In-Situ Calibration for Feedwater Flow Measurement
Bibliographic record
Abstract
With the approval by the Nuclear Regulatory Commission (NRC), of the Appendix K power uprates, it has become important to provide an accurate measurement of the feedwater flow. Failure to meet documented requirements can now more easily lead to plant operations above their analyzed safety limits. Thus, the objective of flow instrumentation used in Appendix K uprates, becomes one of providing precise measurements of the feedwater mass flow that will not allow the plant to be overpowered, but will still assure that maximum licensed thermal output is achieved. The NRC has licensed two technologies that meet these standards. Both are based on ultrasonic measurements of the flow. The first of these technologies, which is referred to as transit-time, relies on the measurement of differences in time for multiple ultrasonic beams to pass up and downstream in the fluid stream. These measurements are then coupled with a numerical integration scheme to compensate for distortions in the velocity profile due to upstream flow disturbances. This technology is implemented using a spool piece that is inserted into the feedwater pipe. The second technology relies on the measurement of the velocity of eddies within the fluid using a numerical process called cross-correlation. This technology is implemented by attaching the ultrasonic flow meter to the external surface of the pipe. Because of the ease in installation, for atypical situations, distortions in the velocity profile can be accounted for by attaching a second ultrasonic flow meter to the same pipe or multiple meters to a similar piping configuration, where the flow is fully developed. The additional meter readings are then used for the calibration of the initial set-up. Thus, it becomes possible to provide an in-situ calibration under actual operating conditions that requires no extrapolation of laboratory calibrations to compensate for distortions in the velocity profile. This paper will focus on the cross-correlation method of flow measurement, starting with the theoretical bases for the velocity profile correction factor and its reliance on only the Reynolds number to produce an accurate measurement of the flow, when the flow is fully developed. The method of laboratory calibration and the verification of these calibrations under actual plant operating conditions will be discussed. This will be followed by a discussion of how this technology is being used today to support the Appendix K uprates. Various examples will be presented of piping configurations, where in-situ calibrations have or will be used to provide an accurate measurement of the feedwater flow at a specific location.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".