Work

Development of a hybrid Digital Twin for the dispersion of transient CO2 clouds accompanying accidental pipeline leaks

Year: 2025
Type: article
Abstract: This study introduces a conceptual Digital Twin framework for real-time modeling of CO 2 dispersion following accidental pipeline leaks or ruptures. Forecasts cloud pathways and concentration gradients both in real-time operations and within a simulated training environment. The system offers simulations on demand for operator training, strengthening preparedness, situational awareness, and rapid decision-making during critical incidents. By integrating high-frequency nondispersive infrared (NDIR) sensor data with a physics-informed long-short-term memory (LSTM) model, validated against synthetic data from DNV Phast software, the developed system generates accurate spatial forecasts of the 5 000 ppm CO 2 dispersion contour. Experimental validation in more than 300 000 simulated scenarios showed a mean squared error just below 5 %, indicating high reliability and operational effectiveness. The proposed Hybrid Gaussian Digital Twin (HyG-CO2DT) offers scalability, maintains robustness under varying sensor densities without requiring model retraining, and provides a practical framework for enhancing safety, regulatory compliance, and effective risk management in industrial carbon capture and storage (CCS) applications.
Authors: Paweł Bielka, Szymon Kuczyński, Stanisław Nagy
Language: English
Open Access status: hybrid
Estimated APC paid: $4,100
OpenAlex ID: W7106523541
FWCI: 1.147
Cites: 26
Cited by: 4
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