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Projection-based model reduction has become a popular approach to reduce the cost associated with integrating large-scale dynamical systems so they can be used in many-query settings such as optimization and uncertainty quantification. For…

Numerical Analysis · Mathematics 2020-08-26 Han Gao , Jian-Xun Wang , Matthew J. Zahr

This paper proposes an active model-based fault and failure tolerant control scheme for a class of marine vehicles with thruster redundancy. Unlike widely used state and parameter estimation methods, where the estimation errors are utilized…

Systems and Control · Electrical Eng. & Systems 2025-02-03 Ji-Hong Li , Hyungjoo Kang , Min-Gyu Kim , Mun-Jik Lee , Han-Sol Jin , Gun Rae Cho

In time-limited model order reduction, a reduced-order approximation of the original high-order model is obtained that accurately approximates the original model within the desired limited time interval. Accuracy outside that time interval…

Systems and Control · Electrical Eng. & Systems 2022-12-19 Umair Zulfiqar , Xin Du , Qiuyan Song , Zhi-Hua Xiao , Victor Sreeram

We present a framework that relates preconditioning with a posteriori error estimates in finite element methods. In particular, we use standard tools in subspace correction methods to obtain reliable and efficient error estimators. As a…

Numerical Analysis · Mathematics 2020-10-13 Yuwen Li , Ludmil Zikatanov

Scientific and engineering problems often involve parametric partial differential equations (PDEs), such as uncertainty quantification, optimizations, and inverse problems. However, solving these PDEs repeatedly can be prohibitively…

Numerical Analysis · Mathematics 2023-07-04 Jun Sur Richard Park , Xueyu Zhu

In dynamical system theory, the process of obtaining a reduced-order approximation of the high-order model is called model order reduction. The closeness of the reduced-order model to the original model is generally gauged by using system…

Systems and Control · Electrical Eng. & Systems 2023-03-07 Umair Zulfiqar , Xin Dua , Qiuyan Song , Muwahida Liaquat , Victor Sreeram

State estimation is key to both analyzing physical mechanisms and enabling real-time control of fluid flows. A common estimation approach is to relate sensor measurements to a reduced state governed by a reduced-order model (ROM). (When…

Fluid Dynamics · Physics 2020-06-10 Nirmal J. Nair , Andres Goza

In this article, goal-oriented a posteriori error estimation for the biharmonic plate bending problem is considered. The error for approximation of goal functional is represented by an estimator which combines dual-weighted residual method…

Numerical Analysis · Mathematics 2021-07-15 Gouranga Mallik

We derive globally reliable a posteriori error estimators for a PDE-constrained optimization problem involving linear models in fluid dynamics as state equation; control constraints are also considered. The corresponding local error…

Numerical Analysis · Mathematics 2017-08-03 Alejandro Allendes , Enrique Otarola , Richard Rankin

We develop and analyze a posteriori error estimators for a proper orthogonal decomposition-discrete empirical interpolation method (Pod-Deim) reduced order model applied to a parametric Poisson equation posed on a parameter-dependent domain…

Numerical Analysis · Mathematics 2026-04-24 Efthymios N. Karatzas

We develop the \textit{a posteriori} error analysis of three mixed finite element formulations for rotation-based equations in elasticity, poroelasticity, and interfacial elasticity-poroelasticity. The discretisations use $H^1$-conforming…

Numerical Analysis · Mathematics 2021-06-18 VerÓnica Anaya , Arbaz Khan , David Mora , Ricardo Ruiz-Baier

In this paper, we study two residual-based a posteriori error estimators for the $C^0$ interior penalty method in solving the biharmonic equation in a polygonal domain under a concentrated load. The first estimator is derived directly from…

Numerical Analysis · Mathematics 2024-08-29 Huihui Cao , Yunqing Huang , Nianyu Yi , Peimeng Yin

This paper introduces a novel data-driven convergence booster that not only accelerates convergence but also stabilizes solutions in cases where obtaining a steady-state solution is otherwise challenging. The method constructs a…

Fluid Dynamics · Physics 2025-04-09 Xukun Wang , Yilang Liu , Xiang Yang , Weiwei Zhang

We consider mixed finite element approximation of a singularly perturbed fourth-order elliptic problem with two different boundary conditions, and present a new measure of the error, whose components are balanced with respect to the…

Numerical Analysis · Mathematics 2016-09-16 Shaohong Du , Runchang Lin , Zhimin Zhang

In this paper, we develop data-driven closure/correction terms to increase the pressure and velocity accuracy of reduced order models (ROMs) for fluid flows. Specifically, we propose the first pressure-based data-driven variational…

Numerical Analysis · Mathematics 2023-01-25 Anna Ivagnes , Giovanni Stabile , Andrea Mola , Traian Iliescu , Gianluigi Rozza

We derive a residual-based $hp$-a posteriori error estimator for hybrid high-order (HHO) methods on simplicial meshes applied to the biharmonic problem posed on two- and three-dimensional polytopal Lipschitz domains. The a posteriori error…

Numerical Analysis · Mathematics 2026-02-09 Zhaonan Dong , Alexandre Ern , Tanvi Wadhawan

Residual-based a~posteriori error estimators are derived for the modified Morley FEM, proposed by Wang, Xu, Hu [J. Comput. Math, 24(2), 2006], for the singularly perturbed biharmonic equation and the nonlinear von K\'arm\'an equations. The…

Numerical Analysis · Mathematics 2026-02-17 A. K. Dond , D. Gallistl , S. Nayak , M. Schedensack

A posteriori error estimators for the symmetric mixed finite element methods for linear elasticity problems of Dirichlet and mixed boundary conditions are proposed. Stability and efficiency of the estimators are proved. Finally, we provide…

Numerical Analysis · Mathematics 2017-05-12 Long Chen , Jun Hu , Xuehai Huang , Hongying Man

In this article, a posteriori error analysis of the elliptic obstacle problem is addressed using hybrid high-order methods. The method involve cell unknowns represented by degree-$r$ polynomials and face unknowns represented by degree-$s$…

Numerical Analysis · Mathematics 2024-05-09 Kamana Porwal , Ritesh Singla

An adaptive scheme to generate reduced-order models for parametric nonlinear dynamical systems is proposed. It aims to automatize the POD-Greedy algorithm combined with empirical interpolation. At each iteration, it is able to adaptively…

Numerical Analysis · Mathematics 2021-10-13 Sridhar Chellappa , Lihong Feng , Peter Benner