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Zago, Vito
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Zago, Vito
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vito.zago@ingv.it
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57200039789
12 results
Now showing 1 - 10 of 12
- PublicationOpen AccessSatellite-driven modeling approach for monitoring lava flow hazards during the 2017 Etna eruption(2019)
; ; ; ; ; ; ; ; ; ; ; The integration of satellite data and numerical modeling represents an efficient strategy to find immediate answers to the main issues raised at the onset of a new effusive eruption. Satellite thermal remote sensing can provide a variety of products suited to timing, locating, and tracking the radiant character of lava flows, including the opening times of eruptive vents. The time-series analysis of thermal satellite data can also provide estimates of the time-averaged discharge rate and volume. High-spatial resolution multispectral satellite data complement field observations for monitoring the lava emplacement in terms of flow length and area. All these satellite-derived parameters can be passed as input to physics-based numerical models in order to produce more accurate and reliable forecasts of effusive scenarios during ongoing eruptions. Here, we demonstrate the potential of the integrated application of satellite remote sensing techniques and lava flow models during the 2017 eruptive activity of Mt Etna. Remote sensing data from SEVIRI are analyzed by the HOTSAT system to output hotspot location, lava thermal flux, and effusion rate estimation. This output is used to drive, as well as to continuously update, lava flow simulations performed by the physics-based MAGFLOW model. We also show how Landsat-8 and Sentinel-2 satellite data complement the field observations to track the flow front position in time and add valuable data on lava flow advancement with which to iteratively validate the numerical simulations.1108 171 - PublicationOpen AccessA physically consistent AI-based SPH emulator for computational fluid dynamics(2024)
; ; ; ; ; The integration of artificial intelligence (AI) into computational fluid dynamics (CFD) has significantly expanded the scope of fluid modeling, allowing enhanced analysis capabilities and improved simulation performance. While Eulerian methods already benefit extensively from AI, notably in reliable weather prediction, the application of AI to Lagrangian methods remains less consolidated. Smoothed particle hydrodynamics (SPH) is a Lagrangian mesh-less numerical method for CFD with well-established advantages for the simulation of highly dynamic free-surface flows. Here, we explore an application of AI to SPH simulations, utilizing an artificial neural network (ANN) to estimate hydrodynamic forces between particle pairs, learning from SPH-simulated results. A model of this nature, which emulates the mathematical representation of physics, is termed an emulator. We examine the physical significance of the emulator, presenting its applications in benchmark tests, assessing its faithfulness to traditional SPH simulations, and highlighting its ability to generalize and simulate test cases with varying levels of complexity beyond its training data.6 2 - PublicationRestrictedAccuracy Improvements for Single Precision Implementations of the SPH Method(2020)
; ; ; ; ; ; ; One of the main issues with naive Smoothed Particle Hydrodynamics (SPH) implementations is the lack of uniform accuracy in the computational domain. If not mastered correctly, this leads to non-physical predictions when dealing with large-domain hydraulic problems or with very fine resolutions. The present article addresses two recommended methodologies to achieve the best numerical accuracy with single-precision SPH implementations, using the GPUSPH engine as reference. A still water test case is examined using different approaches. Instead of operating with the physical particle positions, the use of positions relative to the neighbour-search grid leads to a homogeneous accuracy distribution throughout the domain, with a consequent improvement in energy conservation. Further improvements are attained by evolving the relative density variation in the fluid equations, instead of the physical density. This helps in bounding the numerical errors within the machine epsilon and prevents any spurious behaviour due to error accumulation.323 3 - PublicationOpen AccessSimulating complex fluids with smoothed particle hydrodynamics(2017)
