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Development of an Artificial Neural Network Based Analysis Method for Skin-Stringer Structures
Date
2017-09-26
Author
Cankur, Anıl
Gürses, Ercan
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URI
https://hdl.handle.net/11511/85637
Conference Name
7th EASN International Conference on Innovation in European Aeronautics Research, (26 - 29 Eylül 2017)
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Unverified, Conference / Seminar
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Development of an artificial neural network based analysis method for skin-stringer structures
Cankur, Anıl; Gürses, Ercan; Department of Aerospace Engineering (2017)
The purpose of this work is to develop a tool for the design of skin-stringer structures. The tool to be developed needs to quickly identify the load carrying capacity and weight of these structures. For this purpose, finite element (FE) models of 1440 different skin-stringer structures were created with a script written in Python 2.7, and these models were analyzed using the commercial FE program ABAQUS. The script was used to construct the model, analyze the model, calculate the buckling load, the collaps...
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Block geometry is commonly the most important feature determining the behaviour of a rock mass and directly controls the structural instability in underground openings or surface cuttings. Various methods are used to estimate block geometry and to perform a block survey, and these are standardly divided into empirical-based methods (e.g. spot mapping, linear mapping, areal mapping) and computer-based methods (e.g. laser scanning, image processing, digital image mapping). Empirical approaches are associated ...
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A. Cankur and E. Gürses, “Development of an Artificial Neural Network Based Analysis Method for Skin-Stringer Structures,” presented at the 7th EASN International Conference on Innovation in European Aeronautics Research, (26 - 29 Eylül 2017), Warszawa, Polonya, 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/85637.