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Record W7132985279

Pre-Engineered Hollow Structural Section Welded Connections

2025· dissertation· W7132985279 on OpenAlexaboutno aff
Samuel George Richardson

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsWeldingConnection (principal bundle)Python (programming language)Section (typography)Limit (mathematics)Limit state design
DOInot available

Abstract

fetched live from OpenAlex

In Canada, the standard for the design of steel structures, CSA S16:24, mandates that Hollow Structural Section (HSS) connections consider a specified set of limit states. However, neither CSA S16:24 nor the CISC Commentary on CSA S16:24 presents limit state equations. This research produced two types of design aids for HSS connections. First, a web application was written in Python to analyse popular welded truss-type planar HSS connections. This program produces detailed calculation sheets, offers feedback, and uses machine learning to suggest design solutions. Thereafter, this software program determined several pre-qualified connections. Since the resistance of HSS connections is often given as a force in each branch member, connection solutions where the connection resistance exceeds the branch member resistance are “pre-approved”, within specific bounds of validity. Further tables with capacities for connections, expressed as branch loads, were also produced.

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 score0.091
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.285
Teacher spread0.275 · 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
Published2025
Admission routes1
Has abstractyes

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