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Journal Articles

On the Use of Geometric Deep Learning for the Iterative Classification and Down-Selection of Analog Electric Circuits

Anthony Sirico, Jr., Daniel R. Herber
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051703.
Paper No: MD-23-1443
https://doi.org/10.1115/1.4063659
Published Online: November 21, 2023
View Article titled, On the Use of Geometric Deep Learning for the Iterative Classification and Down-Selection of Analog Electric Circuits
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Topics: Circuits, Design, Gas diffusion layers, Frequency response, Optimization, Machine learning
Journal Articles

Attribute-Sentiment-Guided Summarization of User Opinions From Online Reviews

Yi Han, Gaurav Nanda, Mohsen Moghaddam
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. April 2023, 145(4): 041402.
Paper No: MD-22-1296
https://doi.org/10.1115/1.4055736
Published Online: December 9, 2022
View Article titled, Attribute-Sentiment-Guided Summarization of User Opinions From Online Reviews
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Topics: Durability, E-commerce, Entropy, Natural language processing, Product design, Product development, Stability, User-centered design, Design, Absorption
Journal Articles

ActivationNet : Representation Learning to Predict Contact Quality of Interacting 3D Surfaces in Engineering Designs

Rishikesh Ranade, Jay Pathak
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. July 2022, 144(7): 071705.
Paper No: MD-21-1136
https://doi.org/10.1115/1.4053811
Published Online: March 18, 2022
View Article titled, ActivationNet : Representation Learning to Predict Contact Quality of Interacting 3D Surfaces in Engineering Designs
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Topics: Algorithms, Artificial neural networks, Design, Engineering simulation, Geometry, Machine learning, Testing, Physics, Computer-aided design, Rotation
Journal Articles

GANTL: Toward Practical and Real-Time Topology Optimization With Conditional Generative Adversarial Networks and Transfer Learning

Mohammad Mahdi Behzadi, Horea T. Ilieş
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2022, 144(2): 021711.
Paper No: MD-21-1262
https://doi.org/10.1115/1.4052757
Published Online: December 6, 2021
View Article titled, GANTL: Toward Practical and Real-Time Topology Optimization With Conditional Generative Adversarial Networks and Transfer Learning
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Topics: Boundary-value problems, Design, Optimization, Resolution (Optics), Topology, Machine learning
Journal Articles

Data-Efficient Machine Learning on Three-Dimensional Engineering Data

Vencia Herzog, Stefan Suwelack
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2022, 144(2): 021709.
Paper No: MD-21-1192
https://doi.org/10.1115/1.4052753
Published Online: November 9, 2021
View Article titled, Data-Efficient Machine Learning on Three-Dimensional Engineering Data
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Topics: Design, Machine learning, Shapes, Knowledge transfer, Artificial intelligence, Product design
Journal Articles

Inverse Aerodynamic Design of Gas Turbine Blades Using Probabilistic Machine Learning

Sayan Ghosh, Govinda Anantha Padmanabha, Cheng Peng, Valeria Andreoli, Steven Atkinson, Piyush Pandita, Thomas Vandeputte, Nicholas Zabaras, Liping Wang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2022, 144(2): 021706.
Paper No: MD-21-1275
https://doi.org/10.1115/1.4052301
Published Online: September 21, 2021
View Article titled, Inverse Aerodynamic Design of Gas Turbine Blades Using Probabilistic Machine Learning
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Topics: Design, Modeling, Machine learning, Blades, Computational fluid dynamics
Journal Articles

Scalable Gaussian Processes for Data-Driven Design Using Big Data With Categorical Factors

Liwei Wang, Suraj Yerramilli, Akshay Iyer, Daniel Apley, Ping Zhu, Wei Chen
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2022, 144(2): 021703.
Paper No: MD-21-1235
https://doi.org/10.1115/1.4052221
Published Online: September 15, 2021
View Article titled, Scalable Gaussian Processes for Data-Driven Design Using Big Data With Categorical Factors
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Topics: Data-driven design, Design, Machine learning, Metamaterials, Modeling, Optimization
Journal Articles

Conducting Non-adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size

Nandan Sudarsanam, Ramya Chandran, Daniel D. Frey
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2020, 142(3): 031108.
Paper No: MD-19-1410
https://doi.org/10.1115/1.4045603
Published Online: December 23, 2019
View Article titled, Conducting Non-adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size
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Topics: Algorithms, Design, Design theory, Experimental design, Machine learning, Modeling, Noise (Sound), Optimization, Probability, Resource allocation
Journal Articles

