The Digital Twin Lab is active in the following research, educational and collaborative activities

Research and scientific activities

• Research into computational modelling, including parametric modelling, computational fluid dynamics (CFD), computational structural mechanics (CSM), coupled multiphysics simulations and physics-informed machine learning.
• Research into data curation, processing, analysis, and inference. Development and application of statistical and machine learning models, including for work with big data
• Digital twin interface creation – data fusion and data assimilation. Development of advanced data sharing and data space protocols and connectors.
• Research into verification, validation, uncertainty quantification and reduced order modelling.
• Geometry and computational mesh generation, preparation, cleaning, and manipulation, and CAD modelling for simulation.

Educational activities

• Masters-level courses in data science and machine learning, as part of the Big Data Masters programme.
• Physics-based modelling internships and training courses for industry professionals.

Services and Equipment

The Digital Twin Lab offers a variety of services, enabled by its high-performance computational infrastructure. Equipment, including access to the computing infrastructure as a service, can be made available, subject to use cases assessment by the Digital Twin Lab manager and principal scientist.

Services

• On-demand digital twin concept-to-implementation consultations and custom solutions for academic, industrial and governmental stakeholders
• Design and execution of physics- and data-based modelling, simulation and analysis for the business – multiphysics simulations, reduced order modelling, data analysis, predictive modelling, and visualization.
• Simulation-based design services – model construction, simulation, design under uncertainty – design of experiments, verification and validation, sensitivity analysis, model calibration, optimisation.
• Testing and evaluation of external physics- and data-based models.
• Human-machine interaction analyses – contact GATE’s Digital Health Lab for a detailed feasibility evaluation of your request
• Smart city and intelligent urban development analyses and simulation – contact GATE’s City Living Lab for more information on your case.

Equipment

• DJI Matric 300 RTK unmanned aerial system, with photogrammetric (DJI P1) and thermal/zoom (DJI H20T) cameras and LiDAR (DJI L1) sensor
• Indoor air quality measurement equipment –Testo 440 – a universal device for measuring HVAC, indoor comfort and air quality parameters. The device is equipped with a built-in sensor for absolute and differential pressure, temperature sensors, a turbulence probe, CO₂ probe, a high-precision vane probe head, and a Testovent 417 funnel set for fitting plate outlets and fans.