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Optimized Build Plate Design Tool for Metal Laser Powder Bed Additive Manufacturing

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0321
Agency Tracking Number: N17B-033-0014
Amount: $299,947.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: N17B-T033
Solicitation Number: 17.B
Timeline
Solicitation Year: 2017
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-04-18
Award End Date (Contract End Date): 2020-04-16
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
 Nicole Apetre
 Senior Engineer
 (703) 226-4076
 napetre@tda-i.com
Business Contact
 Patty Walk
Phone: (703) 226-4064
Email: pwalk@tda-i.com
Research Institution
 The Board of Regents of the University of Wisconsin System
 Brenda Egan Brenda Egan
 
21 N Park Street Suite 6401
Madison, WI 53715
United States

 (608) 262-3822
 Nonprofit College or University
Abstract

TDA’s proposed work addresses the target STTR topic objectives of developing an intelligent decision support system to (a) ease the burden of experiments, (b) mitigate the process-induced residual stresses and distortions, (c) include advanced optimization features and (d) help the user in selecting the best part orientation & support for the selected AM platform.Based on our team’s expertise in topology optimization, modeling and design for additive manufacturing and high-performance computing our approach consists of: (a) finding an optimal build orientation to minimize geometry-based cost functions supported by expert advisory system by considering geometrical features of complex components, (b) finding an optimal support structure to minimize thermomechanical performance functions related with part quality and productivity, (c) developing fast thermo-mechanical AM simulations - reduce the computational cost of analysisThe proposed work will include experimental validation to confirm the developed optimization algorithms.

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

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