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pro vyhledávání: '"He, Xiaolong"'
The parametric greedy latent space dynamics identification (gLaSDI) framework has demonstrated promising potential for accurate and efficient modeling of high-dimensional nonlinear physical systems. However, it remains challenging to handle noisy dat
Externí odkaz:
http://arxiv.org/abs/2407.00337
Autor:
Bonneville, Christophe, He, Xiaolong, Tran, April, Park, Jun Sur, Fries, William, Messenger, Daniel A., Cheung, Siu Wun, Shin, Yeonjong, Bortz, David M., Ghosh, Debojyoti, Chen, Jiun-Shyan, Belof, Jonathan, Choi, Youngsoo
Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated t
Externí odkaz:
http://arxiv.org/abs/2403.10748
Recent work in data-driven modeling has demonstrated that a weak formulation of model equations enhances the noise robustness of a wide range of computational methods. In this paper, we demonstrate the power of the weak form to enhance the LaSDI (Lat
Externí odkaz:
http://arxiv.org/abs/2311.12880
Experimental observations suggest that the force output of the skeletal muscle tissue can be correlated to the intra-muscular pressure generated by the muscle belly. However, pressure often proves difficult to measure through in-vivo tests. Simulatio
Externí odkaz:
http://arxiv.org/abs/2310.06191
In deep geological repositories for high level nuclear waste with close canister spacings, bentonite buffers can experience temperatures higher than 100 {\deg}C. In this range of extreme temperatures, phenomenological constitutive laws face limitatio
Externí odkaz:
http://arxiv.org/abs/2309.13519
Autor:
Rustem, Abdurepqet, Lv, Guoliang, Liu, Jinzhong, Zhu, Chunhua, Zhang, Yu, Shen, Dongxiang, Zhang, Yuhao, He, Xiaolong
Magnetic fields are significant in the structure and evolution of stars. We present a comprehensive catalogue of 1784 known magnetic stars, detailing their identifications, HD numbers, precise locations, spectral types, and averaged quadratic effecti
Externí odkaz:
http://arxiv.org/abs/2307.12315
This work presents a multi-resolution physics-informed recurrent neural network (MR PI-RNN), for simultaneous prediction of musculoskeletal (MSK) motion and parameter identification of the MSK systems. The MSK application was selected as the model pr
Externí odkaz:
http://arxiv.org/abs/2305.16593
Autor:
Wang, Pengwan1 (AUTHOR) wangpw_hz@petrochina.com.cn, He, Xiaolong2 (AUTHOR) hexiaolong@stu.cdut.edu.cn, Chen, Ya'na1 (AUTHOR) chenyn_hz@petrochina.com.cn, Xu, Chuan2 (AUTHOR) hexiaolong@stu.cdut.edu.cn, Cao, Quanbin1 (AUTHOR) caoqb_hz@petrochina.com.cn, Yang, Kai2 (AUTHOR), Zhang, Bing2 (AUTHOR)
Publikováno v:
Minerals (2075-163X). Oct2024, Vol. 14 Issue 10, p1046. 20p.
A parametric adaptive greedy Latent Space Dynamics Identification (gLaSDI) framework is developed for accurate, efficient, and certified data-driven physics-informed greedy auto-encoder simulators of high-dimensional nonlinear dynamical systems. In t
Externí odkaz:
http://arxiv.org/abs/2211.13698
Publikováno v:
Computer Methods in Applied Mechanics and Engineering 385 (2021) 114034
Physics-constrained data-driven computing is an emerging computational paradigm that allows simulation of complex materials directly based on material database and bypass the classical constitutive model construction. However, it remains difficult to
Externí odkaz:
http://arxiv.org/abs/2209.04416