Search

Your search keyword '"MA Jiayu"' showing total 414 results
Start Over Author "MA Jiayu"
414 results on '"MA Jiayu"'

1. On-device phase engineering

Author

Liu, Xiaowei, Shan, Junjie, Cao, Tianjun, Zhu, Liang, Ma, Jiayu, Wang, Gang, Shi, Zude, Yang, Qishuo, Ma, Mingyu, Liu, Zenglin, Yan, Shengnan, Wang, Lizheng, Dai, Yudi, Xiong, Junlin, Chen, Fanqiang, Wang, Buwei, Pan, Chen, Wang, Zhenlin, Cheng, Bin, He, Yongmin, Luo, Xin, Lin, Junhao, Liang, Shi-Jun, and Miao, Feng

Published
2024
Full Text
View/download PDF

8. Data-driven modeling of Landau damping by physics-informed neural networks

Author

Qin, Yilan, Ma, Jiayu, Jiang, Mingle, Dong, Chuanfei, Fu, Haiyang, Wang, Liang, Cheng, Wenjie, and Jin, Yaqiu

Subjects
Physics - Plasma Physics, Astrophysics - High Energy Astrophysical Phenomena, Computer Science - Machine Learning, Physics - Computational Physics, Physics - Space Physics
Abstract

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this paper, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. In addition, we introduce a variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems., Comment: 11 pages, 7 figures, accepted for publication in Physical Review Research

Published
2022
Full Text
View/download PDF

9. Data-driven, multi-moment fluid modeling of Landau damping

Author

Cheng, Wenjie, Fu, Haiyang, Wang, Liang, Dong, Chuanfei, Jin, Yaqiu, Jiang, Mingle, Ma, Jiayu, Qin, Yilan, and Liu, Kexin

Subjects
Physics - Plasma Physics, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning, Physics - Space Physics
Abstract

Deriving governing equations of complex physical systems based on first principles can be quite challenging when there are certain unknown terms and hidden physical mechanisms in the systems. In this work, we apply a deep learning architecture to learn fluid partial differential equations (PDEs) of a plasma system based on the data acquired from a fully kinetic model. The learned multi-moment fluid PDEs are demonstrated to incorporate kinetic effects such as Landau damping. Based on the learned fluid closure, the data-driven, multi-moment fluid modeling can well reproduce all the physical quantities derived from the fully kinetic model. The calculated damping rate of Landau damping is consistent with both the fully kinetic simulation and the linear theory. The data-driven fluid modeling of PDEs for complex physical systems may be applied to improve fluid closure and reduce the computational cost of multi-scale modeling of global systems., Comment: 10 pages, 8 figures. Computer Physics Communications, in press

Published
2022
Full Text
View/download PDF

22. Multi-parameter Characterization of Ionospheric Disturbances Based on GNSS Ground-Based CORS Data

Author

Qian, Hongyi, Chen, Yan, Fu, Haiyang, Ye, Junru, Sui, Yun, Ma, Jiayu, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Yang, Changfeng, editor, and Xie, Jun, editor

Published
2022
Full Text
View/download PDF

40. Large Adsorption Capacity for Space Molecular Pollutants Realized by a Metal–Organic Framework

Author

Sun, Rui, Zhang, Yuzhi, Gu, Hongyu, Zhang, Maofei, Wang, Xinyu, Liu, Yangqiao, Li, Haogeng, Ma, Jiayu, and Song, Lixin

Abstract

The rapid development of capable spacecraft coatings for removing volatile organic compounds (VOCs) demands materials with a large adsorption capacity to ensure a long-duration exploration mission in a low Earth orbit (LEO). MIL-53(Al) with abundant sites exhibits resistance to the space environment in the LEO and shows great potential for VOC removal. This study combined an adsorption experiment and first-principles simulations to investigate the adsorption performance of MIL-53(Al). MIL-53(Al) demonstrated an excellent adsorption capacity for various VOCs, reaching 606.04 mg/g for m-xylene and 22.69 cm3/g for methane, which is 6 times higher than traditional adsorption methods. First-principles simulations revealed that the adsorption capacity is significantly influenced by micropores through the pore effect and breath effect, which restrict diffusion and enhance adsorption, respectively. Additionally, we predicted the adsorption properties of VOCs that are difficult to characterize through ground-based simulated experiments, further validating the potential application of MIL-53(Al) for VOC removal in the LEO. This work expands the application range of MIL-53(Al), optimizes VOC removal strategies, and offers a novel approach to protecting spacecraft in the LEO. Our findings contribute to the development of advanced materials for space exploration and provide valuable insights into the design of efficient VOC removal systems for spacecraft in the LEO.

