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Journal Articles

Parametric-ControlNet: Multimodal Control in Foundation Models for Precise Engineering Design Synthesis

Available to Purchase
Accepted Manuscript
Rui Zhou, Yanxia Zhang, Chenyang Yuan, Frank Permenter, Nikos Arechiga, Matt Klenk, Faez Ahmed
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des.
Paper No: MD-24-1872
https://doi.org/10.1115/1.4068661
Published Online: May 13, 2025
View Articletitled, Parametric-ControlNet: Multimodal Control in Foundation Models for Precise Engineering Design Synthesis
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Topics: Artificial intelligence, Computer-aided design, Computer-aided engineering, Conceptual design, Creativity, Data-driven design, Engineering design, Generative design, Machine learning, Product design
Journal Articles

Multi-Objective Optimization and Supervised Machine Learning for Synthesis of Rolling Element Bearing and Lubricant Selection

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Accepted Manuscript
Mohamed Abbas, Sayed Metwalli
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des.
Paper No: MD-24-1887
https://doi.org/10.1115/1.4068662
Published Online: May 13, 2025
View Articletitled, Multi-Objective Optimization and Supervised Machine Learning for Synthesis of Rolling Element Bearing and Lubricant Selection
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Topics: Lubricants, Machine learning, Pareto optimization, Rolling bearings, Design, Artificial intelligence, Machine components, Optimization
Journal Articles

DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction

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Mohamed Elrefaie, Angela Dai, Faez Ahmed
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. April 2025, 147(4): 041712.
Paper No: MD-24-1657
https://doi.org/10.1115/1.4068104
Published Online: March 25, 2025
View Articletitled, DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction
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Topics: Computational fluid dynamics, Design, Drag (Fluid dynamics), Simulation, Pressure, Machine learning, Turbulence, Shapes, Modeling, Deep learning
Journal Articles

A Dataset of 3M Single-DOF Planar 4-, 6-, and 8-Bar Linkage Mechanisms With Open and Closed Coupler Curves for Machine Learning-Driven Path Synthesis

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Anar Nurizada, Rohit Dhaipule, Zhijie Lyu, Anurag Purwar
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. April 2025, 147(4): 041702.
Paper No: MD-24-1483
https://doi.org/10.1115/1.4067014
Published Online: November 18, 2024
View Articletitled, A Dataset of 3M Single-DOF Planar 4-, 6-, and 8-Bar Linkage Mechanisms With Open and Closed Coupler Curves for Machine Learning-Driven Path Synthesis
Open the PDF for A Dataset of 3M Single-DOF Planar 4-, 6-, and 8-Bar Linkage Mechanisms With Open and Closed Coupler Curves for Machine Learning-Driven Path Synthesis in another window
Topics: Linkages, Robustness, Algorithms, Machine learning, Artificial neural networks, Machinery, Kinematics
Journal Articles

Importance-Induced Customer Segmentation Using Explainable Machine Learning

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Seyoung Park, Yilan Jiang, Harrison Kim
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Technical Briefs
J. Mech. Des. April 2025, 147(4): 044501.
Paper No: MD-24-1118
https://doi.org/10.1115/1.4066746
Published Online: October 24, 2024
View Articletitled, Importance-Induced Customer Segmentation Using Explainable Machine Learning
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Topics: Image segmentation, Construction, Machine learning
Journal Articles

NURBS-OT: An Advanced Model for Generative Curve Modeling

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Shaoliang Yang, Jun Wang, Kang Wang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2025, 147(3): 031703.
Paper No: MD-24-1312
https://doi.org/10.1115/1.4066549
Published Online: October 18, 2024
View Articletitled, NURBS-OT: An Advanced Model for Generative Curve Modeling
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Topics: Airfoils, Algorithms, B-splines, Generative adversarial networks, Machine learning, Modeling, Optimization, Shapes, Parametrization, Design
Journal Articles

Deep Learning Conceptual Design of Sit-to-Stand Parallel Motion Six-Bar Mechanisms

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Zhijie Lyu, Anurag Purwar
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. January 2025, 147(1): 013306.
Paper No: MD-24-1019
https://doi.org/10.1115/1.4066036
Published Online: August 21, 2024
View Articletitled, Deep Learning Conceptual Design of Sit-to-Stand Parallel Motion Six-Bar Mechanisms
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Topics: Algorithms, Artificial neural networks, Conceptual design, Databases, Design, Kinematics, Linkages, Pipelines, Machine learning, Deep learning
Journal Articles

Data-Driven Global Sensitivity Analysis of Variable Groups for Understanding Complex Physical Interactions in Engineering Design

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Tuba Dolar, Doksoo Lee, Wei Chen
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2024, 146(9): 091703.
Paper No: MD-23-1749
https://doi.org/10.1115/1.4064633
Published Online: March 5, 2024
View Articletitled, Data-Driven Global Sensitivity Analysis of Variable Groups for Understanding Complex Physical Interactions in Engineering Design
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Topics: Artificial neural networks, Design, Sensitivity analysis, Engineering design, Machine learning
Journal Articles

Untrained and Unmatched: Fast and Accurate Zero-Training Classification for Tabular Engineering Data

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Cyril Picard, Faez Ahmed
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2024, 146(9): 091705.
Paper No: MD-23-1678
https://doi.org/10.1115/1.4064811
Published Online: March 5, 2024
View Articletitled, Untrained and Unmatched: Fast and Accurate Zero-Training Classification for Tabular Engineering Data
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Topics: Design, Engineering design, Machine learning, Trains, Algorithms, Tradeoffs, Solar energy, Optimization, Uncertainty
Journal Articles

Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information

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Yanwen Xu, Hao Wu, Zheng Liu, Pingfeng Wang, Yumeng Li
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. August 2024, 146(8): 081704.
Paper No: MD-23-1618
https://doi.org/10.1115/1.4064492
Published Online: March 5, 2024
View Articletitled, Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information
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Topics: Design, Design under uncertainty, Machine learning, Metamodeling, Optimization, Reliability, Reliability-based optimization, Uncertainty, Complex systems, Uncertainty quantification
Journal Articles

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

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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 Articletitled, 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

Free
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 Articletitled, Attribute-Sentiment-Guided Summarization of User Opinions From Online Reviews
Open the PDF for Attribute-Sentiment-Guided Summarization of User Opinions From Online Reviews in another window
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

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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 Articletitled, 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

Free
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 Articletitled, GANTL: Toward Practical and Real-Time Topology Optimization With Conditional Generative Adversarial Networks and Transfer Learning
Open the PDF for GANTL: Toward Practical and Real-Time Topology Optimization With Conditional Generative Adversarial Networks and Transfer Learning in another window
Topics: Boundary-value problems, Design, Optimization, Resolution (Optics), Topology, Machine learning
Journal Articles

Data-Efficient Machine Learning on Three-Dimensional Engineering Data

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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 Articletitled, 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

Free
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 Articletitled, 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

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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 Articletitled, 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

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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 Articletitled, 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

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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 Articletitled, 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

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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 Articletitled, A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems
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Topics: Algorithms, Machine learning, Modeling, Design, Noise (Sound), Preferences