Modelling lava flows by Cellular Nonlinear Networks (CNN): preliminary results

International audienceThe forecasting of lava flow paths is a complex problem in which temperature, rheology and flux-rate all vary with space and time. The problem is more difficult to solve when lava runs down a real topography, considering that the relations between characteristic parameters of flow are typically nonlinear. An alternative approach to this problem that does not use standard differential equation methods is Cellular Nonlinear Networks (CNNs). The CNN paradigm is a natural and flexible framework for describing locally interconnected, simple, dynamic systems that have a lattice-like structure. They consist of arrays of essentially simple, nonlinearly coupled dynamic circuits containing linear and non-linear elements able to process large amounts of information in real time. Two different approaches have been implemented in simulating some lava flows. Firstly, a typical technique of the CNNs to analyze spatio-temporal phenomena (as Autowaves) in 2-D and in 3-D has been utilized. Secondly, the CNNs have been used as solvers of partial differential equations of the Navier-Stokes treatment of Newtonian flow

Refined Factorizations of Solvable Potentials

A generalization of the factorization technique is shown to be a powerful algebraic tool to discover further properties of a class of integrable systems in Quantum Mechanics. The method is applied in the study of radial oscillator, Morse and Coulomb potentials to obtain a wide set of raising and lowering operators, and to show clearly the connection that link these systems.Comment: 11 pages, LaTeX file, no figure

Discrete derivatives and symmetries of difference equations

We show on the example of the discrete heat equation that for any given discrete derivative we can construct a nontrivial Leibniz rule suitable to find the symmetries of discrete equations. In this way we obtain a symmetry Lie algebra, defined in terms of shift operators, isomorphic to that of the continuous heat equation.Comment: submitted to J.Phys. A 10 Latex page

Understanding the Rhythm of Breathing: So Near, Yet So Far

Breathing is an essential behavior that presents a unique opportunity to understand how the nervous system functions normally, how it balances inherent robustness with a highly regulated lability, how it adapts to both rapidly and slowly changing conditions, and how particular dysfunctions result in disease. We focus on recent advancements related to two essential sites for respiratory rhythmogenesis: (a) the preBotzinger Complex (preBotC) as the site for the generation of inspiratory rhythm and (b) the retrotrapezoid nucleus/parafacial respiratory group (RTN/pFRG) as the site for the generation of active expiration

Simulations of the 2004 lava flow at etna volcano by the magflow cellular automata model

Lava flows represent a challenge for physically based modeling, since the mechanical properties of lava change over time. This change is ruled by a temperature field, which needs to be modeled. MAGFLOW Cellular Automata (CA) model was developed for physically based simulations of lava flows in near real-time. We introduced an algorithm based on the Monte Carlo approach to solve the anisotropic problem. As transition rule of CA, a steady state solution of Navier-Stokes equations was adopted in the case of isothermal laminar pressure-driven Bingham fluid. For the cooling mechanism, we consider the radiative heat loss only from the surface of the flow, and the change of the temperature due to mixture of lavas between cells with different temperatures. The model was applied to reproduce a real lava flow occurred during the 2004-2005 Etna eruption. The simulations were computed using three different empirical relationships between viscosity and temperature

Simulations of the 2004 lava flow at Etna volcano by the magflow cellular automata model

Lava flows represent a challenge for physically based modeling, since the mechanical properties of lava change over time. This change is ruled by a temperature field, which needs to be modeled. MAGFLOW Cellular Automata (CA) model was developed for physically based simulations of lava flows in near real-time. We introduced an algorithm based on the Monte Carlo approach to solve the anisotropic problem. As transition rule of CA, a steady state solution of Navier-Stokes equations was adopted in the case of isothermal laminar pressure-driven Bingham fluid. For the cooling mechanism, we consider the radiative heat loss only from the surface of the flow, and the change of the temperature due to mixture of lavas between cells with different temperatures. The model was applied to reproduce a real lava flow occurred during the 2004-2005 Etna eruption. The simulations were computed using three different empirical relationships between viscosity and temperature

The HOTSAT volcano monitoring system based on combined use of SEVIRI and MODIS multispectral data

Spaceborne remote sensing of high-temperature volcanic features offers an excellent opportunity to monitor the onset and development of new eruptive activity. To provide a basis for real-time response during eruptive events, we designed and developed the volcano monitoring system that we call HOTSAT. This multiplatform system can elaborate both Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, and it is here applied to the monitoring of the Etna volcano. The main advantage of this approach is that the different features of both of these sensors can be used. It can be refreshed every 15 min due to the high frequency of the SEVIRI acquisition, and it can detect smaller and/or less intense thermal anomalies through the MODIS data. The system consists of data preprocessing, detection of volcano hotspots, and radiative power estimation. To locate thermal anomalies, a new contextual algorithm is introduced that takes advantage of both the spectral and spatial comparison methods. The derivation of the radiative power is carried out at all ‘hot’ pixels using the middle infrared radiance technique. The whole processing chain was tested during the 2008 Etna eruption. The results show the robustness of the system after it detected the lava fountain that occurred on May 10 through the SEVIRI data, and the very beginning of the eruption on May 13 through the MODIS data analysis