction expressions are then developed which include the influence of applied torsion. In addition, beam-column interaction relations used in Australia, Canada, China, Great Britain, Japan, Russia, the U.S. and Eurocode are modified to account for applied torsion. Finally, this dissertation presents new load-moment-torsion interaction relations for possible adoption in the international steel design specifications.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.304
Teacher spread0.283 · 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 teacher head, 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

Citations0
Published2022
Admission routes1
Has abstractyes

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