Reliability Modeling and Improvement of Critical Infrastructures: Theory, Simulation, and Computational Methods

This dissertation presents a framework for developing data-driven tools to model and improve the performance of Interconnected Critical Infrastructures (ICIs) in multiple contexts. The importance of ICIs for daily human activities and the large volumes of data in continuous generation in modern industries grant relevance to research efforts in this direction. Chapter 2 focuses on the impact of disruptions in Multimodal Transportation Networks, which I explored from an application perspective. The outlined research directions propose exploring the combination of simulation for decision-making with data-driven optimization paradigms to create tools that may provide stakeholders with optimal policies for a wide array of scenarios and conditions. The flexibility of the developed simulation models, in combination with cutting-edge technologies, such as Deep Reinforcement Learning (DRL), sets the foundation for promising research efforts on the performance, analysis, and optimization of Inland Waterway Transportation Systems. Chapter 3 explores data-driven models for condition monitoring and prognostics, with a focus on using Deep Learning (DL) to predict the Remaining Useful Life of turbofan engines based on sequential sensor measurements. A myriad of approaches exist for this type of problems, and the main contribution for future efforts might be centered around combining this type of data-driven methods with simulation tools and computational methods in the context of network resilience optimization. Chapter 4 revolves around developing data-driven methods for estimating all-terminal reliability of networks with arbitrary structures and outlines research directions for data-driven surrogate models. Furthermore, the use of DRL for network design optimization and maximizing all-terminal network reliability is presented. This poses a promising research venue that has been extended to network reliability problems involving dynamic decision-making on allocating new resources, maintaining and/or improving the edges already in the network, or repairing failed edges due to aging. The outlined research presents various data-driven tools developed to collaborate in the context of modeling and improvement for Critical Infrastructures. Multiple research venues have been intertwined by combining various paradigms and methods to achieve this goal. The final product is a line of research focused on reliability estimation, design optimization, and prognostics and health management for ICIs, by combining computational methods and theory

The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management

Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation

Broadband transverse susceptibility in multiferroic Y-type hexaferrite Ba0.5Sr1.5Zn2Fe12O22

Producción CientíficaNoncollinear spin systems with magnetically induced ferroelectricity from changes in spiral magnetic ordering have attracted significant interest in recent research due to their remarkable magnetoelectric effects with promising applications. Single phase multiferroics are of great interest for these new multifunctional devices, being Y-type hexaferrites good candidates, and among them the ZnY compounds due to their ordered magnetic behaviour over room temperature. Polycrystalline Y type hexaferrites with composition Ba0.5Sr1.5Zn2Fe2O22 (BSZFO) were sintered in 1050 °C–1250 °C temperature range. Transverse susceptibility measurements carried out on these BSZFO samples in the temperature range 80–350 K with DC fields up to ± 5000 Oe reveal different behaviour depending on the sintering temperature. Sample sintered at 1250 °C is qualitatively different, suggesting a mixed Y and Z phase like CoY hexaferrites. Sintering at lower temperatures produce single phase Y-type, but the transverse susceptibility behaviour of the sample sintered at 1150 °C is shifted at temperatures 15 K higher. Regarding the DC field sweeps the observed behaviour is a peak that shifts to lower values with increasing temperature, and the samples corresponding to single Y phase exhibit several maxima and minima in the 250 K–330 K range at low DC applied field as a result of the magnetic field induced spin transitions in this compound.Ministerio de Ciencia, Innovación y Universidades; Agencia Estatal de Investigación with FEDER (MAT2016-80784-P

Hydro Power Plants as Disputed Infrastructures in Latin America

Non-violent methods can strongly support achieving the 2030 Agenda of sustainable development goals, increasing energy efficiency and access in the poorest countries. However, hydroelectric power stations are disputed strategic elements in any region of the world. This paper analyzes, firstly, the role of hydroelectric power stations as elements that have been generating conflicts in Latin America in the period 1982–2018 and, secondly, the conflicts themselves. The results show that indigenous peoples face the most significant risks from constructing dams and, consequently, they are the primary opponents of hydroelectric projects

Population studies of arthropods on Melia azedarach in Seville (Spain), with special reference to Eutetranychus orientalis (Acari: Tetranychidae) and its natural enemies

