78 citations · 99 across the 16 of their papers we have counts for
16 papers
Sparsity-Driven Source Localization in Tomographic Sensing Applications
Marco Mattuschka, Noah An der Lan, Stefanie Schröder +3
Hyperspectral standoff detection systems such as Focal Plane Array (FPA) Fourier Transform Infrared (FTIR) spectrometers provide high spatial resolution in detecting airborne chemi…
Physics-Informed Sensitivity Analysis for Enhanced Structural Health Assessment: Test-Case for a Mixed Steel-Concrete Bridge
Jacopo Bonari, Francesca Marsili, Max von Danwitz +1
Bridges are vital components of transportation systems, that serve as essential links ensuring the safe and efficient movement of people, goods, and emergency responders, especiall…
High-Fidelity Numerical Modeling for the Mechanical Characterization of a Full-Scale Test Bridge
Jacopo Bonari, Max von Danwitz, Alexander Popp
Bridges are vital components of transportation networks, serving as critical lifelines that ensure the safe and efficient movement of people, goods, and emergency services. With ag…
Towards Interpretable Damage Detection based on Aerodynamic Pressure Measurements
Philip Franz, Max von Danwitz, Gregory Duthé +2
The increasing flexibility of modern large wind turbine blades necessitates cost-efficient and reliable structural monitoring solutions. For this purpose, we propose to use aerodyn…
Rapid Identification of Moving Contaminant Sources Through Physics-Based Modelling
Marco Mattuschka, Jacopo Bonari, Max von Danwitz +1
In an act of sabotage or terrorism, hazardous material might be released deliberately into the atmosphere to threaten individuals, e.g., those operating critical infrastructure. Ha…
Experimental and Numerical Study of the Transient Response of a Cantilever Beam with a Piezoelectric Disc Sensor
Radek Kolman, Robert Cimrman, Ladislav Musil +6
Online and real-time sensing and monitoring of the health state of complex structures, such as aircraft and critical components of power stations, are essential aspects of research…
Intrusive and Non-Intrusive Model Order Reduction for Airborne Contaminant Transport: Comparative Analysis and Uncertainty Quantification
Lisa Kühn, Jacopo Bonari, Max von Danwitz +1
Numerical simulations of contaminant dispersion after a gas leakage incident at a chemical plant can provide valuable insights for both emergency response and preparedness. High-fi…
Sparse Source Identification in Transient Advection-Diffusion Problems with a Primal-Dual-Active-Point Strategy
Marco Mattuschka, Daniel Walter, Max von Danwitz +1
This work presents a mathematical model to enable rapid prediction of airborne contaminant transport based on scarce sensor measurements. The method is designed for applications in…
Goal-oriented optimal sensor placement for PDE-constrained inverse problems in crisis management
Marco Mattuschka, Noah An der Lan, Max von Danwitz +2
This paper presents a novel framework for goal-oriented optimal static sensor placement and dynamic sensor steering in PDE-constrained inverse problems, utilizing a Bayesian approa…
Data-Driven Surrogate Modeling Techniques to Predict the Effective Contact Area of Rough Surface Contact Problems
Tarik Sahin, Jacopo Bonari, Sebastian Brandstaeter +1
The effective contact area in rough surface contact plays a critical role in multi-physics phenomena such as wear, sealing, and thermal or electrical conduction. Although accurate…
Physics-Informed Neural Networks for Solving Contact Problems in Three Dimensions
Tarik Sahin, Daniel Wolff, Alexander Popp
This paper explores the application of physics-informed neural networks (PINNs) to tackle forward problems in 3D contact mechanics, focusing on small deformation elasticity. We uti…
Sequential drone routing for data assimilation on a 2D airborne contaminant dispersion problem
Daniele Giovanni Gioia, Jacopo Bonari, Daniel Lichte +1
The combined use of data from different sources can be critical in emergencies, where accurate models are needed to make real-time decisions, but high-fidelity representations and…
Contaminant Dispersion Simulation in a Digital Twin Framework for Critical Infrastructure Protection
Max von Danwitz, Jacopo Bonari, Philip Franz +3
A digital twin framework for rapid predictions of atmospheric contaminant dispersion is developed to support informed decision making in emergency situations. In an offline prepara…
Towards a Hybrid Digital Twin: Physics-Informed Neural Networks as Surrogate Model of a Reinforced Concrete Beam
Tarik Sahin, Daniel Wolff, Max von Danwitz +1
In this study, we investigate the potential of fast-to-evaluate surrogate modeling techniques for developing a hybrid digital twin of a steel-reinforced concrete beam, serving as a…
Towards Real-Time Urban Physics Simulations with Digital Twins
Jacopo Bonari, Lisa Kühn, Max von Danwitz +1
Urban populations continue to grow, highlighting the critical need to safeguard civilians against potential disruptions, such as dangerous gas contaminant dispersion. The digital t…
Solving Forward and Inverse Problems of Contact Mechanics using Physics-Informed Neural Networks
T. Sahin, M. von Danwitz, A. Popp
This paper explores the ability of physics-informed neural networks (PINNs) to solve forward and inverse problems of contact mechanics for small deformation elasticity. We deploy P…