Author(s): Milos Milasinovic; Zeljko Vasilic; Veljko Prodanovic
Linked Author(s):
Keywords: Sensor data; Simulation models; Virtual risk assessment; System underperformance detection
Abstract: Urban Drainage System (UDS) asset management faces growing challenges from climate change, ageing infrastructure, financial constraints, and workforce shortages. Digital Twins (DTs) offer a promising solution by combining sensor data and simulation models to deliver real-time system assessment and virtual risk analysis. However, reliable operation requires integrating localized sensor information with uncertain model predictions. This paper presents a fast, physically interpretable data assimilation approach that updates model states, boundary conditions, and parameters to detect system underperformance and localize critical hotspots, enhancing the functionality and decision-support capabilities of dynamic DTs.
Year: 2026