SHAPE: Safe Hydrogen Agile Pipeline Engineering with XR and AI-Enhanced Digital Twins
Bibliographic record
Abstract
The Safe Hydrogen Agile Pipeline Engineering (SHAPE) project aims to develop and study an innovative Digital Twin (DT) system enhanced by eXtended Reality (XR) and Artificial Intelligence (AI) technologies to improve hydrogen pipeline management. This system connects a custom-built pipeline facility with an immersive XR environment, enabling real-time, bidirectional data exchange. By leveraging AI capabilities for leak detection, risk analysis, and anomaly prediction, the system enhances operational safety, efficiency, and reliability. The XR environment offers intuitive navigation, immersive data visualization, and interactive training experiences, supported by intelligent virtual agents and embodied avatars to facilitate collaboration and decision-making. By sharing these developments, we aim to foster discussions with the workshop audience on advancing XR and AI-enabled DT technologies for safer and more sustainable hydrogen pipeline operations.
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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".