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Record W2490926776 · doi:10.1201/b20891-8

Overview on the structural performance of timber structures under the effects of blast loading &#8211 research and design considerations

2016· book-chapter· en· W2490926776 on OpenAlexaboutno aff
Daniel Lacroix, Christian Viau, D. Côté, Mathieu Michael Poulin, Antonio López, Ghasan Doudak

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringStructural engineeringForensic engineeringConstruction engineeringMaterials science

Abstract

fetched live from OpenAlex

Research on the performance of timber structures to the effect of blast loading is very limited and a holistic and systematic approach is needed. A comprehensive research program has therefore been developed at the University of Ottawa to investigate the performance of various structural timber systems when subjected to blast loads. This paper reports on some of the key findings from the experimental and analytical work since the beginning of this program. Significant results on the effect of strain rate on the material behaviour, failure modes, as well as various retrofit options are discussed. The assessment has paved the way to the development of code provisions that would allow the design of new, and retrofit of existing timber structures.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.008

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 head0.076
GPT teacher head0.299
Teacher spread0.223 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations3
Published2016
Admission routes1
Has abstractyes

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