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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

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

MID-ESM: An Adaptive Median-Based Ensemble of Surrogate Models

Jianji Li, Shuai Zhang, Pengwei Liang, Xiaonan Lai, Xueguan Song

Publisher: ASME

J. Mech. Des. November 2023, 145(11): 114501.

Paper No: MD-22-1776

https://doi.org/10.1115/1.4062977

Published Online: August 16, 2023

View Articletitled, MID-ESM: An Adaptive Median-Based Ensemble of Surrogate Models

Topics: Noise (Sound), Robustness, Weight (Mass), Errors, Dimensions

Journal Articles

Data Fusion With Latent Map Gaussian Processes

Jonathan Tammer Eweis-Labolle, Nicholas Oune, Ramin Bostanabad

Publisher: ASME

J. Mech. Des. September 2022, 144(9): 091703.

Paper No: MD-21-1733

https://doi.org/10.1115/1.4054520

Published Online: June 13, 2022

View Articletitled, Data Fusion With Latent Map Gaussian Processes

Topics: Calibration, Data fusion, Modeling, Noise (Sound), Errors

Journal Articles

An Integrated Surrogate Modeling Method for Fusing Noisy and Noise-Free Data

Kunpeng Li, Shuo Wang, Yin Liu, Xueguan Song

Publisher: ASME

J. Mech. Des. June 2022, 144(6): 061701.

Paper No: MD-21-1378

https://doi.org/10.1115/1.4053044

Published Online: January 17, 2022

View Articletitled, An Integrated Surrogate Modeling Method for Fusing Noisy and Noise-Free Data

Topics: Noise (Sound)

Journal Articles

Stochastic Crashworthiness Optimization Accounting for Simulation Noise

Seyed Saeed Ahmadisoleymani, Samy Missoum

Publisher: ASME

J. Mech. Des. May 2022, 144(5): 051701.

Paper No: MD-21-1123

https://doi.org/10.1115/1.4052903

Published Online: December 6, 2021

View Articletitled, Stochastic Crashworthiness Optimization Accounting for Simulation Noise

Topics: Crashworthiness, Design, Noise (Sound), Optimization, Simulation, Uncertainty, Optimization algorithms

Journal Articles

Phrase Embedding and Clustering for Sub-Feature Extraction From Online Data

Seyoung Park, Harrison M. Kim

Publisher: ASME

J. Mech. Des. May 2022, 144(5): 054501.

Paper No: MD-21-1257

https://doi.org/10.1115/1.4052904

Published Online: December 6, 2021

View Articletitled, Phrase Embedding and Clustering for Sub-Feature Extraction From Online Data

Topics: Batteries, Design, Feature extraction, Fingerprints, Noise (Sound), Preferences, Product design, Security, Storage, Natural language processing

Journal Articles

Evolutionary Gaussian Processes

Robert Planas, Nick Oune, Ramin Bostanabad

Publisher: ASME

J. Mech. Des. November 2021, 143(11): 111703.

Paper No: MD-20-1834

https://doi.org/10.1115/1.4050746

Published Online: May 28, 2021

View Articletitled, Evolutionary Gaussian Processes

Topics: Computer programming, Errors, Interpolation, Maximum likelihood estimation, Modeling, Noise (Sound), Numerical stability, Algorithms, Databases, Optimization

Journal Articles

Automated Keyword Filtering in Latent Dirichlet Allocation for Identifying Product Attributes From Online Reviews

Junegak Joung, Harrison M. Kim

Publisher: ASME

J. Mech. Des. August 2021, 143(8): 084501.

Paper No: MD-20-1445

https://doi.org/10.1115/1.4048960

Published Online: February 9, 2021

View Articletitled, Automated Keyword Filtering in Latent Dirichlet Allocation for Identifying Product Attributes From Online Reviews

Topics: Filtration, Noise (Sound)

Journal Articles

Scalable Adaptive Batch Sampling in Simulation-Based Design With Heteroscedastic Noise

Anton van Beek, Umar Farooq Ghumman, Joydeep Munshi, Siyu Tao, TeYu Chien, Ganesh Balasubramanian, Matthew Plumlee, Daniel Apley, Wei Chen

Publisher: ASME

J. Mech. Des. March 2021, 143(3): 031709.

Paper No: MD-20-1421

https://doi.org/10.1115/1.4049134

Published Online: December 15, 2020

View Articletitled, Scalable Adaptive Batch Sampling in Simulation-Based Design With Heteroscedastic Noise

Topics: Design, Noise (Sound), Optimization, Simulation, Interpolation, Uncertainty, Simulation models, Modeling

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

Publisher: ASME

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

Topics: Algorithms, Design, Design theory, Experimental design, Machine learning, Modeling, Noise (Sound), Optimization, Probability, Resource allocation

Journal Articles

A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems

Feng Zhou, Jackie Ayoub, Qianli Xu, X. Jessie Yang

Publisher: ASME

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

Topics: Algorithms, Machine learning, Modeling, Design, Noise (Sound), Preferences

Journal Articles

Globally Approximate Gaussian Processes for Big Data With Application to Data-Driven Metamaterials Design

Ramin Bostanabad, Yu-Chin Chan, Liwei Wang, Ping Zhu, Wei Chen

Publisher: ASME

J. Mech. Des. November 2019, 141(11): 111402.

Paper No: MD-19-1164

https://doi.org/10.1115/1.4044257

Published Online: September 16, 2019

View Articletitled, Globally Approximate Gaussian Processes for Big Data With Application to Data-Driven Metamaterials Design

