Water Consumption Using Artificial Neural Network Modelling in Commercial Aircraft

Abstract

Amidst the current period of increased environmental consciousness and the aviation industry's dedication to sustainability, the delicate balance between water-carrying and fuel usage in commercial aircraft has become a crucial issue due to the rapid development of aviation technology. The primary purpose of this study is to evaluate the water usage of commercial aeroplanes and to optimise the aeroplanes' usage of water. Moreover, the study focuses on analysing the comparison between water consumption estimated using the Artificial Neural Networks (ANN) and historical data collected precisely. By referring to the actual operational data of water tank usage of the Boeing 787-9 fleet in a commercial airline, the flight hours, total passengers, and also actual portable water tank were obtained. The data were gathered over two years, starting from January 2022 until December 2023, for day and night flight time. After all the collected data were completed, the optimisation of the water consumption was conducted and analysed using ANN. The optimised results were then compared using two conventional methods, IATA and Boeing. In conclusion, the ANN method has the least errors compared to IATA and Boeing. The ANN method is suggested as a method to optimise the water tank volume for commercial aircraft.