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In this paper, we develop a nonparametric system identification method for the nonlinear gradient-flow dynamics. In these systems, the vector field is the gradient field of a potential energy function. This fundamental fact about the…

Optimization and Control · Mathematics 2020-03-30 Mohammad Khosravi , Roy S. Smith

In this paper, we present a novel second-order generalised rotational discrete gradient scheme for numerically approximating the orthonormal frame gradient flow of biaxial nematic liquid crystals. This scheme relies on reformulating the…

Numerical Analysis · Mathematics 2023-10-17 Hanbin Wang , Jie Xu , Zhiguo Yang

We present a numerical scheme for solving a sixth-order Cahn-Hilliard type equation that captures the dynamics of phase transitions in a ternary mixture consisting of two immiscible fluids and a surface active molecule that is amphiphilic.…

Numerical Analysis · Mathematics 2025-04-01 Natasha S. Sharma , Giordano Tierra

We present a second-order-in-time finite difference scheme for the Cahn-Hilliard-Hele-Shaw equations. This numerical method is uniquely solvable and unconditionally energy stable. At each time step, this scheme leads to a system of…

Numerical Analysis · Mathematics 2016-11-10 Wenbin Chen , Wenqiang Feng , Yuan Liu , Cheng Wang , Steven M. Wise

In this paper, we propose novel algorithms integrated projection-free techniques with accelerated gradient flows to minimize bending energies for nonlinear plates with non-convex metric constraints. We discuss the stability and constraint…

Numerical Analysis · Mathematics 2025-06-18 Guozhi Dong , Hailong Guo , Shuo Yang

This paper presents a gradient-based reconstruction approach for simulations of compressible single and multi-species Navier-Stokes equations. The novel feature of the proposed algorithm is the efficient reconstruction via derivative…

Fluid Dynamics · Physics 2022-11-29 Amareshwara Sainadh Chamarthi

Given a particle system obeying overdamped Langevin dynamics, we demonstrate that it is always possible to construct a thermodynamically consistent macroscopic model which obeys a gradient flow with respect to its non-equilibrium free…

Statistical Mechanics · Physics 2025-06-11 Travis Leadbetter , Prashant K. Purohit , Celia Reina

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

We construct first- and second-order time discretization schemes for the Cahn-Hilliard-Navier-Stokes system based on the multiple scalar auxiliary variables approach (MSAV) approach for gradient systems and (rotational) pressure-correction…

Numerical Analysis · Mathematics 2020-09-22 Xiaoli Li , Jie Shen

We propose AEGD, a new algorithm for first-order gradient-based optimization of non-convex objective functions, based on a dynamically updated energy variable. The method is shown to be unconditionally energy stable, irrespective of the…

Optimization and Control · Mathematics 2021-10-04 Hailiang Liu , Xuping Tian

In this paper we propose and analyze a (temporally) third order accurate backward differentiation formula (BDF) numerical scheme for the no-slope-selection (NSS) equation of the epitaxial thin film growth model, with Fourier pseudo-spectral…

Numerical Analysis · Mathematics 2021-02-03 Yonghong Hao , Qiumei Huang , Cheng Wang

A new class of semi-implicit numerical schemes for linear advection equation on Cartesian grids is derived that is inspired by so-called $\kappa$-schemes used with fully explicit discretizations for this type of problems. Opposite to fully…

Numerical Analysis · Mathematics 2016-11-15 Peter Frolkovič , Karol Mikula

We propose a novel stochastic smoothing accelerated gradient (SSAG) method for general constrained nonsmooth convex composite optimization, and analyze the convergence rates. The SSAG method allows various smoothing techniques, and can deal…

Optimization and Control · Mathematics 2026-02-03 Ruyu Wang , Chao Zhang

We introduce a novel algorithm for gradient-based optimization of stochastic objective functions. The method may be seen as a variant of SGD with momentum equipped with an adaptive learning rate automatically adjusted by an 'energy'…

Optimization and Control · Mathematics 2022-03-24 Hailiang Liu , Xuping Tian

We introduce an automatic variationally stable analysis (AVS) for finite element (FE) computations of scalar-valued convection-diffusion equations with non-constant and highly oscillatory coefficients. In the spirit of least squares FE…

Numerical Analysis · Mathematics 2019-04-16 Victor M. Calo , Albert Romkes , Eirik Valseth

Accurate and efficient prediction of multi-scale flows remains a formidable challenge. Constructing theoretical models and numerical methods often involves the design and optimization of parameters. While gradient descent methods have been…

Computational Physics · Physics 2026-02-10 Tianbai Xiao

Fast power system state estimation (SE) solution is of paramount importance for achieving real-time decision making in power grid operations. Semidefinite programming (SDP) reformulation has been shown effective to obtain the global optimum…

Signal Processing · Electrical Eng. & Systems 2019-06-20 Yu Lan , Hao Zhu , Xiaohong Guan

We consider a nonlinear variational wave equation that models the dynamics of the director field in nematic liquid crystals with high molecular rotational inertia. Being derived from an energy principle, energy stability is an intrinsic…

Numerical Analysis · Mathematics 2016-03-31 U. Koley , P. Aursand

Numerical schemes that conserve invariants have demonstrated superior performance in various contexts, and several unified methods have been developed for constructing such schemes. However, the mathematical properties of these schemes…

Numerical Analysis · Mathematics 2024-12-23 Shuto Kawai , Shun Sato , Takayasu Matsuo

As an effective emulator of ill-conditioned power flow, continuous Newton methods (CNMs) have been extensively investigated using explicit and implicit numerical integration algorithms. Explicit CNMs are prone to non-convergence issues due…

Systems and Control · Electrical Eng. & Systems 2024-12-02 Ruizhi Yu , Wei Gu , Yijun Xu , Shuai Lu , Suhan Zhang
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