🚀🔥 Real-Time Prediction of Flammable Volume Ratio in Hydrogen Tunnels 🤖💨 | A Hybrid CFD–Machine Learning Framework for Safety Management 🧠🛡️

🚀💨 Real-time Prediction of Flammable Volume Ratio in Hydrogen Tunnels presents a groundbreaking approach to enhance hydrogen safety in future transportation and storage tunnels. As hydrogen becomes a key clean energy carrier, leakage risks and explosion hazards must be managed effectively. This study introduces an innovative method to predict and prevent flammable gas accumulation using advanced computational techniques. ⚙️🔥💧


🧠📊 The proposed hybrid CFD–machine learning framework combines fluid dynamics modeling with intelligent data algorithms to simulate hydrogen leakage and predict flammable volume ratios in real-time. This integration helps identify risk zones faster, allowing timely safety interventions. Machine learning enhances prediction accuracy while CFD ensures detailed flow and concentration mapping within complex tunnel environments. 💻📈🌬️

🛡️🏗️ The system supports leakage safety management by offering proactive solutions, improving monitoring systems, and guiding emergency responses. Through this hybrid approach, hydrogen infrastructure can achieve greater reliability, public confidence, and environmental safety. 🌱✨ Together, smart modeling and AI-driven insights pave the way toward a safer and sustainable hydrogen-powered future. ⚡🔋🌍

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