Innovative Solutions for Enhanced Safety of Onsite Hydrogen Storage
Bibliographic record
Abstract
Abstract The decarbonization of heavy industries and mobility—such as refineries, green ammonia, e-fuels, and steelmaking—relies increasingly on low-carbon hydrogen, often produced via electrolysis. This introduces variability in supply, making reliable hydrogen storage essential. Where large-scale underground storage (e.g., salt caverns) is unavailable, onsite storage becomes critical, typically requiring capacities from a few to several tens of tons. This paper presents the development, qualification, and safety validation of a novel onsite underground compressed hydrogen storage solution. The system features vertically oriented subsurface pressure vessels designed for large capacity, enhanced safety and minimal space requirement. The research details the validation for hydrogen service of the materials and connections used in this solution. It introduced the full technology qualification process based on DNV RP-A203, including results from a demonstration project in France. Safety performance is assessed through Computational Fluid Dynamics (CFD) and Quantitative Risk Assessment (QRA), comparing this solution with conventional above-ground systems. The paper synthesizes lessons learned from design, testing, and risk modeling, and evaluates the technology’s applicability to hydrogen and derivative production. It demonstrates how this compact, modular, and safer storage option supports project integration and accelerates permitting in the hydrogen economy.
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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 | 0.002 |
| 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) | 0.001 | 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".