13 research outputs found
Multiple resolution surface wave tomography: the Mediterranean basin
No full textFrom a large set of fundamental-mode surface wave phase velocity observations, we map the transversely isotropic lateral heterogeneities in the upper-mantle shear velocity structure. We design a multiple resolution inversion procedure, which allows us to parametrize any selected region more finely than the rest of the globe. We choose, as a high-resolution region, the upper mantle underlying the Mediterranean basin. We formulate the inverse problem as in a previous paper by Boschi & Ekstrom, calculating regional JWKB (Jeffreys-Wentzel-Kramers-Brillouin) surface wave sensitivity kernels for each pixel of a 2degrees x 2degrees starting model, including the high-resolution global crustal map Crust 2.0. We find that the available surface wave data can resolve the most important geophysical features of the region of interest, providing a reliable image of intermediate spatial wavelength. RI Ekstrom, Goran/C-9771-201
Multiple resolution surface wave tomography: the Mediterranean basin
No full textFrom a large set of fundamental-mode surface wave phase velocity observations, we map the transversely isotropic lateral heterogeneities in the upper-mantle shear velocity structure. We design a multiple resolution inversion procedure, which allows us to parametrize any selected region more finely than the rest of the globe. We choose, as a high-resolution region, the upper mantle underlying the Mediterranean basin. We formulate the inverse problem as in a previous paper by Boschi & Ekström, calculating regional JWKB (Jeffreys-Wentzel-Kramers-Brillouin) surface wave sensitivity kernels for each pixel of a 2°× 2° starting model, including the high-resolution global crustal map Crust 2.0. We find that the available surface wave data can resolve the most important geophysical features of the region of interest, providing a reliable image of intermediate spatial wavelengt
Structure and evolution of the intracratonic Congo Basin
No full textSurface wave tomography, heat flow, and crustal thickness measurements have demonstrated that the thickness of the continental lithosphere varies by at least a factor of 2. Since the thermal time constant of the lithosphere depends upon the square of its thickness, subsidence records of extensional sedimentary basins offer a potential way of extending these observations into the past. Here we examine the Congo basin, a large and iconic intracratonic sedimentary basin in Central Africa. This roughly circular basin covers an area in excess of 1.4 × 106 km2 with more than 5 km thickness of sedimentary rocks, the oldest parts of which are late Precambrian in age. First, we assess the thickness of the lithosphere. We have estimated its thickness across Africa using maps of shear wave velocity obtained by inversion of fundamental and higher-mode surface waveforms. The Congo Basin sits on 220 ± 30 km thick lithosphere and appears to be part of a southern core to the continent encompassing both Archean cratons and Proterozoic mobile belts. This thickness is consistent with published estimates from kimberlites. Reappraisal of legacy seismic reflection images demonstrates that the sedimentary section is underlain by a Late Precambrian rift zone and that the basin is still subsiding today. Subsidence modeling of two deep wells is consistent with uniform extension and cooling of the lithosphere by a factor of 1.2 during latest Precambrian and Cambrian time; we argue that the exceptional 0.55 Ga history of the basin is a direct consequence of the lithospheric thermal time constant being a factor of 4 longer than normal. Today, the basin coincides with a long-wavelength −30 to −40 mGal gravity anomaly. We interpret this gravity anomaly as the surficial manifestation of 400–600 m of recent mantle convective drawdown in response to the onset of upwelling plumes around the flanks of the southern African continent. The alternative explanation, that it is the static manifestation of locally thick lithosphere, is inconsistent with global trends of mantle density depletion. Our interpretation is consistent with fast seismic velocities observed throughout the sublithospheric upper mantle underneath the basin and recent geodynamic modeling
3D reconstruction of an inertial-confinement fusion implosion with neural networks using multiple heterogeneous data sources
No full textSubmitted for publication in Review of Scientific Instruments3D asymmetries are major degradation mechanisms in inertial-confinement fusion implosions at the National Ignition Facility (NIF). These asymmetries can be diagnosed and reconstructed with the neutron imaging system (NIS) on three lines of sight around the NIF target chamber. Conventional tomographic reconstructions are used to reconstruct the 3D morphology of the implosion using NIS [Volegov et al., J. Appl. Phys. 127, 083301 (2020)], but the problem is ill-posed with only three imaging lines of sight. Asymmetries can also be diagnosed with the real-time neutron activation diagnostics (RTNAD) and the neutron time-of-flight (nToF) suite. Since the NIS, RTNAD, and nToF each sample a different part of the implosion using different physical principles, we propose that it is possible to overcome the limitations of too few imaging lines of sight by performing 3D reconstructions that combine information from all three heterogeneous data sources. This work presents a new machine learning-based reconstruction technique to do just this. By using a simple physics model and group of neural networks to map 3D morphologies to data, this technique can easily account for data of multiple different types. A simple proof-of-principle is presented, demonstrating that this technique can accurately reconstruct a hot-spot shape using synthetic primary neutron images and a hot-spot velocity vector. In particular, the hot-spot’s asymmetry, quantified as spherical harmonic coefficients, is reconstructed to within ±4% of the radius in 90% of test cases. In the future, this technique will be applied to actual NIS, RTNAD, and nToF data to better understand 3D asymmetries at the NIF
