Е-Публикации
Технически университет - София

Abstract: The performance and reliability of ventilation systems during fire emergencies are critical to ensuring occupant safety, minimizing property damage, and supporting firefighting operations. This study presents a comprehensive assessment of a smart control algorithm, developed to optimize the operation of mechanical ventilation systems under fire-hazardous conditions. The algorithm integrates real-time sensor data, including temperature, smoke concentration, and airflow rates, to dynamically manage ventilation modes and airflow paths in response to evolving fire scenarios. Using a combination of simulation models and controlled experimental setups, the predictive control algorithm was evaluated against traditional ventilation strategies. Key performance indicators included smoke extraction efficiency, excess hydrogen concentration suction, evacuation time improvement, and thermal condition management. The simulations incorporated various fire load scenarios and architectural layouts to test the robustness and adaptability of the algorithm Results demonstrate that the smart algorithm significantly enhances ventilation system responsiveness and performance during hazardous incidents. Compared to conventional control approaches, it achieved faster dangerous gases clearance in critical zones, improved safe evacuation time and energy efficiency.

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