activity
20242026
collaborators

5 papers

cs.CE2026

From Perception to Autonomous Computational Modeling: A Multi-Agent Approach

Daniel N. Wilke

We present a solver-agnostic framework in which coordinated large language model (LLM) agents autonomously execute the complete computational mechanics workflow, from perceptual da…

cs.LG2026

Towards a data-scale independent regulariser for robust sparse identification of non-linear dynamics

Jay Raut, Daniel N. Wilke, Stephan Schmidt

Data normalisation, a common and often necessary preprocessing step in engineering and scientific applications, can severely distort the discovery of governing equations by magnitu…

cond-mat.soft2025

Towards scientific machine learning for granular material simulations -- challenges and opportunities

Marc Fransen, Andreas Fürst, Deepak Tunuguntla +21

Micro-scale mechanisms, such as inter-particle and particle-fluid interactions, govern the behaviour of granular systems. While particle-scale simulations provide detailed insights…

eess.SY2025

Design for Sensing and Digitalisation (DSD): A Modern Approach to Engineering Design

Daniel N. Wilke

This paper introduces Design for Sensing and Digitalisation (DSD), a new engineering design paradigm that integrates sensor technology for digitisation and digitalisation from the…

eess.SP2024

Generalised envelope spectrum-based signal-to-noise objectives: Formulation, optimisation and application for gear fault detection under time-varying speed conditions

Stephan Schmidt, Daniel N. Wilke, Konstantinos C. Gryllias

In vibration-based condition monitoring, optimal filter design improves fault detection by enhancing weak fault signatures within vibration signals. This process involves optimisin…