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Record W1508591347

Seismic retrofitting of deficient Canadian buildings

2009· dissertation· en· W1508591347 on OpenAlexaboutno aff
Marie-Claude Gemme

Bibliographic record

VenueDSpace@MIT (Massachusetts Institute of Technology) · 2009
Typedissertation
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsRetrofittingArchitectural engineeringSeismic retrofitEngineeringForensic engineeringCivil engineeringConstruction engineeringStructural engineeringReinforced concrete
DOInot available

Abstract

fetched live from OpenAlex

Many developed countries such as Canada and the United States are facing a significant infrastructure crisis. Most of their facilities have been built with little consideration of seismic design and durability issues. As a result, these structures are vulnerable to earthquake loadings and are in urgent need of repair and retrofit. This thesis provides a literature review of the vulnerability of Canadian infrastructures built prior to the development of seismic design provisions in actual codes of practice and standards. It describes the performance of typical structures under earthquake loading, such as unreinforced masonry buildings, flat slab concrete buildings and steel frame buildings. It then presents the most common retrofitting strategies applicable to low-rise buildings commonly found in major Canadian cities. A case study assessing the performance of hybrid base isolation systems is then presented. The performance of passive and semi-active hybrid base isolation system is evaluated through the use of a SIMULINK computer model of a typical two-story concrete frame building. A significant reduction in interstory displacement is achieved using the passive system and

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.376
Threshold uncertainty score0.756

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2009
Admission routes1
Has abstractyes

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