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.
","abstract_html":"<p>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.</p>","abstract_has_math":false,"creators":["Wu, Yuxuan"],"institution":null,"degree_name":"Master of Science in Aerospace Engineering","degree_level":"Thesis - Open Access","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-12-01T08:00:00Z","date_published":"2020-12-01T08:00:00Z","updated_at":"2026-07-27T19:26:34Z","subjects":["parametric analysis","particle spreading","discrete element","Aerospace Engineering","Other Materials Science and Engineering","Structures and Materials"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/edt/558","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Wu, Yuxuan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Aerospace Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["parametric analysis","particle spreading","discrete element","Aerospace Engineering","Other Materials Science and Engineering","Structures and Materials"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/edt/558"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.
"]},{"key":"dc:title","label":"Title","values":["Parametric Analysis of Particle Spreading with Discrete Element Method"]}]}],"canonical_facts":{"dc:creator":["Wu, Yuxuan"],"dc:description.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.
"],"dc:identifier":["https://commons.erau.edu/edt/558"],"dc:subject":["parametric analysis","particle spreading","discrete element","Aerospace Engineering","Other Materials Science and Engineering","Structures and Materials"],"dc:title":["Parametric Analysis of Particle Spreading with Discrete Element Method"],"thesis:degree_discipline":["Aerospace Engineering"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Aerospace Engineering"]},"updated_at":"2026-07-27T19:26:34Z"}