1.3k citations
- Universidad Autónoma de MadridES24 papers
- Université de Bretagne SudFR21 papers
- Max Planck Institute for Gravitational PhysicsDE19 papers
- University of Wisconsin–MilwaukeeUS15 papers
- Centre National de la Recherche ScientifiqueFR14 papers
- Pennsylvania State UniversityUS14 papers
- Tsinghua UniversityCN14 papers
- The University of Texas at AustinUS13 papers
- University of MichiganUS13 papers
- California Institute of TechnologyUS12 papers
- Goddard Space Flight CenterUS12 papers
- Instituto de Física TeóricaES12 papers
14 papers · 1 filter
Improving the Accuracy and Consistency of the Scalar Auxiliary Variable (SAV) Method with Relaxation
Maosheng Jiang, Zengyan Zhang, Jia Zhao
The scalar auxiliary variable (SAV) method was introduced by Shen et al. and has been broadly used to solve thermodynamically consistent PDE problems. By utilizing scalar auxiliary…
A Revisit of The Energy Quadratization Method with A Relaxation Technique
Jia Zhao
This letter revisits the energy quadratization (EQ) method by introducing a novel and essential relaxation technique to improve its accuracy and stability. The EQ method has witnes…
Second-order Decoupled Energy-stable Schemes for Cahn-Hilliard-Navier-Stokes equations
Jia Zhao
The Cahn-Hilliard-Navier-Stokes (CHNS) equations represent the fundamental building blocks of hydrodynamic phase-field models for multiphase fluid flow dynamics. Due to the couplin…
A General Framework to Derive Linear, Decoupled and Energy-stable Schemes for Reversible-Irreversible Thermodynamically Consistent Models: Part I Incompressible Hydrodynamic Models
Jia Zhao
In this paper, we present a general numerical platform for designing accurate, efficient, and stable numerical algorithms for incompressible hydrodynamic models that obeys the ther…
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks
Colby L. Wight, Jia Zhao
Phase field models, in particular, the Allen-Cahn type and Cahn-Hilliard type equations, have been widely used to investigate interfacial dynamic problems. Designing accurate, effi…
Discovering Phase Field Models from Image Data with the Pseudo-spectral Physics Informed Neural Networks
Jia Zhao
In this paper, we introduce a new deep learning framework for discovering the phase field models from existing image data. The new framework embraces the approximation power of phy…