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Journal Articles

Designing Connectivity-Guaranteed Porous Metamaterial Units Using Generative Graph Neural Networks

Zihan Wang, Austin Bray, Kiarash Naghavi Khanghah, Hongyi Xu

Publisher: ASME

J. Mech. Des. February 2025, 147(2): 021706.

Paper No: MD-24-1409

https://doi.org/10.1115/1.4066128

Published Online: September 26, 2024

... U.S. Department of Education 10.13039/100000138 Graduate Assistance in Areas of National Need (GAANN) program P200A210089 porous metamaterial graph neural network variational graph autoencoder design optimization generative design connectivity data-driven design design of engineered...

View Articletitled, Designing Connectivity-Guaranteed Porous Metamaterial Units Using Generative Graph Neural Networks

Topics: Design, Metamaterials, Voxel, Thermal conductivity, Graph neural networks

Journal Articles

Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications

Jonathan Tammer Eweis-Labolle, Chuanning Zhao, Yoonjin Won, Ramin Bostanabad

Publisher: ASME

J. Mech. Des. October 2024, 146(10): 101705.

Paper No: MD-23-1728

https://doi.org/10.1115/1.4064813

Published Online: March 18, 2024

... . 17 10 2023 12 02 2024 13 02 2024 18 03 2024 Graphical Abstract Figure Gaussian processes multi-fidelity modeling microstructure reconstruction inverse problems thermal management data-driven design design automation design of engineered materials system...

View Articletitled, Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications

Topics: Design, Modeling

Journal Articles

Safeguarding Multi-Fidelity Bayesian Optimization Against Large Model Form Errors and Heterogeneous Noise

Zahra Zanjani Foumani, Amin Yousefpour, Mehdi Shishehbor, Ramin Bostanabad

Publisher: ASME

J. Mech. Des. June 2024, 146(6): 061703.

Paper No: MD-23-1380

https://doi.org/10.1115/1.4064160

Published Online: December 18, 2023

... . 10.1038/s41524-018-0106-7 Bayesian optimization multi-fidelity modeling emulation Gaussian process interval score data-driven design design of engineered materials system design optimization design representation Directorate for Engineering 10.13039/100000084 2238038...

View Articletitled, Safeguarding Multi-Fidelity Bayesian Optimization Against Large Model Form Errors and Heterogeneous Noise

Topics: Design, Noise (Sound), Optimization, Uncertainty quantification, Modeling, Manifolds, Errors, Uncertainty

Includes: Supplementary data

Journal Articles

Mixed-Variable Global Sensitivity Analysis for Knowledge Discovery and Efficient Combinatorial Materials Design

Yigitcan Comlek, Liwei Wang, Wei Chen

Publisher: ASME

J. Mech. Des. May 2024, 146(5): 051706.

Paper No: MD-23-1471

https://doi.org/10.1115/1.4064133

Published Online: December 12, 2023

...-variable design spaces Bayesian optimization design of engineered materials system metamodeling 10 07 2023 14 11 2023 16 11 2023 12 12 2023 Contributed by the Design Automation Committee of ASME for publication in the J ournal of M echanical D esign . 1...

View Articletitled, Mixed-Variable Global Sensitivity Analysis for Knowledge Discovery and Efficient Combinatorial Materials Design

Topics: Design, Sensitivity analysis, Metal-organic frameworks, Optimization

Journal Articles

Identifying and Leveraging Promising Design Heuristics for Multi-Objective Combinatorial Design Optimization

Roshan Suresh Kumar, Srikar Srivatsa, Emilie Baker, Meredith Silberstein, Daniel Selva

Publisher: ASME

J. Mech. Des. December 2023, 145(12): 121702.

Paper No: MD-23-1014

https://doi.org/10.1115/1.4063238

Published Online: September 11, 2023

... 11 08 2023 17 08 2023 11 09 2023 design methodology design of engineered materials system design optimization multi-objective optimization National Science Foundation 10.13039/100000001 CMMI 1825444 CMMI 1825521 This paper explores approaches to leverage...

View Articletitled, Identifying and Leveraging Promising Design Heuristics for Multi-Objective Combinatorial Design Optimization

Topics: Design, Maintenance, Optimization, Stiffness

Includes: Supplementary data

Journal Articles

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Akshay Iyer, Suraj Yerramilli, James M. Rondinelli, Daniel W. Apley, Wei Chen

Publisher: ASME

J. Mech. Des. March 2023, 145(3): 031701.

Paper No: MD-22-1317

https://doi.org/10.1115/1.4055848

Published Online: October 31, 2022

... Projects Agency - Energy 10.13039/100006133 DE-AR0001209 high dimensional qualitative variables latent variable Gaussian process descriptors Bayesian optimization design of engineered materials system 22 05 2022 26 09 2022 27 09 2022 31 10 2022 Contributed...