; ; ; ; ; ; ; ; ; ; ; ; ;; ;Complex fluid dynamics encompasses a large variety of flows, such as fluids with non-Newtonian rheology, multiphase and multi-fluid flows (suspensions, lather, solid/fluid interaction with floating objects, etc.), violent flows breaking waves, dam-breaks, etc.), fluids with thermal dependencies and phase transition or free-surface flows. Correctly modeling the behavior of such flows can be quite challenging, and has led to significant advances in the field of Computational Fluid Dynamics (CFD). Recently, the Smoothed Particle Hydrodynamics (SPH) method has emerged as a powerful alternative to more classic CFD methods (such as finite volumes or finite elements) in many fields, including oceanography, volcanology, structural engineering, nuclear physics and medicine. With SPH, the fluid is discretized by means of particles and thanks to the meshless, Lagrangian nature of the model, it easily allows the modeling and simulation of both simple and complex fluids, simplifying the treatment of aspects that can be challenging with more traditional methods: dynamic free surfaces, large deformations, phase transition, fluid/solid interaction and complex geometries. In addition, the most common SPH formulations are fully parallelizable, which favors implementation on high-performance parallel computing hardware, such as modern Graphics Processing Units (GPUs). We present here how GPUSPH, an implementation of the SPH method that runs on GPUs, can model a variety of complex fluids, highlighting the computational challenges that arise in its applications to problem of great interest in volcanology.704 159 - PublicationOpen AccessPreliminary validation of lava benchmark tests on the GPUSPH particle engine(2019)
; ; ; ; ; ; ; ; ; ; ; ; ;; ; Lava flow modeling is important in many practical applications, such as the simulation of potential hazard scenarios and the planning of risk mitigation measures, as well as in scientific research to improve our understanding of the physical processes governing the dynamics of lava flow emplacement. Existing predictive models of lava flow behavior include various methods and solvers, each with its advantages and disadvantages. Codes differ in their physical implementations, numerical accuracy, and computational efficiency. In order to validate their efficiency and accuracy, several benchmark test cases for computational lava flow modeling have been established. Despite the popularity gained by the Smoothed Particle Hydrodynamics (SPH) method in Computational Fluid Dynamics (CFD), very few validations against lava flows have been successfully conducted. At the Tecnolab of INGVCatania we designed GPUSPH, an implementation of the weakly-compressible SPH method running fully on Graphics Processing Units (GPUs). GPUSPH is a particle engine capable of modeling both Newtonian and non-Newtonian fluids, solving the three-dimensional Navier– Stokes equations, using either a fully explicit integration scheme, or a semi-implicit scheme in the case of highly viscous fluids. Thanks to the full coupling with the thermal equation, and its support for radiation, convection and phase transition, GPUSPH can be used to faithfully simulate lava flows. Here we present the preliminary results obtained with GPUSPH for a benchmark series for computational lava-flow modeling, including analytical, semi-analytical and experimental problems. The results are reported in terms of correctness and performance, highlighting the benefits and the drawbacks deriving from the use of SPH to simulate lava flows.962 82 - PublicationRestrictedLiving at the edge of an active volcano: Risk from lava flows on Mt. Etna(2020)
; ; ; ; ; ; ; ; ; ; ; Lava flows represent the greatest threat by far to exposed population and infrastructure on Mt. Etna, Italy. The increasing exposure of a larger population, which has almost tripled in the area around Mt. Etna during the past 150 years, has resulted from poor assessment of the volcanic hazard and inappropriate land use in vulnerable areas. Here we quantify the lava flow risk on the flanks of Mt. Etna volcano using a Geographic Information System (GIS)-based approach that integrates the hazard with the exposure of elements at stake. The hazard, which shows the long-term probability related to lava flow inundation, is obtained by combining three different kinds of information: the spatiotemporal probability of new flank eruptive vents opening in the future, the event probability associated with classes of expected eruptions, and the overlapping of lava flow paths simulated by the MAGFLOW model. Data including all exposed elements were gathered from institutional web portals and high-resolution satellite imagery and organized in four thematic layers: population, buildings, service networks, and land use. The total exposure is given by a weighted linear combination of the four thematic layers, where weights are calculated using the Analytic Hierarchy Process (AHP). The resulting risk map shows the likely damage caused by a lava flow eruption and allows rapid visualization of the areas subject to the greatest losses if a flank eruption were to occur on Mt. Etna. The highest risk is found in the southeastern flank due to the combination of high hazard and population density.1094 8 - PublicationOpen Access3D Lava flow mapping of the 17-25 May 2016 Etna eruption using tri-stereo optical satellite data(2019)
