Sorption time based sizing of a solid-state hydrogen storage bed and thermal management system
Bibliographic record
Abstract
Solid-state hydrogen (H2) storage is a promising technology for transitioning to a carbon neutral H2 economy. However, it is limited by the slow exothermic/endothermic reactions that occur during charging/discharging owing to the poor thermal conductivity of most solid-state H2 storage materials. Although many researchers have addressed this challenge using various thermal management systems (TMSs), there is a lack of design tools available for sizing the reaction bed and TMS. This study aims to develop a multi-level model to size the solid-state storage system consisting of the reactor and the corresponding TMS. The sizing models are based on the sorption-time, an indicator that is crucial to the solid-state H2 storage technology. In addition, the proposed sizing procedure contains an inner loop and outer loop that apply the algebraic model (AM) and a combined lumped parameter model/computational fluid dynamics (LPM/CFD) model, respectively, resulting in marked reduction in solution time. Validations are conducted through comparison of AM predicted results with those of the experiments on solid-state H2 storage involving both internal and external TMSs. As the computational cost for the AM is negligible, the developed multi-level model facilitates the sizing of industrial-scale solid-state H2 storage systems with large or complex reactor beds and sophisticated TMSs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".