Graduation Semester and Year




Document Type


Degree Name

Master of Science in Mechanical Engineering


Mechanical and Aerospace Engineering

First Advisor

Kent L Lawrence


The 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.


Aerospace Engineering | Engineering | Mechanical Engineering


Degree granted by The University of Texas at Arlington