Profil

DARLIK Fateme

Main Referenced Co-authors
PETERS, Bernhard  (3)
ADHAV, Prasad  (2)
AMINNIA, Navid  (1)
BESSERON, Xavier  (1)
HASSANZADEH SARAEI, Sina  (1)
Main Referenced Keywords
Discrete element method (2); Biomass source (1); Blast furnace (1); Continuum approach (1); Coupled CFD-DEM (1);
Main Referenced Unit & Research Centers
LuXDEM - University of Luxembourg: Luxembourg XDEM Research Centre (2)
ULHPC - University of Luxembourg: High Performance Computing (1)
Main Referenced Disciplines
Mechanical engineering (3)
Chemical engineering (1)

Publications (total 4)

The most downloaded
260 downloads
Aminnia, N., Adhav, P., Darlik, F., Mashhood, M., Hassanzadeh Saraei, S., Besseron, X., & Peters, B. (15 February 2023). Three-dimensional CFD-DEM simulation of raceway transport phenomena in a blast furnace. Fuel, 334 (2). doi:10.1016/j.fuel.2022.126574 https://hdl.handle.net/10993/53900

The most cited

9 citations (Scopus®)

Aminnia, N., Adhav, P., Darlik, F., Mashhood, M., Hassanzadeh Saraei, S., Besseron, X., & Peters, B. (15 February 2023). Three-dimensional CFD-DEM simulation of raceway transport phenomena in a blast furnace. Fuel, 334 (2). doi:10.1016/j.fuel.2022.126574 https://hdl.handle.net/10993/53900

DARLIK, F. (2023). PHYSICALLY INFORMED NEURAL NETWORKS TO REPRESENT MOTION OF GRANULAR MATERIAL [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60405

Aminnia, N., Adhav, P., Darlik, F., Mashhood, M., Hassanzadeh Saraei, S., Besseron, X., & Peters, B. (15 February 2023). Three-dimensional CFD-DEM simulation of raceway transport phenomena in a blast furnace. Fuel, 334 (2). doi:10.1016/j.fuel.2022.126574
Peer Reviewed verified by ORBi

Darlik, F., & Peters, B. (2023). Reconstruct the biomass particles fields in the particle-fluid problem using continuum methods by applying the physics-informed neural network. Results in Engineering, 17, 100917. doi:10.1016/j.rineng.2023.100917
Peer reviewed

Darlik, F., Adhav, P., & Peters, B. (2022). Prediction of the biomass particles through the physics informed neural network. ECCOMAS Congress 2022 - 8th European Congress on Computational Methods in Applied Sciences and Engineering. doi:10.23967/eccomas.2022.223
Peer reviewed

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