Prolife: Strengthening a Steel Railway Bridge with Deck Sections
Bibliographic record
Abstract
<p>Under funding of the European Union’s Research Fund for Coal &amp; Steel (Grant agreement no. RFSR-CT-2015-00025) the project ProLife (Prolonging lifetime of old steel and steel-concrete bridges) is undertaken to find innovative new ways how to extend the lifetime of existing bridges. Within ProLife many different strategies for strengthening old road and rail bridges are researched by different partners in the project. The goal of the project is to look at different strengthening measures and their influence on the remaining lifetime and life cycle costs of a bridge.</p><p>This paper is a continuation of the paper: “Prolife: Recalculating a steel railway bridge for determining strengthening measures, using an updated FEM model and site measurements” (YVR- 0219-2017) of the 39th conference in Vancouver [1].</p><p>In this paper we will focus on rehabilitating a steel rail bridge with steel deck sections to strengthen the stringers and crossbeams in order to increase the remaining lifetime. These are the governing elements for the lifetime of regular bridges, since the main (truss) girders generally have a high enough capacity to cope with today’s loads. Using the calibrated model (see [1]) it is possible to design the strengthening measurements. As a different strategy we explore advanced recalculation of the structure to prevent any strengthening in [2].</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".