Development and Design of Self-Sensing SMAs using Thermoelectric Effect

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dc.contributor.authorMalladi, Vijaya Venkata Narasimha Sriramen
dc.contributor.committeechairTarazaga, Pablo Albertoen
dc.contributor.committeememberKurdila, Andrew J.en
dc.contributor.committeememberInman, Daniel J.en
dc.contributor.departmentMechanical Engineeringen
dc.date.accessioned2014-03-14T20:39:18Zen
dc.date.adate2013-06-17en
dc.date.available2014-03-14T20:39:18Zen
dc.date.issued2013-05-20en
dc.date.rdate2013-06-17en
dc.date.sdate2013-06-03en
dc.description.abstractActive research of SMAs has shown that its Seebeck coefficient is sensitive to its martensitic phase transformation and has the potential to determine the SMAs state of transformation. The combination of Shape Memory Alloys, which have a positive Seebeck coefficient, and Constantan which has a negative Seebeck coefficient (-35 mV/K) results in a thermocouple capable of measuring temperature. The work presented in this thesis is based on the development and design of this sensor. This sensor is used to study the hysteretic behaviour of SMAs. Although Shape Memory Alloys (SMAs) exhibit a myriad of nonlinearities, SMAs show two major types of nonlinear hysteresis. During cyclic loading of the SMAs, it is observed that one type of hysteretic behavior depends on the rate of heating the SMAs, whilst the variation of maximum temperature of an SMA in each cycle results in the other hysteretic behavior. This later hysteretic behavior gives rise to major and minor nonlinear loops of SMAs. The present work analyzes the nonlinearities of hysteretic envelopes which gives the different maximum temperatures reached for each hysteretic cycle with respect to stress and strain of the SMA. This work then models this behavior using Adaptive Neuro Fuzzy Inference System (ANFIS) and compares it to experimental results. The nonlinear learning and adaptation of ANFIS architecture makes it suitable to model the temperature path hysteresis of SMAs.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-06032013-114013en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-06032013-114013/en
dc.identifier.urihttp://hdl.handle.net/10919/33407en
dc.publisherVirginia Techen
dc.relation.haspartMalladi_VVNS_T_2013_version3.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectANNen
dc.subjectPosition Controlen
dc.subjectANFISen
dc.subjectSeebeck Coefficienten
dc.subjectThermoelectric Effectsen
dc.subjectSensorless Controlen
dc.subjectShape Memory Alloysen
dc.titleDevelopment and Design of Self-Sensing SMAs using Thermoelectric Effecten
dc.typeThesisen
thesis.degree.disciplineMechanical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen
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