61 Publications (Page 1 of 3)
2025
Auxiliary relaxation method to derive thermodynamically consistent phase field models with constraints and structure preserving numerical approximations. Journal of Computational Physics
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Discovery of Governing Equations with Recursive Deep Neural Networks. Communications on Applied Mathematics and Computation
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General numerical framework to derive structure preserving reduced order models for thermodynamically consistent reversible-irreversible PDEs. Journal of Computational Physics
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2024
Computational modeling of microalgal biofilm growth in heterogeneous rotating algal biofilm reactors (RABRs) for wastewater treatment. Applied Mathematical Modelling
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Linear relaxation method with regularized energy reformulation for phase field models. Journal of Computational Physics
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2023
A Physics-Informed Structure-Preserving Numerical Scheme for the Phase-Field Hydrodynamic Model of Ternary Fluid Flows. Numerical Mathematics: Theory, Methods and Applications
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Chaos does not drive lower synchrony for intrinsically-induced population fluctuations. Ecological Modelling
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Experimental and theoretical investigations of rotating algae biofilm reactors (RABRs): Areal productivity, nutrient recovery, and energy efficiency. Biotechnology and Bioengineering
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Linear relaxation schemes for the Allen–Cahn-type and Cahn–Hilliard-type phase field models. Applied Mathematics Letters
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Numerical Approximations of the Allen-Cahn-Ohta-Kawasaki Equation with Modified Physics-Informed Neural Networks (Pinns) International Journal of Numerical Analysis and Modeling
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Thermodynamically consistent hydrodynamic phase-field computational modeling for fluid-structure interaction with moving contact lines. Journal of Computational Physics
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2022
A general framework to derive linear, decoupled and energy-stable schemes for reversible-irreversible thermodynamically consistent models
Zhao, Jia
Computers & Mathematics with Applications, vol. 110, pp. 91–109. | Journal Article
 
Improving the accuracy and consistency of the scalar auxiliary variable (SAV) method with relaxation. Journal of Computational Physics
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Linear energy stable numerical schemes for a general chemo-repulsive model. Journal of Computational and Applied Mathematics
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2021
A revisit of the energy quadratization method with a relaxation technique
Zhao, Jia
Applied Mathematics Letters, vol. 120, pp. 107331. | Journal Article
 
Discovering Phase Field Models from Image Data with the Pseudo-Spectral Physics Informed Neural Networks
Zhao, Jia
Communications on Applied Mathematics and Computation, vol. 3, pp. 357–369. | Journal Article
 
Second-order decoupled energy-stable schemes for Cahn-Hilliard-Navier-Stokes equations. Journal of Computational Physics
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Second order linear decoupled energy dissipation rate preserving schemes for the Cahn-Hilliard-extended-Darcy model. Journal of Computational Physics
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Second order linear thermodynamically consistent approximations to nonlocal phase field porous media models. Computer Methods in Applied Mechanics and Engineering
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Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks. Communications in Computational Physics
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2020
A non-uniform time-stepping convex splitting scheme for the time-fractional Cahn–Hilliard equation
Zhang, Jun⋅Zhao, Jia and Wang, JinRong
Computers & Mathematics with Applications, vol. 80, pp. 837–850. | Journal Article
 
A novel second-order linear scheme for the Cahn-Hilliard-Navier-Stokes equations
Chen, Lizhen and Zhao, Jia
Journal of Computational Physics, vol. 423, pp. 109782. | Journal Article
 
A patient specific forecasting model for human albumin based on deep neural networks. Computer Methods and Programs in Biomedicine
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Arbitrarily high-order linear energy stable schemes for gradient flow models
Gong, Yuezheng⋅Zhao, Jia and Wang, Qi
Journal of Computational Physics, vol. 419, pp. 109610. | Journal Article
 
Arbitrarily high-order unconditionally energy stable SAV schemes for gradient flow models
Gong, Yuezheng⋅Zhao, Jia and Wang, Qi
Computer Physics Communications, vol. 249, pp. 107033. | Journal Article