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An optimal guidance method is developed that reduces sensitivity to parameters in the dynamic model. The method combines a previously developed method for guidance and control using adaptive Legendre-Gauss-Radau (LGR) collocation and a…

Optimization and Control · Mathematics 2024-08-09 Katrina L. Winkler , Anil V. Rao

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

We consider a class of parameter-dependent optimal control problems of elliptic PDEs with constraints of general type on the control variable. Applying the concept of variational discretization, [4], together with techniques from the…

Optimization and Control · Mathematics 2018-08-20 Ahmad Ahmad Ali , Michael Hinze

Accurately modeling power distribution grids is crucial for designing effective monitoring and decision making algorithms. This paper addresses the partial observability issue of data-driven distribution modeling in order to improve the…

Signal Processing · Electrical Eng. & Systems 2021-10-08 Shanny Lin , Hao Zhu

The aim of this paper is to examine the large-scale behavior of dynamical optimal transport on stationary random graphs embedded in $\R^n$. Our primary contribution is a stochastic homogenization result that characterizes the effective…

Probability · Mathematics 2025-07-16 Peter Gladbach , Eva Kopfer

This paper studies an optimal control problem governed by a semilinear elliptic equation, in which the control acts in a multiplicative or bilinear way as the reaction coefficient of the equation. We focus on the numerical discretization of…

Optimization and Control · Mathematics 2025-06-25 Eduardo Casas , Konstantinos Chrysafinos , Mariano Mateos

We perform numerical analysis of a nonlinear gradient flow, which can be regarded as a parabolic minimal surface problem or a regularised total variation flow, using the gradient discretisation method (GDM). GDM is a unified convergence…

Numerical Analysis · Mathematics 2026-04-21 Jerome Droniou , Kim-Ngan Le , Huateng Zhu

We consider dynamical systems evolving near an equilibrium statistical state where the interest is in modelling long term behavior that is consistent with thermodynamic constraints. We adjust the distribution using an entropy-optimizing…

Fluid Dynamics · Physics 2014-11-25 Keith Myerscough , Jason Frank , Benedict Leimkuhler

Nonlinear optimal control problems for trajectory planning with obstacle avoidance present several challenges. While general-purpose optimizers and dynamic programming methods struggle when adopted separately, their combination enabled by a…

Optimization and Control · Mathematics 2024-08-09 Rebecca Richter , Alberto De Marchi , Matthias Gerdts

An efficient topology optimization method applicable to both continuum and rarefied gas flows is proposed in the framework of gas-kinetic theory. The areas of gas and solid are marked by the material density, based on which a fictitious…

Fluid Dynamics · Physics 2023-08-15 Ruifeng Yuan , Lei Wu

In this paper, we use tools from sheaf theory to model and analyze optimal network control problems and their associated discrete relaxations. We consider a general problem setting in which pieces of equipment and their causal relations are…

Algebraic Topology · Mathematics 2020-12-02 Griffin M. Kearney , Kevin F. Palmowski , Michael Robinson

The aim of this work is to develop general optimization methods for finite difference schemes used to approximate linear differential equations. The specific case of the transport equation is exposed. In particular, the minimization of the…

Analysis of PDEs · Mathematics 2007-05-23 Claire David , Pierre Sagaut

Gas transport and other complex real-world challenges often require solving and controlling partial differential equations (PDEs) defined on graph structures, which typically demand substantial memory and computational resources. The Random…

Numerical Analysis · Mathematics 2025-06-16 Martín Hernández , Enrique Zuazua

We consider systematic numerical approximation of a viscoelastic phase separation model that describes the demixing of a polymer solvent mixture. An unconditionally stable discretisation method is proposed based on a finite element…

Numerical Analysis · Mathematics 2024-07-08 Aaron Brunk , Herbert Egger , Oliver Habrich , Maria Lukacova-Medvidova

This paper is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are…

Mathematical Finance · Quantitative Finance 2025-07-22 Jinniao Qiu , Antony Ware , Yang Yang

The numerical simulation of complex physical processes requires the use of economical discrete models. This lecture presents a general paradigm of deriving a posteriori error estimates for the Galerkin finite element approximation of…

Numerical Analysis · Mathematics 2025-10-20 Rolf Rannacher

This paper develops a framework connecting discrete adjoint gradient-error analysis with an optimization method that uses directional error tolerances, and applies it to airfoil shape optimization governed by a conservative full-potential…

Optimization and Control · Mathematics 2026-05-19 Humberto Gimenes Macedo , Luís Felipe Bueno

In this paper, an abstract framework for the error analysis of discontinuous finite element method is developed for the distributed and Neumann boundary control problems governed by the stationary Stokes equation with control constraints.…

Numerical Analysis · Mathematics 2021-11-01 Asha K Dond , Thirupathi Gudi , Ramesh Ch. Sau

In this paper we will consider distributed Linear-Quadratic Optimal Control Problems dealing with Advection-Diffusion PDEs for high values of the P\'eclet number. In this situation, computational instabilities occur, both for steady and…

Numerical Analysis · Mathematics 2024-05-03 Fabio Zoccolan , Maria Strazzullo , Gianluigi Rozza

The aim of this paper is a short survey of models and methods that developed by the authors. These models and methods are used to optimize general networks with nonlinear non-convex restrictions and objectives possessing mixed…

Optimization and Control · Mathematics 2019-11-12 Emmanuel M. Livshits , Leonid A. Ostromuhov