Phosphate Ester-based Fluid Specific Resistance: Effects of Outside Contamination and Improvement Using Novel Media
Bibliographic record
Abstract
The ASTM D1169-11 test method is currently used to determine the continued functionality of operational, fire-resistant phosphate ester (PE) fluids. The theory behind this is that greater resistance will reduce the propensity of lubricating fluids to cause streaming-current corrosion; however, to the average PE fluid user, the method provides a quantitative value that describes the overall general cleanliness of PE fluids. Specific PE contamination, such as by acids and water, negatively affects (lowers) the bulk volume specific resistance. The specific resistance can potentially fall below the condemning limit set by the PE fluid provider(s) and the original equipment manufacturer (5 GΩ · cm) if such contamination levels are high. Conversely, there is contamination that will increase the resistance of operational PE fluids; this contamination is in the form of extremely small, abrasive, dielectric aluminosilicate particles. This contamination comes from the manufacturer-recommended PE purification media Selexsorb GT. The dielectric nature of the particulate gives the user, and ASTM D1169-11, the appearance of resistance improvement, but particle abrasiveness is concomitantly catalyzing fluid degradation and causing undue mechanical wear. Data documenting the misleading PE fluid resistance improvement induced by aluminosilicate contamination are described. Novel methods to improve specific resistance without any deleterious side effects also are presented to help PE fluid users avoid condemning entire reservoirs as a result of low specific resistance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".