Introducing passive matched field acoustic tomography

In acoustic tomography sea-basin environmental parameters such as temperature profiles and current-velocities are derived, when ray propagation models are adopted, by the travel time estimates relative to the identifiable ray paths. The transmitted signals are either single frequency, or impulsive, or intermittent and deterministic. When the wavelength is comparable with the scale lengths present in the propagation scenario, Matched Field Tomography (MFT) is used, entailing the consideration of waveguide modes instead of rays. A new concept in tomography is introduced in the paper, that employs passively the noise emitted by ships of opportunity (cargoes, ferries) as source signals. The passive technique is acoustic-pollution-free, and if a basin is selected in which a regular ship traffic occurs data can be received on a regular schedule, with no transmission cost. A novel array pre-processor for passive tomography is introduced, such that the signal structure at the pre-processor output is nearly the same as that obtainable in the case of single-frequency source signals. Hence, at the pre-processor output all the tomographic inversion methods valid for active tomography employing single-frequency sources can be applied. The differences between active and passive tomography are pointed out and the potential of passive techniques is illustrated by simple propagation scenarios adopting either rays or waveguide modes

Probabilistic prediction of Dst storms one-day-ahead using Full-Disk SoHO Images

We present a new model for the probability that the Disturbance storm time (Dst) index exceeds -100 nT, with a lead time between 1 and 3 days. $Dst$ provides essential information about the strength of the ring current around the Earth caused by the protons and electrons from the solar wind, and it is routinely used as a proxy for geomagnetic storms. The model is developed using an ensemble of Convolutional Neural Networks (CNNs) that are trained using SoHO images (MDI, EIT and LASCO). The relationship between the SoHO images and the solar wind has been investigated by many researchers, but these studies have not explicitly considered using SoHO images to predict the $Dst$ index. This work presents a novel methodology to train the individual models and to learn the optimal ensemble weights iteratively, by using a customized class-balanced mean square error (CB-MSE) loss function tied to a least-squares (LS) based ensemble. The proposed model can predict the probability that Dst<-100 nT 24 hours ahead with a True Skill Statistic (TSS) of 0.62 and Matthews Correlation Coefficient (MCC) of 0.37. The weighted TSS and MCC from Guastavino et al. (2021) is 0.68 and 0.47, respectively. An additional validation during non-Earth-directed CME periods is also conducted which yields a good TSS and MCC score.Comment: accepted by journal <Space Weather

Characterizing the cardiovascular functions during atrial fibrillation through lumped-parameter modeling

Atrial fibrillation (AF), causing irregular and rapid heartbeats, is the most common arrhythmia. Due to the widespread impact on the population and the disabling symptoms related to rapid heart rate, AF is a subject of growing interest under several aspects: statistical analyses on the heartbeat distributions, risk factors, impact on quality of life, correlation with other cardiac pathologies. However, several key points on the consequences induced by AF on the cardiovascular system are still not completely understood. The proposed work aims at quantifying the impact of AF on the most relevant cardiovascular parameters by means of a lumped-parameter modeling, paying particular attention to the stochastic nature of the irregular heartbeats and the reduced contractility of the heart. The global response leads to a rather impressive overall agreement with the clinical state-of-the-art measures regarding AF: reduced cardiac output with correlated arterial hypotension, as well as higher left atrial volume and pressure values are some of the most representative outcomes emerging during AF. Moreover, new insights on hemodynamic parameters such as cardiac flow rates, which are difficult to measure and almost never offered in literature, are here provided

River bedform inception by flow unsteadiness: a modal and nonmodal analysis

River bedforms arise as a result of morphological instabilities of the stream-sediment interface. Dunes and antidunes constitute the most typical patterns, and their occurrence and dynamics are relevant for a number of engineering and environmental applications. Although flow variability is a typical feature of all rivers, the bedform-triggering morphological instabilities have generally been studied under the assumption of a constant flow rate. In order to partially address this shortcoming, we here discuss the influence of (periodic) flow unsteadiness on bedform inception. To this end, our recent one-dimensional validated model coupling Dressler's equations with a refined mechanistic sediment transport formulation is adopted, and both the asymptotic and transient dynamics are investigated by modal and nonmodal analyses

Adaptive selection of sampling points for uncertainty quantification

We present a simple and robust strategy for the selection of sampling points in Uncertainty Quantification. The goal is to achieve the fastest possible convergence in the cumulative distribution function of a stochastic output of interest. We assume that the output of interest is the outcome of a computationally expensive nonlinear mapping of an input random variable, whose probability density function is known. We use a radial function basis to construct an accurate interpolant of the mapping. This strategy enables adding new sampling points one at a time, adaptively. This takes into full account the previous evaluations of the target nonlinear function. We present comparisons with a stochastic collocation method based on the Clenshaw-Curtis quadrature rule, and with an adaptive method based on hierarchical surplus, showing that the new method often results in a large computational saving.Comment: 22 pages, 15 figures; to appear in Int. J. Uncertainty Quantificatio

