Optimization of the Design of Underground Hydrogen Storage in Salt Caverns in Southern Ontario, Canada
Bibliographic record
Abstract
With the issue of energy shortages becoming increasingly serious, the need to shift to sustainable and clean energy sources has become urgent. However, due to the intermittent nature of most renewable energy sources, developing underground hydrogen storage (UHS) systems as backup energy solutions offers a promising solution. The thick and regionally extensive salt deposits in Unit B of Southern Ontario, Canada, have demonstrated significant potential for supporting such storage systems. Based on the stratigraphy statistics of unit B, this study investigates the feasibility and stability of underground hydrogen storage (UHS) in salt caverns, focusing on the effects of cavern shape, geometric parameters, and operating pressures. Three cavern shapes—cylindrical, cone-shaped, and ellipsoid-shaped—were analyzed using numerical simulations. Results indicate that cylindrical caverns with a diameter-to-height ratio of 1.5 provide the best balance between storage capacity and structural stability, while ellipsoid-shaped caverns offer reduced stress concentration but have less storage space, posing practical challenges during leaching. The results also indicate that the optimal pressure range for maintaining stability and minimizing leakage lies between 0.4 and 0.7 times the vertical in situ stress. Higher pressures increase storage capacity but lead to greater stress, displacements, and potential leakage risks, while lower pressure leads to internal extrusion tendency for cavern walls. Additionally, hydrogen leakage rate drops with the maximum working pressure, yet total leakage mass keeps a growing trend.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".