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Record W3168705078 · doi:10.1139/cjce-2020-0655

Parallelized finite element modelling of unreinforced concrete masonry infills bounded by reinforced concrete (RC) frames

2021· article· en· W3168705078 on OpenAlexaffvenue
Reza Rahimi, Yi Liu, Gordon A. Fenton

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsFinite element methodMasonryAccelerationStructural engineeringComputer scienceBounded functionComputational scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

This paper presents the implementation of a new parallelized finite element technique for modelling the in-plane behaviour of concrete masonry infilled reinforced concrete (RC) frames using the disturbed stress field method (DSFM). The new technique, referred to as the vectorized and parallelized finite element method (VPFEM), was developed with a key feature of significantly accelerating finite element model run speed using parallel computing algorithms. In this paper, the DSFM modelling details and its implementation in the VPFEM are presented. The iterative analysis required by the DSFM was performed using parallel computing techniques to achieve acceleration using graphical processing units (GPUs). A comparison with experimental results shows that the DSFM is able to accurately predict the behaviour, ultimate load, and cracking pattern of masonry infilled RC frames. The run speed acceleration achieved by the VPFEM when implemented on GPUs is demonstrated to be significant.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.178
Teacher spread0.169 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

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