Nikolaj T. Mücke

Integrating score-based diffusion models with machine learning-enhanced localization for advanced data assimilation in geological carbon storage

Gabriel Serrão Seabra, Nikolaj T. Mücke, Vinicius Luiz Santos Silva, Alexandre A. Emerick, Denis Voskov, Femke C. Vossepoel

Abstract Accurate characterization of subsurface heterogeneity is important for the safe and effective implementation of geological carbon storage (GCS) projects. This paper explores how machine learning methods can enhance data assimilation for GCS with a framework that integrat…Read more

Machine Learning-Based Digital Twin for Water Distribution Network Anomaly Detection and Localization

Prerna Pandey, Nikolaj T. Mücke, Shashi Jain, Parthasarathy Ramachandran, Sander M. Bohté, Cornelis W. Oosterlee

A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning

Nikolaj T. Mücke, Prerna Pandey, Shashi Jain, Sander M. Bohté, Cornelis W. Oosterlee

Localizing leakages in large water distribution systems is an important and ever-present problem. Due to the complexity originating from water pipeline networks, too few sensors, and noisy measurements, this is a highly challenging problem to solve. In this work, we present a met…Read more