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Record W4206984124 · doi:10.32920/16840387

Statistical Evaluation of the Europe Bridge Between Kehl and Strasbourg According to the “Guideline for the Recalculation of Existing Road Bridges” with Specific Mathematical and Structural Examination of the Cracks in the Superstructure

2021· preprint· en· W4206984124 on OpenAlexaff
Leonhard Oechsle

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBridge (graph theory)GuidelineLoad bearingStructural engineeringFinite element methodSuperstructureBearing (navigation)EngineeringComputer science

Abstract

fetched live from OpenAlex

<div>This master´s project re-evaluates the Europe Bridge after 60 years of service. The framework for the calculations is provided by the “Guideline for the Recalculation of Existing Road Bridges”. With the help of a computer model, generated by the program SOFiSTiK, and the prescribed loads of the guideline, the required checks in the ULS were performed at the main load bearing system. As the results indicate a high exceedance of the capacity, different alternatives were evaluated to restore the structural safety.</div><div><br></div><div>A specific focus was laid on the assessment of the cracks in a connection of the lateral load bearing system. Initially, a literature research on the crack formation in the superstructure of steel bridges was conducted. The gathered information points towards category three fatigue cracks that were caused by poor fatigue design and a discrepancy between static modelling and execution on site. These conclusions were confirmed by the fatigue checks of the affected connections. However, an analysis of the crack detail with a FE-model of the lateral system shows that the crack has no significant impact on the load bearing behaviour of other components. </div>

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)0.002
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
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 head0.082
GPT teacher head0.323
Teacher spread0.241 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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