MétaCan
Menu
Back to cohort

Experimental Performance of Steel Beams under Blast Loading

2011· article· en· W2020682410 on OpenAlexaff
Amr A. Nassr, A. Ghani Razaqpur, Michael J. Tait, Manuel Campidelli, Simon Foo

Bibliographic record

VenueJournal of Performance of Constructed Facilities · 2011
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsMcMaster University
Fundersnot available
KeywordsExplosive materialStructural engineeringMaterials scienceFlangeDisplacement (psychology)Range (aeronautics)Blast waveComposite materialMechanicsEngineeringShock wave

Abstract

fetched live from OpenAlex

In this study, the dynamic response of typical wide-flange steel beams was experimentally evaluated under blast loading. A total of 13 beams were field tested using live explosives, where the charge size ranged from 50 to 250 kg of ammonium nitrate-fuel oil mixture, and the ground stand-off distance was from 7.0 to 10.3 m. Blast wave characteristics, including incident and reflected pressures, were recorded. In addition, time-dependent displacements, accelerations, and strains at different locations along the steel members were measured, and the postblast damage and mode of failure of the test specimens were observed. The blast load characteristics were compared with those obtained using the Technical Manual UFC 3-340-02 results. The displacement response results were used to validate the results obtained from a nonlinear dynamic analysis based on a single degree-of-freedom (SDOF) model. Results showed that the UFC 3-340-02 pressure predictions compare reasonably well with the measured pressure in the positive phase in terms of both the peak pressure and overall time variations. The SDOF model predicted the maximum displacements of beams in the elastic range reasonably well, but it overestimated them in the plastic range.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.204
Teacher spread0.188 · 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 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

Citations56
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Performance of Constructed FacilitiesSame topicStructural Response to Dynamic LoadsFrench-language works237,207