Fluid Dynamics digital twins design and development: Risk Maps

Task 4.3 Fluid Dynamics digital twins design and development: Risk Maps


The technical development has been carried out entirely by ITAINNOVA.

The end-users have supported ITAINNOVA in the definition of the activities according to their interests and needs; MARINI and TAPOJARVI regarding the air quality models, and TITANIA regarding the water quality model. 

Objective and Outcomes

The purpose of this task is to build fluid dynamic RT-DTs for air and water quality. To that end, a CFD methodology is developed and validated with experimental data. Finally, this methodology is used to simulate a large number of different scenarios (a  design of experiments, DoE). The CFD results are then postprocessed with the library developed in T4.4 to build the virtual sensors of each mine (real time digital twins). Those virtual sensors will be integrated in the DecisionSupport System (DSS) of the Dig-IT IoT platform to allow the end-user to see in real time the risk maps on the air/water quality.

The main goal of this WP is to develop RT-DTs of engineering assets, geotechnical and fluid dynamic processes, so this task contributes directly to the achievement of this goal.

Task 5.6 will directly use the outcomes of this task, as the final ROM for each use-case will be integrated and displayed in DSS of the final IoT platform.

What has been done in Task 4.3?

On the one hand, regarding the air quality models from MARINI and KEMI, a CFD methodology has been developed and validated with experimental measurements performed in the real use-cases. In this way, a specific solver for each use case has been developed using the open-source CFD software OpenFOAM, including the appropriate modifications in the code according to the requirements of each mine, regarding heat transfer and buoyancy phenomena, pollutants transport, etc. After that, a Design of Experiments has been designed and run, covering the range of the input variables according to the end-users requirements. Finally, the results of all these simulations have been used in order to build the virtual sensor (ROM), which will be finally implemented in the IoT platform. 

On the other hand, regarding the water quality analysis from TITANIA, a data-based model has been developed in order to predict in real time the relevant pollutants (suspended solids and nickel) released to the environment. For such task, historical data was used in order to generate and train the prediction model generated through Python scripting. Likewise, the resulting model will be embedded in the DSS of the IoT platform to provide real time information on the prediction of the pollutants in the mine water streams. 

For this task, open-source code OpenFOAM was used in order to perform the CFD simulations. Besides, Python scripting was used to automatize the pre and post processing activities of the workflow, and to develop the data-based model from the TITANIA use-case. The library developed in T4.4 has been used to generate the ROMs.
CO2 concentration prediction in the operating area of Kemi mine (CFD results).

Ventilation flow path in the operating area of Kemi mine  (CFD results), when the rocks loading is starting and the stope is blocked by the rocks.