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Record W2972841022 · doi:10.1139/cjce-2019-0341

The first rolling load simulator (ROLLS) for testing bridges in Canada and its application on a full-scale precast box girder

2019· article· en· W2972841022 on OpenAlex
Amir Fam, Dustin Brennan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsQueen's University
Fundersnot available
KeywordsPrecast concreteStructural engineeringGirderEngineeringTruckAxleLoad testingScale modelFull scaleDesign loadBox girderFinite element methodBridge (graph theory)StiffnessAxle loadStructural loadAutomotive engineering

Abstract

fetched live from OpenAlex

This paper describes the development of a unique rolling load simulator (ROLLS) for testing bridge superstructure with a footprint up to 4 m ×17 m, and its first application to test a full-scale 1220 mm ×900 mm ×16000 mm B900 prestressed concrete box girder. This facility at Queen’s University in Kingston, Ontario, is the first of its kind in Canada. ROLLS can apply cyclic loading in a controlled laboratory environment, under realistic highway scale ‘rolling wheel loads’, in lieu of the conventional ‘pulsating stationary loads’. It has two half-axles of a large tandem, each comprising a dual 1140 mm diameter air-inflated tires spaced at either 1.2 or 2.4 m. Each half-axle can apply up to 125 kN, representing the heaviest half-axle load of the CL-625 design truck of the Canadian Highway Bridge Design Code (CHBDC). The maximum travel range and speed are 14.9 m and 6 m/s, respectively. A case study involving analysis of a bridge with eight adjacent B900 box girders of 27.6 m span was carried out prior to experimentally testing one of the girders using ROLLS. Load distribution analyses were conducted using both (i) a finite element model of the full bridge under various CL-625 truck loading configurations and (ii) the CHBDC load distribution method, and both agreed well. Scaling analysis of the girder load share was then conducted to account for shortening it to 16 m to fit in the laboratory, resulting in two-115 kN ROLLS design loads, 1.2 m apart. Multiple passes were conducted at various loads of 40%–100% of the design load, at speeds of 1–5 m/s to examine the machine and girder behaviours. It was found that the applied load fluctuates by less than 10% of full capacity and a 0.13 s/cycle time lag occurs. The measured girder deflection and elastic strains were 11%–20% lower than predicted theoretically. With the two half-axles assembly spaced at 1.2 m, the apparatus has the ability to complete three million cycles in approximately 4.5 months if ran continuously at 5 m/s.

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.

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: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.958

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 head0.005
GPT teacher head0.160
Teacher spread0.156 · 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