Please use this identifier to cite or link to this item: http://dspace.dtu.ac.in:8080/jspui/handle/repository/15750
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBHATI, SUMIT RAJ-
dc.date.accessioned2017-06-14T12:16:36Z-
dc.date.available2017-06-14T12:16:36Z-
dc.date.issued2013-07-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/15750-
dc.description.abstractEarthquakes are considered to be the most devastating catastrophic activity. Earthquakes, as of themselves, do not cause the damages of life and property, but they affect the structures, thereby causing serious threat to life and property in the structure. The recent development in the field of structural control has enabled us to predict, as well as control the response of a structure under seismic loading, in a simplified and effective manner. The application of Artificial Neural Networks (ANN) in the field of Structural Control has further simplified the problem of prediction of responses and other control parameters. The semi-active control has emerged as a very attractive proposition of structural control in last one decade. Researchers have been investigating various semi-active devices through experimental and analytical studies. In this study the effectiveness of Magneto Rheological (MR) damper, which is one of the most effective semi-active control device has been studied. Then, an Artificial Neural Network (ANN) has been developed to predict the response of the structure considering the parameters of two different ground motions and the parameters of the structure. This report investigates the feasibility of structural control systems in combination with the artificial neural networks (ANN) techniques. The objective of this study is to know the basics of neural network and in further studies compare the results of Uncontrolled and controlled (MR Dampers) by using artificial neural networks. ANN has the ability to learn and simplify from examples without knowledge of rules. In the field of “structural engineering” problems research in to artificial neural networks is growing rapidly.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTD NO.1260-A;-
dc.subjectMULTISTORIED BUILDINGen_US
dc.subjectMAGNETO RHEOLOGICALen_US
dc.subjectNEURAL NETWORKen_US
dc.subjectANNen_US
dc.titleRESPONSE OF MULTISTORIED BUILDING USING SEMI-ACTIVE MAGNETO RHEOLOGICAL (MR) DAMPER BY NEURAL NETWORKen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Structural Engineering

Files in This Item:
File Description SizeFormat 
word-to-pdf.pdf35.1 kBAdobe PDFView/Open
Major Project Report ANN SUMIT.pdf1.93 MBAdobe PDFView/Open
front page bhati.pdf35.29 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.