Dajung Kim
The Hong Kong University of Science and Technology
Dajung Kim is a postdoctoral researcher in the Department of Mechanical and Aerospace Engineering at The Hong Kong University of Science and Technology (HKUST), where she received her Ph.D. under the supervision of Prof. Rhea P. Liem. Her research focuses on data-enhanced physics-based modeling and multi-objective optimization with applications in aircraft design and path planning for sustainable aviation. She holds two patents and published 11 papers in journals and conferences as a first author. She is the recipient of the Anita Conti Sustainable Innovation Fellowship 2023, an HKUST RedBird Academic Excellence Award 2021/22, two Best Teaching Assistant Awards 2019/20, the Zonta Club Victoria WISE Scholarship 2018/19.
Aircraft Trajectory Optimization for Low Fuel Consumption and Low Perceived Noise with Data-driven Flight Simulations
The reduction of aircraft noise is one of the major challenges with the increase in air traffic over the past decades. Flight operating conditions that decrease noise possibly increase the fuel consumption of aircraft, which is an important factor in airline cost management. We developed a methodology to support flight path planning with the aim of optimizing both perceived noise and fuel consumption. Our approach enables the consideration of complex air transportation constraints, such as guide points according to the flight destination, runway angles, spatial separation of aircraft near the airport, population distribution, and steering motion. The developed path planning gives the Pareto front, which is a set of efficient choices for low-perceived noise and low-fuel consumption. A modified nondominated sorting genetic algorithm II for discrete optimization is also developed to reduce the computational time for multi-objective optimization. The developed methodology is demonstrated by simulating flights for three different origin-destination routes. The results are then compared with the current practice, Quick Access Recorder data and Standard Instrument Departure (SID). The resulting Pareto front exhibits reductions in fuel consumption and perceived noise levels. The trade-offs between fuel consumption and perceived noise levels are also discussed in our papers.