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Record W644083656

Successful Launch: Constructing a Curved Steel Bridge High Above a Canyon Floor Presents a Unique Set of Conundrums

2008· article· en· W644083656 on OpenAlexaboutno aff
Ahmad Khashan, Robert J. Gale, Paul M. Hopkins, Greg Orsolini

Bibliographic record

VenueCivil engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBracingEngineeringBridge (graph theory)Structural engineeringCanyonLaunchedGirderGeology
DOInot available

Abstract

fetched live from OpenAlex

A unique launching process is used in constructing a replacement bridge over the Kicking Horse Canyon on a section of the Trans-Canada Highway as it passes through the Rocky Mountains near Golden, Canada. The project was carried out by a design-build, public-private partnership involving three companies, two from the U.S. and one from Canada. Because of the need to place the bridge roughly 300 feet above the riverbed at the bottom of the canyon and because of harsh weather, including unpredictable, dangerous gusts, a steel superstructure was chosen. Steep mountain slopes on either side also influenced the decision, since cranes would have been problematic. It has a horizontally curved steel plate girder superstructure designed to be installed incrementally. The steel also had to withstand stresses in the various stages of launching in addition to the final in-service requirements. It being a curved bridge complicated the calculations and the load requirements. Two independent finite-element models (FEMs) were developed, one by the designer and one by the erector, to calculate elements such as deflections and member forces. Special lateral bracing was required, and additional design elements were added to make fabrication by this new method more feasible. The assembly bed was a 400-ft. long region sloped to the same grade as the bridge. The launch system had four major components: flange clamps, pushing cylinders, wedge brakes, and a return carriage. Four launch cylinders, each with a capacity of 60 tons, were used. Launch times ran from a high of three successive 10-hour shifts for the first to 4.5 hours. In the future, such systems could be used in crowded urban areas or other places where it is not possible to impose lane closures on traffic below.

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)0.001
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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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 designCase report
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
Published2008
Admission routes1
Has abstractyes

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