Enhancing removal of air contaminants in existing aircraft cabins by optimizing supply air direction based on Re-field synergy and Bayesian optimization

Abstract

There are a large number of airplanes currently being operated, in which the ventilation system needs to be improved to more effectively remove air contaminants. A potential approach is to adjust the supply air directions with the use of simple airflow deflectors. This study proposed a method for optimizing the supply air direction of ventilation in aircraft cabins based on the Re-field synergy index and Bayesian optimization. A validated numerical model was used to calculate the air distribution and air contaminant transport in a single-row single-aisle aircraft cabin to obtain the Re-field synergy values. The Bayesian optimization approach was used to identify the supply air direction which maximizes the Re-field synergy, namely, maximizes the mass transfer effectiveness. Finally, the air contaminant transport in a 7-row single-aisle aircraft cabin with the optimized supply air direction was evaluated to demonstrate the enhancement of ventilation performance. The results show that the proposed method based on the Re-field synergy index and Bayesian optimization can efficiently optimize the supply air direction in order to enhance the air contaminant removal in aircraft cabins. In the 7-row single-aisle aircraft cabin, the optimized supply air direction can reduce the average air contaminant concentration in the breathing zone of the passengers by up to 23 %.