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Record W4406696915 · doi:10.3390/mining5010009

Optimization of the Design of Underground Hydrogen Storage in Salt Caverns in Southern Ontario, Canada

2025· article· en· W4406696915 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMining · 2025
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsUniversity of Waterloo
FundersMitacs
KeywordsHydrogen storageSalt (chemistry)Environmental scienceHydrogenChemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.178
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it