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Record W7162403927 · doi:10.65521/ijasret.v9i6.1566

Study on Parametric Behaviour of Single Cell Box Girder under Different Radius of Curvature

2025· article· W7162403927 on OpenAlexaff
Harshit Aniya, Sumit Pahwa

Bibliographic record

VenueInternational Journal of Advance Scientific Research and Engineering Trends · 2025
Typearticle
Language
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsPrairie Improvement Network
Fundersnot available
KeywordsBox girderCurvatureParametric statisticsDeflection (physics)GirderFinite element methodRadius of curvatureTorsion (gastropod)Tapering

Abstract

fetched live from OpenAlex

For the purpose of the parametric study, five box girder bridge models with constant span length and varying curvature. In order to validate the finite element modelling method, an example of box girder bridge is selected from literature to conduct a validation study. The example box girder is modelled and analysed in SAP 2000 and the responses are found to be fairly matching with the results reported in literature. For the purpose of the parametric study, the five box girder bridges are modelled in SAP2000. The span length , cross-section and material property remains unchanged. The only parameter that changes is the radius of curvature. The cross section of the superstructure of the box girder bridge consists of single cell box. The curvature of the bridges varies only in horizontal direction. All the models are subjected to self weight and moving load of IRC class A tracked vehicle. A static analysis for dead load and moving load, and a modal analysis are performed. The longitudinal stress at top and bottom of cross sections, bending moment, torsion, deflection and fundamental frequency are recorded. The responses of a box girder bridge curved in plan are compared with that of a straight bridge. The ratio of responses is expressed in terms of a parameter. From the responses it is found that; the parameters like torsion, bending moment, and deflection is increasing as curvature of the bridges increase.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.328
Teacher spread0.300 · 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.

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
Published2025
Admission routes1
Has abstractyes

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