Published
2024
Full Text
View/download PDF

41. CSRM‐1.0: A China Seismological Reference Model.

Author

Xiao, Xiao, Cheng, Shihua, Wu, Jianping, Wang, Weilai, Sun, Li, Wang, Xiaoxin, Ma, Jiayu, Tong, Yinghua, Liang, Xiaofeng, Tian, Xiaobo, Li, Hongyi, Chen, Qi‐Fu, Yu, Sheng, and Wen, Lianxing

Subjects
GROUP velocity dispersion, MAFIC rocks, GREEN'S functions, MANTLE plumes, HAZARD mitigation, MICROSEISMS, SURFACE waves (Seismic waves), RAYLEIGH waves
Abstract

High‐resolution seismic model is crucial for advancing our understandings on geological processes and enhancing seismic hazard mitigation programs. We construct a high‐resolution China Seismological Reference Model (CSRM‐1.0) in the top 100 km of the crust and uppermost mantle in continental China following a top‐down construction process. The employed seismic constraints include P‐wave polarization angle from tele‐seismic event, short‐period Rayleigh wave ellipticity from ambient noise, long‐period Rayleigh wave ellipticity from earthquake data, receiver function, empirical Green's function from ambient noise, Rayleigh wave phase/group velocity dispersion curves from regional earthquakes, and Pn‐wave travel time extracted from seismic data of 4,435 stations. CSRM‐1.0 has a spatial crustal resolution of ∼60 km beneath the north‐south seismic belt and trans‐North China orogen regions and ∼120 km beneath the rest of continental China, and a spatial mantle resolution of ∼300 km. CSRM‐1.0 exhibits prominent velocity heterogeneities in the crust and uppermost mantle and an eastward thinning of the crust, geographically correlating with geological settings. CSRM‐1.0 improvements include accurate estimation of shallow seismic structure, increased spatial resolution and improved model accuracy. Crustal composition inferred from CSRM‐1.0 exhibits a general transition from a felsic upper crust to a mafic lower crust. Mafic rocks in the lower crust are found predominantly along inter‐block boundaries and sporadically within the interiors of blocks, likely resulted from preferential inter‐block intrusions of magmas related to various oceanic plate subductions and the Emeishan mantle plume. This study contributes seismic constraints and CSRM‐1.0 to the CSRM product center (http://chinageorefmodel.org) as a backbone open‐access geophysical cyberinfrastructure. Plain Language Summary: High‐resolution seismic imaging of the crust and uppermost mantle offers crucial insights into regional geological histories and enhances seismic and volcanic hazard mitigation programs. We construct a high‐resolution China Seismological Reference Model (CSRM‐1.0) of the crust and mantle beneath continental China with various types of seismic constraints extracted from seismic data recorded by 4,435 stations deployed across continental China since 1990. CSRM‐1.0 has a spatial resolution of ∼60–120 km in the crust and 300 km in the uppermost mantle. CSRM‐1.0 improvements include accurate estimation of shallow seismic structure, increased spatial resolution and improved model accuracy. Crustal composition inferred from CSRM‐1.0 exhibits a general transition from a felsic upper crust to a mafic lower crust. Mafic rocks in the lower crust are found predominantly along inter‐block boundaries and sporadically within the interiors of blocks, likely resulted from preferential inter‐block intrusions of magmas related to various oceanic plate subductions and the Emeishan mantle plume. This study contributes seismic constraints and CSRM‐1.0 to the CSRM product center (http://chinageorefmodel.org) as a backbone open‐access geophysical cyberinfrastructure. Key Points: CSRM‐1.0 is constructed with various seismic constraints from data of 4,435 stations using a self‐consistent top‐down construction processCSRM‐1.0 improvements include accurate estimation of shallow seismic structure, increased spatial resolution, and enhanced model accuracyCSRM‐1.0 reveals major crustal mafic rocks related to the past subductions, an Emeishan mantle plume and geological inter‐block boundaries [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results