The data-driven future of high energy density physics
No full textHigh-energy-density physics is the field of physics concerned with studying matter at extremely high temperatures and densities. Such conditions produce highly nonlinear plasmas, in which several phenomena that can normally be treated independently of one another become strongly coupled. The study of these plasmas is important for our understanding of astrophysics, nuclear fusion and fundamental physics—however, the nonlinearities and strong couplings present in these extreme physical systems makes them very difficult to understand theoretically or to optimize experimentally. Here we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proved far too nonlinear for human researchers. From a fundamental perspective, our understanding can be improved by the way in which machine learning models can rapidly discover complex interactions in large datasets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to approximately daily), thus moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we suggest proposals for the community in terms of research design, training, best practice and support for synthetic diagnostics and data analysis
Vers une tomographie haute résolution du manteau inférieur terrestre
No full textLa couche D" est une des zones les plus hétérogène de la Terre, abritant des structures mal comprises, probablement à l'origine de la dynamique globale du manteau. Les méthodes actuelles de tomographie sismique ne résolvent pas correctement cette région. La résolution des images de la structure interne de la Terre est fortement liée à la localisation précise des séismes, ainsi qu'à la connaissance du contenu fréquentiel des ondes sismiques. Cette thèse a pour objectif la construction d'une base de données globale de temps de trajet des ondes, mesures utilisées pour l'élaboration des images tomographiques. Notre méthode utilise une détermination plus précise de la profondeur des séismes permettant d'améliorer la mesure des temps de trajet. Pour une meilleure évaluation du contenu fréquentiel, ces mesures sont réalisées dans plusieurs gammes de fréquence. Une nouvelle approche de calcul de corrections visant à éliminer la complexité de la croûte est également présentée. Enfin, une imagerie préliminaire est présentée aux échelles régionale et globale sous l'approximation de la théorie des rais, avant une description plus complète par l'approximation de Born.The D" layer is one of Earth's most heterogeneous location, hosting poorly understood features, which are most likely linked to the global dynamics of the mantle. Present days tomographic approaches cannot resolve correctly this area. The resolution of images from Earth's inner structure is strongly linked to precisely localizing earthquakes, and to have a good knowlegde of the frequency content of seismic waves. This thesis aims at building a global database of seismic travel times, data used for the development of tomographic images. Our method uses a more precise determination of the depths of earthquakes, allowing an improvement in measuring travel times. To a better evaluation of the frequency content, these measurements are performed in several frequency bands. A new approach for the computation of corrections to the complexity of the crust is presented as well. Finally, a preliminary imaging is presented, at regional and global scale, under the approximation of the ray theory, before a more complete description under Born approximation
Surface wave tomography in the european and mediterranean region
No full textThe broad European and Mediterranean region is characterized by an extremely com-
plex tectonic setting, driven by the ma jor convergence between Eurasian and African
plates. A detailed model of the upper mantle in this region is fundamental to improve
our understanding of its geodynamical evolution. Seismic tomography can help to ad-
dress this problem modeling seismic speed anomalies, that can be related to different
tectonic features, such as continental roots, rifting areas, magmatic provinces, plumes
or subducting slabs. Due to high seismicity rates and dense seismograph coverage, this
region has been the sub ject of many tomographic studies from regional to local scale.
Traveltime high resolution models of P-wave speed anomalies [Spakman et al., 1993;
Piromal lo and Morel li , 2003] have illuminated the deep structure of the mantle, but
at shallow depth they often suffer from uneven ray coverage, being strongly dependent
on station and epicenter distribution. Regional S-wave velocity models have been re-
trieved from the analysis of surface wave group or phase velocity [Ritzwol ler and Levshin ,
1998; Vil lase˜
nor et al., 2001], from waveform inversion of surface waves [Marquering and
Snieder , 1996] or both surface and body waves [Marone et al., 2004]. However, the
non-optimal distribution of observatories and seismic sources has affected regional to-
mographic models. Global models derived from surface wave data image the large-scale
structures of the region, but their resolution is insufficient to describe its complexity
[Shapiro and Ritzwol ler , 2002; Boschi and Ekstr¨
om , 2002; Ritsema et al., 1999; Zhou
et al., 2006; Trampert and Woodhouse , 1995]. Global models with finer parameteriza-
tion on Mediterranean [Boschi et al., 2004] have been proposed and recent modeling of
surface waves from ambient noise gave new insights into the shallowest European upper
mantle [Yang et al., 2006].
