Aircraft conceptual design for optimal environmental performance

Abstract

Consideration of the environmental impact of aircraft has become critical in commercial aviation. The continued growth of air traffic has caused increasing demands to reduce aircraft emissions, imposing new constraints on the design and development of future airplane concepts. In this paper, an aircraft design optimisation framework is used to design aircraft that minimise specific environmental metrics. Multidisciplinary design optimisation is used to optimise aircraft by simultaneously considering airframe, engine and mission. The environmental metrics considered in this investigation are CO 2 emissions -which are proportional to fuel burn -and landingtakeoff NO x emissions. The results are compared to those of an aircraft with minimum direct operating cost. The design variables considered in the optimisation problems include aircraft geometry, engine parameters, and cruise settings. An augmented Lagrangian particle swarm optimiser and a genetic algorithm are used to solve the single objective and multi-objective optimisation problems, respectively.

Fuel consumption optimization in air transport: a review, classification, critique, simple meta-analysis, and future research implications

“…According to Majka A. et al [9] at one time fuel extraction cost and availability had little impact on the evolution of the air transport industry. Furthermore, aircraft fuel burn is proportional to CO 2 emission [10,11]. Therefore, as the fuel consumption increases the aviation emission shall also increase and that is a big environmental concern today.…”

Optimization of Unmanned Aerial Vehicles: Expanding the Multidisciplinary Capabilities

“…According to the review of paper I, the majority of authors abstain from specifying the development stage that they are working on, while at the same time, there is general tendency where the choice of tools is based on availability rather than suitability. Overall, it is stressed that the MDO tools should be able to capture the correct physics of the problem (Reuter et al, 2016), but also to be as computationally efficient as possible in order to enable even faster design evaluations (Henderson et al, 2012). To this end, it can be seen that a prevalent trend is to build modular frameworks that can adapt to different fidelity requirements, whereas it can be argued that the main gap herein is the lack of a complete list regarding the available software solutions (see Figure 16).…”

Analyzing the moderating effects of respondent type and experience on the fuel efficiency improvement in air transport using structural equation modeling

“…The relationships between operational efficiency and efficiency are expressed by payload fuel efficiency equation [21,32]. Therefore, aircraft operational efficiency were measured in terms of parameters such as aircraft range [4,51], fuel weight, reserve fuel weight, payload, aircraft speed, crew weight, takeoff filed length, and landing filed length ( [2,4,5,27,29,65]). Aircraft range is the total distance that an aircraft can fly with full fuel tank.…”