View Articletitled, Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Topics: Design, Modeling, Optimization

Journal Articles

Bio-Inspired Avenues for Advancing Brain Injury Prevention

Jessica Ezemba, Astrid Layton

Publisher: ASME

J. Mech. Des. December 2022, 144(12): 121403.

Paper No: MD-22-1335

https://doi.org/10.1115/1.4055737

Published Online: October 6, 2022

... design for humans traumatic brain injury bio-inspired design design of engineered materials system creativity and concept generation 06 06 2022 12 09 2022 16 09 2022 06 10 2022 Contributed by the Design Theory and Methodology Committee of ASME for publication in the J...

View Articletitled, Bio-Inspired Avenues for Advancing Brain Injury Prevention

Topics: Biomimetics, Composite materials, Design, Energy dissipation, Failure, Fracture (Materials), Sandwich structures, Shells, Traumatic brain injury, Innovation

Journal Articles

Design of Phononic Bandgap Metamaterials Based on Gaussian Mixture Beta Variational Autoencoder and Iterative Model Updating

Zihan Wang, Weikang Xian, M. Ridha Baccouche, Horst Lanzerath, Ying Li, Hongyi Xu

Publisher: ASME

J. Mech. Des. April 2022, 144(4): 041705.

Paper No: MD-21-1373

https://doi.org/10.1115/1.4053814

Published Online: February 22, 2022

... metamaterial phononic bandgap Gaussian mixture variational autoencoder Gaussian process iterative model updating multiobjective optimization artificial intelligence design of engineered materials system machine learning multiobjective optimization structural optimization 3M 10.13039...

View Articletitled, Design of Phononic Bandgap Metamaterials Based on Gaussian Mixture Beta Variational Autoencoder and Iterative Model Updating

Topics: Design, Energy gap, Metamaterials, Optimization

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

Publisher: ASME

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

... intelligence data-driven design design of engineered materials system National Science Foundation 10.13039/100000001 OAC 1835782 In this case study, we demonstrate the usefulness of the proposed method in data-driven multiscale designs by applying it to a large database of unit-cell...

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

Topics: Data-driven design, Design, Machine learning, Metamaterials, Modeling, Optimization

Journal Articles

Bone Adaptation-Driven Design of Periodic Scaffolds

David O. Cohen, Sohaila M. G. Aboutaleb, Amy Wagoner Johnson, Julian A. Norato

Publisher: ASME

J. Mech. Des. December 2021, 143(12): 121701.

Paper No: MD-20-1812

https://doi.org/10.1115/1.4050928

Published Online: June 9, 2021

... ) I in (6) , where I is the identity two-tensor. design of engineered materials system simulation-based design structural optimization Bone scaffolds are porous materials designed to offer an alternative to natural bone for use in bone grafting [ 1 ]. Bone grafting is a surgical...

View Articletitled, Bone Adaptation-Driven Design of Periodic Scaffolds

Topics: Bone, Design, Density, Simulation

Journal Articles

Lattice Structure Optimization With Orientation-Dependent Material Properties

Conner Sharpe, Carolyn C. Seepersad

Publisher: ASME

J. Mech. Des. September 2021, 143(9): 091708.

Paper No: MD-20-1473

https://doi.org/10.1115/1.4050299

Published Online: March 24, 2021

... esign . 25 06 2020 09 02 2021 17 02 2021 24 03 2021 design for manufacturing design of engineered materials system lattice structures design for additive manufacturing Additive manufacturing (AM) processes have a number of advantages over traditional...

View Articletitled, Lattice Structure Optimization With Orientation-Dependent Material Properties

Topics: Design, Optimization, Rotation, Struts (Engineering), Materials properties, Stiffness, Geometry

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Designing Connectivity-Guaranteed Porous Metamaterial Units Using Generative Graph Neural Networks

Multi-Fidelity Design of Porous Microstructures for Thermofluidic Applications

Safeguarding Multi-Fidelity Bayesian Optimization Against Large Model Form Errors and Heterogeneous Noise

Mixed-Variable Global Sensitivity Analysis for Knowledge Discovery and Efficient Combinatorial Materials Design

Identifying and Leveraging Promising Design Heuristics for Multi-Objective Combinatorial Design Optimization

Descriptor Aided Bayesian Optimization for Many-Level Qualitative Variables With Materials Design Applications

Bio-Inspired Avenues for Advancing Brain Injury Prevention

Design of Phononic Bandgap Metamaterials Based on Gaussian Mixture Beta Variational Autoencoder and Iterative Model Updating

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

Bone Adaptation-Driven Design of Periodic Scaffolds

Lattice Structure Optimization With Orientation-Dependent Material Properties

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