Special Issue: Machine Learning for Engineering Design

Jitesh H. Panchal, Mark Fuge, Ying Liu, Samy Missoum, Conrad Tucker
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Guest Editorial
J. Mech. Des. November 2019, 141(11): 110301.
Paper No: MD-19-1579
https://doi.org/10.1115/1.4044690
Published Online: October 18, 2019
View Article titled, Special Issue: Machine Learning for Engineering Design
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Topics: Design, Engineering design, Machine learning, Optimization
Journal Articles

A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems

Feng Zhou, Jackie Ayoub, Qianli Xu, X. Jessie Yang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. January 2020, 142(1): 011101.
Paper No: MD-19-1275
https://doi.org/10.1115/1.4044435
Published Online: October 3, 2019
View Article titled, A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems
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Topics: Algorithms, Machine learning, Modeling, Design, Noise (Sound), Preferences
Journal Articles

A Comparative Evaluation of Supervised Machine Learning Classification Techniques for Engineering Design Applications

Conner Sharpe, Tyler Wiest, Pingfeng Wang, Carolyn Conner Seepersad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. December 2019, 141(12): 121404.
Paper No: MD-19-1180
https://doi.org/10.1115/1.4044524
Published Online: October 3, 2019
View Article titled, A Comparative Evaluation of Supervised Machine Learning Classification Techniques for Engineering Design Applications
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Topics: Algorithms, Design, Engineering design, Machine learning, Optimization, Support vector machines, Artificial neural networks
Includes: Supplementary data
Journal Articles

Machine Learning to Aid Tuning of Numerical Parameters in Topology Optimization

Matthew E. Lynch, Soumalya Sarkar, Kurt Maute
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Technical Briefs
J. Mech. Des. November 2019, 141(11): 114502.
Paper No: MD-19-1149
https://doi.org/10.1115/1.4044228
Published Online: September 16, 2019
View Article titled, Machine Learning to Aid Tuning of Numerical Parameters in Topology Optimization
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Topics: Design, Machine learning, Optimization, Topology, Algorithms
Journal Articles

Automated Manufacturing Process Selection During Conceptual Design

Michael J. Hoefer, Matthew C. Frank
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research-Article
J. Mech. Des. March 2018, 140(3): 031701.
Paper No: MD-17-1283
https://doi.org/10.1115/1.4038686
Published Online: January 10, 2018
View Article titled, Automated Manufacturing Process Selection During Conceptual Design
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Topics: Casting, Conceptual design, Design, Geometry, Machining, Manufacturing, Machine learning, Computer-aided design, Algorithms, Machine tools
Journal Articles

A Bayesian Sampling Method for Product Feature Extraction From Large-Scale Textual Data

Sunghoon Lim, Conrad S. Tucker
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research-Article
J. Mech. Des. June 2016, 138(6): 061403.
Paper No: MD-15-1456
https://doi.org/10.1115/1.4033238
Published Online: April 20, 2016
View Article titled, A Bayesian Sampling Method for Product Feature Extraction From Large-Scale Textual Data
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Topics: Algorithms, Errors, Feature extraction, Information retrieval, Probability, Sampling methods, Product design, Machinery, Machine learning, Mining
Journal Articles

Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels

Heidi Q. Chen, Tomonori Honda, Maria C. Yang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research-Article
J. Mech. Des. June 2013, 135(6): 061007.
Paper No: MD-12-1419
https://doi.org/10.1115/1.4024232
Published Online: May 9, 2013
View Article titled, Approaches for Identifying Consumer Preferences for the Design of Technology Products: A Case Study of Residential Solar Panels
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Topics: Preferences, Solar energy, Design, Machine learning, Artificial neural networks
Journal Articles

Using Support Vector Machines to Formalize the Valid Input Domain of Predictive Models in Systems Design Problems

Richard J. Malak, Jr., Christiaan J. J. Paredis
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2010, 132(10): 101001.
https://doi.org/10.1115/1.4002151
Published Online: September 30, 2010
View Article titled, Using Support Vector Machines to Formalize the Valid Input Domain of Predictive Models in Systems Design Problems
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Topics: Algorithms, Design, Engines, Machine learning, Modeling, Optimization, Support vector machines, Fittings