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Title: Additive Manufacturing/Diagnostics via the High Frequency Induction Heating of Metal Powders: The Determination of the Power Transfer Factor for Fine Metallic Spheres

Abstract

Grid Logic Inc. is developing a method for sintering and melting fine metallic powders for additive manufacturing using spatially-compact, high-frequency magnetic fields called Micro-Induction Sintering (MIS). One of the challenges in advancing MIS technology for additive manufacturing is in understanding the power transfer to the particles in a powder bed. This knowledge is important to achieving efficient power transfer, control, and selective particle heating during the MIS process needed for commercialization of the technology. The project s work provided a rigorous physics-based model for induction heating of fine spherical particles as a function of frequency and particle size. This simulation improved upon Grid Logic s earlier models and provides guidance that will make the MIS technology more effective. The project model will be incorporated into Grid Logic s power control circuit of the MIS 3D printer product and its diagnostics technology to optimize the sintering process for part quality and energy efficiency.

Authors:
 [1];  [1];  [2];  [2]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Grid Logic, Inc., Lapeer, MI (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Manufacturing Demonstration Facility (MDF)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1224158
Report Number(s):
ORNL/TM-2015/34
ED2701000; CEED492
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Rios, Orlando, Radhakrishnan, Balasubramaniam, Caravias, George, and Holcomb, Matthew. Additive Manufacturing/Diagnostics via the High Frequency Induction Heating of Metal Powders: The Determination of the Power Transfer Factor for Fine Metallic Spheres. United States: N. p., 2015. Web. doi:10.2172/1224158.
Rios, Orlando, Radhakrishnan, Balasubramaniam, Caravias, George, & Holcomb, Matthew. Additive Manufacturing/Diagnostics via the High Frequency Induction Heating of Metal Powders: The Determination of the Power Transfer Factor for Fine Metallic Spheres. United States. doi:10.2172/1224158.
Rios, Orlando, Radhakrishnan, Balasubramaniam, Caravias, George, and Holcomb, Matthew. Wed . "Additive Manufacturing/Diagnostics via the High Frequency Induction Heating of Metal Powders: The Determination of the Power Transfer Factor for Fine Metallic Spheres". United States. doi:10.2172/1224158. https://www.osti.gov/servlets/purl/1224158.
@article{osti_1224158,
title = {Additive Manufacturing/Diagnostics via the High Frequency Induction Heating of Metal Powders: The Determination of the Power Transfer Factor for Fine Metallic Spheres},
author = {Rios, Orlando and Radhakrishnan, Balasubramaniam and Caravias, George and Holcomb, Matthew},
abstractNote = {Grid Logic Inc. is developing a method for sintering and melting fine metallic powders for additive manufacturing using spatially-compact, high-frequency magnetic fields called Micro-Induction Sintering (MIS). One of the challenges in advancing MIS technology for additive manufacturing is in understanding the power transfer to the particles in a powder bed. This knowledge is important to achieving efficient power transfer, control, and selective particle heating during the MIS process needed for commercialization of the technology. The project s work provided a rigorous physics-based model for induction heating of fine spherical particles as a function of frequency and particle size. This simulation improved upon Grid Logic s earlier models and provides guidance that will make the MIS technology more effective. The project model will be incorporated into Grid Logic s power control circuit of the MIS 3D printer product and its diagnostics technology to optimize the sintering process for part quality and energy efficiency.},
doi = {10.2172/1224158},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Mar 11 00:00:00 EDT 2015},
month = {Wed Mar 11 00:00:00 EDT 2015}
}

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