Hierarchy of models for meandering rivers and related morphodynamic processes

We review the importance of the physical mechanisms involved in river meandering by comparing some existing linear models and extensions thereof. Such models are hierarchically derived from a common and general mathematical framework and then analyzed with a detailed discussion of the physical processes and relevant hypotheses that are involved. Experiments and field data are also used to discuss the related morphodynamic processes. The analysis of the models shows the importance of the closure of secondary currents especially in the modeling of eddy viscosity. This aspect confirms the usefulness of using simplified models for some practical applications, provided the secondary currents are modeled in detail. On the other hand, the free response of the sediments, the phase lag of secondary currents, and the momentum redistribution due to the coupling between the main and the transverse flow are shown to be less relevant. Hence the second-order models, which neglect the effect of superelevation induced by the topography-driven lateral flow on the longitudinal flow, can reasonably be considered a good approximation for both predictive analysis and the computation of the resonant conditions. Finally, the analysis of higher harmonics suggests that the multilobed pattern can intrinsically be present in both second- and fourth-order models

Hybrid solar-biomass combined Brayton/organic Rankine-cycle plants integrated with thermal storage: Techno-economic feasibility in select Mediterranean areas

This paper presents a thermodynamic analysis and techno-economic assessment of a novel hybrid solar-biomass power-generation system configuration composed of an externally fired gas-turbine (EFGT) fuelled by biomass (wood chips) and a bottoming organic Rankine cycle (ORC) plant. The main novelty is related to the heat recovery from the exhaust gases of the EFGT via thermal energy storage (TES), and integration of heat from a parabolic-trough collectors (PTCs) field with molten salts as a heat-transfer fluid (HTF). The presence of a TES between the topping and bottoming cycles facilitates the flexible operation of the system, allows the system to compensate for solar energy input fluctuations, and increases capacity factor and dispatchability. A TES with two molten salt tanks (one cold at 200 °C and one hot at 370 °C) is chosen. The selected bottoming ORC is a superheated recuperative cycle suitable for heat conversion in the operating temperature range of the TES. The whole system is modelled by means of a Python-based software code, and three locations in the Mediterranean area are assumed in order to perform energy-yield analyses: Marseille in France, Priolo Gargallo in Italy and Rabat in Morocco. In each case, the thermal storage that minimizes the levelized cost of energy (LCE) is selected on the basis of the estimated solar radiation and CSP size. The results of the thermodynamic simulations, capital and operational costs assessments and subsidies (feed-in tariffs for biomass and solar electricity available in the Italian framework), allow estimating the global energy conversion efficiency and the investment profitability in the three locations. Sensitivity analyses of the biomass costs, size of PTCs, feed-in tariff and share of cogenerated heat delivered to the load are also performed. The results show that the high investment costs of the CSP section in the proposed size range and hybridization configuration allow investment profitability only in the presence of a dedicated subsidy framework such as the one available in the Italian energy market. In particular, the LCE of the proposed system is around 140 Eur/MWh (with the option to discharge the cogenerated heat) and the IRR is around 15%, based on the Italian electricity subsidy tariffs. The recovery of otherwise discharged heat to match thermal energy demand can significantly increase the investment profitability and compensate the high investment costs of the proposed technology

Coherent structures and spectral energy transfer in turbulent plasma: A space-filter approach

Plasma turbulence at scales of the order of the ion inertial length is mediated by several mechanisms, including linear wave damping, magnetic reconnection, the formation and dissipation of thin current sheets, and stochastic heating. It is now understood that the presence of localized coherent structures enhances the dissipation channels and the kinetic features of the plasma. However, no formal way of quantifying the relationship between scale-to-scale energy transfer and the presence of spatial structures has been presented so far. In the Letter we quantify such a relationship analyzing the results of a two-dimensional high-resolution Hall magnetohydrodynamic simulation. In particular, we employ the technique of space filtering to derive a spectral energy flux term which defines, in any point of the computational domain, the signed flux of spectral energy across a given wave number. The characterization of coherent structures is performed by means of a traditional two-dimensional wavelet transformation. By studying the correlation between the spectral energy flux and the wavelet amplitude, we demonstrate the strong relationship between scale-to-scale transfer and coherent structures. Furthermore, by conditioning one quantity with respect to the other, we are able for the first time to quantify the inhomogeneity of the turbulence cascade induced by topological structures in the magnetic field. Taking into account the low space-filling factor of coherent structures (i.e., they cover a small portion of space), it emerges that 80% of the spectral energy transfer (both in the direct and inverse cascade directions) is localized in about 50% of space, and 50% of the energy transfer is localized in only 25% of space