Date of Award

Fall 12-2020

Access Type

Thesis - Open Access

Degree Name

Master of Science in Aerospace Engineering

Department

Aerospace Engineering

Committee Chair

Sirish Namilae

First Committee Member

Marwan S. Al-Haik

Second Committee Member

Daewon Kim

Abstract

The spreading of metallic powder on the printing platform is vital in most additive manufacturing methods, including direct laser sintering. Several processing parameters such as particle size, inter-particle friction, blade speed, and blade gap size affect the spreading process and, therefore, the final product quality. The objective of this study is to parametrically analyze the particle flow behavior and the effect of the aforementioned parameters on the spreading process using the discrete element method (DEM). To effectively address the vast parameter space within computational constraints, novel parameter sweep algorithms based on low discrepancy sequence (LDS) are utilized in conjunction with parallel computing. Based on the parametric analysis, optimal material properties and machine setup are proposed for a higher quality spreading. Modeling suggests that lower friction, smaller particle size, lower blade speed, and a gap of two times the particle diameter result in a higher quality spreading process. In addition, a twoparameter Weibull distribution is adopted to investigate the influence of particle size distribution. The result suggests that smaller particles with a narrower distribution produce a higher-quality flow, with a proper selection of gap. Finally, parallel computing, in conjunction with the LDS parameter sweep algorithm, effectively shrinks the parameter space and improves the overall computational efficiency.

Download

Share

COinS