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This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

Fluid Dynamics · Physics 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

Differentiable programming is revolutionizing computational science by enabling automatic differentiation (AD) of numerical simulations. While first-order gradients are well-established, second-order derivatives (Hessians) for implicit…

Computational Engineering, Finance, and Science · Computer Science 2025-05-20 Tianju Xue

Stabilised mixed velocity-pressure formulations are one of the widely-used finite element schemes for computing the numerical solutions of laminar incompressible Navier-Stokes. In these formulations, the Newton-Raphson scheme is employed to…

Computational Engineering, Finance, and Science · Computer Science 2020-07-15 Chennakesava Kadapa , Wulf G Dettmer , Djordje Peric

We study monotone P1 finite element methods on unstructured meshes for fully non-linear, degenerately parabolic Isaacs equations with isotropic diffusions arising from stochastic game theory and optimal control and show uniform convergence…

Numerical Analysis · Mathematics 2021-05-07 Bartosz Jaroszkowski , Max Jensen

Many recent studies on first-order methods (FOMs) focus on \emph{composite non-convex non-smooth} optimization with linear and/or nonlinear function constraints. Upper (or worst-case) complexity bounds have been established for these…

Optimization and Control · Mathematics 2025-05-14 Wei Liu , Qihang Lin , Yangyang Xu

This paper develops a computational framework with unfitted meshes to solve linear piezoelectricity and flexoelectricity electromechanical boundary value problems including strain gradient elasticity at infinitesimal strains. The high-order…

Numerical Analysis · Mathematics 2020-10-08 David Codony , Onofre Marco , Sonia Fernández-Méndez , Irene Arias

In this work we derive a second-order approach to bilevel optimization, a type of mathematical programming in which the solution to a parameterized optimization problem (the "lower" problem) is itself to be optimized (in the "upper"…

Optimization and Control · Mathematics 2022-05-06 Robert Dyro , Edward Schmerling , Nikos Arechiga , Marco Pavone

This paper presents a one-sided immersed boundary (IB) method using kernel functions constructed via a moving least squares (MLS) method. The resulting kernels effectively couple structural degrees of freedom to fluid variables on only one…

Numerical Analysis · Mathematics 2021-05-27 Rahul Bale , Amneet Pal Singh Bhalla , Boyce E. Griffith , Makoto Tsubokura

This paper presents the design and analysis of a Hybrid High-Order (HHO) approximation for a distributed optimal control problem governed by the Poisson equation. We propose three distinct schemes to address unconstrained control problems…

Numerical Analysis · Mathematics 2025-01-14 Gouranga Mallik , Ramesh Chandra Sau

Meshing of geometric domains having curved boundaries by affine simplices produces a polytopial approximation of those domains. The resulting error in the representation of the domain limits the accuracy of finite element methods based on…

Numerical Analysis · Mathematics 2018-02-09 James Cheung , Mauro Perego , Pavel Bochev , Max Gunzburger

We explore a new way to handle flux boundary conditions imposed on level sets. The proposed approach is a diffuse interface version of the shifted boundary method (SBM) for continuous Galerkin discretizations of conservation laws in…

Numerical Analysis · Mathematics 2022-05-11 Dmitri Kuzmin , Jan-Phillip Bäcker

Standard gradient descent methods are susceptible to a range of issues that can impede training, such as high correlations and different scaling in parameter space.These difficulties can be addressed by second-order approaches that apply a…

Machine Learning · Computer Science 2020-04-29 Ted Moskovitz , Rui Wang , Janice Lan , Sanyam Kapoor , Thomas Miconi , Jason Yosinski , Aditya Rawal

We present a novel deep learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. These systems arise from many problems in applied science, e.g., in numerical methods for…

Machine Learning · Computer Science 2022-10-04 Ayano Kaneda , Osman Akar , Jingyu Chen , Victoria Kala , David Hyde , Joseph Teran

We study stochastic optimization from a joint continuous-discrete point of view. Starting from a second-order stochastic differential equation interpreted as a noisy accelerated gradient flow, we discretize the dynamics by a fully implicit…

Optimization and Control · Mathematics 2026-05-07 Valentin Leplat , Roland Hildebrand

Quadratic programming is a workhorse of modern nonlinear optimization, control, and data science. Although regularized methods offer convergence guarantees under minimal assumptions on the problem data, they can exhibit the slow…

Optimization and Control · Mathematics 2026-05-18 Jeremy Bertoncini , Alberto De Marchi , Matthias Gerdts , Simon Gottschalk

Robust, broadly applicable fluid-structure interaction (FSI) algorithms remain a challenge for computational mechanics. In previous work, we introduced an immersed interface method (IIM) for discrete surfaces and an extension based on an…

Computational Physics · Physics 2025-11-14 Qi Sun , Ebrahim M. Kolahdouz , Boyce E. Griffith

First-order methods have been popularly used for solving large-scale problems. However, many existing works only consider unconstrained problems or those with simple constraint. In this paper, we develop two first-order methods for…

Optimization and Control · Mathematics 2017-11-23 Yangyang Xu

A fourth-order finite volume embedded boundary (EB) method is presented for the unsteady Stokes equations. The algorithm represents complex geometries on a Cartesian grid using EB, employing a technique to mitigate the "small cut-cell"…

Numerical Analysis · Mathematics 2022-09-08 Nathaniel Overton-Katz , Xinfeng Gao , Stephen Guzik , Oscar Antepara , Daniel T. Graves , Hans Johansen

In this paper, we study the iteration complexity of cubic regularization of Newton method for solving composite minimization problems with uniformly convex objective. We introduce the notion of second-order condition number of a certain…

Optimization and Control · Mathematics 2021-05-21 Nikita Doikov , Yurii Nesterov

A discrete unified gas kinetic scheme (DUGKS) coupled with the immersed boundary (IB) method is developed to perform interface-resolved simulation of particle-laden flows. The present method (IB-DUGKS) preserves the respective advantages of…

Fluid Dynamics · Physics 2018-10-17 Shi Tao , Haolong Zhang , Zhaoli Guo , Lian-Ping Wang