Machine learning assisted intelligent design of meta structures: a review

He, L., Li, Y., Torrent, D., Zhuang, X., Rabczuk, T. & Jin, Y., 9 Okt. 2023, in: Microstructures. 3, 4, 2023037.

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In-situ aligning magnetic nanoparticles in thermoplastic adhesives for contactless rapid joining of composite structures

Sha, Z., Cheng, X., Charles, A. D. M., Zhou, Y., Islam, M. S., Rider, A. N., Peng, S., Lim, M., Timchenko, V. & Wang, C. H., 1 Okt. 2023, in: Composite Structures. 321, 117304.

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Prediction of Early Compressive Strength of Ultrahigh-Performance Concrete Using Machine Learning Methods

Zhu, H., Wu, X., Luo, Y., Jia, Y., Wang, C., Fang, Z., Zhuang, X. & Zhou, S., 1 Okt. 2023, in: International Journal of Computational Methods. 20, 8, 23 S., 2141023.

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Computational modeling of quasi static fracture using the nonlocal operator method and explicit phase field model

Sahin, U., Ren, H., Imrak, C. E. & Rabczuk, T., Okt. 2023, in: Engineering with computers. 39, 5, S. 3617-3628 12 S.

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Enrichment of three-dimensional numerical manifold method with cover-based contact theory for static and dynamic mechanical response analysis

Kang, G., Ni, K. S., Zhuang, X., Rabczuk, T., Ning, Y. J. & Chen, P. W., Okt. 2023, in: Applied mathematical modelling. 122, S. 524-554 31 S.

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Weak form of bond-associated peridynamic differential operator for solving differential equations

Li, Z., Huang, D., Ren, H. & Rabczuk, T., Okt. 2023, in: Engineering with computers. 39, 5, S. 3491-3507 17 S.

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Search for Gravitational Waves Associated with Fast Radio Bursts Detected by CHIME/FRB during the LIGO–Virgo Observing Run O3a

The LIGO Scientific Collaboration, T. L. S. C., Bose, S., Danilishin, S., Danzmann, K., Heurs, M., Hreibi, A., Lück, H., Vahlbruch, H., Wilken, D., Willke, B., Wu, D. S., Affeldt, C., Bergamin, F., Bisht, A., Bode, N., Booker, P., Brinkmann, M., Gohlke, N., Heidt, A., Heinze, J., Hochheim, S., Junker, J., Kastaun, W., Kirchhoff, R., Koch, P., Koper, N., Kringel, V., Krishnendu, N. V., Kuehn, G., Leavey, S., Lehmann, J., Liu, J., Lough, J., Matiushechkina, M., Mehmet, M., Meylahn, F., Mukund, N., Nadji, S. L., Nery, M., Ohme, F., Schneewind, M., Schulte, B. W., Schutz, B. F., Venneberg, J., von Wrangel, J., Weinert, M., Wellmann, F., Weßels, P., Winkler, W. & Woehler, J., 28 Sept. 2023, in: Astrophysical Journal. 955, 2, 155.

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Physics-informed deep learning for three-dimensional transient heat transfer analysis of functionally graded materials

Guo, H., Zhuang, X., Fu, X., Zhu, Y. & Rabczuk, T., Sept. 2023, in: Computational mechanics. 72, 3, S. 513-524 12 S.

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Simultaneous improvement of heating efficiency and mechanical strength of a self-healing thermoplastic polymer by hybridizing magnetic particles with conductive fibres

Sha, Z., Cheng, X., Zhou, Y., Rider, A. N., Charles, A. D. M., Chang, W., Peng, S., Lim, M., Timchenko, V. & Wang, C. H., Sept. 2023, in: Composites Part A: Applied Science and Manufacturing. 172, 107597.

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Physics-informed deep learning for melting heat transfer analysis with model-based transfer learning

Guo, H., Zhuang, X., Alajlan, N. & Rabczuk, T., 1 Aug. 2023, in: Computers and Mathematics with Applications. 143, S. 303-317 15 S.

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