Effect of Hydrogen Refueling Parameters on Final State of Charge
Bibliographic record
Abstract
The state of charge (SOC) is a key indicator to show whether a compressed hydrogen tank meets refueling requirements, so it is worth to study effects of the refueling parameters on it. A new SOC analytical solution is obtained based on a simple thermodynamic model. By applying a mass balance equation and an energy balance equation for a hydrogen storage system, a differential equation was obtained. An analytical solution of hydrogen temperature was deduced from the solution of the differential equation, then an analytical solution of hydrogen mass was further deduced based on the analytical solution of hydrogen temperature with some mathematical modifications. By assuming the hydrogen density inside the tank is uniform, the SOC, which defined as a ratio of hydrogen density to the full-fill density, can be transformed to be the ratio of hydrogen mass to the full-fill mass. The hydrogen mass can be calculated from analytical solution of hydrogen mass, while the full-fill mass is supposed to be a constant value. The full-fill density of 35 MPa and 70 MPa tanks at 15 °C are respectively 24.0 g/L and 40.2 g/L, and if the volume of the tank is known, the full-fill mass can also be calculated. The analytical solution of SOC can be unitized to express the reference data, the contributions of inflow temperature and mass flow rate on SOC are presented for a Dynetek type III tank (40 L, metallic liner) and a Hexagon type IV tank (29 L, plastic liner). In addition, the two-parameter effect of inflow temperature and mass flow rate on SOC are presented. The Nusselt number and Reynolds number are utilized to modify the analytical model, the relationship between SOC and refueling parameters can be obtained through the method of fitting. The fittings show a good agreement. The SOC can be determined from the refueling parameters based on the model with more physical meaning. The method developed in this research can be applied to the control algorithm of refueling stations to ensure safety and efficiency.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".