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Study on Cable Force Optimization for Extradosed Cable-Stayed Bridge under the Rational Completion Stage

2014· article· en· W2126813281 on OpenAlexaff
Xiao‐Lei Wang, Liang Tian, Tie Dong Qi

Bibliographic record

VenueApplied Mechanics and Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsBridge (graph theory)Internal forcesStructural engineeringEngineeringConstraint (computer-aided design)Moment (physics)Range (aeronautics)Mechanical engineering

Abstract

fetched live from OpenAlex

The extradosed cable-stayed bridge is a new type of bridge developed in recent year. The optimization methods commonly used are based on the cable-stayed bridge and not entirely suit for the extradosed cable-stayed bridge. The paper puts forward a new optimization method, which applies the unknown coefficient functions aided by MIDAS/CIVIL, it takes the reasonable feasible range of dead moment solved by stress balanced method as the constraint condition, makes the square of unknown coefficients as objective function, and solves the cable force based on the effect matrix method thus to determine the cable force in reasonably completion state. This new method is verified with favorable effect, the internal force of this structure appear significant improvement. And finally, the results show better cable force obtained under the method in this paper compared with the cable force under other constraint conditions and objective functions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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 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

Citations5
Published2014
Admission routes1
Has abstractyes

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