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Record W2895763612 · doi:10.22215/etd/2017-11874

Residual Capacity of Blast-Damaged Reinforced Concrete Columns

2017· dissertation· en· W2895763612 on OpenAlexaff
Isaac Kwaffo

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsCarleton University
Fundersnot available
KeywordsResidualStructural engineeringReinforced concreteColumn (typography)Residual strengthDisplacement (psychology)EngineeringMaterials scienceGeotechnical engineeringComputer science

Abstract

fetched live from OpenAlex

The use of suitcase bombs has severe consequences on infrastructures as they can be placed close to or in contact with key structural elements.The detonation of such an explosive charge may cause severe structural damage to key load-bearing members leading to their failure and initiation of progressive (disproportionate) collapse of the structure due to the localized failure of the load-bearing member.One of the most useful information when assessing the post-event capacity of a structure and the possibility of progressive collapse of a damaged structure is the residual axial capacity of its loadbearing members such as columns.This research project forms part of a larger program designed to assess the blast resistance and residual capacity of reinforced concrete columns.Earlier phases of the program included the testing of reinforced concrete column under live explosion loading and numerical modelling of the columns.The primary objective of this current phase of vii 3.3.2.4 Data Acquisition ....

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.237
Teacher spread0.225 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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