2063 research outputs found
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Fire-spotting modelling in operational wildfire simulators based on Cellular Automata: A comparison study
Get PDFOne crucial mechanism in the spread of wildfires is the so-called fire-spotting: a random phenomenon that occurs when embers are transported over large distances. Fire-spotting speeds up the rate of spread and starts new ignitions that can jeopardise firefighting operations. Unfortunately, operational fire-spread simulators may not account for spotting events, thus overlooking the harmful consequences associated with this phenomenon. In this work, three fire spotting parametrisations are integrated in the operational wildfire simulator PROPAGATOR based on Cellular Automata (CA). RandomFront, a physics-based parametrisation of fire-spotting, is tested for the first time in the context of CA simulators. RandomFront is compared with other two parametrisations already adopted in CA based simulators, those by Alexandridis and co-authors and by Perryman and collaborators. A wildfire occurred in the summer of 2021 in the municipality of Campomarino (Molise, Italy), and where spotting effects were clearly reported, is used as a case study. This case study, featuring evident airborne transport of firebrands, paves the way for a framework for comparing parameterised spotting models used in operational scenarios. RandomFront produced a more complex burning probability pattern than the other parametrisations and it predicted a higher probability of burning in the zone mainly affected by the fire-spotting
Thermodynamic Game and the Kac Limit in Quantum Lattices
Get PDFA mathematically rigorous computation of the pressure and equilibrium states of important short-range quantum models on lattices (like the Hubbard model) to show possible phase transitions is generally elusive, beyond perturbative arguments, even after decades of mathematical studies. By contrast, such a question can be solved for mean-field models. This is done by using some form of the Bogoliubov approximation, leading to the thermodynamic game introduced in Bru and de Siqueira Pedra (Non-cooperative Equilibria of Fermi Systems with Long Range Interactions. Memoirs AMS, vol. 224, no. 1052. American Mathematical Society, Providence, 2013). Here we illustrate this abstract result on a specific, albeit still general, example. We then state recent results contributing a precise mathematical relation between mean-field and short-range models via the long-range limit that is known in the literature as the the Kac or van der Waals limit. This paves the way for studying phase transitions, or at least important fingerprints of them like strong correlations at long distances, for models having interactions whose ranges are finite, but very large as compared to the lattice constant. It also sheds a new light on mean-field models. If both attractive and repulsive long-range forces are present then it turns out that the limit mean-field model is not necessarily what one traditionally guesses.This work is additionally supported by CNPq (309723/2020-5) as well as by the Basque Government through the grant IT1615-22, by the COST Action CA18232 financed by the European Cooperation in Science and Technology (COST), and by the Ministry of Science and Innovation via the grant PID2020-112948GB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”
The Arc-Floer conjecture for plane curves
No full textIn [4] it was conjectured that the compactly supported cohomology of the restricted
m-contact locus of an isolated hypersurface singularity coincides, up to a shift, with the Floer
cohomology of the m-th iterate of the monodromy of the Milnor fiber. In this paper we give
an affirmative answer to this conjecture in the case of plane curves
Localization of Beltrami fields: global smooth solutions and vortex reconnection for the Navier-Stokes equations
No full textAbstract. We introduce a class of divergence-free vector fields on R3 obtained after a suitable
localization of Beltrami fields. First, we use them as initial data to construct unique global smooth
solutions of the three dimensional Navier-Stokes equations. The relevant fact here is that these
initial data can be chosen to be large in any critical space for the Navier–Stokes problem, however
they satisfy the nonlinear smallness assumption introduced in [10]. As a further application of
the method, we use these vector fields to provide analytical example of vortex-reconnection for
the three-dimensional Navier-Stokes equations on R3. To do so, we exploit the ideas developed
in [13] but differently from this latter we cannot rely on the non-trivial homotopy of the three-
dimensional torus. To overcome this obstacle we use a different topological invariant, i.e. the
number of hyperbolic zeros of the vorticity field
Remarks on vector-valued Gagliardo and Poincar ́e-Sobolev type inequalities with weights
Get PDFIn this paper we review certain extensions of the Gagliardo and Poincar ́e-Sobolev type inequalities to later explore the possibility of extending them to the vector-valued setting. We restrict ourselves to the most classical case of lq-valued functions, where already some difficulties arise, due to the lack of a vector-valued variant of the truncation method, both on the classical and the fractional case. We think that these difficulties may be overcome in the future, and we pose some conjectures in this direction
The effect of mixed vaccination rollout strategy: A modelling study
Get PDFVaccines have measurable efficacy obtained first from vaccine trials. However, vaccine efficacy (VE) is not a static measure and long-term population studies are needed to evaluate its performance and impact. COVID-19 vaccines have been developed in record time and the currently licensed vaccines are extremely effective against severe disease with higher VE after the full immunization schedule.
