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The Numerical Assembly Technique is extended to investigate arbitrary planar frame structures with the focus on the computation of natural frequencies. This allows us to obtain highly accurate results without resorting to spatial…

Numerical Analysis · Mathematics 2022-04-26 Thomas Kramer , Michael Helmut Gfrerer

In this paper the simplicial cone constrained convex quadratic programming problem is studied. The optimality conditions of this problem consist in a linear complementarity problem. This fact, under a suitable condition, leads to an…

Optimization and Control · Mathematics 2015-03-11 J. G. Barrios , O. P. Ferreira , S. Z. Németh

We propose Newton-PIPG, an efficient method for solving quadratic programming (QP) problems arising in optimal control, subject to additional set constraints. Newton-PIPG integrates the Proportional-Integral Projected Gradient (PIPG) method…

Optimization and Control · Mathematics 2025-03-31 Dayou Luo , Yue Yu , Maryam Fazel , Behçet Açıkmeşe

Nowadays, analysing data from different classes or over a temporal grid has attracted a great deal of interest. As a result, various multiple graphical models for learning a collection of graphical models simultaneously have been derived by…

Optimization and Control · Mathematics 2021-04-23 Ning Zhang , Yangjing Zhang , Defeng Sun , Kim-Chuan Toh

The solidification and macro-segregation problem involving unsteady multi-physics and multi-phase fields is typically a complex process with mass, momentum, heat, and species transfers among solid, mushy, and liquid phase regions. The…

Fluid Dynamics · Physics 2023-03-21 Xiaoyu Feng , Huangxin Chen , Bo Yu , Shuyu Sun

In this article, we introduce a new class of coupled fractional Lane-Emden boundary value problems. We employ a novel approach, the fractional Haar wavelet collocation method with the Newton-Raphson method. We analyze the conditions in two…

General Mathematics · Mathematics 2025-07-02 Lok Nath Kannaujiya , Narendra Kumar , Amit K. Verma

Complex soft matter systems can be efficiently studied with the help of adaptive resolution simulation methods, concurrently employing two levels of resolution in different regions of the simulation domain. The non-matching properties of…

We introduce an inertial quasi-Newton Forward-Backward Splitting Algorithm to solve a class of monotone inclusion problems. While the inertial step is computationally cheap, in general, the bottleneck is the evaluation of the resolvent…

Optimization and Control · Mathematics 2024-03-18 Shida Wang , Jalal Fadili , Peter Ochs

We present the numerical methods and GPU-accelerated implementation underlying a Total Lagrangian finite element framework for finite-deformation flexible multibody dynamics, introduced in the companion paper [1]. The framework supports…

Computational Engineering, Finance, and Science · Computer Science 2026-05-04 Zhenhao Zhou , Ruochun Zhang , Ganesh Arivoli , Dan Negrut

We review a scalable two- and three-dimensional computer code for low-temperature plasma simulations in multi-material complex geometries. Our approach is based on embedded boundary (EB) finite volume discretizations of the minimal…

Computational Physics · Physics 2019-05-01 Robert Marskar

Many metal manufacturing processes involve phase change phenomena, which include melting, boiling, and vaporization. These phenomena often occur concurrently. A prototypical 1D model for understanding the phase change phenomena is the…

Materials Science · Physics 2026-02-11 Yavkreet Swami , Jacob Barajas , Amneet Pal Singh Bhalla

In this paper, we introduce a novel parallel contact algorithm designed to run efficiently in High-Performance Computing based supercomputers. Particular emphasis is put on its computational implementation in a multiphysics finite element…

Computational Engineering, Finance, and Science · Computer Science 2022-08-02 G. Guillamet , M. Rivero , M. Zavala-Aké , M. Vázquez , G. Houzeaux , S. Oller

Many learning problems involve multiple agents optimizing different interactive functions. In these problems, the standard policy gradient algorithms fail due to the non-stationarity of the setting and the different interests of each agent.…

Machine Learning · Computer Science 2021-09-03 Giorgia Ramponi , Marcello Restelli

In this paper, we present a Newton-like method based on model reduction techniques, which can be used in implicit numerical methods for approximating the solution to ordinary differential equations. In each iteration, the Newton-like method…

Numerical Analysis · Mathematics 2023-03-14 Tobias K. S. Ritschel

In this paper, we introduce a quasi-Newton method optimized for efficiently solving quasi-linear elliptic equations and systems, with a specific focus on GPU-based computation. By approximating the Jacobian matrix with a combination of…

Numerical Analysis · Mathematics 2025-03-25 Wenrui Hao , Sun Lee , Xiangxiong Zhang

Simulating large-scale articulated assemblies poses a significant challenge due to the numerical stiffness and geometric complexity of jointed structures. Conventional rigid body solvers struggle with the high nonlinearity induced by…

We are concerned with structured $\ell_0$-norms regularization problems, with a twice continuously differentiable loss function and a box constraint. This class of problems have a wide range of applications in statistics, machine learning…

Optimization and Control · Mathematics 2023-12-27 Yuqia Wu , Shaohua Pan , Xiaoqi Yang

The rotated multipliers method is performed in the case of the boundary stabilization by means of a(linear or non-linear) Neumann feedback. this method leads to new geometrical cases concerning the "active" part of the boundary where the…

Optimization and Control · Mathematics 2011-11-11 Pierre Cornilleau , Jean-Pierre Loheac , Axel Osses

In contact mechanics computation, the constraint conditions on the contact surfaces are typically enforced by the Lagrange multiplier method, resulting in a saddle point system. The mortar finite element method is usually employed to…

Numerical Analysis · Mathematics 2024-09-24 Xiaoyu Duan , Hengbin An , Zeyao Mo

Solving nonlinear partial differential equations (PDEs) with multiple solutions using neural networks has found widespread applications in various fields such as physics, biology, and engineering. However, classical neural network methods…

Machine Learning · Computer Science 2024-05-24 Wenrui Hao , Xinliang Liu , Yahong Yang