Digitalization is a key focus in
transformation of environmental and process engingeering world in the recent
years. One of the main derivatives of this transformation is the concept of
Digital Twin (DT). DTs are virtual replicas of physical systems that can mimic
the operation of the systems in real-time. Their applications in environmental
context can be for drinking water systems, water resource recovery facilities,
air quality systems, sewer networks, etc. The main elements that characterise a
DT can be different depending on its application and specific objective.
However, some that can be generally mentioned are integration with other parts
of the system, using real-time data, recalibration/validation of the models,
having a two-directional flow of information between models and physical
systems, and being capable of predicting the state of the system for the near
future. DTs can be operation-focused relying on (near) real-time data from the
physical system or they can be used as a discision support tool for design,
planning, construction and investment purposes. On the way of developing DT for
a physical system, some challenges are present that need to be tackled.
Choosing a right level of complexity for the models (mechanistic, data-driven
or hybrid models) , data requirements and their quality, handling
uncertainties, automatic model calibration/validation, trust in operational
staff and managers to use and rely on DTs, are some examples of these
challenges. This session will focus on DTs and their applications to
environmental systems. It emphasizes on real case applications of DT for
different environmental sectors (e.g. drinking water, wastewater, air quality,
etc.) and on the attempts to overcome the existing challenges for DT
development.