In this paper we present the extension of a full-wave FEM model (COMSOL®+MATLAB®) - initially developed to compute the electromagnetic field in presence of the anisotropic inhomogeneous plasma of the Electron Cyclotron Resonance Ion Sources (ECRISs) [1] - to the Ion Cyclotron Range of Frequency (ICRF). The model - based on the full non-uniform dielectric tensor in "cold plasma" approximation - has been employed to study antenna geometries of increasing complexity. Various antenna types have been analyzed, starting from single flat strap up to the two straps of an antenna option considered for the Divertor Tokamak Test facility (DTT) [2]. The results have been compared, cross-checked and validated with a simpler COMSOL-based tool [3] and with the TOPICA code [4].

In recent years, a new tomographic inversion method based on the Maximum Likelihood (ML) approach has been adapted to JET bolometry. Apart from its accuracy and reliability, the key advantage is its ability to provide reliable estimates of the uncertainties in the reconstructions. The original algorithm was implemented and validated using the MATLAB software tool. This work presents the accelerated version of the algorithm implemented using a compatible ITER fast controller platform with the Ubuntu 18.04 or the ITER Codac Core System distributions (6.1.2). The algorithm has been implemented in C++ using the open-source libraries: ArrayFire, ALGLIB, and MATIO. These libraries simplify the management of specific hardware accelerators such as GPUs and increase performance. The speed-up factor obtained is approximately 10 times. The work presents the methodology followed, the results obtained, and the advantages and drawbacks of implementation.

Matrices with hierarchical low-rank structure, including HODLR and HSS matrices, constitute a versatile tool to develop fast algorithms for addressing large-scale problems. While existing software packages for such matrices often focus on linear systems, their scope of applications is in fact much wider and includes, for example, matrix functions and eigenvalue problems. In this work, we present a new MATLAB toolbox called hm-toolbox, which encompasses this versatility with a broad set of tools for HODLR and HSS matrices, unmatched by existing software. While mostly based on algorithms that can be found in the literature, our toolbox also contains a few new algorithms as well as novel auxiliary functions. Being entirely based on MATLAB, our implementation does not strive for optimal performance. Nevertheless, it maintains the favorable complexity of hierarchical low-rank matrices and offers, at the same time, a convenient way of prototyping and experimenting with algorithms. A number of applications illustrate the use of the hm-toolbox.

A reliable energy supply is fundamental to ensure energy security and support the mitigation of climate change by promoting the use of renewable sources and reducing carbon emissions. Energy system analysis provides a sound methodology to assess energy needs, allowing to investigate the energy system behavior and to individuate the optimal energy-technology configurations for the achievement of strategic energy and environmental policy targets. In this framework, the estimation of future trends of exogenous variables such as energy demand has a fundamental importance to obtain reliable and effective solutions, contributing remarkably to the accuracy of models' input data. This study illustrates an application of regression analysis to predict energy demand trends in end use sectors. The proposed procedure is applied to characterize statistically the relationships between population and gross domestic product (independent variables) and energy demands of Residential, Transport and Commercial in order to determine the energy demand trends over a long-term horizon. The effectiveness of linear and nonlinear regression models for energy demand forecasting has been validated by classical statistical tests. Energy demand projections have been tested as input data of the bottom-up TIMES model in two applications (the TIMES-Basilicata and TIMES-Italy models) confirming the validity of the forecasting approach. (C) 2020 Elsevier Ltd. All rights reserved.

Quasi Toeplitz (QT) matrix is a semi-infinite matrix of the kind $A=T(a)+E$ where $T(a)=(a_{j-i})_{i,j\in\mathbb Z^+}$, $E=(e_{i,j})_{i,j\in\mathbb Z^+}$ is compact and the norms $\lVert a\rVert_{\mathcal W} = \sum_{i\in\mathbb Z}|a_i|$ and $\lVert E \rVert_2$ are finite. These properties allow to approximate any QT-matrix, within any given precision, by means of a finite number of parameters. QT-matrices, equipped with the norm $\lVert A \rVert_{\mathcal QT}=\alpha\lVert a\rVert_{\mathcal{W}} \lVert E \rVert_2$, for $\alpha = (1+\sqrt 5)/2$, are a Banach algebra with the standard arithmetic operations. We provide an algorithmic description of these operations on the finite parametrization of QT-matrices, and we develop a MATLAB toolbox implementing them in a transparent way. The toolbox is then extended to perform arithmetic operations on matrices of finite size that have a Toeplitz plus low-rank structure. This enables the development of algorithms for Toeplitz and quasi-Toeplitz matrices whose cost does not necessarily increase with the dimension of the problem. Some examples of applications to computing matrix functions and to solving matrix equations are presented, and confirm the effectiveness of the approach.

