activity
20242026
most citedData-Driven Surrogate Modeling Techniques to Predict the Effective Contact Area of Rough Surface Contact Problems

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

math.NA2026

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…

cs.CE20251 cited

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…

cs.CE2025

Solving adhesive rough contact problems with Atomic Force Microscope data

Maria Rosaria Marulli, Jacopo Bonari, Pasqualantonio Pingue +1

This study presents an advanced numerical framework that integrates experimentally acquired Atomic Force Microscope (AFM) data into high-fidelity simulations for adhesive rough con…

cs.CE2025

A computational framework for evaluating tire-asphalt hysteretic friction including pavement roughness

Ivana Ban, Jacopo Bonari, Marco Paggi

Pavement surface textures obtained by a photogrammetry-based method for data acquisition and analysis are employed to investigate if related roughness descriptors are comparable to…

eess.SY2024

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…

cs.CE2024

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…