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    16.07 Dynamics, Fall 2004 by Peraire, Jaume

    Published 2004
    Subjects:
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    Learning Object
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    Data-driven forward and inverse analysis of two-dimensional soil consolidation using physics-informed neural network by Wang, Yu, Shi, Chao, Shi, Jiangwei, Lu, Hu

    Published 2024
    “…Different random seeds are used to test the robustness of the PINN developed and quantify the associated model uncertainty. …”
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    Journal Article
  18. 318

    Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool by Mukhmetov, Olzhas, Zhao, Yong, Mashekova, Aigerim, Zarikas, Vasilios, Ng, Eddie Yin Kwee, Aidossov, Nurduman

    Published 2024
    “…This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast forward simulation of heat transfer through cancerous breast models. …”
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    Journal Article
  19. 319

    Cationic distribution, exchange interactions, and relaxation dynamics in Zn-diluted MnCo2O4 nanostructures by Tiwari, Nidhi, Pramanik, P., Joshi, D. C., Sarkar, T., Pittala, S., Salman, O. O., Manga, M.-M., Thota, S.

    Published 2019
    “…This behavior is similar to the de Almeida-Thouless (AT-line) analysis in the T-H phase diagram which supports the existence of spin-glass like behavior below TF in these Zn diluted spinels.…”
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    Journal Article
  20. 320

    Direct observation of deterministic domain wall trajectory in magnetic network structures by Sethi, Pankaj, Murapaka, Chandrasekhar, Goolaup, Sarjoosing, Chen, Yun Jie, Leong, Siang Huei, Lew, Wen Siang

    Published 2018
    “…The DW propagation in the network structure is governed by the geometrically induced potential barrier and pinning strength against the propagation. This technique can be extended for controlling the trajectory of magnetic charge carriers in an artificial spin ice lattice.…”
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    Journal Article