To assess the impact of the initial phase of the COVID-19 vaccination rollout programmes, we used an extended Susceptible - Hospitalized - Asymptomatic/mild - Recovered () model. Vaccination models were proposed to evaluate different vaccine types: vaccine type 1 which protects against severe disease only but fails to block disease transmission, and vaccine type 2 which protects against both severe disease and infection. VE was assumed as reported by the vaccine trials incorporating the difference in efficacy between one and two doses of vaccine administration. We described the performance of the vaccine in reducing hospitalizations during a momentary scenario in the Basque Country, Spain. With a population in a mixed vaccination setting, our results have shown that reductions in hospitalized COVID-19 cases were observed five months after the vaccination rollout started, from May to June 2021. Specifically in June, a good agreement between modelling simulation and empirical data was well pronounced.BERC 2022-2025
Marie Curie No~792494
Severo Ochoa CEX2021-001142-S/ MICIN / AEI / 10.13039/501100011033
EITB Marathon 2021 call BIO21/COV/00
A simple catch: Fluctuations enable hydrodynamic trapping of microrollers by obstacles
Get PDFIt is known that obstacles can hydrodynamically trap bacteria and synthetic microswimmers in orbits, where the trapping time heavily depends on the swimmer flow field and noise is needed to escape the trap. Here, we use experiments and simulations to investigate the trapping of microrollers by obstacles. Microrollers are rotating particles close to a bottom surface, which have a prescribed propulsion direction imposed by an external rotating magnetic field. The flow field that drives their motion is quite different from previously studied swimmers. We found that the trapping time can be controlled by modifying the obstacle size or the colloid-obstacle repulsive potential. We detail the mechanisms of the trapping and find two remarkable features: The microroller is confined in the wake of the obstacle, and it can only enter the trap with Brownian motion. While noise is usually needed to escape traps in dynamical systems, here, we show that it is the only means to reach the hydrodynamic attractor.“la Caixa” Foundation (ID 100010434), fellowship LCF/BQ/-PI20/11760014.
The European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie
grant agreement no. 847648
Faulty wind farm simulation: An estimation/control-oriented model
Get PDFA large percentage of the electricity generation cost of wind turbines (WTs) is related to the operation and maintenance of the WTs. To reduce such costs, fault detection and isolation (FDI) and fault tolerant control (FTC) methods have become popular over the last decade, but most works focus on single WTs or WT subsystems. The present paper introduces a Simulink-based simulator able to simulate WT farms with the capacity to recreate different fault scenarios on the subsystems composing the WTs. The objective of the simulator is to be used by researchers to develop FDI and FTC strategies for wind farms. By way of example, the paper shows a case study illustrating the effects that different faults have on a wind farm
Machine learning discovery of optimal quadrature rules for isogeometric analysis
Get PDFWe propose the use of machine learning techniques to find optimal quadrature rules for the construction of stiffness and mass matrices in isogeometric analysis (IGA). We initially consider 1D spline spaces of arbitrary degree spanned over uniform and non-uniform knot sequences, and then the generated optimal rules are used for integration over higher-dimensional spaces using tensor products. The quadrature rule search is posed as an optimization problem and solved by a machine learning strategy based on adaptive gradient-descent. However, since the optimization space is highly non-convex, the success of the search strongly depends on the number of quadrature points and the parameter initialization. Thus, we use a dynamic programming strategy that initializes the parameters from the optimal solution over the spline space with a lower number of knots. With this method, we found optimal quadrature rules for spline spaces when using IGA discretizations with up to 50 uniform elements and polynomial degrees up to 8, showing the generality of the approach in this scenario. For non-uniform partitions, the method also finds an optimal rule in a reasonable number of test cases. We also assess the generated optimal rules in two practical case studies, namely, the eigenvalue problem of the Laplace operator and the eigenfrequency analysis of freeform curved beams, where the latter problem shows the applicability of the method to curved geometries. In particular, the proposed method results in savings with respect to traditional Gaussian integration of up to 44% in 1D, 68% in 2D, and 82% in 3D spaces.Euskampus Foundation through the ORLEG-IA project in the Misiones Euskampus 2.0 program.
RYC2021-032853-I/MCIN/AEI/10.13039/501100011033 funded by the Spanish Ministry of Science and Innovation and by the European Union NextGenerationEU/PRTR