The Use of Additive Manufactured Plastic in Small-Scale Poppet Valves and Pressure Vessels
Bibliographic record
Abstract
Abstract Small-scale (< 100 W), low-pressure (4 MPa), low-cost hydraulic components, such as pumps and cylinders, have recently become more available. These components have potential uses in demanding applications such as in a pump-controlled electrohydrostatic actuators (EHA)s. This is limited by the fact that the unbalanced flows of a single-rod cylinder require a valve to reconcile the imbalance, which is commercially unavailable in this size and price range. We have hypothesized that it would be feasible to produce this component using additive manufactured (3D printed) plastic. Such a system would be relatively low cost with a high specific power, and could have applications in hand tools, prosthetics, robotics, and more. This paper focuses on some of the challenges in the use of 3D printed plastic for small-scale poppet valves and pressure vessels. The objectives of this research include the investigations of the sealing performance of 3D printed plastic poppet valves and the mechanical strength of 3D printed plastic pressure vessels. Experimental results included in this paper reveal the effects of surface finish and poppet and seat geometry on sealing performance. The influences of print process, material, and orientation on the strength of a 3D printed pressure vessel are examined and the results can inform valve casing design considerations. Mechanical tensile testing of fused deposition modelling (FDM) printed polyethylene terephthalate glycol (PETG) and stereolithography (SLA) printed acrylonitrile butadiene styrene (ABS)-like test specimens provided insight to the corresponding burst strength of that material and print process. The work presented in this paper advances the state-of-the-art of using 3D printed plastic for the construction of small-scale hydraulic components.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".