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Record W4293240863 · doi:10.18280/mmep.090230

Finite Element Modeling of Partially Composite Light-Gage Steel Tube Beam with Lightweight Concrete Deck Slab

2022· article· en· W4293240863 on OpenAlexvenueno aff
Tiba H. Saadi, Salah R. Al-Zaidee

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDeckFinite element methodSlabStructural engineeringMaterials scienceComposite numberBeam (structure)Composite materialEngineering

Abstract

fetched live from OpenAlex

For the time being, the steel-concrete composite floors are commonly used in residential, office, and commercial buildings. A traditional composite floor is often constructed with hot-rolled steel. The utilization of hot-rolled steel sections in small and medium-sized buildings is not cost-efficient. Because of the material, cutting process, and labor costs. In addition, the common usage of light-gage cold-formed members, which are often utilized in a non-composite manner, has led to the employment of bigger section sizes. Consequently, the replacement of hot-rolled steel sections with light-gage steel ones to act compositely is a cost-efficient solution. Therefore, this study uses FE modeling with ABAQUS software to investigate the structural behavior of the partially composite light-gage tube beam with a lightweight concrete deck slab. Results of the analysis show that changing the concrete type has a minor influence on strength and stiffness. Changing the concrete type from lightweight to normal weight increases the strength by 3.5%, and increasing the yield stress has a major contribution to the strength. Increasing the yield stress of the beam from 355 MPa to 700 MPa increases the strength by 35.8%.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.184
Teacher spread0.170 · 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.

Study designSimulation or modeling
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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