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Currently existing energy-stable parametric finite element methods for surface diffusion flow and other flows are usually limited to first-order accuracy in time. Designing a high-order algorithm for geometric flows that can also be…

Numerical Analysis · Mathematics 2024-07-15 Meng Li , Yihang Guo , Jingjiang Bi

New criteria for energy stability of multi-step, multi-stage, and mixed schemes are introduced in the context of evolution equations that arise as gradient flow with respect to a metric. These criteria are used to exhibit second and third…

Numerical Analysis · Mathematics 2023-10-09 Saem Han , Selim Esedoglu , Krishna Garikipati

We introduce a class of high order accurate, semi-implicit Runge-Kutta schemes in the general setting of evolution equations that arise as gradient flow for a cost function, possibly with respect to an inner product that depends on the…

Numerical Analysis · Mathematics 2021-10-04 Alexander Zaitzeff , Selim Esedoglu , Krishna Garikipati

We present a numerical scheme for approximating the incompressible Navier-Stokes equations based on an auxiliary variable associated with the total system energy. By introducing a dynamic equation for the auxiliary variable and…

Fluid Dynamics · Physics 2019-05-01 Lianlei Lin , Suchuan Dong

Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the…

Numerical Analysis · Mathematics 2017-05-29 Max Gunzburger , Nan Jiang , Zhu Wang

In this work, we investigate the use of data-driven equation discovery for dynamical systems to model and forecast continuous-time dynamics of unconstrained optimization problems. To avoid expensive evaluations of the objective function and…

Optimization and Control · Mathematics 2026-02-19 Grant Norman , Conor Rowan , Kurt Maute , Alireza Doostan

We present a fast, unconditionally energy-stable numerical scheme for simulating vesicle deformation under osmotic pressure using a phase-field approach. The model couples an Allen-Cahn equation for the biomembrane interface with a…

Numerical Analysis · Mathematics 2026-01-16 Zhiwei Zhang , Shuwang Li , John Lowengrub , Steven M. Wise

We consider a family of steady free-surface flow problems in two dimensions, concentrating on the effect of nonlinearity on the train of gravity waves that appear downstream of a disturbance. By exploiting standard complex variable…

Fluid Dynamics · Physics 2018-03-14 Ravindra Pethiyagoda , Timothy J. Moroney , Scott W. McCue

We investigate the numerical approximation of the stochastic Allen--Cahn equation with multiplicative noise on a periodic domain. The considered scheme uses a recently proposed augmented variant of scalar auxiliary variable method for the…

Numerical Analysis · Mathematics 2025-06-27 Stefan Metzger

In this paper, we develop an energy dissipative numerical scheme for gradient flows of planar curves, such as the curvature flow and the elastic flow. Our study presents a general framework for solving such equations. To discretize time, we…

Numerical Analysis · Mathematics 2016-10-11 Tomoya Kemmochi

We present a framework for devising discretely energy-stable schemes for general dissipative systems based on a generalized auxiliary variable. The auxiliary variable, a scalar number, can be defined in terms of the energy functional by a…

Computational Physics · Physics 2020-01-29 Zhiguo Yang , Suchuan Dong

We present compact semi-implicit finite difference schemes on structured grids for numerical solutions of the advection by an external velocity and by a speed in normal direction that are applicable in level set methods. The most involved…

Numerical Analysis · Mathematics 2023-12-01 Peter Frolkovič , Nikola Gajdošová

Flow matching (FM) has shown promising results in data-driven planning. However, it inherently lacks formal guarantees for ensuring state and action constraints, whose satisfaction is a fundamental and crucial requirement for the safety and…

Machine Learning · Computer Science 2025-12-02 Tzu-Yuan Huang , Armin Lederer , Dai-Jie Wu , Xiaobing Dai , Sihua Zhang , Stefan Sosnowski , Shao-Hua Sun , Sandra Hirche

Analyzing unsteady fluid flows often requires access to the full distribution of possible temporal states, yet conventional PDE solvers are computationally prohibitive and learned time-stepping surrogates quickly accumulate error over long…

Computational Engineering, Finance, and Science · Computer Science 2026-04-14 Mario Lino , Nils Thuerey

We propose novel algorithms combining accelerated gradient flows with linearized projection-free treatments of non-convex constraints and BDF pseudo-temporal discretization for quadratic energy minimization. A general framework is developed…

Numerical Analysis · Mathematics 2025-06-13 Guozhi Dong , Zikang Gong , Ziqing Xie , Shuo Yang

We propose an energy-optimized invariant energy quadratization method to solve the gradient flow models in this paper, which requires only one linear energy-optimized step to correct the auxiliary variables on each time step. In addition to…

Numerical Analysis · Mathematics 2024-04-03 Xiaoqing Meng , Aijie Cheng , Zhengguang Liu

We propose in this paper efficient first/second-order time-stepping schemes for the evolutional Navier-Stokes-Nernst-Planck-Poisson equations. The proposed schemes are constructed using an auxiliary variable reformulation and sophisticated…

Numerical Analysis · Mathematics 2023-05-17 Xiaolan Zhou , Chuanju Xu

We present a paradigm for developing arbitrarily high order, linear, unconditionally energy stable numerical algorithms for gradient flow models. We apply the energy quadratization (EQ) technique to reformulate the general gradient flow…

Numerical Analysis · Mathematics 2020-07-15 Yuezheng Gong , Jia Zhao , Qi Wang

We discuss an extension of the scalar auxiliary variable approach, which was originally introduced by Shen et al. ([Shen, Xu, Yang, J. Comput. Phys., 2018]) for the discretization of deterministic gradient flows. By introducing an…

Numerical Analysis · Mathematics 2024-09-20 Stefan Metzger

Training expressive flow-based policies with off-policy reinforcement learning is notoriously unstable due to gradient pathologies in the multi-step action sampling process. We trace this instability to a fundamental connection: the flow…

Robotics · Computer Science 2026-01-15 Yixian Zhang , Shu'ang Yu , Tonghe Zhang , Mo Guang , Haojia Hui , Kaiwen Long , Yu Wang , Chao Yu , Wenbo Ding
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