Integration of a needle valve mechanism with cura slicing software for improved retraction in pellet-based material extrusion
Bibliographic record
Abstract
Fused granular fabrication (FGF) is a cost-effective and increasingly popular additive technology that enables the production of parts using a wide range of exotic materials that are not typically available with material extrusion additive manufacturing. This paper presents a novel needle valve approach for flow control in a FGF system that uses flexibly connected screw extruders. The addition of a needle valve to the existing system allows complex travel moves to be performed without stringing, greatly increasing the available part complexity of the printer. The needle valve is actuated by one of the 3D printer’s extruder stepper motors and can be controlled by g-code generated by off-the shelf slicer software. This paper also proposes a mathematical model for predicting the oozing volume of the valve, which is the small quantity of material that escapes through the nozzle during valve actuation. This model is important for calibration and g-code generation, which could be integrated with commercial slicers to use this needle valve design without writing custom code. The model is tested experimentally, and results show a strong correlation between predicted and measured oozing volumes. The performance of the valve is also characterized in terms of flow rate versus needle position. Experiments showed that the needle stroke (the vertical distance that the needle travels between open and closed states of the needle valve) is the most important parameter in minimizing oozing. An optimized stroke of 0.4 mm was used, with a maximum flow rate of 346 mm3/min when using a nozzle inner bore diameter of 0.8 mm. Using the optimized valve parameters, parallel cube structures were printed to demonstrate the reduction of stringing, along with various demonstration parts including a 3Dbenchy benchmark print and a soft robotic actuator. Overall, this study demonstrates that needle valves present a reliable and low-cost approach for controlling the flow of polymer in FGF systems with a remotely connected screw extruder.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".