Topics: Design, Metamaterials, Modeling, Optimization, Dimensions, Databases, Shapes, Noise (Sound)

Journal Articles

Evaluating Clustering Algorithms for Identifying Design Subproblems

Jeffrey W. Herrmann, Michael Morency, Azrah Anparasan, Erica L. Gralla

Publisher: ASME

J. Mech. Des. August 2018, 140(8): 081401.

Paper No: MD-17-1814

https://doi.org/10.1115/1.4040176

Published Online: May 23, 2018

View Articletitled, Evaluating Clustering Algorithms for Identifying Design Subproblems

Topics: Algorithms, Design, Teams, Noise (Sound)

Journal Articles

Characterizing the Effects of Multiple Analogs and Extraneous Information for Novice Designers in Design-by-Analogy

Hyeon Ik Song, Ricardo Lopez, Katherine Fu, Julie Linsey

Publisher: ASME

J. Mech. Des. March 2018, 140(3): 031101.

Paper No: MD-17-1340

https://doi.org/10.1115/1.4038565

Published Online: December 21, 2017

View Articletitled, Characterizing the Effects of Multiple Analogs and Extraneous Information for Novice Designers in Design-by-Analogy

Topics: Design, Noise (Sound)

Journal Articles

Extending Expected Improvement for High-Dimensional Stochastic Optimization of Expensive Black-Box Functions

Piyush Pandita, Ilias Bilionis, Jitesh Panchal

Publisher: ASME

J. Mech. Des. November 2016, 138(11): 111412.

Paper No: MD-16-1215

https://doi.org/10.1115/1.4034104

Published Online: September 12, 2016

View Articletitled, Extending Expected Improvement for High-Dimensional Stochastic Optimization of Expensive Black-Box Functions

Topics: Design, Optimization, Uncertainty, Simulation, Noise (Sound), Approximation

Journal Articles

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

Sunghoon Lim, Conrad S. Tucker

Publisher: ASME

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

Topics: Algorithms, Errors, Feature extraction, Information retrieval, Probability, Sampling methods, Product design, Machinery, Machine learning, Mining

Journal Articles

A Mixed Interval Arithmetic/Affine Arithmetic Approach for Robust Design Optimization With Interval Uncertainty

Shaobo Wang, Xiangyun Qing

Publisher: ASME

J. Mech. Des. April 2016, 138(4): 041403.

Paper No: MD-15-1491

https://doi.org/10.1115/1.4032630

Published Online: February 19, 2016

View Articletitled, A Mixed Interval Arithmetic/Affine Arithmetic Approach for Robust Design Optimization With Interval Uncertainty

Topics: Approximation, Design, Optimization, Robustness, Uncertainty, Noise (Sound)

Journal Articles

Multi-Objective Wind Farm Layout Optimization Considering Energy Generation and Noise Propagation With NSGA-II

Wing Yin Kwong, Peter Yun Zhang, David Romero, Joaquin Moran, Michael Morgenroth, Cristina Amon

Publisher: ASME

J. Mech. Des. September 2014, 136(9): 091010.

Paper No: MD-13-1029

https://doi.org/10.1115/1.4027847

Published Online: July 3, 2014

View Articletitled, Multi-Objective Wind Farm Layout Optimization Considering Energy Generation and Noise Propagation With NSGA-II

Topics: Modeling, Noise (Sound), Optimization, Turbines, Wakes, Wind farms, Energy generation, Design, Wind, Wind velocity

Journal Articles

Objective-Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Paul D. Arendt, Daniel W. Apley, Wei Chen

Publisher: ASME

J. Mech. Des. May 2013, 135(5): 051005.

Paper No: MD-12-1307

https://doi.org/10.1115/1.4023922

Published Online: April 23, 2013

View Articletitled, Objective-Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Topics: Design, Uncertainty, Interpolation, Algorithms, Noise (Sound), Simulation

Journal Articles

Application of Multiparameter Optimization for Robust Product Design

Douglas K. Herrmann

Publisher: ASME

J. Mech. Des. February 2009, 131(2): 024501.

https://doi.org/10.1115/1.3042162

Published Online: January 7, 2009

View Articletitled, Application of Multiparameter Optimization for Robust Product Design

Topics: Design, Noise (Sound), Optimization, Product design, Testing

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

MID-ESM: An Adaptive Median-Based Ensemble of Surrogate Models

Data Fusion With Latent Map Gaussian Processes

An Integrated Surrogate Modeling Method for Fusing Noisy and Noise-Free Data

Stochastic Crashworthiness Optimization Accounting for Simulation Noise

Phrase Embedding and Clustering for Sub-Feature Extraction From Online Data

Evolutionary Gaussian Processes

Automated Keyword Filtering in Latent Dirichlet Allocation for Identifying Product Attributes From Online Reviews

Scalable Adaptive Batch Sampling in Simulation-Based Design With Heteroscedastic Noise

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

A Machine Learning Approach to Customer Needs Analysis for Product Ecosystems

Globally Approximate Gaussian Processes for Big Data With Application to Data-Driven Metamaterials Design

Evaluating Clustering Algorithms for Identifying Design Subproblems

Characterizing the Effects of Multiple Analogs and Extraneous Information for Novice Designers in Design-by-Analogy

Extending Expected Improvement for High-Dimensional Stochastic Optimization of Expensive Black-Box Functions

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

A Mixed Interval Arithmetic/Affine Arithmetic Approach for Robust Design Optimization With Interval Uncertainty

Multi-Objective Wind Farm Layout Optimization Considering Energy Generation and Noise Propagation With NSGA-II

Objective-Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Application of Multiparameter Optimization for Robust Product Design

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