Eutetranychus orientalis has become an important pest of the ornamental tree Melia 8 azedarach in the city of Seville (Spain). Trees suffer total defoliation at the end of summer. 9 Studies were conducted in a regular plantation of this tree in the Miraflores Park in 2008 and 10 2009, to determine the arthropod faunal composition, with particular interest in the possible 11 natural enemies of E. orientalis. Eutetranychus orientalis accounted for 98.3% of the 12 arthropods found on the leaflets. Two species of phytoseiids were found, Euseius scutalis and 13 Euseius stipulatus, but they only represented 0.2% of the arthropods. The most abundant 14 insect was the predator thrips Scolothrips longicornis, which accounted for 0.9% of the 15 arthropods found. The population of E. orientalis reached two peaks in 2008, with 325 16 individuals per leaflet in August, and 100 individuals per leaflet in November. Scolothrips 17 longicornis densities closely followed E. orientalis, and predation was observed on various 18 mite instars. Phytoseiids did not show such a response to the E. orientalis densities. 19 Eutetranychus orientalis was more abundant in the exterior part of the plantation. No 20 differences of arthropod densities were found between the various orientations in the 21 plantation (north vs. south, east vs. west), although E. orientalis densities were different 22 between rows. Distribution of E. orientalis population was highly aggregative, that of S. 23 longicornis population was less aggregative, whereas the phytoseiid population showed a 24 random distribution

A Comparison of Deep Learning Methods for Timbre Analysis in Polyphonic Automatic Music Transcription

Automatic music transcription (AMT) is a critical problem in the field of music information retrieval (MIR). When AMT is faced with deep neural networks, the variety of timbres of different instruments can be an issue that has not been studied in depth yet. The goal of this work is to address AMT transcription by analyzing how timbre affect monophonic transcription in a first approach based on the CREPE neural network and then to improve the results by performing polyphonic music transcription with different timbres with a second approach based on the Deep Salience model that performs polyphonic transcription based on the Constant-Q Transform. The results of the first method show that the timbre and envelope of the onsets have a high impact on the AMT results and the second method shows that the developed model is less dependent on the strength of the onsets than other state-of-the-art models that deal with AMT on piano sounds such as Google Magenta Onset and Frames (OaF). Our polyphonic transcription model for non-piano instruments outperforms the state-of-the-art model, such as for bass instruments, which has an F-score of 0.9516 versus 0.7102. In our latest experiment we also show how adding an onset detector to our model can outperform the results given in this work

Critical analysis of the European Union directive which regulates the use of biofuels: An approach to the Spanish case

In recent times, the global debate on the environment has been centered on CO2 emissions. This gas is the major cause of the “greenhouse effect” and people are more concerned with the idea that the emissions of this gas should be minimized. As a result of this concern, the Kyoto Protocol was enacted and subscribed to by many countries, setting the maximum gas emissions for them. Fossil fuels are a major source of CO2 emissions. For some years now The European Union has been seeking to promote some years now the use of biofuels as substitutes for diesel or petrol for transport purposes. As a result of this policy, in 2003 the European Union (EU) Directive 2003/30/EC [1] was developed with the aim of promoting the use of biofuels as a substitute for diesel or gasoline among European Union countries as well as to contribute to fulfilling the commitments acquired on climate change, security of supply in environmentally friendly conditions and the promotion of renewable energy sources. In order to achieve these goals, the directive forces all EU members to ensure that before December 31 of 2010 at least 5.75% of all gasoline and diesel fuels sold for transport purposes are biofuels. European Union countries have social and economic characteristics unique to themselves. The energy dependence on foreign sources, the features of the agricultural sector or the degree of industrialization varies greatly from one country to another. In this context, it is questionable whether the obligation imposed by this directive is actually achieving in its application uniform and/or identical goals in each of the countries involved and whether the actions of the various governments are also aligned with these goals. All these ideas were developed in a previous report (Sobrino and Monroy (2009) [2]). This report examines the possibility of using hydrogen as an alternative to fossil fuels and biofuels from a technical, economic and environmental point of view in the specific case of a European Union country: Spain

Líquenes psammófilos de Las Naves de la Reserva Biológica de Doñana (Huelva)

Se han estudiado las comunidades de líquenes psammó fi los en Las Naves de la Reserva Biológica de Doñana (Huelva), su composición y su relación con el medio físico y las comunidades de matorral. Se han descrito seis comunidades liquénicas asociadas a cinco comunida- des de vegetación leñosa. Las diferencias en la composición liquénica parecen responder al microambiente creado por las comunidades le- ñosas en función de la disponibilidad de luz, suelo desnudo y pertur- baciónOn a etudié les communautées des lichens psammophiles de Las Naves de la Reserve Biologique de Doñana (Huelva, Espagne), leur composition et leur relation avec le milieu et avec les communautées des plantes du matorral. Six communautées de lichens ont été décri- tes et associées á cinq communautées du matorral. Les differences en composition des lichens paraissent répondre au microhabitat crée par les communautées du matorral en fonction de la disponibilité de la lumière, du sol nu et de la pérturbationThe composition of several communities of psammophilous lichens, and their relationships with environment and plant communities were studied in the Naves of Doñana Biological Reserve (Huelva, Spain). The six lichen communities described were associated to fi ve woody plant species. Differences in lichen species composition seem to be due to the microenvironment created by the woody plant communities, related to light availability, bare soil and disturbanc