A New Method to Detect Pipe Leaks during Pneumatic Testing
Why this work is in the frame
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Bibliographic record
Abstract
A pneumatic test is often used to detect leaks in a pipe. However, current practices would become problematic for a visual inspection when the pipe is inaccessible or for a leak-based algorithm using the measured pressure reduction trend, which could be caused by decreased ambient temperature rather than by a leak. The paper develops a new method to resolve these issues using conservation of gas mass. The gas mass decreases with a leak. When the gas mass drops below its accuracy limit, the leak could be detected. The detectible leak mass of gas depends on the pressure of gas, the temperature of gas, the volume of gas, the molar mass of gas, and the accuracy of gas mass. The detectible leak hole size not only depends on the detectible leak mass of gas but also on the test duration, the discharge coefficient of the hole, and the flow velocity. A parametric study is to investigate the relationship between the detectible leak hole size and these parameters. The study finds that the detectible leak hole sizes can range from 0.1 to 1.2 mm, mainly dependent on the volume of gas, the accuracies of the pressure and temperature measurement devices, and the test duration become smaller when the test duration increases and/or when the accuracies are enhanced are larger if the volume of gas is increased and do not depend on the test pressure for an ideal gas. The test temperature and other parameters have limited effects on the detectible hole sizes. Although the above results are derived from nitrogen, they are applicable to other gases. The method can detect tiny leaks but cannot detect the leak locations.
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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 | 0.001 |
| 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 it