Hydraulic Bridge for Pressure Control in a P-Q Multiple Line Segment Control Valve
Bibliographic record
Abstract
The conventional device for flow rate and pressure multiple control is a combination of a flow rate valve and a pressure relief valve. For the pressure control, a hydraulic bridge can also be used instead of using a pressure relief valve. In this paper, a special hydraulic bridge was developed to undertake pressure control in a pressure compensated flow rate valve and thus a new type of P-Q control valve is constructed. The pressure control in this P-Q control valve is a hydraulic bridge formed by the serial connection between a metering orifice and a drain orifice. The contour of the valve port has a significant effect on the linearity of the output pressure. Theoretical analysis shows that the linear pressure output characteristic corresponds to a valve port contour of a hyperbolic. Due to the difficult machining of this hyperbolic contour, a multiple line with two segment lines is used to approximate the valve port contour for linear pressure output. The pressure bridge is constructed in a 2D P-Q control valve and an experimental investigation is carried out. It is demonstrated that linearity of the output pressure is greatly improved by using the multiple segment line contour of the valve port and it is demonstrated that the output pressure is not sensitive to the variation of the temperature. With the introduction of the pressure control bridge, the P-Q valve is indeed greatly simplified.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".