Oscillating Back Pressure Regulator (OBPR) for High-Pressure Core Flooding
Bibliographic record
Abstract
The challenge in the core analysis industry is the availability of a versatile back pressure regulator (BPR) that can operate efficiently at ultra-low or no-flow conditions at very high pressure. The existing models of back pressure regulators are limited to a specific range of operating conditions, automation, and robust core flooding environment. In this work, we developed an initial stage prototype of an Oscillating BPR (OBPR), emphasizing detailed instrumentation and implemented automation. The critical component in an OBPR is the valve that needs to operate within defined close and open position based on the feedback received from an encoder rather than the oscillation created by the flow system or by using a square wave oscillator. The paper investigates the static and dynamic characteristics of the newly designed OBPR instrument. The paper discusses the graphical programming LabVIEW software used to create the feedback control loop using the PID controller. Initial results of the test run were done with the different core flooding systems like Water, Brine, and CO2. The study also included comparing OBPR pressure performance with the standard back pressure regulator in the market.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".