Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
Aviation operations are projected to increase, potentially resulting in increased environmental impacts with respect to fuel burn, NOx emissions, and community noise. A number of programs are involved in identifying technological advances required to mitigate these environmental impacts. These technologies must be analyzed at the vehicle-level, but also at the fleet-level to predict the expected impact in the face of increasing operations. Airport community noise is particularly difficult to model due to the spatial and temporal nature of noise, resulting in a reduced understanding of noise exposure contributions by certain aircraft types. The objective of this research is to analyze the contribution to the total noise exposure at several airport types. By using a generic framework to intelligently reduce aircraft and airport diversity, contributions of aircraft types at different airport types can be reported. Results include spatial analysis of noise contributions, demonstrating that the largest contributors affect the lateral regions of a noise contour, while a greater number of vehicle classes impact the noise near the ground track. Results demonstrate that there is some variation in the greatest contributors by airport type between the Regional Jet, Small Single-Aisle, Large Single-Aisle, and Small Twin-Aisle classes. Conversely, the Large Twin-Aisle and the Very Large Aircraft generally contribute little to total airport noise exposure.
Journal of Aerospace Operations – IOS Press
Published: Jan 1, 2017
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.