The increased availability of high quality seismic records from permanent observato-
ries and from the recent temporary deployment RETREAT in the Northern Apennines
gave us the opportunity to exploit new data, that can provide new and finer constraints
to the tomographic problem. We present in this thesis a new surface wave tomography
study, aimed at exploiting the high sensitivity of these waves to shallow structure and
their wide spatial coverage in the complex sources-stations distribution of the European
and Mediterranean domain.
The inverse problem of obtaining a VS three-dimensional model from analysis of
surface wave can be solved in different ways. [Marone et al., 2004] use the partitioned
waveform inversion of [Van der Lee and Nolet , 1997], where the 1-D average S-velocity
structure along each path is first determined by non-linear waveform fitting, and in a
second step the 1-D path averaged structures are combined in a damped least-squares
linear inversion for a 3-D S-velocity model. [Shapiro and Ritzwol ler , 2002] in a first
step estimate 2-D dispersion maps with a linear tomographic inversion of path average
fundamental mode group and phase velocities, and afterwards apply a Monte-Carlo
method to perform the non-linear inversion of the dispersion curves at each geographical
point and retrieve the 3-D shear-velocity model. [Boschi and Ekstr¨om , 2002] carry
out a single non-linear inversion of phase anomaly measurements making use of JWKB
ray-theoretical sensitivity kernels computed in a reference 3-D model. [Zhou et al.,
2006] invert long period fundamental mode phase delays with finite-frequency 3-D Born
approximation kernels, calculated in a reference 1-D model. We will proceed with a 2
steps scheme, first inverting group path averaged speeds for a regionalized group velocity
model assuming a linearized ray theoretical wave propagation. In a second step, we will
use the group velocity maps as data to perform a non-linear iterative depth inversion for
the local 1-D structure, accounting for the lateral variations of the Crust.
This thesis presents a new model along with a discussion of the robustness and
resolution of its main features. We will firstly present the group velocity measurement
technique and an analysis of measurement errors (Chapter 2), then we will introduce
the linear inversion of the regional data starting from a reference global model, with an
accurate examination of the implication of different regularization constraints (Chapter
3). Group velocity maps will then be shown and discussed. Subsequently we will invert
the group velocity for the Vs structure of upper mantle (Chapter 4). Our resulting 3-D
radially anisotropic model will be discussed in detail and compared with other published
global and regional models.Universita' di BolognaPublished3.3. Geodinamica e struttura dell'interno della Terraope
2022 Review of Data-Driven Plasma Science
No full textData-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required
The impact of low-mode symmetry on inertial fusion energy output in the burning plasma state
No full textAbstract Indirect Drive Inertial Confinement Fusion Experiments on the National Ignition Facility (NIF) have achieved a burning plasma state with neutron yields exceeding 170 kJ, roughly 3 times the prior record and a necessary stage for igniting plasmas. The results are achieved despite multiple sources of degradations that lead to high variability in performance. Results shown here, for the first time, include an empirical correction factor for mode-2 asymmetry in the burning plasma regime in addition to previously determined corrections for radiative mix and mode-1. Analysis shows that including these three corrections alone accounts for the measured fusion performance variability in the two highest performing experimental campaigns on the NIF to within error. Here we quantify the performance sensitivity to mode-2 symmetry in the burning plasma regime and apply the results, in the form of an empirical correction to a 1D performance model. Furthermore, we find the sensitivity to mode-2 determined through a series of integrated 2D radiation hydrodynamic simulations to be consistent with the experimentally determined sensitivity only when including alpha-heating
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The impact of low-mode symmetry on inertial fusion energy output in the burning plasma state.
No full textIndirect Drive Inertial Confinement Fusion Experiments on the National Ignition Facility (NIF) have achieved a burning plasma state with neutron yields exceeding 170 kJ, roughly 3 times the prior record and a necessary stage for igniting plasmas. The results are achieved despite multiple sources of degradations that lead to high variability in performance. Results shown here, for the first time, include an empirical correction factor for mode-2 asymmetry in the burning plasma regime in addition to previously determined corrections for radiative mix and mode-1. Analysis shows that including these three corrections alone accounts for the measured fusion performance variability in the two highest performing experimental campaigns on the NIF to within error. Here we quantify the performance sensitivity to mode-2 symmetry in the burning plasma regime and apply the results, in the form of an empirical correction to a 1D performance model. Furthermore, we find the sensitivity to mode-2 determined through a series of integrated 2D radiation hydrodynamic simulations to be consistent with the experimentally determined sensitivity only when including alpha-heating
