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Record W4416133335 · doi:10.1177/13694332251394825

Capacity and failure mode prediction of long-bolted connection in panelized modular houses

2025· article· en· W4416133335 on OpenAlexaffabout
Mostafa Elhadary, Ahmed Bediwy, Ahmed Elshaer

Bibliographic record

VenueAdvances in Structural Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsLakehead University
Fundersnot available
KeywordsModular designFinite element methodMoment (physics)Failure mode and effects analysisParametric statisticsConnection (principal bundle)Process (computing)Mode (computer interface)

Abstract

fetched live from OpenAlex

This study investigates the structural performance of a newly proposed bolted connection for panelized modular structures, using high-strength bolts and extended plates, aimed at addressing Canada’s housing shortage, particularly in remote areas. A finite element model (FEM) was developed and validated against experimental data to evaluate the connection’s behaviour. A parametric study of 240 FEMs was conducted on unstiffened connections, examining the effects of extended plate thickness, bolt configuration, and bolt diameter. Results show these parameters significantly affect moment capacity, failure mode, and inelastic rotational behaviour. The bolt arrangement and quantity fostered a “strong column–weak beam” mechanism, enabling plastic hinging in the beam. Additionally, bolt diameter and plate thickness were found to govern ultimate rotation capacity and failure modes. To support practical application, design charts and a mathematical equation based on genetic regression were developed to predict ultimate capacity, thereby streamlining the design process and reducing trial iterations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.004
GPT teacher head0.207
Teacher spread0.203 · 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 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
Published2025
Admission routes2
Has abstractyes

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