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Arbitrarily High-Order Unconditionally Energy Stable Schemes for Thermodynamically Consistent Gradient Flow Models

Yuezheng Gong, Jia Zhao, Qi Wang

2020SIAM Journal on Scientific Computing73 citationsDOI

Abstract

We present a systematic approach to developing arbitrarily high-order, unconditionally energy stable numerical schemes for thermodynamically consistent gradient flow models that satisfy energy dissipation laws. Utilizing the energy quadratization method, we formulate the gradient flow model into an equivalent form with a corresponding quadratic free energy functional. Based on the equivalent form with a quadratic energy, we propose two classes of energy stable numerical approximations. In the first approach, we use a prediction-correction strategy to improve the accuracy of linear numerical schemes. In the second approach, we adopt the Gaussian collocation method to discretize the equivalent form with a quadratic energy, arriving at an arbitrarily high-order scheme for gradient flow models. Schemes derived using both approaches are proved rigorously to be unconditionally energy stable. The proposed schemes are then implemented in four gradient flow models numerically to demonstrate their accuracy and effectiveness. Detailed numerical comparisons among these schemes are carried out as well. These numerical strategies are rather general so that they can be readily generalized to solve any thermodynamically consistent PDE models.

Topics & Concepts

Balanced flowDiscretizationMathematicsQuadratic equationApplied mathematicsFlow (mathematics)DissipationEnergy (signal processing)Numerical analysisCollocation (remote sensing)GaussianMathematical optimizationMathematical analysisComputer scienceGeometryPhysicsQuantum mechanicsMachine learningThermodynamicsStatisticsFluid Dynamics and Turbulent FlowsPhase Equilibria and ThermodynamicsComputational Fluid Dynamics and Aerodynamics