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Search Publications by: Jason Fox (Fed)

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Displaying 51 - 75 of 96

Data-driven characterization of computational models for powder-bed-fusion additive manufacturing

July 31, 2020
Author(s)
Yan Lu, Zhuo Yang, Paul W. Witherell, Wentao Yan, Kevontrez Jones, Gregory Wagner, Wing-Kam Liu, Jason C. Fox
Computational modeling for additive manufacturing has proven to be a powerful tool to understand the physical mechanisms, predict fabrication quality, and guide design and optimization. Varieties of models have been developed with different assumptions and

Outcomes and Conclusions from the 2018 AM-Bench Measurements, Challenge Problems, Modeling Submissions, and Conference

February 13, 2020
Author(s)
Lyle E. Levine, Brandon M. Lane, Jarred C. Heigel, Kalman D. Migler, Mark R. Stoudt, Thien Q. Phan, Richard E. Ricker, Maria Strantza, Michael R. Hill, Fan Zhang, Jonathan E. Seppala, Edward J. Garboczi, Erich D. Bain, Daniel Cole, Andrew J. Allen, Jason C. Fox, Carelyn E. Campbell
The Additive Manufacturing Benchmark Test Series (AM-Bench) was established to provide rigorous measurement test data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM-Bench includes

PROBABILITY OF DETECTION OF X-RAY COMPUTED TOMOGRAPHY OF ADDITIVE MANUFACTURING DEFECTS

July 19, 2019
Author(s)
Felix H. Kim, Adam L. Pintar, Jason C. Fox, Jared B. Tarr, M A. Donmez, Anne-Fran?oise Obaton
A methodology to determine probability of detection (POD) of X-ray Computed Tomography (XCT) was developed using Additive Manufacturing defects. A signal response POD analysis (a^ vs a) was used, where both signal response (a^) and true defect size (a)

Complementary Use of Optical Metrology and X-Ray Computed Tomography for Surface Finish and Defect Detection in Laser Powder Bed Fusion Additive Manufacturing

July 25, 2018
Author(s)
Jason C. Fox, Felix H. Kim, Zachary C. Reese, Christopher Evans
The development of additive manufacturing (AM) has allowed for production of high-value and complex parts that reduce time-to-market and cost to manufacture. A key benefit to the AM process is the capability to create lattice structures and highly complex

Implementation of Advanced Laser Control Strategies for Powder Bed Fusion Systems

June 21, 2018
Author(s)
Ho Yeung, Brandon Lane, Alkan Donmez, Jason Fox, Jorge Neira
Laser path, scan speed, and laser power are critical machine parameters determining the quality of the output of laser-based powder bed fusion (LPBF) processes. A jerk-limited control strategy is implemented for laser path planning on a LPBF additive