Mass movements and delta collapses are significant sources of tsunamis in lacustrine environments, impacting human societies enormously. Paleotsunamis studies play an essential role in understanding historical events and their consequences, along with their return periods. This study investigates a paleotsunami induced by a subaqueous mass movement during the Younger Dryas to Early Holocene transition, ca. 11,700 years ago in Lake Aiguebelette (NW Alps, France). Utilizing high‐resolution seismic and bathymetric surveys associated with sedimentological, geochemical, and magnetic analyses, we uncovered a paleotsunami triggered by a seismically induced mass transport deposit. Numerical simulations of mass movement have been conducted using a visco‐plastic Herschel‐Bulkeley rheological model and corresponding tsunami wave modeled with dispersive and nondispersive models. Our findings reveal for the first time that dispersive effects may be negligible for subaqueous landslides in a relatively small lake. This research reconstructs a previously unreported paleotsunami event and enhances our understanding of tsunami dynamics in lacustrine environments.
I will be the speaker this time and I'll talk about Shape Optimization. I will explain what are the problems that we try to solve and give a few examples then I will present some of the main tools that we use (\gamma-convergence, Buttazzo- Dal Maso existence theorem and Lions Concentration Compactness principle) and finaly if we still have some time, I will try to introduce the work that I'm doing at the moment. All of this with maybe some proofs to give you an idea of how the field works.
I will introduce the field, the kind of objects we manipulate, the sub fields and the kind of problems we want to solve... I will also focus on discrete diferential geometry and our current work on trying to adapt existing tools to geometry defined by surfels (surfaces of voxels).
In this talk, I will introduce you to the main electrical concepts to model the electrical response of a solar module. We will answer some questions like 'Why do we need an electrical model?', 'What is the electrical data we can extract from the real world?', and 'How do we treat such data?'. For this purpose, the main concepts will be conceptualized with a simple example.
Motivic integration is a powerful tool in algebraic geometry for studying singularities. The theory was conceived by Kontsevich in 1989 to provide a shorter proof of Batyrev's theorem. In 2009, a more "modern" form of this theory has emerged, spearheaded by Cluckers and Loeser. First, I'll talk about p-adic integration and motivations. Then I'll try to introduce the theory's basic objects, such as model theory and Grothendieck groups. Finally, if time permits, I'll set out some axioms of the motivic integral.
In this study, we propose a new hyperbolic model capable to capture the wave breaking phenomenon. The modelling of breaking waves is obtained by the depth- averaging method of Large-Eddy Simulations (LES) where the small scale turbulence is modeled by a turbulent viscosity, whereas the large scales are taken into account in the model by an anisotropic tensor variable called enstrophy. The hyperbolic structure is derived by replacing the depth-averaged non-hydrostatic pressure with an additional variable. The hyperbolisation of the equations is based on taking into account the finite character of the sound speed and introducing acoustic energy into the system. The resulting model can be viewed as a hyperbolic approximation of the Serre-Green-Naghdi (SGN) equations. Additionally, it has asymptotic dispersive properties to SGN equations as approaching to infinite sound speed. The treatment of breaking wave is to use the so-called switching method which certain terms describing the energy dissipation are activated once the wave breaks. So, we also present a more-robust breaking criteria on which only depends the local variables.
I will be talking about simplicial sets, which are combinatorial objects widely used in topology. But this time, I'll explain how some of them can characterize graphs, and by extension categories. After defining what simplicial sets are, I will show how to associate to each graph a simplicial set, called its nerve. I will then give a nerve for partial order and categories as well. Then, we will study which simplicial sets arise as nerves from a category, given by the so- called Segal condition. Finally, I will show how to recover graphs, partial orders and categories from their nerve.
Most of you probably heard about ZFC, this formal theory of sets from the early 20th that is said to be the fundamental language for modern math. Much rarer are the mathematicians that actually make use of it! Since the introduction of ZFC, formal logic has evolved a lot and since several decades other formal systems, more general (some would say more useful!) have been brought up. I will try to introduce the motivations for constructive systems, the links with computation, and demystify the law of excluded middle.