Faculty Advisor

Apelian, Diran

Abstract

Current experimental optimization methods take extended periods of time and do not have a systematic way to get closer to the optimum. As a result, the team set out to generate a new, systematic approach to experimental optimization that costs time and cost. First, a theoretical goodness equation was used to predict the influential trends of parameters in the Laser-Assisted Cold Spray (LACS) process on three material properties. This was also used to select the algorithm used, Mine Blast Algorithm. The equation and algorithm was then modified for the experimental process which included a fourth variable. The team was able to achieve a goodness of 0.66 after only 5 iterations of the estimated 25 iterations necessary to achieve optimization (30 samples).

Publisher

Worcester Polytechnic Institute

Date Accepted

March 2017

Major

Mechanical Engineering

Project Type

Major Qualifying Project

Accessibility

Unrestricted

Advisor Department

MPI

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