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When a chemical or biological agent is suddenly released into a ventilation system, its dispersion needs to be promptly and accurately detected. In this work, an optimization method for sensors layout in air ductwork was presented. Three optimal objectives were defined, i.e. the minimum detection time, minimum contaminant exposure, and minimum probability of undetected pollution events. Genetic algorithm (GA) method was used to obtain the non-dominated solutions of multiobjectives optimization problem and the global optimal solution was selected among all of the non-dominated solutions by ordering solutions method. Since the biochemical attack occurred in a ventilation system was a random process, two releasing scenarios were proposed, i.e. the uniform and the air volume-based probability distribution. It was found that such a probability distribution affected the results of optimal sensors layout and also resulted in different detect time and different probability of undetected events. It was discussed how the objective functions are being compatible and competitive with each other, and how sensor quantity affect the optimal results and computational load. The impact of changes on other parameters was given, i.e. the deposition coefficient, the air volume distribution and the manual releasing. This work presents an angle of air ductwork design for indoor environment protection and expects to help in realizing the optimized sensor system design for sudden contaminant releasing within ventilation systems.

Multi-objective optimization for sensor placement against suddenly released contaminant in air duct system