Physics-informed machine learning enabled virtual experimentation for 3D printed thermoplastic

被引:0
|
作者
Chen, Zhenru [1 ]
Wu, Yuchao [1 ]
Xie, Yunchao [2 ]
Sattari, Kianoosh [1 ]
Lin, Jian [1 ]
机构
[1] Department of Mechanical and Aerospace Engineering, University of Missouri, Columbia,MO,65211, United States
[2] Department of Mechanical and Manufacturing Engineering, Miami University, Oxford,OH,45056, United States
基金
美国国家科学基金会;
关键词
Microcomputers; -; Thermoplastics;
D O I
10.1039/d4mh01022a
中图分类号
学科分类号
摘要
引用
收藏
页码:6028 / 6039
相关论文
共 50 条
  • [1] Physics-informed machine learning
    George Em Karniadakis
    Ioannis G. Kevrekidis
    Lu Lu
    Paris Perdikaris
    Sifan Wang
    Liu Yang
    Nature Reviews Physics, 2021, 3 : 422 - 440
  • [2] Physics-informed machine learning
    Karniadakis, George Em
    Kevrekidis, Ioannis G.
    Lu, Lu
    Perdikaris, Paris
    Wang, Sifan
    Yang, Liu
    NATURE REVIEWS PHYSICS, 2021, 3 (06) : 422 - 440
  • [3] Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning
    Mandl, Luis
    Goswami, Somdatta
    Lambers, Lena
    Ricken, Tim
    Computer Methods in Applied Mechanics and Engineering, 2025, 434
  • [4] A Taxonomic Survey of Physics-Informed Machine Learning
    Pateras, Joseph
    Rana, Pratip
    Ghosh, Preetam
    APPLIED SCIENCES-BASEL, 2023, 13 (12):
  • [5] Physics-informed Machine Learning for Accelerated Testing of Roll-to-roll Printed Sensors
    Mouli, S. Chandra
    Sedaghat, Sotoudeh
    Oduncu, Muhammed Ramazan
    Saha, Ajanta
    Rahimi, Rahim
    Alam, Muhammad A.
    Wei, Alexander
    Shakouri, Ali
    Ribeiro, Bruno
    PROCEEDINGS OF ASME 2022 17TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, MSEC2022, VOL 2, 2022,
  • [6] Numerical analysis of physics-informed neural networks and related models in physics-informed machine learning
    De Ryck, Tim
    Mishra, Siddhartha
    ACTA NUMERICA, 2024, 33 : 633 - 713
  • [7] Physics-informed machine learning for modeling multidimensional dynamics
    Abbasi, Amirhassan
    Kambali, Prashant N.
    Shahidi, Parham
    Nataraj, C.
    NONLINEAR DYNAMICS, 2024, : 21565 - 21585
  • [8] Physics-informed Machine Learning for Modeling Turbulence in Supernovae
    Karpov, Platon I.
    Huang, Chengkun
    Sitdikov, Iskandar
    Fryer, Chris L.
    Woosley, Stan
    Pilania, Ghanshyam
    ASTROPHYSICAL JOURNAL, 2022, 940 (01):
  • [9] Physics-Informed Machine Learning for DRAM Error Modeling
    Baseman, Elisabeth
    DeBardeleben, Nathan
    Blanchard, Sean
    Moore, Juston
    Tkachenko, Olena
    Ferreira, Kurt
    Siddiqua, Taniya
    Sridharan, Vilas
    2018 IEEE INTERNATIONAL SYMPOSIUM ON DEFECT AND FAULT TOLERANCE IN VLSI AND NANOTECHNOLOGY SYSTEMS (DFT), 2018,
  • [10] The scaling of physics-informed machine learning with data and dimensions
    Miller S.T.
    Lindner J.F.
    Choudhary A.
    Sinha S.
    Ditto W.L.
    Chaos, Solitons and Fractals: X, 2020, 5