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Cerminara, Matteo
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Cerminara, Matteo
Email
matteo.cerminara@ingv.it
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staff
ORCID
Scopus Author ID
55216776900
Researcher ID
B-2081-2017
38 results
Now showing 1 - 10 of 38
- PublicationOpen Access
37 38 - PublicationRestrictedVolcanic plume vent conditions retrieved from infrared images: A forward and inverse modeling approach(2015)
; ; ; ; ;Cerminara, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Pisa, Pisa, Italia ;Esposti Ongaro, T.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Pisa, Pisa, Italia ;Valade, S. ;Harris, A. J. L.; ; ;We present a coupled fluid-dynamic and electromagnetic model for volcanic ash plumes. In a forward approach, the model is able to simulate the plume dynamics from prescribed input flow conditions and generate the corresponding synthetic thermal infrared (TIR) image, allowing a comparison with field-based observations. An inversion procedure is then developed to retrieve vent conditions from TIR images, and to independently estimate the mass eruption rate. The adopted fluid-dynamic model is based on a one-dimensional, stationary description of a self-similar turbulent plume, for which an asymptotic analytical solution is obtained. The electromagnetic emission/absorption model is based on Schwarzschild's equation and on Mie's theory for disperse particles, and we assume that particles are coarser than the radiation wavelength (about 10 μm) and that scattering is negligible. In the inversion procedure, model parameter space is sampled to find the optimal set of input conditions which minimizes the difference between the experimental and the synthetic image. Application of the inversion procedure to an ash plume at Santiaguito (Santa Maria volcano, Guatemala) has allowed us to retrieve the main plume input parameters, namely mass flow rate, initial radius, velocity, temperature, gas mass ratio, entrainment coefficient and their related uncertainty. Moreover, by coupling with the electromagnetic model we have been able to obtain a reliable estimate of the equivalent Sauter diameter of the total particle size distribution. The presented method is general and, in principle, can be applied to the spatial distribution of particle concentration and temperature obtained by any fluid-dynamic model, either integral or multidimensional, stationary or time-dependent, single or multiphase. The method discussed here is fast and robust, thus indicating potential for applications to real-time estimation of ash mass flux and particle size distribution, which is crucial for model-based forecasts of the volcanic ash dispersal process.422 106 - PublicationOpen AccessDestructiveness of pyroclastic surges controlled by turbulent fluctuations(2021)
; ; ; ; ; ; ; ; ; ;; ; ; ; ;Pyroclastic surges are lethal hazards from volcanoes that exhibit enormous destructiveness through dynamic pressures of 100–102 kPa inside flows capable of obliterating reinforced buildings. However, to date, there are no measurements inside these currents to quantify the dynamics of this important hazard process. Here we show, through large-scale experiments and the first field measurement of pressure inside pyroclastic surges, that dynamic pressure energy is mostly carried by large-scale coherent turbulent structures and gravity waves. These perpetuate as low-frequency high-pressure pulses downcurrent, form maxima in the flow energy spectra and drive a turbulent energy cascade. The pressure maxima exceed mean values, which are traditionally estimated for hazard assessments, manifold. The fre- quency of the most energetic coherent turbulent structures is bounded by a critical Strouhal number of ~0.3, allowing quantitative predictions. This explains the destructiveness of real- world flows through the development of c. 1–20 successive high-pressure pulses per minute. This discovery, which is also applicable to powder snow avalanches, necessitates a re- evaluation of hazard models that aim to forecast and mitigate volcanic hazard impacts globally.187 12 - PublicationOpen AccessOn floating point precision in computational fluid dynamics using OpenFOAM(2024)
; ; ; ; ; ; ; ; ; ; ; Thanks to the computational power of modern cluster machines, numerical simulations can provide, with an unprecedented level of details, new insights into fluid mechanics. However, taking full advantage of this hardware remains challenging since data communication remains a significant bottleneck to reaching peak performances. Reducing floating point precision is a simple and effective way to reduce data movement and improve the computational speed of most applications. Nevertheless, special care needs to be taken to ensure the quality and convergence of computed solutions, especially when dealing with complex fluid simulations. In this work, we analyse the impact of reduced (single and mixed compared to double) precision on computational performance and accuracy for computational fluid dynamics. Using the open source library OpenFOAM, we consider incompressible, compressible, and multiphase fluid solvers for testing on relevant benchmarks for flows in the laminar and turbulent regime and in the presence of shock waves. Computational gain and changes in the scalability of applications in reduced precision are also discussed. In particular, an ad hoc theoretical model for the strong scaling allows us to interpret and understand the observed behaviours, as a function of floating point precision and hardware specifics. Finally, we show how reduced precision can significantly speed up a hybrid CPU–GPU implementation, made available to OpenFOAM end-users recently, that simply relies on a GPU linear algebra solver developed by hardware vendors.44 19 - PublicationOpen AccessTsunami risk management for crustal earthquakes and non-seismic sources