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Journal Articles

Physics-Informed Fully Convolutional Networks for Forward Prediction of Temperature Field and Inverse Estimation of Thermal Diffusivity

Tong Zhu, Qiye Zheng, Yanglong Lu
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. November 2024, 24(11): 111004.
Paper No: JCISE-23-1469
https://doi.org/10.1115/1.4064555
Published Online: July 22, 2024
View Article titled, Physics-Informed Fully Convolutional Networks for Forward Prediction of Temperature Field and Inverse Estimation of Thermal Diffusivity
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Topics: Heat conduction, Physics, Temperature, Thermal diffusivity, Artificial neural networks, Boundary-value problems, Inverse problems
Proceedings Papers

Temperature Field Monitoring in Fused Filament Fabrication Process Based on Physics-Constrained Dictionary Learning

Yanglong Lu, Yan Wang
Proc. ASME. IAM2022, 2022 International Additive Manufacturing Conference, V001T03A003, October 19–20, 2022
Publisher: American Society of Mechanical Engineers
Paper No: IAM2022-93987
https://doi.org/10.1115/IAM2022-93987
View Paper titled, Temperature Field Monitoring in Fused Filament Fabrication Process Based on Physics-Constrained Dictionary Learning
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Topics: Manufacturing, Physics, Temperature, Sensors, Additive manufacturing, Compression, Imaging, Process monitoring, Resolution (Optics), Sensor placement
Proceedings Papers

Concurrent Shape and Topology Optimization of Metamaterials Based on Periodic Surface Modeling

Yanglong Lu, Yan Wang
Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A048, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-91214
https://doi.org/10.1115/DETC2022-91214
View Paper titled, Concurrent Shape and Topology Optimization of Metamaterials Based on Periodic Surface Modeling
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Topics: Metamaterials, Modeling, Optimization, Shapes, Topology, Design, Poisson ratio, Shape optimization, Structural optimization, Weight (Mass)
Journal Articles

Physics-Constrained Bayesian Neural Network for Bias and Variance Reduction

Luka Malashkhia, Dehao Liu, Yanglong Lu, Yan Wang
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. February 2023, 23(1): 011012.
Paper No: JCISE-22-1123
https://doi.org/10.1115/1.4055924
Published Online: November 8, 2022
View Article titled, Physics-Constrained Bayesian Neural Network for Bias and Variance Reduction
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Topics: Algorithms, Artificial neural networks, Heat transfer, Physics, Simulation, Temperature, Uncertainty, Phase transitions, Finite element methods, Additive manufacturing
Journal Articles

Physics-Based Compressive Sensing to Enable Digital Twins of Additive Manufacturing Processes

Yanglong Lu, Eduard Shevtshenko, Yan Wang
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. June 2021, 21(3): 031009.
Paper No: JCISE-20-1239
https://doi.org/10.1115/1.4050377
Published Online: March 25, 2021
View Article titled, Physics-Based Compressive Sensing to Enable Digital Twins of Additive Manufacturing Processes
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Topics: Additive manufacturing, Cooling, Physics, Temperature, Temperature distribution, Errors, Process monitoring, Gears
Proceedings Papers

An Improvement of Physics Based Compressive Sensing With Domain Decomposition to Monitor Temperature in Fused Filament Fabrication Process

Yanglong Lu, Yan Wang
Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T01A032, June 10–14, 2019
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2019-2899
https://doi.org/10.1115/MSEC2019-2899
View Paper titled, An Improvement of Physics Based Compressive Sensing With Domain Decomposition to Monitor Temperature in Fused Filament Fabrication Process
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Topics: Manufacturing, Physics, Temperature
Proceedings Papers

Manufacturing Energy Consumption Estimation Using Machine Learning Approach

Ruoyu Song, Yanglong Lu, Cassandra Telenko, Yan Wang
Proc. ASME. IDETC-CIE2017, Volume 4: 22nd Design for Manufacturing and the Life Cycle Conference; 11th International Conference on Micro- and Nanosystems, V004T05A037, August 6–9, 2017
Publisher: American Society of Mechanical Engineers
Paper No: DETC2017-67679
https://doi.org/10.1115/DETC2017-67679
View Paper titled, Manufacturing Energy Consumption Estimation Using Machine Learning Approach
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Topics: Energy consumption, Machine learning, Manufacturing, Computer-aided design, Design, Modeling