AICE-ITC
Non-Academic
Experts in:
Modeling and simulation
- Fluids: gases, liquids.
- Combustion.
- Thermal or thermodynamic.
- Mechanical or structural.
- Simulation and modelling of particulate matter using the discrete element method (DEM).
Artificial intelligence
- Development of digital twins.
- Machine learning.
- Automatic learning.
Computing
- Programming in scientific languages: Fortran, C, C++, Python, Matlab, R.
- Use of free software packages.
- Parallelisation of algorithms.
- GPU programming.
- High performance computing.
Ámbitos de experiencia:
Challenge 3: Energy
- Numerical simulation of heat transfer and combustion processes.
Use cases:
MOULDFEED
In this project, the rheological behaviour of powdery ceramic materials during mould filling was studied and modelled. An industrial problem-oriented simulation software called ScaleDEM was successfully developed. As can be seen in the picture, the software allowed to simulate correctly and in a short time the filling of moulds at laboratory and industrial level.
Software link: http://www.scaledem.org
INTGEOTHER
In this project, an integrated tool was developed for the safe and efficient implementation of shallow geothermal energy collection systems-SGE in the Valencian Community. The tool simplifies and democratises access to information on the feasibility of shallow geothermal energy in buildings. Through a general form the tool is able to simulate the behaviour of the ground and predict the feasibility of using geothermal energy as an energy source.
SINTERSIM
This project modelled and simulated the sintering process of porcelain stoneware tiles during firing. This process is vital in the manufacture of tiles and ultimately defines the mechanical and dimensional properties of the product. During sintering, the porcelain tile becomes denser, its size decreases and its mechanical strength increases, depending on the temperature cycle it has undergone, the raw material used and the mechanical and dimensional state of the raw tile. The model makes it possible to predict the final properties of porcelain stoneware tiles after firing, and thus optimise the process with the aim of obtaining higher quality products with a lower amount of energy.
TWINXIndustry
In this project, a complete ceramic tile manufacturing plant was modelled using the discrete event method (DES). The digital model developed makes it possible to predict the evolution of production, its quality, energy consumption and the state of the equipment. This model can be used as a digital twin of a real plant via an OPC-UA communication protocol.
More information: Boix, J., Mallol, G., Tiscar, J.M., Cantero, J.I., Olmedilla, A., Vinaroz, M. Discrete event modelling and simulation of the ceramic tile manufacturing process. Qualicer, 2020.
