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Innovative Multi-scale/Multi-physics Model for Surface Finish Prediction and Optimization of Metal Additively Manufactured Parts

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68936-20-C-0023
Agency Tracking Number: N19B-034-0042
Amount: $139,921.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N19B-T034
Solicitation Number: 19.B
Timeline
Solicitation Year: 2019
Award Year: 2020
Award Start Date (Proposal Award Date): 2019-10-22
Award End Date (Contract End Date): 2020-04-23
Small Business Information
3190 Fairview Park Drive Suite 650
Falls Church, VA 22042
United States
DUNS: 010983174
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Lei Yan
 Engineer
 (703) 226-4068
 lyan@tda-i.com
Business Contact
 Patty Walk
Phone: (703) 226-4064
Email: pwalk@tda-i.com
Research Institution
 University of Louisville
 Matthew J. Hawthoren Matthew J. Hawthoren
 
300 East Market Street, Suite 300
Louisville, KY 40202
United States

 (502) 852-3156
 Nonprofit College or University
Abstract

In this STTR effort, TDA and its team partner University of Louisville will focus on developing an innovative intelligent decision support tool using data-driven multi-scale multi-physics models (DDMM) to derive process-surface roughness relationships for selective laser melting (SLM). The proposed models account for both powder characteristics and AM processing/path planning, including powder size distribution, laser power, scanning speed, scanning strategy, geometry features, and build orientation. Critical experiments will be performed during the course of this research as part of verification and validation. The goal of this DDMM computational framework is to predict and optimize component-level surface roughness within a reasonable time. Proposed DDMM computational framework will address surface roughness caused by rippling marks, balling effect, staircase effect, and sintered powders. Solution for the DDMM framework will be obtained by discrete element method (DEM), computational fluid dynamics (CFD), finite element method (FEM) and data-driven modeling.

* Information listed above is at the time of submission. *

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