in Italy(2021)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ; ; ;; ;; ; ; ;; ; ;; ; ;; ; Destructive tsunamis are most often generated by large earthquakes occurring at subduction interfaces, but also other “atypical” sources—defined as crustal earthquakes and non-seismic sources altogether—may cause significant tsunami threats. Tsunamis may indeed be generated by different sources, such as earthquakes, submarine or coastal landslides, volcano-related phenomena, and atmospheric perturbations. The consideration of atypical sources is important worldwide, but it is especially prominent in complex tectonic settings such as the Mediterranean, the Caribbean, or the Indonesian archipelago. The recent disasters in Indonesia in 2018, caused by the Palu-Sulawesi magnitude Mw 7.5 crustal earthquake and by the collapse of the Anak-Krakatau volcano, recall the importance of such sources. Dealing with atypical sources represents a scientific, technical, and computational challenge, which depends on the capability of quantifying and managing uncertainty efficiently and of reducing it with accurate physical modelling. Here, we first introduce the general framework in which tsunami threats are treated, and then we review the current status and the expected future development of tsunami hazard quantifications and of the tsunami warning systems in Italy, with a specific focus on the treatment of atypical sources. In Italy, where the memory of historical atypical events like the 1908 Messina earthquake or the relatively recent 2002 Stromboli tsunami is still vivid, specific attention has been indeed dedicated to the progressive development of innovative strategies to deal with such atypical sources. More specifically, we review the (national) hazard analyses and their application for coastal planning, as well as the two operating tsunami warning systems: the national warning system for seismically generated tsunamis (SiAM), whose upstream component—the CAT-INGV—is also a Tsunami Service Provider of the North-eastern Atlantic, the Mediterranean and connected seas Tsunami Warning System (NEAMTWS) coordinated by the Intergovernmental Coordination Group established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO, and the local warning system for tsunamis generated by volcanic slides along the Sciara del Fuoco of Stromboli volcano. Finally, we review the state of knowledge about other potential tsunami sources that may generate significant tsunamis for the Italian coasts, but that are not presently considered in existing tsunami warning systems. This may be considered the first step towards their inclusion in the national tsunami hazard and warning programs.1187 102 - PublicationOpen AccessPerformance Comparison of CFD Microbenchmarks on Diverse HPC Architectures(2024-05)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ;OpenFOAM is a CFD software widely used in both industry and academia. The exaFOAM project aims at enhancing the HPC scalability of OpenFOAM, while identifying its current bottlenecks and proposing ways to overcome them. For the assessment of the software components and the code profiling during the code development, lightweight but significant benchmarks should be used. The answer was to develop microbenchmarks, with a small memory footprint and short runtime. The name microbenchmark does not mean that they have been prepared to be the smallest possible test cases, as they have been developed to fit in a compute node, which usually has dozens of compute cores. The microbenchmarks cover a broad band of applications: incompressible and compressible flow, combustion, viscoelastic flow and adjoint optimization. All benchmarks are part of the OpenFOAM HPC Technical Committee repository and are fully accessible. The performance using HPC systems with Intel and AMD processors (x86_64 architecture) and Arm processors (aarch64 architecture) have been benchmarked. For the workloads in this study, the mean performance with the AMD CPU is 62% higher than with Arm and 42% higher than with Intel. The AMD processor seems particularly suited resulting in an overall shorter time-to-solution.35 4 - PublicationOpen AccessThe Transition From Eruption Column to Umbrella CloudWe present a coflowing integral plume model for the transition from an eruption column to an umbrella cloud. This transition occurs above the level of neutral buoyancy where the rising plume is surrounded by a descending annulus. We model this transition by extending the coflowing integral plume model of Bloomfield and Kerr (2000, https://doi.org/10.1029/2018JB015841), which was originally developed for Boussinesq fountains, to volcanic plumes. In addition to the transition region, the new model includes the part of the eruption column below the level of neutral buoyancy. The eruption column and the transition to an umbrella cloud are treated as a continuous process from the vent upward. Equations for the variation with height of the mass, momentum, enthalpy, and moisture fluxes are presented for both the upward and downward plumes. The interaction between the upward and downward plumes is accounted for by two entrainment relations: from the upward to the downward plume and vice versa; entrainment from the environment into the downward plume (or the upward plume in the absence of a downward plume) is also accounted for. The model is applied to the two eruptions considered by Costa et al. (2016, https://doi.org/10.1016/j.jvolgeores.2016.01.017) for the volcanic-plume intercomparison study. Profiles of the mass and momentum fluxes are compared with those from an equivalent large-eddy simulation. The new model captures the order of magnitude of the fluxes, the relative magnitudes of the upward and downward fluxes and aspects of the profiles’ shape. In particular, the upward plume reaches a maximum before decreasing toward the top of the plume consistent with the large-eddy simulation plume.