; ; ; ; ; ; ; ; ; ; ;During basaltic eruptions, the average rate at which lava is erupted (effusion rate) is one of the most important factors controlling the evolution, growth and extent of the flow field. This has implications both for forecasting purposes, highlighting the importance of the effusion rate as input parameter of physics-based numerical models, and to advance knowledge on the shallow feeder system by constraining the supplied mass. Satellite remote sensing provides a mean to estimate the average effusion rate by applying a direct conversion from the measured radiant heat loss by an active lava flow. This conversion relies on a set of parameters of lava (e.g. rock density, heat capacity, vesicularity, emissivity, etc.) and suffers of multiple sources of uncertainties and measurements errors, whose quantification is still an open problem. Here we constrain the volume of lava emitted at Mt Etna on 17-25 May 2016 and emplaced out of the summit craters, by using preeruptive and post eruptive digital elevation models (DEMs) obtained processing satellite images acquired by the Pléiades constellation, which provides images at 50 cm resolution in stereo and tristereo mode. The 3D processing of the tri-stereo Pléiades imagery (acquired on 24 December 2015 and 18 July 2016), performed using the free and open source MicMac photogrammetric library, provides estimations of the distribution of thickness and the bulk volume emitted. The integration of multi-platform remote sensing products represents a new potential of merging capabilities to enable a more comprehensive response to effusive crises.803 86 - PublicationOpen AccessMapping Volcanic Deposits of the 2011–2015 Etna Eruptive Events Using Satellite Remote Sensing(2018-06-21)
; ; ; ; ; ; ; ; ; ; ; Estimates of lava volumes provide important data on the lava flooding history and evolution of a volcano. For mapping volcanic deposits, including lava flows, the advancement of satellite remote sensing techniques offers a great potential. Here we characterize the eruptive events occurred at Mt Etna between January 2011 and December 2015 leading to the emplacement of numerous lava flows and to the formation of a new pyroclastic cone (NSEC) on the eastern flank of the South East Crater. The HOTSAT system is used to analyze remote sensing data acquired by the SEVIRI sensor in order to detect the thermal anomalies from active lava flows and calculate the associated radiative power. The time-series analysis of SEVIRI data provides an estimation of event magnitude and intensity of the effusive material erupted during each event. The cumulative volume estimated from SEVIRI images from 2011 to 2015 adds up to ~106 millions of cubic meters of lava, with a time-averaged rate of ~0.68 m3 s−1. This estimate is independently supported and bounded using a topographic approach, i.e., by subtracting the last topography of Etna updated to 2005 from a 2015 digital elevation model (DEM), produced using tri-stereo Pléiades satellite images acquired on December 18, 2015. The total volume of products erupted from 2005 to 2015, calculated from topography difference by integration of the thickness distribution over the area covered, is about 287 × 106 m3, of which ~55 × 106 m3 is the volume of the NSEC cone. This 10-year volume is below the typical erupted volumes on decadal scale at Mt Etna, interrupting its stable and resilient output trend.626 83 - PublicationOpen AccessA numerically robust, parallel-friendly variant of BiCGSTAB for the semi-implicit integration of the viscous term in Smoothed Particle Hydrodynamics(2022-06-29)
; ; ; ; ; ; ; ; ;; ;; ; Implicit integration of the viscous term can significantly improve performance in computational fluid dynamics for highly viscous fluids such as lava. We show improvements over our previous proposal for semi-implicit viscous integration in Smoothed Particle Hydrodynamics, extending it to support a wider range of boundary models. Due to the resulting loss of matrix symmetry, a key advancement is a more robust version of the biconjugate gradient stabilized method to solve the linear systems, that is also better suited for parallelization in both shared-memory and distributed-memory systems. The advantages of the new solver are demostrated in applications with both Newtonian and non-Newtonian fluids, covering both the numerical aspect (improved convergence thanks to the possibility to use more accurate boundary model) and the computing aspect (with excellent strong scaling and satisfactory weak scaling).277 44 - PublicationOpen AccessOvercoming excessive numerical dissipation in SPH modeling of water wavesExcessive nonphysical energy dissipation is a problem in Smoothed Particle Hydrodynamics (SPH) when modeling free surface waves, resulting in a significant decrease in wave amplitude within a few wavelengths for progressive waves. This dissipation poses a limitation to the physical scale of SPH applications involving water wave propagation. Some prior solutions to this wave decay problem rely on elaborate schemes, which require a complex, or non-straightforward, implementation. Other approaches demand large smoothing lengths that lead to longer simulation times and potential degradation of the results. In this work we present an approach based on a kernel gradient correction. Our scheme is fully 3D and solves the main known drawbacks of kernel gradient corrections, such as instabilities and lack of momentum conservation. The latter is ensured by adopting an averaged correction matrix, so as to conserve reciprocity during particle interactions. We test our model with a standing wave in a basin and a progressive wave train in a wave tank, and in both cases no nonphysical decay occurs. A comparison to an approach based on large smoothing factors shows advantages both in quality of the results and simulation time.
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