Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Prediction of Modal Response of Towers Using Artificial Neural Networks
Date
2022-01-01
Author
Yücel, Özge
Demir, Berkan
Ates, H. Ibrahim
ALDEMİR, ALPER
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
73
views
0
downloads
Cite This
Overhead transmission line towers may be subjected to a severe level of earthquake-related forces if the line lies in a seismically active region. However, the traditional practice in the industry generally overlooks the effect of seismic forces on the structural demand in parallel with universally valid design codes claiming that the base shear that emerges on an earthquake would generally be less than wind or wind + ice combined conditions. On the other side, in recent years, a rising number of scientific articles in relation to the possibility of severe consequences of an earthquake on the components of a transmission line (e.g., towers) have been published. Additionally, in late 2019, the Ministry of Environment and Urbanization of the Turkish Republic put a comprehensive earthquake code along with a new seismic map of the country into effect, also covering transmission line towers. Preliminary studies revealed that earthquake-related forces might be critical for specific components of towers, especially in case the line was located close to the fault zones. In this regard, modal analyses of towers have become a must for the industry of transmission line engineering in some countries. In addition, even the most common commercial software packages used in tower analysis and design do not have the option to perform the modal analysis. In order to determine the modal response of towers, the finite element model (FEM) of the tower or whole tower family must be generated or be transferred to an alternative FEM software, which is a cumbersome procedure. At this point, artificial neural networks (ANN) can be a practical solution. In brief, this study aims to construct and train an ANN architecture in order to determine the relationship between the structural parameters related to the mass and stiffness of the tower with first mode frequencies. In this way, required modal response data of the considered tower can be obtained rapidly with a high accuracy rate.
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139505865&origin=inward
https://hdl.handle.net/11511/101610
DOI
https://doi.org/10.1061/9780784484463.033
Conference Name
Electrical Transmission and Substation Structures Conference 2022: Innovating for Critical Global Infrastructure
Collections
Department of Geological Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Simulation Based Optimal Sensor Actuator Positioning on a Fin Like Structure
Pedremasl, Nıma; Şahin, Melin; Acar, Erdem (2015-06-26)
Aircraft structures are subjected to high amplitude dynamic loads under service conditions; hence, it is necessary to determine their dynamic properties. Dynamic properties of a structure can be determined using simulation-based methods (e.g., finite element method) or using experimental modal analysis (EMA) methods. An EMA system should be lightweight and accurate so that it does not have a negative impact on the dynamic performance of the structure. For this purpose, the transducers (sensor and actuators)...
Prediction of input energy spectrum: attenuation models and velocity spectrum scaling
Alici, F. S.; Sucuoğlu, Haluk (Wiley, 2016-10-25)
Recent improvements in performance-based earthquake engineering require realistic description of seismic demands and accurate estimation of supplied capacities in terms of both forces and deformations. Energy based approaches have a significant advantage in performance assessment because excitation and response durations, accordingly energy absorption and dissipation characteristics, are directly considered whereas force and displacement-based procedures are based only on the maximum response parameters. En...
Optimization of types, numbers and locations of sensors and actuators used in modal analysis of aircraft structures using genetic algorithm
Pedramasl, Nima; Şahin, Melin; Acar, Erdem; Department of Aerospace Engineering (2017)
Aircraft structures are exposed to dynamic loads under service conditions and therefore, it is necessary to determine their dynamic characteristics. Dynamic characteristics of a structure can be determined using simulation-based methods such as finite element analysis (FEA) or test-based methods such as experimental modal analysis (EMA). In order to perform an EMA with reliable and high quality results, test equipment must be lightweight and have high accuracy. In addition, the sensors and actuators must be...
Detailed load rating analyses of bridge populations using nonlinear finite element models and artificial neural networks
Hasançebi, Oğuzhan (2013-11-01)
For assessing load rating capacity of bridges, American Association of State Highway and Transportation Officials Manual (AASHTO) recommends a simple method, where distribution of the forces in transverse direction is estimated by axle-load distribution factors on a simply supported beam. Although the method is practical in the sense that it allows for rapid evaluation of bridge populations, it leads to over-conservative load ratings. A finite element (FE) based load rating analysis is conceived as a more a...
Reliability simulation of scouring downstream of outlet facilities
Yanmaz, Ali Melih (TÜBİTAK, 2003-03-01)
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Ö. Yücel, B. Demir, H. I. Ates, and A. ALDEMİR, “Prediction of Modal Response of Towers Using Artificial Neural Networks,” presented at the Electrical Transmission and Substation Structures Conference 2022: Innovating for Critical Global Infrastructure, Florida, Amerika Birleşik Devletleri, 2022, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139505865&origin=inward.