2,410 research outputs found
次世代リージョナルジェット機開発のための多目的設計探査と空力弾性解析
要約のみTohoku University大林茂課
NASA scientific and technical publications: A catalog of special publications, reference publications, conference publications, and technical papers, 1989
This catalog lists 190 citations of all NASA Special Publications, NASA Reference Publications, NASA Conference Publications, and NASA Technical Papers that were entered into the NASA scientific and technical information database during accession year 1989. The entries are grouped by subject category. Indexes of subject terms, personal authors, and NASA report numbers are provided
State-of-the-art in aerodynamic shape optimisation methods
Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners
Improved Aircraft Environmental Impact Segmentation via Metric Learning
Accurate modeling of aircraft environmental impact is pivotal to the design
of operational procedures and policies to mitigate negative aviation
environmental impact. Aircraft environmental impact segmentation is a process
which clusters aircraft types that have similar environmental impact
characteristics based on a set of aircraft features. This practice helps model
a large population of aircraft types with insufficient aircraft noise and
performance models and contributes to better understanding of aviation
environmental impact. Through measuring the similarity between aircraft types,
distance metric is the kernel of aircraft segmentation. Traditional ways of
aircraft segmentation use plain distance metrics and assign equal weight to all
features in an unsupervised clustering process. In this work, we utilize
weakly-supervised metric learning and partial information on aircraft fuel
burn, emissions, and noise to learn weighted distance metrics for aircraft
environmental impact segmentation. We show in a comprehensive case study that
the tailored distance metrics can indeed make aircraft segmentation better
reflect the actual environmental impact of aircraft. The metric learning
approach can help refine a number of similar data-driven analytical studies in
aviation.Comment: 32 pages, 11 figure
サイレント超音速飛行実現のための実験・計算融合研究
平成15年度-平成18年度科学研究費補助金(基盤研究(A))研究成果報告書,課題番号:1520609
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