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Journal Articles

Accelerating Thermal Simulations in Additive Manufacturing by Training Physics-Informed Neural Networks With Randomly Synthesized Data

Jiangce Chen, Justin Pierce, Glen Williams, Timothy W. Simpson, Nicholas Meisel, Sneha Prabha Narra, Christopher McComb
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. January 2024, 24(1): 011004.
Paper No: JCISE-23-1058
https://doi.org/10.1115/1.4062852
Published Online: July 20, 2023
View Article titled, Accelerating Thermal Simulations in Additive Manufacturing by Training Physics-Informed Neural Networks With Randomly Synthesized Data
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Topics: Artificial neural networks, Simulation, Physics, Temperature, Additive manufacturing
Proceedings Papers

Analyzing Expert Design Cost Estimation for Additive Manufacturing

Glen Williams, Nicholas A. Meisel, Timothy W. Simpson, Christopher McComb
Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A032, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-90260
https://doi.org/10.1115/DETC2022-90260
View Paper titled, Analyzing Expert Design Cost Estimation for Additive Manufacturing
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Topics: Additive manufacturing, Design, Computer-aided design, Experimental design, Lasers, Manufacturing, Metals, Project cost estimation, Statistics, Tooling
Journal Articles

Design for Artificial Intelligence: Proposing a Conceptual Framework Grounded in Data Wrangling

Glen Williams, Nicholas A. Meisel, Timothy W. Simpson, Christopher McComb
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Technical Briefs
J. Comput. Inf. Sci. Eng. December 2022, 22(6): 060903.
Paper No: JCISE-22-1206
https://doi.org/10.1115/1.4055854
Published Online: October 17, 2022
View Article titled, Design for Artificial Intelligence: Proposing a Conceptual Framework Grounded in Data Wrangling
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Topics: Artificial intelligence, Design, Manufacturing
Proceedings Papers

Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion

Justin Pierce, Glen Williams, Timothy W. Simpson, Nicholas A. Meisel, Christopher McComb
Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A004, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-70557
https://doi.org/10.1115/DETC2021-70557
View Paper titled, Stochastically-Trained Physics-Informed Neural Networks: Application to Thermal Analysis in Metal Laser Powder Bed Fusion
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Topics: Artificial neural networks, Lasers, Metals, Physics, Thermal analysis, Engineering simulation, Machine learning, Manufacturing, Simulation, Transients (Dynamics)
Proceedings Papers

Deriving Metamodels to Relate Machine Learning Quality to Design Repository Characteristics in the Context of Additive Manufacturing

Glen Williams, Nicholas A. Meisel, Timothy W. Simpson, Christopher McComb
Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A006, August 17–19, 2020
Publisher: American Society of Mechanical Engineers
Paper No: DETC2020-22518
https://doi.org/10.1115/DETC2020-22518
View Paper titled, Deriving Metamodels to Relate Machine Learning Quality to Design Repository Characteristics in the Context of Additive Manufacturing
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Topics: Additive manufacturing, Design, Machine learning, Artificial neural networks, Trains, Fuels, Simulation, Thread
Proceedings Papers

Comparing Attribute- and Form-Based Machine Learning Techniques for Component Prediction

Glen Williams, Lucas Puentes, Jacob Nelson, Jessica Menold, Conrad Tucker, Christopher McComb
Proc. ASME. IDETC-CIE2020, Volume 11B: 46th Design Automation Conference (DAC), V11BT11A019, August 17–19, 2020
Publisher: American Society of Mechanical Engineers
Paper No: DETC2020-22256
https://doi.org/10.1115/DETC2020-22256
View Paper titled, Comparing Attribute- and Form-Based Machine Learning Techniques for Component Prediction
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Topics: Machine learning, Algorithms, Gears, Engineers, Neural network models, Sales, Three-dimensional models
Journal Articles

Detection of System Compromise in Additive Manufacturing Using Video Motion Magnification

Sakthi Kumar Arul Prakash, Tobias Mahan, Glen Williams, Christopher McComb, Jessica Menold, Conrad S. Tucker
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2020, 142(3): 031109.
Paper No: MD-19-1429
https://doi.org/10.1115/1.4045547
Published Online: December 23, 2019
View Article titled, Detection of System Compromise in Additive Manufacturing Using Video Motion Magnification
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Topics: Additive manufacturing, Computer security, Magnification, Printing, Data collection, Tensile testing, Errors, Image processing
Proceedings Papers

On the Analysis of a Compromised Additive Manufacturing System Using Spatio-Temporal Decomposition

Sakthi Kumar Arul Prakash, Tobias Mahan, Glen Williams, Christopher McComb, Jessica Menold, Conrad S. Tucker
Proc. ASME. IDETC-CIE2019, Volume 2B: 45th Design Automation Conference, V02BT03A018, August 18–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: DETC2019-97732
https://doi.org/10.1115/DETC2019-97732
View Paper titled, On the Analysis of a Compromised Additive Manufacturing System Using Spatio-Temporal Decomposition
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Topics: Additive manufacturing, Errors, Computer software, Cyber-physical systems, End effectors, Engineering prototypes, Failure, Hardware, Optical quality control, Printing
Journal Articles

Design Repository Effectiveness for 3D Convolutional Neural Networks: Application to Additive Manufacturing

Glen Williams, Nicholas A. Meisel, Timothy W. Simpson, Christopher McComb
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. November 2019, 141(11): 111701.
Paper No: MD-19-1160
https://doi.org/10.1115/1.4044199
Published Online: September 16, 2019
View Article titled, Design Repository Effectiveness for 3D Convolutional Neural Networks: Application to Additive Manufacturing
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Topics: Artificial neural networks, Design, Additive manufacturing, Regression models