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PhD Thesis Defense – Hydromechanical Simulation of Argillaceous Rocks for Radioactive Waste Disposal Applications

PhD Thesis Defense – Hydromechanical Simulation of Argillaceous Rocks for Radioactive Waste Disposal Applications

by smerce | Nov 11, 2025 | Thesis Defense

ABSTRACT Argillaceous claystones are primarily composed of clay particles of sedimentary origin and contain a substantial amount of chemically precipitated cement, often calcium carbonate, which acts as a bonding agent. Due to their favorable properties—such as low...
PhD Thesis Defense – Data assimilation for real-time dynamic prediction of wind-induced forces in vehicle platooning

PhD Thesis Defense – Data assimilation for real-time dynamic prediction of wind-induced forces in vehicle platooning

by smerce | Nov 11, 2025 | Thesis Defense

ABSTRACT We consider the vehicle platoon problem from an aerodynamic point of view. That is, the multiparametric problem of predicting the aerodynamic forces acting on a vehicle following another one under realistic road conditions. We develop a RANS methodology to...
LàCaN/CIMNE Seminar – “From neurons and plants to elephant trunks. The multiscale mechanics of smart active solids” by Prof. Alain Goriely

LàCaN/CIMNE Seminar – “From neurons and plants to elephant trunks. The multiscale mechanics of smart active solids” by Prof. Alain Goriely

by smerce | Nov 7, 2025 | Seminars

ABSTRACT The world around us is filled with structures that respond to external stimuli and adapt their internal structures to perform specific functions. For example, plants have the ability to sense changes in their environment, such as changes in gravity or light,...
CENIT Magazine: Issue 4 of ‘Innovation in Transport Review’ out now

CENIT Magazine: Issue 4 of ‘Innovation in Transport Review’ out now

by smerce | Nov 3, 2025 | CENIT, In depth, Innovation Units

CENIT, CIMNE’s Innovation Unit in Transport, has just released Issue 4 of CENIT magazine: Innovation in Transport Review. The innovation team presents insights and findings from some of their latest research, focusing on topics such as electrification in public...
PhD Thesis Defense – Reduced order models and machine learning techniques for digital twin applications

PhD Thesis Defense – Reduced order models and machine learning techniques for digital twin applications

by smerce | Oct 30, 2025 | Thesis Defense

ABSTRACT This thesis advances intrusive projection-based reduced order modeling (PROM) as a scalable, physics-consistent foundation for real-time digital twins in industrial applications. By integrating high-fidelity numerical methods with robust model reduction...
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