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Record W2772379793 · doi:10.2749/222137817822208681

Soil Structure Interaction and Performance Based Design for the Port Mann Cable Stayed Bridge

2017· article· en· W2772379793 on OpenAlexaboutno aff
H. T. Lund, Adam Mitchell

Bibliographic record

VenueReport · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Port (circuit theory)MetreSpan (engineering)DeckSeismic analysisEngineeringStructural engineeringGeotechnical engineeringCivil engineeringGeologyElectrical engineering

Abstract

fetched live from OpenAlex

<p>The performance based seismic design of the Port Mann Bridge, a 10 lane cable-stayed bridge located 30min outside of Vancouver, BC, is presented in detail. The Port Mann Bridge is the centerpiece of the Port Mann/Highway 1 Improvement Project. Located in a high seismic region, the design-build project includes the 850-meter-long Port Mann Bridge carrying the Trans Canada Highway over the Fraser River. With a 470-meter-long main span and 190-meter-long side spans, and 52-meter-wide deck, the Port Mann Bridge is the largest main span crossing in Western Canada, the second longest cable-stayed bridge in North America, and one of the widest bridges in the world. The geotechnical conditions varied along the 2 km bridge length, and included soil layers that are highly susceptible to liquefaction in the larger events. The geotechnical development of ground motions and the site-specific non-linear soil response are discussed. The three-dimensional modeling techniques used to capture the soil structure interaction (SSI) in the global seismic analysis of the Port Mann Bridge are described, with special focus on the approach to non-linear structural modeling and the implementation of a strain-based seismic design.</p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.551
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.242
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2017
Admission routes1
Has abstractyes

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