A feasibility study for the installation of Wave Energy Converters (WEC) in a Spanish Mediterranean port is evaluated in this paper. The final aim is to evaluate the possibility of building a new infrastructure which combines a breakwater and a WEC able to provide energy to the commercial port of Valencia. An estimation of the wave power potential is made according to existing databases from different sources. A review of the existing WEC types is carried out in order to choose the most suitable technology for its installation in a port environment. The authors discuss the main advantages and issues of the integration of WEC in port breakwaters. A prospective study for the Port of Valencia is made, considering the port energy demand evolution, historical data on wave energy potential and the port expansion plans. We conclude that Overtopping Devices (OTDs) are the most suitable ones to allow the good integration with the new breakwater needed for the expansion of the Port of Valencia and we give an estimation on the power available from the resource in our case study.
Heart failure constitutes a major public health problem worldwide. Affected patients experience a number of changes in the electrical function of the heart that predispose to potentially lethal cardiac arrhythmias. Due to the multitude of electrophysiological changes that may occur during heart failure, the scientific literature is complex and sometimes ambiguous, perhaps because these findings are highly dependent on the etiology, the stage of heart failure, and the experimental model used to study these changes. Nevertheless, a number of common features of failing hearts have been documented. Prolongation of the action potential (AP) involving ion channel remodeling and alterations in calcium handling have been established as the hallmark characteristics of myocytes isolated from failing hearts. Intercellular uncoupling and fibrosis are identified as major arrhythmogenic factors. Multi-scale computational simulations are a powerful tool that complements experimental and clinical research. The development of biophysically detailed computer models of single myocytes and cardiac tissues has contributed greatly to our understanding of processes underlying excitation and repolarization in the heart. The electrical, structural, and metabolic remodeling that arises in cardiac tissues during heart failure has been addressed from different computational perspectives to further understand the arrhythmogenic substrate. This review summarizes the contributions from computational modeling and simulation to predict the underlying mechanisms of heart failure phenotypes and their implications for arrhythmogenesis, ranging from the cellular level to whole-heart simulations. The main aspects of heart failure are presented in several related sections. An overview of the main electrophysiological and structural changes that have been observed experimentally in failing hearts is followed by the description and discussion of the simulation work in this field at the cellular level, and then in 2D and 3D cardiac structures. The implications for arrhythmogenesis in heart failure are also discussed including therapeutic measures, such as drug effects and cardiac resynchronization therapy. Finally, the future challenges in heart failure modeling and simulation will be discussed.
In rural areas or in isolated communities in developing countries it is increasingly common to install micro-renewable sources, such as photovoltaic (PV) systems, by residential consumers without access to the utility distribution network. The reliability of the supply provided by these stand-alone generators is a key issue when designing the PV system. The proper system sizing for a minimum level of reliability avoids unacceptable continuity of supply (undersized system) and unnecessary costs (oversized system). This paper presents a method for the accurate sizing of stand-alone photovoltaic (SAPV) residential generation systems for a pre-established reliability level. The proposed method is based on the application of a sequential random Monte Carlo simulation to the system model. Uncertainties of solar radiation, energy demand, and component failures are simultaneously considered. The results of the case study facilitate the sizing of the main energy elements (solar panels and battery) depending on the required level of reliability, taking into account the uncertainties that affect this type of facility. The analysis carried out demonstrates that deterministic designs of SAPV systems based on average demand and radiation values or the average number of consecutive cloudy days can lead to inadequate levels of continuity of supply.
Motor imagery has been suggested as an efficient alternative to improve the rehabilitation process of affected limbs. In this study, a low-cost robotic guide is implemented so that linear position can be controlled via the user’s motor imagination of movement intention. The patient can use this device to move the arm attached to the guide according to their own intentions. The first objective of this study was to check the feasibility and safety of the designed robotic guide controlled via a motor imagery (MI)-based brain–computer interface (MI-BCI) in healthy individuals, with the ultimate aim to apply it to rehabilitation patients. The second objective was to determine which are the most convenient MI strategies to control the different assisted rehabilitation arm movements. The results of this study show a better performance when the BCI task is controlled with an action–action MI strategy versus an action–relaxation one. No statistically significant difference was found between the two action–action MI strategies.
This paper studies modular decomposition as an approach for failure diagnosis based on Discrete Event Systems. This paper also analyses the problem of coupling produced in the implementation of centralized modular diagnosers, as coupled diagnosers cannot carry out their own diagnosis task, when there is a failure in another subsystem sharing a common energy or material flow.In addition, we propose a method to avoid diagnoser coupling, by means of decoupling functions using nonlocal information with respect to the coupled diagnoser and generated in the diagnoser where the failure has been isolated.
In this paper, an application for the management and supervision by predictive fault diagnosis (PFD) of solar power generation systems is developed through a National Marine Electronics Association (NMEA) 2000 smart sensor network. Here, the NMEA 2000 network sensor devices for measuring and supervising the parameters inherent to solar power generation and renewable energy supply are applied. The importance of renewable power generation systems in ships is discussed, as well as the causes of photovoltaic modules (PVMs) aging due to superimposed causes of degradation, which is a natural and inexorable phenomenon that affects photovoltaic installations in a special way. In ships, PVMs are doubly exposed to inclement weather (solar radiation, cold, rain, dust, humidity, snow, wind, electrical storms, etc.), pollution, and a particularly aggressive environment in terms of corrosion. PFD techniques for the real-world installation and safe navigation of PVMs are discussed. A specific method based on the online analysis of the time-series data of random and seasonal I–V parameters is proposed for the comparative trend analyses of solar power generation. The objective is to apply PFD using as predictor symptom parameter (PS) the generated power decrease in affected PVMs. This PFD method allows early fault detection and isolation, whose appearance precedes by an adequate margin of maneuver, from the point of view of maintenance tasks applications. This early detection can stop the cumulative degradation phenomenon that causes the development of the most frequent and dangerous failure modes of solar modules, such as hot-spots. It is concluded that these failure modes can be conveniently diagnosed by performing comparative trend analyses of the measured power parameters by NMEA sensors.
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