The ambition to achieve climate-neutral aviation by 2070 and sustainable space exploration will require ground-breaking technological solutions to the numerous bottleneck problems we face today, particularly in the design of future lightweight structures and materials. They will require high-fidelity computational models to predict their performance under different loading and radiation conditions and powerful optimization algorithms to find the best configurations for design. The recent developments of Artificial Intelligence (AI) and Quantum Computing (QC) offer new ways of approaching these problems.
In QAIMS lab, we will dive into the niche area of Quantum-enhanced Artificial Intelligence (QAI) to establish sustainable processes and solutions for materials and structural designs in aerospace. When the problem is classical (e.g., structural mechanics), QAI algorithms could potentially speed up the classical solution methods. When the problem is quantum mechanical (e.g., radiation), QAI methods could replace or complement the classical predictive models. Through this lab, we aim to develop the key enabling technologies empowered by QAI to fulfil the ambitions of the AE Faculty in sustainable aviation and space.
The Team
Supervisors
Dr. Qi-Jun Hong
Materials Science and Engineering, School of Engineering, Arizona State University