Show simple item record

dc.contributor.authorMenon, Ajaykumaren_US
dc.date.accessioned2007-08-23T01:56:25Z
dc.date.available2007-08-23T01:56:25Z
dc.date.issued2007-08-23T01:56:25Z
dc.date.submittedDecember 2005en_US
dc.identifier.otherDISS-1129en_US
dc.identifier.urihttp://hdl.handle.net/10106/286
dc.description.abstractThe high computational expense of large non-linear and complex finite element analysis limits or often prohibits the use of conventional codes in engineering design and multidisciplinary optimization. Consequently alternate methods such as Design of experiments (DOE) and Response surface approximation are commonly used to minimize the computational cost of running such analysis and simulation. The basic approach of such methods is to construct a simplified mathematical approximation of the computationally expensive simulation and analysis code, which is then used in place of the original code to facilitate multidisciplinary optimization, design space exploration, reliability analysis etc. When such codes along with powerful finite element analysis tools such as ANSYS are tied with good optimization algorithms, solving complex structural optimization problems are no longer an issue. This research work aims at defining such an automation process in MATLAB that incorporates a response surface approximating tool called MQR which is based on Radial basis function, ANSYS a finite element solver and a suitable gradient based optimization algorithm (SQP). Certain standard test cases are considered that are based on size and dynamic response optimization. The results obtained from the proposed method are compared with ANSYS DesignXplorer goal driven optimization which is based on DOE and also with ANSYS First order optimization technique. The comparison of the results demonstrates the accuracy and effectiveness of the proposed MQR based optimization process.en_US
dc.description.sponsorshipLawrence, Kent L.en_US
dc.language.isoENen_US
dc.publisherMechanical Engineeringen_US
dc.titleStructural Optimization Using ANSYS And Regulated Multiquadric Response Surface Modelen_US
dc.typeM.S.M.E.en_US
dc.contributor.committeeChairLawrence, Kent L.en_US
dc.degree.departmentMechanical Engineeringen_US
dc.degree.disciplineMechanical Engineeringen_US
dc.degree.grantorUniversity of Texas at Arlingtonen_US
dc.degree.levelmastersen_US
dc.degree.nameM.S.M.E.en_US
dc.identifier.externalLinkhttps://www.uta.edu/ra/real/editprofile.php?onlyview=1&pid=256
dc.identifier.externalLinkDescriptionLink to Research Profiles


Files in this item

Thumbnail


This item appears in the following Collection(s)

Show simple item record