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Bilotta, Giuseppe
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Bilotta, Giuseppe
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giuseppe.bilotta@ingv.it
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staff
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B-7129-2012
53 results
Now showing 1 - 10 of 53
- 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 - PublicationRestrictedFrom Multi-Hazard to Multi-Risk at Mount Etna: Approaches and Strategies of the PANACEA Project(Springer, 2023-04)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; The management of multiple hazards simultaneously impacting on a territory is a challenge for effective risk mitigation. This is particularly true on active volcanoes like Mt. Etna, characterized by effusive and explosive eruptions, often coupled with an intense seismic activity. This work aims at presenting the approach of the PANACEA project on the treatment of multi-hazards in terms of risk, which requires a common definition of the exposed elements and their vulnerability. Another aspect emerging from the recent and historical volcanic crises at Etna, is the occurrence of cascading effects and the problem of assessing their short-term interactions. Here we present a risk model taking into account a set of sequences of hazardous events which may result from a volcano unrest to possible impacts to some infrastructural elements. The outcomes of the project are intended to be a significant step towards a more comprehensive resilience to volcanic disasters, leading to a more safe society.66 7 - PublicationOpen AccessModeling of Geophysical Flows through GPUFLOW(2022)
; ; ; ; ; We present a new model called GPUFLOW for the modeling and simulation of geophysical flows. GPUFLOW, which is based on the cellular automaton paradigm, features a physical model for the thermal and rheological evolution of lava flows (including temperature-dependent emissivity and cooling by radiation and air convection), support for debris flows without thermal dependency, a parallel implementation on graphic processing units (GPUs), and a simpler and computationally more efficient solution to the grid bias problem. Here, we describe the physical–mathematical model implemented in GPUFLOW and estimate the influence of input data on the flow emplacement through different synthetic test cases. We also perform a validation using two real applications: a debris flow that occurred in July 2006 in the Dolomites (Italy) and the December 2018 lava flow from the Etna volcano. GPUFLOW’s reliability prediction is accomplished by fitting the simulation with the actual flow fields, obtaining average values between ~55% and 75%.290 58 - PublicationOpen AccessThe Impact of Dynamic Emissivity–Temperature Trends on Spaceborne Data: Applications to the 2001 Mount Etna Eruption(2022)
; ; ; ; ; ; ; ; ;; ; ;; ; ;Spaceborne detection and measurements of high-temperature thermal anomalies enable monitoring and forecasts of lava flow propagation. The accuracy of such thermal estimates relies on the knowledge of input parameters, such as emissivity, which notably affects computation of temperature, radiant heat flux, and subsequent analyses (e.g., effusion rate and lava flow distance to run) that rely on the accuracy of observations. To address the deficit of field and laboratory-based emissivity data for inverse and forward modelling, we measured the emissivity of ‘a’a lava samples from the 2001 Mt. Etna eruption, over the wide range of temperatures (773 to 1373 K) and wavelengths (2.17 to 21.0 µm). The results show that emissivity is not only wavelength dependent, but it also increases non-linearly with cooling, revealing considerably lower values than those typically assumed for basalts. This new evidence showed the largest and smallest increase in average emissivity during cooling in the MIR and TIR regions (~30% and ~8% respectively), whereas the shorter wavelengths of the SWIR region showed a moderate increase (~15%). These results applied to spaceborne data confirm that the variable emissivity-derived radiant heat flux is greater than the constant emissivity assumption. For the differences between the radiant heat flux in the case of variable and constant emissivity, we found the median value is 0.06, whereas the 25th and the 75th percentiles are 0.014 and 0.161, respectively. This new evidence has significant impacts on the modelling of lava flow simulations, causing a dissimilarity between the two emissivity approaches of ~16% in the final area and ~7% in the maximum thickness. The multicomponent emissivity input provides means for ‘best practice’ scenario when accurate data required. The novel approach developed here can be used to test an improved version of existing multi-platform, multi-payload volcano monitoring systems.300 15 - PublicationRestrictedSensitivity analysis of the MAGFLOW Cellular Automaton model(2012-07)
; ; ; ; ; ; ;Bilotta, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Cappello, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Herault, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Vicari, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Russo, G.; Dipartimento di Matematica e Informatica, Università di Catania ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; ; ; ; MAGFLOW is a physics-based numerical model for lava flow simulations based on the Cellular Automaton approach that has been successfully used to predict the lava flow paths during the recent eruptions on Mt Etna. We carried out an extensive sensitivity analysis of the physical and rheological parameters that control the evolution function of the automaton and which are measured during eruptive events, in an effort to verify the reliability of the model and improve its applicability to scenario forecasting. The results obtained, which include Sobol' sensitivity indices computed using polynomial chaos expansion, confirm the consistency of MAGFLOW with the underlying physical model and identify water content and solidus temperature as critical parameters for the automaton. Additional tests also indicate that flux rates can have a strong influence on the emplacement of lava flows, and that to obtain more accurate simulations it is better to have continuous monitoring of the effusion rates, even if with moderate errors, rather than sparse accurate measurements.276 28 - PublicationRestrictedOptimizing Satellite Monitoring of Volcanic Areas Through GPUs and Multi-Core CPUs Image Processing: An OpenCL Case Study(2013-12)
