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In this work, a multirate in time approach resolving the different time scales of a convection-dominated transport and coupled fluid flow is developed and studied in view of goal-oriented error control by means of the Dual Weighted Residual…

Numerical Analysis · Mathematics 2022-12-09 Marius Paul Bruchhäuser , Uwe Köcher , Markus Bause

In this work, a flexible higher-order space-time adaptive finite element approximation of convection-dominated transport with coupled fluid flow is developed and studied. Convection-dominated transport is a challenging subproblem in…

Numerical Analysis · Mathematics 2021-02-26 Markus Bause , Marius Paul Bruchhäuser , Uwe Köcher

This work presents a numerical investigation of different approximation techniques for the temporal weights used in the Dual Weighted Residual (DWR) method applied to a time-dependent convection-diffusion equation which is assumed to be…

Numerical Analysis · Mathematics 2024-07-19 Marius Paul Bruchhäuser , Markus Bause

The cost- and memory-efficient numerical simulation of coupled volume-based multi-physics problems like flow, transport, wave propagation and others remains a challenging task with finite element method (FEM) approaches. Goal-oriented space…

Mathematical Software · Computer Science 2019-05-01 Uwe Köcher , Marius Paul Bruchhäuser , Markus Bause

In this work, we present an anisotropic multi-goal error control based on the Dual Weighted Residual (DWR) method for time-dependent convection-diffusion-reaction (CDR) equations. This multi-goal oriented approach allows for an accurate and…

We present an anisotropic goal-oriented error estimator based on the Dual Weighted Residual (DWR) method for time-dependent convection-dominated problems. Using elementwise p-anisotropic finite element spaces, the estimator is elementwise…

Numerical Analysis · Mathematics 2026-02-17 Nils Margenberg , Marius Paul Bruchhäuser , Bernhard Endtmayer

Even though substantial progress has been made in the numerical approximation of convection-dominated problems, its major challenges remain in the scope of current research. In particular, parameter robust a posteriori error estimates for…

Numerical Analysis · Mathematics 2022-12-15 Marius Paul Bruchhäuser , Kristina Schwegler , Markus Bause

The efficient and reliable approximation of convection-dominated problems continues to remain a challenging task. To overcome the difficulties associated with the discretization of convection-dominated equations, stabilization techniques…

Numerical Analysis · Mathematics 2022-12-15 Marius Paul Bruchhäuser , Kristina Schwegler , Markus Bause

This paper introduces a novel framework for model adaptivity in the context of heterogeneous multiscale problems. The framework is based on the idea to interpret model adaptivity as a minimization problem of local error indicators, that are…

Numerical Analysis · Mathematics 2017-12-04 Matthias Maier , Rolf Rannacher

We present an anisotropic goal-oriented error estimator based on the Dual Weighted Residual (DWR) method for time-dependent convection-diffusion-reaction (CDR) equations. Using anisotropic interpolation operators the estimator is…

Numerical Analysis · Mathematics 2025-04-22 M. Bause , M. Bruchhäuser , B. Endtmayer , N. Margenberg , I. Toulopoulos , T. Wick

Transportation occupies one-third of the amount in the logistics costs, and accordingly transportation systems largely influence the performance of the logistics system. This work presents an adaptive data-driven innovative modular approach…

Artificial Intelligence · Computer Science 2020-01-08 Emir Zunic , Dzenana Donko , Emir Buza

We consider goal-oriented adaptive space-time finite-element discretizations of the regularized parabolic p-Laplace problem on completely unstructured simplicial space-time meshes. The adaptivity is driven by the dual-weighted residual…

Numerical Analysis · Mathematics 2023-06-13 B. Endtmayer , U. Langer , A. Schafelner

This paper proposes a weight-aware deep reinforcement learning (WADRL) approach designed to address the multiobjective vehicle routing problem with time windows (MOVRPTW), aiming to use a single deep reinforcement learning (DRL) model to…

Artificial Intelligence · Computer Science 2024-07-19 Rixin Wu , Ran Wang , Jie Hao , Qiang Wu , Ping Wang , Dusit Niyato

This chapter describes how a posteriori error estimates targeting a user-defined quantity of interest, using the Dual Weighted Residual (DWR) technique, can be easily applied for biomechanical simulations in current engineering practice.…

Numerical Analysis · Mathematics 2025-11-13 Roland Becker , Franz Chouly , Michel Duprez , Thomas Richter , Pierre-Yves Rohan , Thomas Wick

In this work, the dual-weighted residual method is applied to a space-time formulation of nonstationary Stokes and Navier-Stokes flow. Tensor-product space-time finite elements are being used to discretize the variational formulation with…

Numerical Analysis · Mathematics 2022-10-07 Julian Roth , Jan Philipp Thiele , Uwe Köcher , Thomas Wick

The numerical approximation of convection-dominated problems continues to remain subject of strong interest. Families of stabilization techniques for finite element methods were developed in the past. Adaptive techniques based on a…

Numerical Analysis · Mathematics 2018-03-20 Kristina Schwegler , Marius P. Bruchhäuser , Markus Bause

In this paper we continue our work on adaptive timestep control for weakly non- stationary problems. The core of the method is a space-time splitting of adjoint error representations for target functionals due to S\"uli and Hartmann. The…

Numerical Analysis · Mathematics 2014-06-19 Christina Steiner , Siegfried Müller , Sebastian Noelle

Differential-driven wheeled robots (DWR) represent the quintessential type of mobile robots and find extensive appli- cations across the robotic field. Most high-performance control approaches for DWR explicitly utilize the linear and…

Robotics · Computer Science 2025-11-18 Yong Li , Yujun Huang , Yi Chen , Hui Cheng

In this paper we present distributed and adaptive algorithms for motion coordination of a group of m autonomous vehicles. The vehicles operate in a convex environment with bounded velocity and must service demands whose time of arrival,…

Robotics · Computer Science 2016-11-17 Marco Pavone , Emilio Frazzoli , Francesco Bullo

Large-scale machine learning models are often trained by parallel stochastic gradient descent algorithms. However, the communication cost of gradient aggregation and model synchronization between the master and worker nodes becomes the…

Machine Learning · Computer Science 2020-07-03 Xiaorui Liu , Yao Li , Jiliang Tang , Ming Yan
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