Jun Zhang
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Multiscale Modelling and Machine Learning

  The discovery of governing equations from data is revolutionizing the development of some research fields, where the scientific data are abundant, but the well-characterized quantitative descriptions are probably scarce. We proposed to combine molecular simulations and machine learning to discover the governing equations for fluid dynamics [9], as shown in Fig 5. The prediction from data-driven discovery not only provides the right form of governing equation, but also determines the accurate values of transport coefficients such as viscosity and diffusion. This strategy is expected to help discover constitutive relationships and establish governing equations for nonequilibrium flows and complex fluids [10].

data-driven.png

Fig. 5. Data-driven discovery of governing equations based on molecular simulations.

[9] J. Zhang*, and W. Ma, "Data-driven discovery of governing equations for fluid dynamics based on molecular simulation," Journal of Fluid Mechanics 892, A5 (2020).

[10] W. Ma, J. Zhang*, et al., "Dimensional homogeneity constrained gene expression programming for discovering governing equations," Journal of Fluid Mechanics 985, A12 (2024).



Personal information

Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

E-Mail:

Date of Employment:2017-02-01

School/Department:航空科学与工程学院

Gender:Male

Contact Information:jun.zhang@buaa.edu.cn

Status:Employed

Discipline:Mechanics
Aeronautical and Astronautical Science and Technology

Honors and Titles:

国家级青年人才  2018

中科院青年创新促进会会员  2012

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