Long-term-monitoring of CFRP-cables over almost a quarter of a century
Bibliographic record
Abstract
A safe use of traffic infrastructures like bridges has to be guaranteed during the whole service time. Increasing number and weight of vehicles are a burden for these objects. Implementing structural health monitoring aims to detect evolving critical deviations in timely manner. In particular novel construction materials with limited knowledge of their long-term behavior should be surveyed.<br /><br />\nThis contribution focuses on the long-term behavior of carbon fiber reinforced polymers for tensioning cables. Measuring systems were implemented on three different kinds of bridges. Essential is a reliable and long-term stable measuring system. For this purpose reference measurements in the laboratory and redundant 'in situ' data were performed to discriminate between change of the infrastructure object and sensing artefacts.<br /><br />\nAn overview is given of the data obtained on the bridges and in the laboratory from resistive strain gages, fiber Bragg grating sensors and displacement transducers, covering a period of almost a quarter of a century.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".