Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Recep M. Gorguluarslan"'
Publikováno v:
Applied Sciences, Vol 10, Iss 16, p 5650 (2020)
Recent advancements in computer technology have allowed designers to have direct control over the production process through the help of computer-based tools, creating the possibility of completely integrated design and manufacturing processes [...]
Externí odkaz:
https://doaj.org/article/4bdf475b2cde469cb7e1fffd9633d7b9
Publikováno v:
Applied Sciences, Vol 10, Iss 2, p 643 (2020)
Interests in strain gauge sensors employing stretchable patch antenna have escalated in the area of structural health monitoring, because the malleable sensor is sensitive to capturing strain variation in any shape of structure. However, owing to the
Externí odkaz:
https://doaj.org/article/3877d65a521d47a4a984b2228683c63b
Autor:
Recep M Gorguluarslan, Arda I Ozay
Publikováno v:
Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications. 237:1548-1561
In this study, an efficient fatigue life estimation approach is proposed based on an equivalent solid model, along with two stress concentration factors, instead of a lattice model to simplify simulations for the strain-life method. One of the stress
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68cbfa1236a57a188aa12e4b98463fd0
https://doi.org/10.1177/14644207221148854
https://doi.org/10.1177/14644207221148854
Publikováno v:
Structural and Multidisciplinary Optimization. 66
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0c6973f4e9b72705646d1c7a2b7c2b6
https://doi.org/10.1007/s00158-023-03557-1
https://doi.org/10.1007/s00158-023-03557-1
Publikováno v:
Meccanica. 56:2825-2841
The objective of this study is to investigate the energy absorption performance of the graded lattice energy absorbers designed by a stiffness-based size optimization process under static loadings applied during the in-service conditions. The energy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f367797180ca320b4fd338f918b9087b
https://doi.org/10.1007/s11012-021-01404-5
https://doi.org/10.1007/s11012-021-01404-5
Publikováno v:
Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology.
The applicability of artificial neural networks (ANNs) on the prediction of the structural optimization results of a truss structure is investigated. Two different ANN architectures are employed and the effect of using various optimizers and activati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cecf0f273f0282e1d05a2c6120f8c782
https://doi.org/10.1115/imece2022-95870
https://doi.org/10.1115/imece2022-95870
Autor:
Hüseyin Karabiyik, Osman Eroglu, Muhammed Metin Eskimez, Berk Oncu Oncul, Muhammet Tayyip Yilmaz, İstemihan Gökdağ, Recep M. Gorguluarslan
Publikováno v:
Volume 3: Advanced Materials: Design, Processing, Characterization and Applications; Advances in Aerospace Technology.
The most important need in the aviation industry is the realization of high-strength and lightweight designs. For this reason, topology optimization methods have become widespread recently. Besides, meeting the natural frequency requirements is one o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9a1b9120f26c3fef0f1e398e0947e27
https://doi.org/10.1115/imece2022-95843
https://doi.org/10.1115/imece2022-95843
Publikováno v:
Structural and Multidisciplinary Optimization. 63:1927-1950
A vital necessity when employing state-of-the-art deep neural networks (DNNs) for topology optimization is to predict near-optimal structures while satisfying pre-defined optimization constraints and objective function. Existing studies, on the other
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32301ebc56dac3fc35d075c0c67eeb4c
https://doi.org/10.1007/s00158-020-02788-w
https://doi.org/10.1007/s00158-020-02788-w
Publikováno v:
Journal of Computing and Information Science in Engineering. 22
Additive manufacturing (AM) introduces geometric uncertainties on the fabricated strut members of lattice structures. These uncertainties result in deviations between the modeled and fabricated geometries of struts. The use of deep neural networks (D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c58fe9f75f380df2515ea38b7a8cbb9d
https://doi.org/10.1115/1.4053001
https://doi.org/10.1115/1.4053001
Publikováno v:
Volume 2A: Advanced Manufacturing.
The aim of this study is to evaluate the differences between the tensile test results of individual strut members fabricated by the material extrusion process and finite element analysis (FEA) predictions of the struts modeled with the geometric vari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e51cf94234ad4b94d32ddf9d3b331e9
https://doi.org/10.1115/imece2021-71563
https://doi.org/10.1115/imece2021-71563