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contributor authorTekin, Abdurrahman
contributor authorXiao, Tianhang
contributor authorYu, Xiongqing
date accessioned2026-08-20T21:13:37Z
date available2026-08-20T21:13:37Z
date copyright2025/09/18
date issued2026
identifier otherJAEEEZ.ASENG-6258.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314145
description abstractAbstractAirfoil optimization is crucial for enhancing aerodynamic performance and efficiency in aerospace engineering because accurate and rapid predictions of the lift-to-drag ratio (CL/CD) directly influence design decisions. However, traditional methods are ...
publisherAmerican Society of Civil Engineers
titleRapid Lift-to-Drag Ratio Prediction for NACA Four-Digit Airfoils Using a Deep Neural Network
typeJournal Article
journal volume39
journal issue1
journal titleJournal of Aerospace Engineering
identifier doi10.1061/JAEEEZ.ASENG-6258
journal fristpage04025106-1
journal lastpage04025106-12
page12
treeJournal of Aerospace Engineering:;2026:;Volume ( 039 ):;issue: 001
contenttypeFulltext


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