Digital Twin
Virtual replicas for enhanced system understanding and optimization
What is a digital twin?
According to the National Research Council's NASA space technology roadmaps and priorities report (2012):
A Digital Twin is an integrated multiphysics, multiscale simulation of a vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to mirror the life of its corresponding flying twin. The Digital Twin is ultra-realistic and may consider one or more important and interdependent vehicle systems, including propulsion/energy storage, avionics, life support, vehicle structure, thermal management/TPS, etc.
In essence, a digital twin is a virtual representation of a physical object or system that serves as a real-time digital counterpart, enabling simulation, analysis, and optimization.
Our Research Contributions
BAC-Bench is our co-simulation environment for benchmarking the performance of Building Automation and Control Systems (BACS). At its core, BAC-Bench is a calibrated EnergyPlus model of the living lab UMAR (Urban Mining and Recycling) at NEST, Empa.
Key Features of Our Digital Twin Framework
- Real-time data integration from sensors and building management systems
- Predictive modeling for energy consumption and comfort parameters
- Optimization algorithms for control strategy development
- Decision support tools for building operators and energy managers
Applications
Our digital twin technology provides valuable insights for:
- Reducing building energy consumption
- Optimizing renewable energy integration
- Improving occupant comfort
- Predictive maintenance of building systems
- Testing control strategies before implementation
Open Source Contributions
We're committed to advancing the field through open collaboration. Visit our GitHub repository for open-source tools and frameworks we've developed for digital twin implementation.