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Record W3118165942 · doi:10.1177/2041419620984487

Strong-axis response of steel I-sections subjected to close-in detonations

2020· article· en· W3118165942 on OpenAlexafffund
Hezi Y. Grisaro, Michael V. Seica, Jeffrey A. Packer, Wei Li

Bibliographic record

VenueInternational Journal of Protective Structures · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsDetonationMechanicsParametric statisticsFlangeStructural engineeringExplosive materialStiffeningFlow (mathematics)ComputationMaterials scienceEngineeringPhysicsComputer scienceMathematics

Abstract

fetched live from OpenAlex

The analysis of structural members subjected to close-in detonations involves a complicated dynamic scenario. Since the charge is very close to the structural member, the reflected pressure distribution on the member surface is highly non-uniform. In addition, the level of damage to the structural member may be high because of the large magnitude of the load. Due to these phenomena, the response of a structural member to close-in detonation cannot be accurately modelled by relatively simple methods like single-degree of freedom models, and more complicated models are required. Such models need to include numerical simulation of the detonation process, which produces a non-uniform pressure environment, allowing the pressure to reflect and flow around the member section. The local damage and flow around the section are especially of interest in I-shaped, or wide-flange-section members. Herein, the response of such sections is modelled by numerical simulations using a novel technique, which overcomes the difficulty of computation time, and is validated through various calculations. The model is used to perform a parametric study to investigate the response of I-sections subjected to close-in detonations, in terms of local damage and global behaviour, with scaled distances of 0.15–0.29 m/kg 1/3 and loading causing flexure about the strong axis. Various aspects that affect the performance are studied, such as: the effect of scaled distance, the addition of welded stiffening plates between the flanges and web, the effect of boundary conditions and the effect of charge shape. Resulting local damage and residual deformations are assessed for the cases studied.

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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.275
Teacher spread0.262 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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