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Nonlinear Stability Impact of Concrete-Filled Steel Tube Arch Bridge

2013· article· en· W2083778508 on OpenAlex

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.

Bibliographic record

VenueAdvanced materials research · 2013
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsArchStructural engineeringNonlinear systemInstabilityStability (learning theory)Finite element methodSpan (engineering)Arch bridgeEngineeringDeformation (meteorology)Structural stabilityMaterials scienceMechanicsComputer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

CFST Arch Bridge under pressure mainly stability is one of the key factors restricting its development. Most of the arch of instability belongs to the second type of instability, and that the non-linear deformation of the structure is nonlinear state, the mechanical properties of the structure also change from elastic state into nonlinear state. In this paper, based on nonlinear and stability theory and using the finite element software ANSYS, parameters of affecting the main arch stability were studied. By analyzing the geometric and material nonlinear factors on the structural stability, the parameters of influence on the stability of the main arch were discussed, including width-span ratio, arch-rib inside inclination, rise-span ratio and arch-axis coefficient. The influence law of these parameters were summarized and will be used to guide the actual project.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.998

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)0.0030.000

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 head0.041
GPT teacher head0.346
Teacher spread0.304 · 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