With an annual growth in travel demand of about 5% globally, managing the environmental impact is a challenge. In 2019, the International Civil Aviation Organisation (ICAO) issued emission reduction targets, including well-to-wake greenhouse gas (GHG) emissions reduced at least 50% from 2005 levels by 2050. This discusses several technologies from an aircraft design perspective that can contribute to achieving these targets. One thing is certain: aircraft will look different in the future. The Transonic Truss-Braced Wing and Flying V configurations are promising significant efficiency improvements over conventional configurations. Electric propulsion, in various architectures, is becoming a feasible option for general aviation and commuter aircraft. It will be a growing field of aviation with zero-emissions flight and opportunities for special missions. Lastly, this paper discusses methods and design processes that include all relevant disciplines to ensure that the aircraft is optimised as a complete system. While empirical methods are essential for initial design, Multidisciplinary Design Optimisation (MDO) incorporates models and simulations integrated in an optimisation environment to capture critical trade-offs. Concurrent design places domain experts in one site to facilitate collaboration, interaction, and joint decision-making, and to ensure all disciplines are equally considered. It is supported by a Collaborative Design Facility (CDF), an information technology facility with connected hardware and software tools for design analysis.

This paper presents a multi-disciplinary design optimization (MDO) framework for design of a general aviation aircraft wing considering the effects of tractor propellers on the wing aerodynamic characteristics. In pursuit of this objective, a wing–propeller full-interaction aerodynamic routine was developed and integrated with structural and performance models. A substantive contribution of the work is the approach for effectively modeling wing effects on propeller slipstream development while still leveraging traditional propeller and wing analysis tools. Several optimizations were carried out, starting from an existing aircraft design, to test different local and global surrogate-based optimization frameworks and to allow for the assessment of the resulting solutions and corresponding computational performance metrics. Examination of the total function calls and run times showed that the use of surrogate models improves overall optimization performance, provided that suitable surrogate modeling techniques are chosen.