An AI-Enhanced Multidisciplinary Optimization Framework for Net-Zero Transport Aircraft

Addressing environmental concerns is driving the development of cleaner and more efficient transportation systems. Analyzing these complex systems and their lifecycle environmental impacts, especially with the increasing number of technologies and stakeholders, is a challenging task. This work presents a multidisciplinary analysis and optimization framework for aircraft design, leveraging synergies with novel generative algorithms based on artificial intelligence. We demonstrate its application to a non-conventional, medium-range aircraft equipped with distributed propulsion and hybrid engines. The framework facilitates rapid and comprehensive system analyses, utilizing surrogate models to balance computational cost and accuracy across different design stages. Our approach shows promise for designing and forecasting the performance of next-generation aircraft.