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Topology optimization (TO) provides a principled mathematical approach for optimizing the performance of a structure by designing its material spatial distribution in a pre-defined domain and subject to a set of constraints. The majority of…

Machine Learning · Computer Science 2024-08-08 Amin Yousefpour , Shirin Hosseinmardi , Carlos Mora , Ramin Bostanabad

This paper deals with the applications of stochastic spectral methods for structural topology optimization in the presence of uncertainties. A non-intrusive polynomial chaos expansion is integrated into a topology optimization algorithm to…

Computational Engineering, Finance, and Science · Computer Science 2021-08-04 Nilton Cuellar , Anderson Pereira , Ivan F. M. Menezes , Americo Cunha

In the current industry, the development of optimized mechanical components able to satisfy the customer requirements evolves quickly. Therefore, companies are asked for efficient solutions to improve their products in terms of stiffness…

Computational Engineering, Finance, and Science · Computer Science 2023-07-31 Rafael Merli , Antolín Martínez-Martínez , Juan José Ródenas , Marc Bosch-Galera , Enrique Nadal

We develop and evaluate a numerical procedure for a system of nonlinear differential equations, which describe the propagation of solitons into ideal dielectric optical fibers. This problem has analytical solutions known. The numerical…

Exactly Solvable and Integrable Systems · Physics 2019-04-17 Diogo Albino de Queiroz , Paulo Laerte Natti , Neyva Maria Lopes Romeiro , Érica Regina Takano Natti

Comparing with the classical local gradient flow and phase field models, the nonlocal models such as nonlocal Cahn-Hilliard equations equipped with nonlocal diffusion operator can describe more practical phenomena for modeling phase…

Analysis of PDEs · Mathematics 2019-03-12 Zhengguang liu , Aijie Cheng , Xiaoli Li

In this paper, we propose a new numerical scheme for a spatially discrete model of constrained total variation flows, which are total variation flows whose values are constrained in a Riemannian manifold. The difficulty of this problem is…

Analysis of PDEs · Mathematics 2020-05-05 Yoshikazu Giga , Koya Sakakibara , Kazutoshi Taguchi , Masaaki Uesaka

We consider nonsmooth optimal control problems subject to a linear elliptic partial differential equation with homogeneous Dirichlet boundary conditions. It is well-known that local solutions satisfy the celebrated Pontryagin maximum…

Optimization and Control · Mathematics 2024-06-28 Daniel Wachsmuth

Within this work, we consider optimization settings for nonlinear, nonstationary fluid-structure interaction. The problem is formulated in a monolithic fashion using the arbitrary Lagrangian-Eulerian framework to set-up the fluid-structure…

Numerical Analysis · Mathematics 2020-06-29 Thomas Wick , Winnifried Wollner

Uniform flow distribution across parallel channels directly impacts the performance and efficiency of many fluid and energy systems. However, designing efficient flow manifolds that ensure uniform flow distribution remains a challenge. This…

Fluid Dynamics · Physics 2025-10-06 Sanjay Vermani , Nitish Anand

In this paper, we present an efficient numerical method to address a thermodynamically consistent gas flow model in porous media involving compressible gas and deformable rock. The accurate modeling of gas flow in porous media often poses…

Numerical Analysis · Mathematics 2026-02-16 Huangxin Chen , Yuxiang Chen , Jisheng Kou , Shuyu Sun

Multi-material structural topology and shape optimization problems are formulated within a phase field approach. First-order conditions are stated and the relation of the necessary conditions to classical shape derivatives are discussed. An…

Optimization and Control · Mathematics 2013-12-10 Luise Blank , M. Hassan Farshbaf-Shaker , Harald Garcke , Christoph Rupprecht , Vanessa Styles

In this paper, we present a stochastic augmented Lagrangian approach on (possibly infinite-dimensional) Riemannian manifolds to solve stochastic optimization problems with a finite number of deterministic constraints.We investigate the…

Optimization and Control · Mathematics 2025-04-01 Caroline Geiersbach , Tim Suchan , Kathrin Welker

This paper is devoted to the study of acceleration methods for an inequality constrained convex optimization problem by using Lyapunov functions. We first approximate such a problem as an unconstrained optimization problem by employing the…

Optimization and Control · Mathematics 2024-11-25 Juan Liu , Nan-Jing Huang , Xian-Jun Long , Xue-song Li

We consider model order reduction of parameterized Hamiltonian systems describing nondissipative phenomena, like wave-type and transport dominated problems. The development of reduced basis methods for such models is challenged by two main…

Numerical Analysis · Mathematics 2021-05-27 Cecilia Pagliantini

Optimization, a key tool in machine learning and statistics, relies on regularization to reduce overfitting. Traditional regularization methods control a norm of the solution to ensure its smoothness. Recently, topological methods have…

Machine Learning · Computer Science 2020-11-11 Arnur Nigmetov , Aditi S. Krishnapriyan , Nicole Sanderson , Dmitriy Morozov

In this paper, we investigate a distributed optimal control problem for a convective viscous Cahn-Hilliard system with dynamic boundary conditions. Such systems govern phase separation processes between two phases taking place in an…

Analysis of PDEs · Mathematics 2017-09-13 Pierluigi Colli , Gianni Gilardi , Jürgen Sprekels

A common problem in the optimization of structures is the handling of uncertainties in the parameters. If the parameters appear in the constraints, the uncertainties can lead to an infinite number of constraints. Usually the constraints…

Optimization and Control · Mathematics 2012-05-01 Daniel P. Mohr , Ina Stein , Thomas Matzies , Christina A. Knapek

Invariant solutions of the Navier-Stokes equations play an important role in the spatiotemporally chaotic dynamics of turbulent shear flows. Despite the significance of these solutions, their identification remains a computational…

Fluid Dynamics · Physics 2023-10-11 Omid Ashtari , Tobias M. Schneider

In this paper we present a novel approach to the geometric formulation of solid and fluid mechanics within the port-Hamiltonian framework, which extends the standard Hamiltonian formulation to non-conservative and open dynamical systems.…

Mathematical Physics · Physics 2024-04-19 Ramy Rashad , Stefano Stramigioli

We introduce a finite-volume numerical scheme for solving stochastic gradient-flow equations. Such equations are of crucial importance within the framework of fluctuating hydrodynamics and dynamic density functional theory. Our proposed…