Dear Geo-Fellows,
As we gear up for the holiday season and prepare to bid adieu to an eventful year, Edition 44 of our newsletter is a testament to the incredible journey we’ve shared over the last three months. Let’s take a moment to revel in our collective achievements, relish the milestones, and share in the anticipation of what lies ahead.
Please colleagues, enjoy and forward this letter to fellows and friends.
If you have something you want to share in the next newsletter, please do not hesitate to contact us at: geomecanique.newsletter@3sr-grenoble.fr.
PhD graduates
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On December 14th, Marylin SARKIS defended her PhD thesis on “Caractérisation micro-mécanique des contacts pour la prédiction de propriétés macroscopiques du sable bio-cimenté ” under the supersion of Christian GEINDREAU, Fabrice EMERIAULT and Antoine NAILLON. The jury was composed of Pierre PHILIPPE (INRAE, Aix-en-Provence), Anh Minh TANG – (École des Ponts ParisTech), Gaël COMBE (Université Grenoble Alpes), Hannelore DERLUYN (Univ Pau & Pays Adour) Annette ESNAULT FILET (Soletanche Bachy).
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On 4th of December Lu AN defended his PhD thesis whose title is “Analyse de la stabilité des barrages en terre à l’aide d’approches basées sur l’apprentissage automatique” under the supervision of Daniel DIAS, Laurent PEYRAS, Claudio CARVAJAL, Orianne JENCK and Pierre BREUL. Farimah MASSROURI (Université de Lorraine), Jean-Michel PEREIRA (École des Ponts ParisTech), Alaa CHATEAUNEUF (Université Blaise Pascal) and Julien BAROTH (Université Grenoble Alpes) took part in the jury.
GCER 2022-2023!
- The kick-off meeting took place on September 11. This year, the students are fewer than last year — they are 14. For the first time ever there are no italian students in the class (!). They will start their research project in February next year.
ALERT-Geomaterials, annual meeting in Aussois!
One of the sessions of the workshop (Sept. 25 to Sept. 27) was co-organized by Cino (“Anisotropy in geomaterials: theory, experiments and modelling“, see https://alertgeomaterials.eu/alert-workshop/).
The doctoral school (Sept. 28 to Sept. 30) was co-organized by Félix (“Machine Learning in Geomechanics“, see https://alertgeomaterials.eu/alert-doctoral-school/).
PhD prize!
- Our Angela Casarella was one of the three finalists for the Ioannis Vardoulakis PhD Prize 2023 for her thesis entitled “Multi-scale investigation of the thermomechanical behaviour of non-active clay“. Warm congratulations to her!
Publications!
- Barés J., Cárdenas-Barrantes M., Pinzón G., Andò E., Renouf M., Viggiani G., Azéma E. (2023) – Compacting an assembly of soft balls far beyond the jammed state: insights from 3D imaging. Physical Review E 108, 044901-1-1.
- Seo D., Tengattini A., Viggiani G., Buscarnera G. (2024) – Experimental and Analytical Assessment of Fracture Criteria for Non-Spherical Sand Grains. Granular Matter, Granular Matter 26, 1.
- Pan J., Pinzón G., Wang R., Andò E., Viggiani G., Zhang J.M. (2024) – Lessons learned from matching 3D DEM and experiments at macro, meso and fabric scales for triaxial compression tests on lentils, JMPS, accepted November 2023.
- A benchmark study of 8 different open-source codes for DEM has been accepted in Computer Physics Communication. The paper, entitled “Comparing open-source DEM frameworks for simulations of common bulk processes” involves Robert Caulk, Vasileios Angelidakis, and Bruno Chareyre for the Yade-DEM part and is here.
Conferences!
- Michela Arciero and Cino attended to IS-PORTO 2023, the 8th International Symposium on Deformation Characteristics of Geomaterials, held from the 3rd to the 6th September 2023 in Porto. Michela gave a talk.
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Bilal Al Tfaily presented his work titled “A 3D discrete element model for studying soil-structure interaction on shallow foundations subjected to seismic loads” at the XVII International Conference on Computational Plasticity, COMPLAS 2023, held in Barcelona, Spain, from 5th to 7th September 2023. An image of his numerical sample of Ticino sand is presented below.
Seminars!
- On October 5, Filipo Masi gave a talk on Thermodynamics-based Artificial Neural Networks (Masi et al. 2021; Masi and Stefanou, 2022) which embed the fundamental laws of thermodynamics directly into their structure, thus ensure thermodynamically consistent predictions.