1-9 of 9
Airfoils
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Journal Articles

NURBS-OT: An Advanced Model for Generative Curve Modeling

Accepted Manuscript
Shaoliang Yang, Jun Wang, Kang Wang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des.
Paper No: MD-24-1312
https://doi.org/10.1115/1.4066549
Published Online: September 13, 2024
View Article titled, NURBS-OT: An Advanced Model for Generative Curve Modeling
Open the PDF for NURBS-OT: An Advanced Model for Generative Curve Modeling in another window
Topics: Modeling, B-splines, Generative adversarial networks, Airfoils, Computer-aided design, Computers, Data-driven design, Deep learning, Design automation, Generative design
Journal Articles

Characterizing Designs Via Isometric Embeddings: Applications to Airfoil Inverse Design

Qiuyi Chen, Mark Fuge
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051702.
Paper No: MD-23-1475
https://doi.org/10.1115/1.4063363
Published Online: November 21, 2023
View Article titled, Characterizing Designs Via Isometric Embeddings: Applications to Airfoil Inverse Design
Open the PDF for Characterizing Designs Via Isometric Embeddings: Applications to Airfoil Inverse Design in another window
Topics: Airfoils, Design, Shapes, Dimensions
Journal Articles

Reinforcement Learning-Based Sequential Batch-Sampling for Bayesian Optimal Experimental Design

Yonatan Ashenafi, Piyush Pandita, Sayan Ghosh
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2022, 144(9): 091705.
Paper No: MD-21-1780
https://doi.org/10.1115/1.4054631
Published Online: June 13, 2022
View Article titled, Reinforcement Learning-Based Sequential Batch-Sampling for Bayesian Optimal Experimental Design
Open the PDF for Reinforcement Learning-Based Sequential Batch-Sampling for Bayesian Optimal Experimental Design in another window
Topics: Algorithms, Design, Experimental design, Optimization, Airfoils, Reinforcement learning
Journal Articles

Inverse Design of Two-Dimensional Airfoils Using Conditional Generative Models and Surrogate Log-Likelihoods

Qiuyi Chen, Jun Wang, Phillip Pope, Wei (Wayne) Chen, Mark Fuge
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2022, 144(2): 021712.
Paper No: MD-21-1228
https://doi.org/10.1115/1.4052846
Published Online: December 6, 2021
View Article titled, Inverse Design of Two-Dimensional Airfoils Using Conditional Generative Models and Surrogate Log-Likelihoods
Open the PDF for Inverse Design of Two-Dimensional Airfoils Using Conditional Generative Models and Surrogate Log-Likelihoods in another window
Topics: Airfoils, Design, Optimization
Includes: Supplementary data
Journal Articles

Generalizability of Convolutional Encoder–Decoder Networks for Aerodynamic Flow-Field Prediction Across Geometric and Physical-Fluidic Variations

Kaustubh Tangsali, Vinayak R. Krishnamurthy, Zohaib Hasnain
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2021, 143(5): 051704.
Paper No: MD-20-1208
https://doi.org/10.1115/1.4048221
Published Online: November 13, 2020
View Article titled, Generalizability of Convolutional Encoder–Decoder Networks for Aerodynamic Flow-Field Prediction Across Geometric and Physical-Fluidic Variations
Open the PDF for Generalizability of Convolutional Encoder–Decoder Networks for Aerodynamic Flow-Field Prediction Across Geometric and Physical-Fluidic Variations in another window
Topics: Airfoils, Flow (Dynamics), Simulation, Computational fluid dynamics, Physics, Reynolds number, Geometry, Design, Mach number
Includes: Supplementary data
Journal Articles

PaDGAN: Learning to Generate High-Quality Novel Designs

Wei Chen, Faez Ahmed
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. March 2021, 143(3): 031703.
Paper No: MD-20-1313
https://doi.org/10.1115/1.4048626
Published Online: November 10, 2020
View Article titled, PaDGAN: Learning to Generate High-Quality Novel Designs
Open the PDF for PaDGAN: Learning to Generate High-Quality Novel Designs in another window
Topics: Design, Airfoils
Journal Articles

A Relative Adequacy Framework for Multi-Model Management in Design Optimization

Ahmed H. Bayoumy, Michael Kokkolaras
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2020, 142(2): 021401.
Paper No: MD-18-1676
https://doi.org/10.1115/1.4044109
Published Online: October 16, 2019
View Article titled, A Relative Adequacy Framework for Multi-Model Management in Design Optimization
Open the PDF for A Relative Adequacy Framework for Multi-Model Management in Design Optimization in another window
Topics: Airfoils, Design, Optimization, Algorithms, Shapes
Journal Articles

Experimental and Numerical Investigations on Nonlinear Aeroelasticity of Forward-Swept, Compliant Wings

Ghalib Y. Thwapiah, L. Flavio Campanile
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. January 2012, 134(1): 011009.
https://doi.org/10.1115/1.4005441
Published Online: January 5, 2012
View Article titled, Experimental and Numerical Investigations on Nonlinear Aeroelasticity of Forward-Swept, Compliant Wings
Open the PDF for Experimental and Numerical Investigations on Nonlinear Aeroelasticity of Forward-Swept, Compliant Wings in another window
Topics: Airfoils, Deformation, Wind tunnels, Wings, Pressure, Fluid structure interaction, Aeroelasticity, Modeling
Journal Articles

A Learning Shell for Iterative Design (L’SID): Concepts and Applications

V. R. Jamalabad, N. A. Langrana
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. June 1998, 120(2): 203–209.
https://doi.org/10.1115/1.2826960
Published Online: June 1, 1998
View Article titled, A Learning Shell for Iterative Design (L’SID): Concepts and Applications
Open the PDF for A Learning Shell for Iterative Design (L’SID): Concepts and Applications in another window
Topics: Design, Shells, Airfoils, Computer software, Extruding, Noise (Sound)