Experimental investigation and numerical modelling of hydrogen exposed piezoelectric actuators for fuel injector applications
Bibliographic record
Abstract
Piezoelectric actuators are increasingly used for the electronic control of fuel injector opening valves.Hydrogen is considered an attractive clean alternative fuel for automobile and power generation applications.Current understanding of the performance of piezoelectric actuators in a hydrogen environment is very limited.This work is aimed at experimentally investigating the performance of hydrogen-exposed piezoelectric actuators under conditions directly relevant to a hydrogen-based fuel injector.The performance is assessed with both quasi-static and dynamic electric loads.It is found that up to 12 weeks of continuous exposure to hydrogen at 100°C and 10 MPa has a negligible effect on the actuator stroke when testing is conducted at temperatures of 5-80°C.Cyclic exposure and exposure done on fatigue cycled actuators also yields similar results.Microstructure and dielectric investigations confirm this behavior.The reason for a negligible effect of hydrogen is attributed to the presence of a protective ceramic insulation around the lateral surface of actuators which deactivates the hydrogen diffusion mechanism.A fully-coupled 3-D FEM-based numerical model of a Thermo-Electro-Mechanical continuum in hydrogen environment is developed using the 'Equation Based Modeling' feature of COMSOL Multiphysics.The model provides a useful tool for understanding the localized responses of the actuators in hydrogen environment and to predict their durability and applicability under different conditions.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".