Development of an Experimental Optimization Method in Laser-Assisted Cold Spray
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open in viewerCurrent 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).
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- E-project-032217-130630
- Advisor
- Year
- 2017
- Sponsor
- Date created
- 2017-03-22
- Resource type
- Major
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