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BCAM obtains funding for six projects through the PID 2024 CALL from the State Research Agency
This call is aimed at funding scientific research and knowledge advancement, both in non-oriented areas and in areas oriented towards solving specific problems. BCAM has successfully obtained funding for six of its research projects through the prestigious PID 2024 (Proyectos de Generación de…
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Book of Abstracts for ESGI 188 now available
- The 188th European Study Group with Industry (ESGI 188), hosted from May 26 to 30 at Bilbao's B Accelerator Tower (BAT), has concluded with the release of its Book of Abstracts.
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- What if Artificial Intelligence could remember things not just well, but faster or more reliably?
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- The jury of these awards has taken into account her contributions to machine learning in the field of adaptation to temporal changes, both in its mo
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View allModelling swelling effects in real espresso extraction using a 1-dimensional coarse-grained model
Mo, Chaojie; Navarini, Luciano; Liverani, Furio Suggi; Ellero, Marco; Ellero, M. (2024-03-01)
Swelling of coffee particle is difficult to measure and control, but it could have significant effects on espresso extraction. In this article, we incorporate a particle-level swelling model to a one dimensional bed-level ex...
A SEMI-ANALYTICAL SOLUTION FOR THE LUBRICATION FORCE BETWEEN TWO SPHERES APPROACHING IN VISCOELASTIC FLUIDS DESCRIBED BY THE OLDROYD-B MODEL UNDER SMALL DEBORAH NUMBERS
Rosales-Romero, A; Vazquez-Quesada, A; Ellero, M.; López-Aguilar, J. E. (2025-01-01)
Viscoelastic fluids play a critical role in various engineering and biological applications, where their lubrication properties are strongly influenced by relaxation times ranging from microseconds to min- utes. Although t...
Simulating non-Brownian suspensions with non-homogeneous Navier slip boundary conditions
Moreno, D.; Balboa, F.; Moreno, N.; Ellero, M. (2025-01-01)
Fluid-structure interactions are commonly modeled using no-slip boundary conditions. However, small deviations from these conditions can significantly alter the dynamics of sus- pensions and particles, especially at the mi...
A GENERIC-guided active learning SPH method for viscoelastic fluids using Gaussian process regression
Dong, X.; Nieto, D.; Ouyang, J.; Wang, X.; Ellero, M. (2025-01-01)
When applying machine learning methods to learn viscoelastic constitutive relations, the poly- mer history dependence in viscoelastic fluids and the generalization ability of machine learn- ing models are challenging. In t...