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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
... 09 04 2024 Graphical Abstract Figure data-driven design design of experiments design optimization design process machine learning simulation-based design Advanced Research Projects Agency - Energy 10.13039/100006133 DE-AR0001427 National Science Foundation...
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
...). The concept of latent crossover enables the integration of evolutionary algorithms and machine learning methods. In our future work, we plan to incorporate various types of evolutionary algorithms other than RCGAs, as well as VAE-based advanced machine learning methods into the proposed framework. In addition...
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
... 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 swarms, bird flights, and so on. The industry has been inspired...
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
... 05 03 2024 Graphical Abstract 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...
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
... Networks (IJCNN) , Padua, Italy , July 18–23 , pp. 1 – 8 . [5] Pascanu , R. , Mikolov , T. , and Bengio , Y. , 2013 , “ On the Difficulty of Training Recurrent Neural Networks ,” Proceedings of the 30th International Conference on Machine Learning , Atlanta, GA , June 17–19 , S...
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
...] Saltelli , 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...
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
... in the Journal of Mechanical Design . 10 07 2023 24 08 2023 31 08 2023 21 11 2023 design optimization design representation design visualization machine learning Advanced Research Projects Agency 10.13039/100009224 DEAR0001216 National Science Foundation...
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
... . [29] Chen , T. , Kornblith , S. , Norouzi , M. , and Hinton , G. , 2020 , “ A Simple Framework for Contrastive Learning of Visual Representations ,” International conference on machine learning , Vienna, Austria , July 12–18 , pp. 1597 – 1607 . [30] Chen , T...
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 Transfer Learning used in machine learning, the ability to kick-start the Bayesian optimization process by reusing (and possibly combining) feasibility surrogate models [ 45 ]. This second problem started with more initial sample points (35 instead of 20) since accurately modeling the objective function...
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