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Keywords: machine learning
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Journal Articles
Journal Articles
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2024, 146(10): 101708.
Paper No: MD-23-1722
Published Online: April 9, 2024
.... Army Research Laboratory 10.13039/100006754 W911NF-22-2-0106 data-driven design design of experiments design optimization design process machine learning simulation-based design Graphical Abstract Figure 16 10 2023 08 03 2024 09 03 2024 09 04 2024...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051713.
Paper No: MD-23-1482
Published Online: March 28, 2024
... nonlinearity of the P -norm measure. Hence, the data-driven MFTD approach is expected to yield a unique set of Pareto solutions through gradient-free searching. The concept of latent crossover enables the integration of evolutionary algorithms and machine learning methods. In our future work, we plan...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2024, 146(10): 101704.
Paper No: MD-23-1686
Published Online: March 18, 2024
... 18 03 2024 Graphical Abstract Figure Bayesian optimization optimization-under-uncertainty efficient robust global optimization hypervolume expected improvement crash constraints Bayesian classification design optimization machine learning metamodeling multi-objective...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051711.
Paper No: MD-23-1466
Published Online: March 18, 2024
... self-organizing system compromise decision-support problem box-pushing problem. artificial intelligence design methodology design optimization machine learning metamodeling multi-objective optimization systems design Group behavior is widespread with phenomena like ant colonies, fish...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. August 2024, 146(8): 081704.
Paper No: MD-23-1618
Published Online: March 5, 2024
... of reliability analysis and design optimization. The proposed multi-fidelity multi-task machine learning model utilizes a Bayesian framework, which significantly improves the performance of the predictive model and provides uncertainty quantification of the prediction. Additionally, the model provides a highly...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2024, 146(10): 101702.
Paper No: MD-23-1583
Published Online: March 5, 2024
... Figure multi-fidelity surrogate neural network machine learning mapping model different input spaces artificial intelligence computer-aided engineering metamodeling Output data from engineering systems, whether observed or predicted, can be categorized into multiple fidelity...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. October 2024, 146(10): 101703.
Paper No: MD-23-1269
Published Online: March 5, 2024
... echanical D esign . 06 05 2023 08 02 2024 13 02 2024 05 03 2024 Graphical Abstract Figure artificial intelligence data-driven design machine learning References [1] Lea , C. , Vidal , R. , Reiter , A. , and Hager , G. D. , 2016...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. September 2024, 146(9): 091705.
Paper No: MD-23-1678
Published Online: March 5, 2024
... data to delineate feasible domains, accelerate optimization, or evaluate designs. However, the implementation of these methods usually demands machine learning expertise and multiple trials to choose the right method and hyperparameters. This makes them less accessible for numerous engineering...
Journal Articles
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. July 2024, 146(7): 071704.
Paper No: MD-23-1483
Published Online: January 29, 2024
... 2023 29 01 2024 design automation design optimization machine learning sensitivity analysis for design topology optimization Division of Graduate Education 10.13039/100000082 1842164 Office of Naval Research 10.13039/100000006 NAVAIR - Naval Air Systems Command...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051709.
Paper No: MD-23-1484
Published Online: January 29, 2024
...Xiaoping Du Machine learning is gaining prominence in mechanical design, offering cost-effective surrogate models to replace computationally expensive models. Nevertheless, concerns persist regarding the accuracy of these models, especially when applied to safety-critical products. To address...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. June 2024, 146(6): 061702.
Paper No: MD-23-1335
Published Online: December 12, 2023
... 12 12 2023 computational geometry computer-aided design data-driven design machine learning topology optimization There has been a recent increase in machine learning-driven topology optimization approaches, particularly using neural networks for performing topology optimization...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051706.
Paper No: MD-23-1471
Published Online: December 12, 2023
... , A. , Tarantola , S. , and Campolongo , F. , 2000 , “ Sensitivity Analysis as an Ingredient of Modeling ,” Stat. Sci. , 15 ( 4 ), pp. 377 – 395 . [18] Rasmussen , C. E. , and Williams , C. K. I. , 2005 , Gaussian Processes for Machine Learning , The MIT Press , Cambridge, MA . [19...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051702.
Paper No: MD-23-1475
Published Online: November 21, 2023
... machine learning has opened up new avenues for accelerating both human- and computer-generate designs in several ways [ 1 ]. For instance, in works like Refs. [ 2 – 7 ], researchers developed conditional inverse design models that can generate new designs satisfying the performance requirements, without...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051703.
Paper No: MD-23-1443
Published Online: November 21, 2023
...Anthony Sirico, Jr.; Daniel R. Herber Many complex engineering systems can be represented in a topological form, such as graphs. This paper utilizes a machine learning technique called Geometric Deep Learning (GDL) to aid designers with challenging, graph-centric design problems. The strategy...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2024, 146(5): 051701.
Paper No: MD-23-1349
Published Online: November 21, 2023
... explainable AI feature recognition design automation machine learning signal processing data-driven design design visualization product design artificial intelligence 02 06 2023 30 09 2023 02 10 2023 21 11 2023 Contributed by the Design Automation Committee of ASME...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. April 2024, 146(4): 041703.
Paper No: MD-23-1035
Published Online: November 13, 2023
... of Supervised Machine Learning Classification Techniques for Engineering Design Applications ,” ASME J. Mech. Des. , 141 ( 12 ), p. 121404 . 10.1115/1.4044524 [4] Larson , B. J. , and Mattson , C. A. , 2012 , “ Design Space Exploration for Quantifying a System Model’s Feasible Domain...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2024, 146(2): 020902.
Paper No: MD-23-1435
Published Online: November 13, 2023
... proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges...
Topics: Tires