Geodesic
Recursive neural network as a high-speed plate collision emulator
Čelâbinskij fiziko-matematičeskij žurnal, Tome 9 (2024) no. 1, pp. 134-143.

Voir la notice de l'article provenant de la source Math-Net.Ru

Based on a database obtained using a high-speed plate impact model that relates impact parameters and material model parameters to the free surface velocity profile, the study compares the learning process and accuracy of a feedforward artificial neural network and a recursive neural network. A recursive neural network provides a significantly greater accuracy and requires less training time. Using a recursive neural network as a fast model emulator and Bayesian calibration can make it possible to solve the inverse problem of determining the substance model parameters from the free surface velocity profile with a greater accuracy.
Keywords: recursive neural network, artificial neural network, artificial neural network training, high-speed plate collision. 
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V. V. Pogorelko; A. E. Mayer; E. V. Fedorov. Recursive neural network as a high-speed plate collision emulator. Čelâbinskij fiziko-matematičeskij žurnal, Tome 9 (2024) no. 1, pp. 134-143. http://geodesic.mathdoc.fr/item/CHFMJ_2024_9_1_a10/

[1] De Resseguier T., Hemery S., Lescoute E., Villechaise P., Kannel G. I., Razorenov S. V., “Spall fracture and twinning in laser shockloaded single-crystal magnesium”, Journal of Applied Physics, 121:16 (2017), 165104 | DOI

[2] Garkushin G. V., Kannel G. I., Razorenov S. V., Savinykh A. S., “Anomaly in the dynamic strength of austenitic stainless steel 12Cr19Ni10Ti under shock wave loading”, Mechanics of Solids, 52:4 (2017), 407–416 | DOI

[3] Zaretsky E. B., Kannel G. I., “The high temperature impact response of tungsten and chromium”, Journal of Applied Physics, 122:11 (2017), 115901 | DOI

[4] Saveleva N. V., Bayandin Y. V., Savinykh A. S., Garkushin G. V., Razorenov S. V., Naimark O. B., “The formation of elastoplastic fronts and spall fracture in AMg6 alloy under shock-wave loading”, Technical Physics Letters, 44:9 (2018), 823–826 | DOI

[5] Qi M., He H., Yan S., “Measurement and analysis of spall characteristics of high-pure aluminum at one-dimensional strain loading”, Chinese Physics Letteers, 24 (2007), 2338 | DOI

[6] Colvin J. D., Minich R. W., Kalantar D. H., “A model for plasticity kinetics and its role in simulating the dynamic behavior of Fe at high strain rates”, International Journal of Plasticity, 25 (2009), 603–611 | DOI | Zbl

[7] Winey J. M., LaLone B. M., Triverdi P. B., Gupta Y. M., “Elastic wave amplitudes in shock-compressed thin polycrystalline aluminum samples”, Journal of Applied Physics, 106:7 (2009), 073508 | DOI

[8] Glam B., Moreno D., Eliezer S., Eliezer D., “Study of dislocation walls evolution during spall in pure aluminum”, AIP Conference Proceedings, 1426 (2012), 987 | DOI

[9] Zaretsky E. B., Kannel G. I., “Effect of temperature, strain, and strain rate on the flow stress of aluminum under shock-wave compression”, Journal of Applied Physics, 112:11 (2012), 073504 | DOI

[10] Barker L. M., Hollenbach R. E., “Laser interferometer for measuring high velocities of any reflecting surface”, Journal of Applied Physics, 43:11 (1972), 4669–4672 | DOI

[11] Armstrong R. W., Arnold W., Zerilli F. J., “Dislocation mechanics of shock-induced plasticity”, Metallurgical and Materials Transactions A, 38 (2007), 2605–2610 | DOI

[12] Vasu K. R. S., Vinith Y. G., Uday S. G., Suneesh G., Krishna M. B., “A review on Johnson Cook material model”, Materials Today: Proceedings, 62:6 (2022), 3450–3456

[13] Austin R. A., McDowell D. L., “Parameterization of a rate-dependent model of shock-induced plasticity for copper, nickel, and aluminum”, International Journal of Plasticity, 32:3 (2012), 134–154 | DOI

[14] Austin R. A., “Elastic precursor wave decay in shock-compressed aluminum over a wide range of temperature”, Journal of Applied Physics, 123 (2018), 035103 | DOI

[15] Hansen B. L., Beyerlein I. J., Bronkhorst C. A., Cerreta E. K., Dennis-Koller D. A., “A dislocation-based multi-rate single crystal plasticity model”, International Journal of Plasticity, 44 (2013), 129–146 | DOI

[16] Luscher D. J., Bronkhorst C. A., Alleman C. N., Addessio F. L., “A model for finite-deformation nonlinear thermomechanical response of single crystal copper under shock conditions”, Journal of the Mechanics and Physics of Solids, 61 (2013), 1877–1894 | DOI | MR

[17] Jianqiao H., Zhanli L., Kaiguo C., Zhuo Z., “Investigations of shock-induced deformation and dislocation mechanism by a multiscale discrete dislocation plasticity model”, Computational Materials Science, 131 (2017), 78–85 | DOI

[18] Tohme T., Vanslette K., Youcef-Toumi K., “A generalized Bayesian approach to model calibration”, Reliability Engineering and System Safety, 204 (2020), 107141 | DOI

[19] Pogorelko V.V., Mayer A.E., Fomin E.V., Fedorov E.V., “Emulation of high-speed plate collision with an artificial neural network”, Chelyabinsk Physical and Mathematical Journal, 8:1 (2023), 129–139

[20] Popova T. V., Mayer A. E., Khishchenko K. V., “Evolution of shock compression pulses in polymethylmethacrylate and aluminum”, Journal of Applied Physics, 123 (2018), 235902 | DOI

[21] Khishchenko K. V., Mayer A. E., “High- and low-entropy layers in solids behind shock and ramp compression waves”, International Journal of Mechanical Science, 189 (2021), 105971 | DOI

[22] Kingma D. P., Ba J., Adam: a method for stochastic optimization, arXiv: 1412.6980