California is located in one of the Earth's most tectonically active areas, where San Andreas fault system that crosses the state has provoked a series of major earthquakes. In addition, San Francisco has experienced a long history of such phenomena that almost destroyed the entire city in the past. In this paper we investigate the hydrological network and the tectonic setting of the San Francisco bay area (fig. 1) which includes a vast number of lakes, rivers and structural systems, among which the most tectonic active parts of San Andreas Fault, making it a quite interest case study. In order to achieve this information, a Digital Elevation Model (DEM) of San Francisco bay area was processed through ArcGIS and MATLAB softwares which allowed to obtain results such the hydrological network and fault system, while extracted maps and plots provided more specific information. These output showed the composite catchment of the study area which is a result of its complex and dense tectonic background that triggers a lot of seismic breakups.

Purpose - The purpose of this paper is to optimize the performance of an incinerator plant in terms of NO emissions and temperature of particles 2 s after the last air injection, which must be above 850°C as established from the Directive 2000/76/EC of the European Parliament and of the Council - December 4, 2000 on dioxins formation in waste incineration plants. Design/methodology/approach - Investigation ismade by coupling proper models developed within three commercial software environments: FLUENT, to reproduce the thermodynamic field inside the combustion chamber of the incinerator plant taken into account, MATLAB, to evaluate the position and temperatures of the particles 2 s after the last air injection, MODEFRONTIER, to change both the secondary air mass flow rate and the equivalent heat transfer coefficient of the refractory walls to fulfill the conflicting objectives of reducing the NO formation and increasing the mean gases temperature as required by the Directive. Findings - The investigations suggest that it is possible to create the conditions allowing the reduction of NO emissions and the fulfilment of the European limits. In particular, the obtained results suggest that increasing the overall mass flow rate of the secondary air and using a different refractory material on the walls, the environmental performance of the incinerator plant can be improved. Research limitations/implications - Many other parameters could be optimized and, at the same time, more detailed models could be used for the Computational Fluid Dynamics simulations. Moreover, also the energy generated at the plant would need a better investigation in order to understand if optimal conditions can be really achieved. Originality/value - The work covers new aspects of Waste-to-Energy (WtE) systems, since it deals with an optimization study of plant design and operating parameters. This kind of investigation allows not only to improve already existing technologies for WtE systems, but also to develop new ones.

This paper introduces PVID, an interactive application for performing parameter identification of both complete (5-parameter) and simplified (4-parameter) single-diode photovoltaic (PV) models. Two equations are presented that allow to perform on-line 4-parameter identification without exploiting iterative methods. They are useful, for example, to support a maximum power point tracking (MPPT) algorithm. On the other hand, the 5-parameter identification is based on an inherently iterative algorithm. User can interactively simulate the behavior of both models and compare their ability to reconstruct the current-voltage curve of the PV source. Moreover, since iterative methods could return a wrong solution, PVID also allows to select arbitrary initial conditions to verify their effect on the reconstruction of the current-voltage curve. Finally, the user can evaluate whether/how much the maximum power point moves when the initial conditions are varied. A verification of the effectiveness of the proposed tool against measured data of commercial PV modules is given. The proposed application can be advantageously applied for educational purpose to better understand the potential and the limitations of the different PV models and their parameter identification procedures. © 2014 IEEE.

A collection of MATLAB software to simulate: - multirobot systems behaviours (motion coordination and rendering using Robotic Toolbox) - inverse kinematic algorithms - interpolation algorithms - accuracy error propagation

Electrochemical Impedance Spectroscopy (EIS) has been widely used in biological studies like tissue and cells characterization, both in vivo and in vitro. The objective of this study was to investigate cells adhesion over a microelectrodes array by monitoring the electrical impedance. A comprehensive electrical model of the cell-electrode interface has been used to fit experimental data. The electrode surface coverage has been evaluated both with the variation of impedance measurements and with the variation of parameters extracted from the electrical model. A cover factor has been used in the model in order to quantify the presence of different number of cells over an electrode surface. © 2011 IEEE.

We obtain analytical formulas enabling automatic design procedures of circular Substrate Integrated Waveguide (SIW) resonators, assuming a prescribed resonance frequency fres. On the one hand, such formulas allow us to write flexible codes. On the other hand, they yield sharp estimates of the SIW geometrical parameters, which are subsequently passed as inputs to a Support Vector Regression Machine (SVRM), especially trained to make compensation. In particular, the SVRM uses such estimates to compute a further frequency f' res, possibly different from fres, and the overall process is restarted over and over through a feedback loop, until the relative error |fres - f'res|/fres is reduced under a given threshold. To validate the proposed approach, we finally compare the design outputs provided by its implementation in the Matlab environment with the results of HFSS simulations. © 2010 VSP.