Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2761
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dc.contributor.authorKumar, Puneet-
dc.contributor.authorSrinivas, J-
dc.date.accessioned2017-09-13T10:03:57Z-
dc.date.available2017-09-13T10:03:57Z-
dc.date.issued2017-09-
dc.identifier.citationThirty-third National Convention of Mechanical Engineers on Advances in MEMS and Robotics in Manufacturing Industries, Udaipur, Rajastan, India, 01-02 September, 2017en_US
dc.identifier.urihttp://hdl.handle.net/2080/2761-
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractMicroelectro mechanical systems have widespread applications as sensing elements in manufacturing operations. Small scale, self-energizing sensors are very much required in the modern machining industries. This work presents use of functional graded nanopolymer composites as a microbeam sensing elements in milling application towards prediction of workpiece displacement. A model to investigate the dynamic-pull-in characteristics of a functionally carbon nanotube (FG-CNT) reinforced polymer composite microbeam is developed. Based Eular-Burnoulli theory the dynamic governing equation of an electrostatically actuated micro resonator is derived. The material properties of the FG-CNT composite microbeam are estimated using modified Halpin-Tsai model and rule of mixture. A squeeze film damping is accounted along with electrostatic actuation. The influences of voltage effect, volume fraction, and distribution of CNTs and initial amplitude on dynamic-pull-in behaviors of the microbeam are discussed. A dynamic model of machining process is considered to illustrate the relative motion sensed by the microbeam resonator.en_US
dc.subjectMicrobeam resonatoren_US
dc.subjectFunctionally graded materialen_US
dc.subjectHalpin-Tsai modeen_US
dc.subjectElectrostatic actuationen_US
dc.titleComprehensive study on a functionally graded Carbon Nanotube reinforced dielectric elastomeric nanocomposite microbeam resonatoren_US
dc.typeArticleen_US
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