Framework for Aircraft Conceptual Design and Environmental Performance Studies
Abstract
Although aircraft environmental impact has been a concern since the beginning of commercial aviation, continuous growth in passenger traffic and increasing public awareness make aircraft noise and emissions critical considerations in the design of future aircraft. This research explores the feasibility of including environmental performance as an optimization objective at the aircraft conceptual design stage, allowing a quantitative analysis of the trade-offs between environmental performance and operating cost. A program for aircraft design and optimization was developed, using a multiobjective genetic algorithm to determine optimal aircraft configurations and to estimate the sensitivities between the conflicting objectives of low noise, low emissions, and operating costs. The design tool is based on a new application integration framework incorporating a detailed noise prediction code, engine simulator, and aircraft analysis and optimization modules. This paper describes the framework and design approach, including initial results that illustrate environmental performance trades and explore the feasibility of very low-noise and low-emissions designs that could dramatically decrease the environmental impact of commercial aviation. I.
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Heuristics and meta-heuristic techniques are still the dominant solution techniques in the literature of FCO.
“Heuristics and meta-heuristic techniques are still the dominant solution techniques in the literature of FCO [10,58,66,68,118,120,176].”
From Fuel consumption optimization in air transport: a review, classification, critique, simple meta-analysis, and future research implications (2015) · cites this paper as [58]
GAs has been proven to be a highly effective and efficient tool in solving complex aircraft design, and some of their successful applications in the optimization of fuel consumption models have been proposed in the literature.
“GAs has been proven to be a highly effective and efficient tool in solving complex aircraft design, and some of their successful applications in the optimization of fuel consumption models have been proposed in the literature [58,68,176].”
From Fuel consumption optimization in air transport: a review, classification, critique, simple meta-analysis, and future research implications (2015) · cites this paper as [58]
GA algorithms are well suited to multiobjective optimization problems because they can handle large populations of solutions.
“GA algorithms are well suited to multiobjective optimization problems because they can handle large populations of solutions [58].”
From Fuel consumption optimization in air transport: a review, classification, critique, simple meta-analysis, and future research implications (2015) · cites this paper as [58]
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Can we accelerate the improvement of energy efficiency in aircraft systems?
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Singh, V., & Sharma, S. K. (2015) · European Transport Research Review · doi:10.1007/s12544-015-0160-x · Cited by 95 · see citing works
Factors Affecting the Rate of Fuel Consumption in Aircrafts
Hassan, T. H., Sobaih, A. E. E., & Salem, A. E. (2021) · Sustainability · doi:10.3390/su13148066 · Cited by 26 · see citing works
- Authors
- Antoine, N. E., & Kroo, I. M.
- Affiliations
- Stanford University (US)
- Venue
- AIAA Journal
- Published
- 2005-10
- Volume
- 43
- Issue
- 10
- Pages
- 2100-2109
- ISSN
- 0001-1452 (ISSN-L)
- 1533-385X
- OpenAlex
- W2107866430
- Cited by
- 155
- References
- 0
- Citations by year
- 2026: 4 · 2024: 6 · 2023: 8 · 2022: 6 · 2021: 11 · 2020: 8 · 2019: 10 · 2018: 10 · 2017: 12 · 2016: 13 · 2015: 9 · 2014: 7 · 2013: 7 · 2012: 12
- FWCI
- 2.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- AIAA Journal (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Advanced Aircraft Design and Technologies
- Physical Sciences › Engineering › Aerospace Engineering › Air Traffic Management and Optimization
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
- Keywords
- conceptual aircraft design, aircraft noise, aviation emissions, multi-objective optimization, genetic algorithm, operating costs, noise prediction, engine simulation, design tool integration
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