A Numerical Solution to the Flow-Induced Vibration of a Hanging String in a Storage Cavern
Bibliographic record
Abstract
ABSTRACT: A hanging string is the center pipe or tube in a storage cavern. It is situated inside of a cemented casing and, in conjunction with the cemented casing, is used to move product (crude oil, propane, natural gas, etc.) into and out from the storage cavern. When the injected fluid exits the hanging string, it exerts a back-pressure, causing the string to vibrate. Above a certain injection flow rate, the vibration becomes unstable. Before this condition, however, the string may bend and even break due to fatigue. Recently a field test (Reitze, A. 2019) was conducted at four different injection rates to assess the tendency for the hanging string to vibrate. This provided the opportunity to validate closed form solutions (Ratigan, J. 2004, 2017). The purpose of this communication is to provide a numerical solution to this problem. The numerical model produced results within the minimum and maximum vibration amplitudes recorded in the field test, at all four flow rates. Furthermore the numerical solution affords the opportunity to capture effects not normally addressed in closed form solutions. 1. INTRODUCTION As early as 2004 SMRI (Solution Mining Research Institute) (Ratigan, J. 2004) has taken an interest in the vibrations of hanging strings in storage caverns by virtue of it's funding research into this phenomenon. A cavern operator would naturally prefer to maximize the flow rate while avoiding any possible damage. Consequently there exists a motivation to definitively characterize this phenomenon. While it may be most common that the hanging string is a 10.75 inch (0.273 meter) diameter pipe, the length of the string beyond the cemented casing as well as the fluids involved would certainly impact the flow rate at which instability develops. To this end SMRI recently funded a field test (Reitze, A. 2019) in which a hanging string was instrumented and motions were measured at four different flow rates. Prior to this McGill University undertook research into this phenomenon which involved the development of analytical models as well as bench-scale testing. This work may be summarized in the thesis of S. L. Minas (Minas, S.L. 2017).
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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 | 0.001 |
| 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 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".