collaborators

11 papers

math.OC2026

Benchmark cases for gradient-based optimization in linear elastic solid mechanics using lattice Boltzmann methods

Johannes L. Grafen, Florian Kaiser, Stephan Simonis +2

Gradient-based optimization (GBO) of problems constrained by partial differential equations is central to parameter identification and structural design in solid mechanics. Lattice…

physics.flu-dyn2026

A Scalable OpenLB LAMMPS Framework for Fully Resolved Simulations of Hindered Settling of Arbitrary Non-Spherical Particles

Varghese Babu, Adrian Kummerländer, Mathias J. Krause +2

Hindered settling of non spherical particles remains significantly less understood than spherical particles due to the computational challenges in resolving the complex contact mec…

physics.flu-dyn2026

Mean-Flow Adjoint Sensitivity Analysis of Unsteady Flow Around Porous Cylinders Using a Homogenized Lattice Boltzmann Method

Shota Ito, Johannes L. Grafen, Fedor Bukreev +2

Adjoint-based sensitivity analysis is an indispensable tool for large-scale fluid-dynamic design and distributed control problems, yet its application to unsteady and turbulent flo…

physics.flu-dyn2025

Efficient Wall-Modelled Large Eddy Simulation of Rotors using Homogenized Lattice Boltzmann Methods

Adrian Kummerländer, Shota Ito, Maximilian Schecher +4

Accurately capturing the dynamic forces acting on rotors as well as their wake effects presents a significant challenge for computational fluid dynamics (CFD) due to high Reynolds…

physics.flu-dyn2025

Uncertain data assimilation for urban wind flow simulations with OpenLB-UQ

Mingliang Zhong, Dennis Teutscher, Adrian Kummerländer +3

Accurate prediction of urban wind flow is essential for urban planning, pedestrian safety, and environmental management. Yet, it remains challenging due to uncertain boundary condi…

physics.flu-dyn2025

OpenLB-UQ: An Uncertainty Quantification Framework for Incompressible Fluid Flow Simulations

Mingliang Zhong, Adrian Kummerländer, Shota Ito +3

Uncertainty quantification (UQ) is crucial in computational fluid dynamics to assess the reliability and robustness of simulations, given the uncertainties in input parameters. Ope…

physics.flu-dyn2025

Analytical solution for dynamic evaporation of liquid in isothermal condition

Luiz Eduardo Czelusniak, Tim Niklas Bingert, Stephan Simonis +2

An analytical solution based on a diffuse interface model is presented for an isothermal evaporation problem under sub-saturation pressure. The macroscopic equations are derived fr…

physics.flu-dyn2025

On the consistency of pseudo-potential lattice Boltzmann methods

Luiz Eduardo Czelusniak, Tim Niklas Bingert, Mathias J. Krause +1

We derive the partial differential equation (PDE) to which the pseudo-potential lattice Boltzmann method (P-LBM) converges under diffusive scaling, providing a rigorous basis for i…

physics.flu-dyn2025

On the range of validity of parabolic models for fluid flow through isotropic homogeneous porous media

Davide Dapelo, Stephan Simonis, Mohaddeseh Mousavi Nezhad +2

Lattice-Boltzmann methods are established mesoscopic numerical schemes for fluid flow, that recover the evolution of macroscopic quantities (viz., velocity and pressure fields) evo…

cs.LG2025

Predicting Filter Medium Performances in Chamber Filter Presses with Digital Twins Using Neural Network Technologies

Dennis Teutscher, Tyll Weber-Carstanjen, Stephan Simonis +1

Efficient solid-liquid separation is crucial in industries like mining, but traditional chamber filter presses depend heavily on manual monitoring, leading to inefficiencies, downt…

physics.soc-ph2025

A Digital Urban Twin Enabling Interactive Pollution Predictions and Enhanced Planning

Dennis Teutscher, Fedor Bukreev, Adrian Kummerlaender +5

Digital twin (DT) technology is increasingly used in urban planning, leveraging real-time data integration for environmental monitoring. This paper presents an urban-focused DT tha…