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Lele Luan
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Proceedings Papers

Industrial Applications of Transfer Learning Methods for Aircraft Propulsion Systems

Ryan Jacobs, Sandipp Krishnan, Anindya Bhaduri, Lele Luan, Piyush Pandita, Sayan Ghosh, Liping Wang
Proc. ASME. GT2024, Volume 10B: Structures and Dynamics — Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V10BT25A004, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-125838
https://doi.org/10.1115/GT2024-125838
View Paper titled, Industrial Applications of Transfer Learning Methods for Aircraft Propulsion Systems
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Topics: Aircraft propulsion, Design, Maintenance, Propulsion, Blades, Machine learning, Artificial neural networks, Cycles, Deep neural networks, Downtime
Journal Articles

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Accepted Manuscript
Anirban Samaddar, Sandipp Krishnan Ravi, Nesar Ramachandra, Lele Luan, Sandeep Madireddy, Anindya Bhaduri, Piyush Pandita, Changjie Sun, Liping Wang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des.
Paper No: MD-24-1156
https://doi.org/10.1115/1.4066224
Published Online: August 16, 2024
View Article titled, Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields
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Topics: Metamodeling, Modeling, Stress, Simulation, Tensors, Artificial intelligence, Artificial neural networks, Compression, Convolutional neural networks, Data-driven design
Journal Articles

Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data

Anindya Bhaduri, Nesar Ramachandra, Sandipp Krishnan Ravi, Lele Luan, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. May 2024, 24(5): 051008.
Paper No: JCISE-23-1360
https://doi.org/10.1115/1.4064622
Published Online: March 5, 2024
View Article titled, Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data
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Topics: Computer-aided engineering, Convolutional neural networks, Shapes, Stress
Proceedings Papers

Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data

Anindya Bhaduri, Nesar Ramachandra, Sandipp Krishnan Ravi, Lele Luan, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang
Proc. ASME. IDETC-CIE2023, Volume 2: 43rd Computers and Information in Engineering Conference (CIE), V002T02A004, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-115077
https://doi.org/10.1115/DETC2023-115077
View Paper titled, Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data
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Topics: Artificial neural networks, Shapes, Stress
Proceedings Papers

Scalable Probabilistic Modeling and Machine Learning With Dimensionality Reduction for Expensive High-Dimensional Problems

Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi, Anindya Bhaduri, Piyush Pandita, Prasanna Balaprakash, Mihai Anitescu, Changjie Sun, Liping Wang
Proc. ASME. IDETC-CIE2023, Volume 2: 43rd Computers and Information in Engineering Conference (CIE), V002T02A011, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-110704
https://doi.org/10.1115/DETC2023-110704
View Paper titled, Scalable Probabilistic Modeling and Machine Learning With Dimensionality Reduction for Expensive High-Dimensional Problems
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Topics: Artificial neural networks, Machine learning, Metamodeling, Modeling
Proceedings Papers

Physics Discovery of Engineering Applications With Constrained Optimization and Genetic Programming

Lele Luan, Ryan Jacobs, Sayan Ghosh, Liping Wang
Proc. ASME. GT2023, Volume 11B: Structures and Dynamics — Emerging Methods in Engineering Design, Analysis, and Additive Manufacturing; Fatigue, Fracture, and Life Prediction; Probabilistic Methods; Rotordynamics; Structural Mechanics and Vibration, V11BT25A005, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-104043
https://doi.org/10.1115/GT2023-104043
View Paper titled, Physics Discovery of Engineering Applications With Constrained Optimization and Genetic Programming
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Topics: Computer programming, Engineering systems and industry applications, Machine learning, Optimization, Physics