64 12 - PublicationRestrictedModeling the dynamics of a geothermal reservoir fed by gravity driven flow through overstanding saturated rocks(2012-03-30)
; ; ;Cerminara, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Pisa, Pisa, Italia ;Fasano, A.; We formulate a mathematical model for a geothermal basin with an idealized geometry characterized by: (1) radial symmetry around an extracting well (or a cluster of wells), (2) a relatively thin horizontal fractured layer lying underneath a low permeability, low porosity rock layer, saturated with water. Vaporization is allowed only at the boundary of the extracting well (or well cluster). The model is based on the assumption that the flow from the reservoir to the well is fed by a gravity driven flow through the overstanding rocks. Despite the various simplifying assumptions, the resulting mathematical problem is considerably difficult also because we consider the effect of thermal expansion and thermal variation of viscosity. Though there is no evidence that the assumed configuration of the basin approaches the structure of a known geothermal field, the results obtained match with surprising accuracy the data of a specific field in the Mt. Amiata area (data kindly provided by ENEL Green Power through Tuscany Region).446 92 - PublicationOpen AccessASHEE-1.0: a compressible, equilibrium-Eulerian model for volcanic ash plumes(2016)
; ; ; ; ; A new fluid-dynamic model is developed to nu- merically simulate the non-equilibrium dynamics of polydisperse gas–particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model, valid for low-concentration regimes (particle volume frac- tion less than 10−3) and particle Stokes number (St – i.e., the ratio between relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capa- bility to describe gas–particle non-equilibrium effects. Direct Numerical Simulation accurately reproduces the dynamics of isotropic, compressible turbulence in subsonic regimes. For gas–particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of high-Reynolds number and high-temperature regimes in the presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to repro- duce the averaged and instantaneous flow properties. In par- ticular, the self-similar Gaussian radial profile and the de- velopment of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of the important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal and maximum plume height. For very fine particles (St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and prefer- entially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas–particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.202 22 - PublicationOpen AccessAsh plume properties retrieved from infrared images: a forward and inverse modeling approach(2015)
; ; ; ; ;Cerminara, M.; Scuola Normale Superiore, Pisa (Italy) ;Esposti Ongaro, T.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Pisa, Pisa, Italia ;Valade, S.; Università di Firenze, Dip.to di Scienze della Terra (Italy) ;Harris, A. J. L.; Université Blaise-Pascal, Clermont-Ferrand (FR); ; ;We present a coupled fluid-dynamic and electromagnetic model for volcanic ash plumes. In a forward approach, the model is able to simulate the plume dynamics from prescribed input flow conditions and generate the corresponding synthetic thermal infrared (TIR) image, allowing a comparison with field-based observations. An inversion procedure is then developed to retrieve ash plume properties from TIR images. The adopted fluid-dynamic model is based on a one-dimensional, stationary description of a self-similar (top-hat) turbulent plume, for which an asymptotic analytical solution is obtained. The electromagnetic emission/absorption model is based on the Schwarzschild's equation and on Mie's theory for disperse particles, assuming that particles are coarser than the radiation wavelength and neglecting scattering. In the inversion procedure, model parameters space is sampled to find the optimal set of input conditions which minimizes the difference between the experimental and the synthetic image. Two complementary methods are discussed: the first is based on a fully two-dimensional fit of the TIR image, while the second only inverts axial data. Due to the top-hat assumption (which overestimates density and temperature at the plume margins), the one-dimensional fit results to be more accurate. However, it cannot be used to estimate the average plume opening angle. Therefore, the entrainment coefficient can only be derived from the two-dimensional fit. Application of the inversion procedure to an ash plume at Santiaguito volcano (Guatemala) has allowed us to retrieve the main plume input parameters, namely the initial radius $b_0$, velocity $U_0$, temperature $T_0$, gas mass ratio $n_0$, entrainment coefficient $k$ and their related uncertainty. Moreover, coupling with the electromagnetic model, we have been able to obtain a reliable estimate of the equivalent Sauter diameter $d_s$ of the total particle size distribution. The presented method is general and, in principle, can be applied to the spatial distribution of particle concentration and temperature obtained by any fluid-dynamic model, either integral or multidimensional, stationary or time-dependent, single or multiphase. The method discussed here is fast and robust, thus indicating potential for applications to real-time estimation of ash mass flux and particle size distribution, which is crucial for model-based forecasts of the volcanic ash dispersal process.410 281