; ; ; ;Bilotta, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Sanchez, R.; INFN ;Ganci, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; Satellite image processing algorithms often offer a very high degree of parallelism (e.g., pixel-by-pixel processing) that make them optimal candidates for execution on high-performance parallel computing hardware such as modern graphic processing units (GPUs) and multicore CPUs with vector processing capabilities. By using the OpenCL computing standard, a single implementation of a parallel algorithm can be deployed on a wide range of hardware platforms. However, achieving the best performance on each individual platform may still require a custom implementation. We show some possible approaches to the optimization of satellite image processing algorithms on a range of different platforms, discussing the implementation in OpenCL of the classic Brightness Temperature Difference ash-cloud detection algorithm.269 47 - PublicationRestrictedSemi-implicit 3D SPH on GPU for lava flows(2018-12-15)
; ; ; ; ; ; ; ; ; ; ; ; ;; ; GPUSPH is an implementation of Weakly-Compressible Smoothed Particle Hydrodynamics with an explicit predictor–corrector integration scheme, that takes advantage of the parallel nature of the method to run on Graphic Processing Units (GPUs). Despite the massive speed-up granted by the use of GPUs, the application of GPUSPH to the simulation of highly viscous fluids is still problematic, due to the severe time-stepping restrictions imposed by the explicit integration scheme when the viscous term becomes dominant. This is an issue in the simulation of lava flows, where the thermal-dependent rheology can lead to kinematic viscosities in the order of 104m2s−1 or more at low temperatures. To overcome this limitation, we introduce a semi-implicit integration scheme, where only the viscous part of the momentum equation is solved implicitly. Here we show the significant advantages of our approach in terms of simulation run times as well as better quality of the results over the fully explicit scheme.689 2 - PublicationRestrictedLava flow hazards at Mount Etna: constraints imposed by eruptive history and numerical simulations(2013-12-13)
; ; ; ; ; ; ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Cappello, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Neri, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Bilotta, G.; Dipartimento di Matematica e Informatica, Universita` di Catania, Catania, Italy, ;Herault, A.; Conservatoire des Arts et Me´tiers, De´partement Inge´nierie Mathe´matique, Paris, France. ;Ganci, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; ; ; ; Improving lava flow hazard assessment is one of the most important and challenging fields of volcanology, and has an immediate and practical impact on society. Here, we present a methodology for the quantitative assessment of lava flow hazards based on a combination of field data, numerical simulations and probability analyses. With the extensive data available on historic eruptions of Mt. Etna, going back over 2000 years, it has been possible to construct two hazard maps, one for flank and the other for summit eruptions, allowing a quantitative analysis of the most likely future courses of lava flows. The effective use of hazard maps of Etna may help in minimizing the damage from volcanic eruptions through correct land use in densely urbanized area with a population of almost one million people. Although this study was conducted on Mt. Etna, the approach used is designed to be applicable to other volcanic areas.379 51 - PublicationOpen AccessAssessing impending hazards from summit eruptions: the new probabilistic map for lava flow inundation at Mt. Etna(2023-11-09)
; ; ; ; ; ; ; ; ; The development of probabilistic maps associated with lava flow inundation is essential to assess hazard in open vent volcanoes, especially those that have highly urbanized flanks. In this study we present the new lava flow hazard map linked to the summit eruptions of Mt. Etna, which has been developed using a probabilistic approach that integrates statistical analyses of the volcanological historical data with numerical simulations of lava flows. The statistical analysis of volcanological data (including vent location, duration and lava volumes) about all summit eruptions occurred since 1998 has allowed us both to estimate the spatiotemporal probability of future vent opening and to extract the effusion rate curves for lava flow modelling. Numerical simulations were run using the GPUFLOW model on a 2022 Digital Surface Model derived from optical satellite images. The probabilistic approach has been validated through a back-analysis by calculating the fit between the expected probabilities of inundation and the lava flows actually emplaced during the 2020-2022 period. The obtained map shows a very high probability of inundation of lava flows emitted at vents linked to the South East Crater, according to the observation of the eruptive dynamics in the last decades.132 16 - PublicationRestrictedSPH MODELING OF LAVA FLOWS WITH GPU IMPLEMENTATION(2010)
; ; ; ; ; ;Hérault, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Bilotta, G.; Università degli studi di Catania ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Russo, G.; Università degli studi di Catania ;Vicari, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; ; ; ; ; ; ;Fortuna, Luigi; Università degli studi di Catania ;Fradkov, Alexander; Institute for Problems of Mechanical Engineering ;Frasca, Mattia; Università degli studi di Catania; ; We describe the implementation of the Smoothed Particle Hydrodynamics (SPH) method on graphical processing units (GPU) using the Compute Unified Device Architecture (CUDA) developed by NVIDIA. The entire algorithm is executed on the GPU, fully exploiting its computational power. The code faces all three main components of an SPH simulation: neighbor list constructions, force computation, integration of the equation of motion. The simulation speed achieved is one to two orders of magnitude higher than the equivalent CPU code. Applications are shown for simulating the paths of lava flows during volcano eruptions. Both static problems with purely thermal effects (such as lava lake solidification) and dynamic problems with a complete lava flow were simulated.157 35