In an exciting leap forward, researchers at the University of Bahrain (UoB) have crafted an AI model that can slash fuel use during aircraft takeoffs by more than 10%. This innovation promises to transform the aviation industry, cutting both costs and carbon emissions.
At the heart of this groundbreaking project is Ahmed Khalil Al Owainaty, a PhD student in Mechanical Engineering at UoB’s College of Engineering. Using advanced AI techniques, including genetic algorithms and neural networks, Al Owainaty has found a way to optimize the takeoff and landing paths of Airbus A320 aircraft. His goal? To reduce fuel consumption, carbon emissions, and the costs tied to maintenance and operations.
His research, titled “Optimising Takeoff and Landing Path for Airbus A320 Aircraft Using Artificial Intelligence Techniques,” dives into 17 key factors that affect flight efficiency. This impressive study recently earned him his PhD from UoB.
Al Owainaty explains, “We created a model for the Airbus A320 takeoff process, considering factors like aircraft weight, temperature, wind conditions, and runway elevation. We then used AI, including machine learning and neural networks, to optimize the aircraft’s paths.”
To test this model, virtual simulations were run at three regional airports, and the results were promising.
Moreover, Al Owainaty’s team conducted thorough risk assessments to address the potential challenges of applying AI to takeoff and landing procedures. By identifying and mitigating these risks, they ensured the model meets the safety standards set by the US Federal Aviation Administration.
This AI-driven approach could soon be a game-changer in aviation, making flights more efficient and eco-friendly. As this technology advances, it holds the promise of smoother skies and a greener future for air travel.
