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The deployment of offshore wind turbines has focused primarily on shallow seas (such as the North Sea, Chinese coastal waters, and the New England coast) using bottom fixed foundations. However, much of the world’s offshore wind resource lies in deeper waters where bottom-fixed foundations are not suitable, and floating platforms must be utilised. To date, the majority of floating concepts have been developed to support a single wind turbine. This leads to a high capital cost for each individual platform and consequently a high levelised cost of energy. The W2Power platform (developed by EnerOcean S.L, Spain) currently supports a pair of 6 MW wind turbines on outward-leaning towers. The design significantly reduces the cost per installed MW, increases the structure’s natural period, added mass, and radiation damping. The platform, patented in 2009, was the world’s first twin-turbine platform and the first to be demonstrated at sea (2019). This paper presents the hydrodynamics of a 1:40 scale model of the W2Power platform using the well-known OrcaFlex software. The analysis has been carried out under extreme and operational conditions, and the resulting hydrodynamic loads and motion response are presented. The mooring system was found to be sensitive to wave direction, particularly when propagating along the current direction. Furthermore, the results showed advantages in the hydrodynamic responses for the W2Power platform as an innovative floating system.

This research presents the modeling and prediction of the harmonic behavior of current in an electric power supply grid with the integration of photovoltaic power by inverters using artificial neural networks to determine if the use of the proposed neural network is capable of capturing the harmonic behavior of the photovoltaic energy integrated into the user’s electrical grids. The methodology used was based on the use of recurrent artificial neural networks of the nonlinear autoregressive with external input type. Work data were obtained from experimental sources through the use of a test bench, measurement, acquisition, and monitoring equipment. The input–output parameters for the neural network were the current values in the inverter and the supply grid, respectively. The results showed that the neural network can capture the dynamics of the analyzed system. The generated model presented flexibility in data handling, allowing to represent and predict the behavior of the harmonic phenomenon. The obtained algorithm can be transferred to physical or virtual systems for the control or reduction of harmonic distortion.

Most tidal turbine blades are currentlymade from glass or carbon fibre reinforced epoxycomposites. These represent a significantpart of theturbine cost, but few data are available either tovalidate current safety factors or to proposealternative more environmentally-friendly materials. This study, performed within the EU H2020 RealTideproject, aimed to provide these data. First, a detailedinvestigation of the staticand fatigue behavior wasperformed at the coupon scale, including not onlythose materials currently used, but also alternative recyclable thermoplastic matrix composites andnatural fibre reinforced materials. Tests wereperformed before and after seawater saturation, inorder to quantify the change in design properties withwater uptake. Then a first full scale 5 meter longcomposite blade was designed and tested to failure. Aspecific test frame was built, allowing loads up to 75tons to be applied and simulating theappliedmoments corresponding to service loads. Static andcyclic loads were applied and extensiveinstrumentation was used to detect changes inbehavior, inluding optical fibres implanted duringmanufacture, acoustic emission recording,andspecificinstrumentation developed within the project.The results have enabled numerical simulations to beverified,and this has provided confidence in themodelling tools. These were then employed in orderto propose an improveddesign of a lower cost blade.

Cardiopulmonary auscultation is a diagnostic procedure that has a challenging task since the components of heart rate and lung sounds overlap. There were many approaches to quantify the characteristics of these signals, and one of the newest is the voice activity detection (VAD) and the Gaussian Mixture Models (GMM). Considering the lung and heart sounds as acoustic events, this paper proposes a novel assessment methodology of these diagnostic indicators. Here, VAD-GMM was applied to detect and extract the main events in lung sound and heart sounds. VAD- GMM results were compared with other VAD methodology based on statistical approach, and it was found that VAD-GMM give more definite results. Since Mel Frequency Cepstral coefficients (MFCC) and Quartiles feature vectors, were already successful in pattern recognition, VAD-GMM was carried out using this kind of acoustic vectors. Therefore, this method could add in a transition from qualitative traditional auscultation to quantitative assessment and assisted computerized diagnosis by identifying abnormal acoustic indicators. Diagnosis by computerized detection promises to be a more efficient method than traditional methods, which are limited by the auditory capability and experience of a medical professional.

The trend in our days seems to drive to hybrid renewable offshore platforms. Several European projects have advanced in this sense. One of these hybrid configurations is obtained by combination of wind and wave energy which allows higher production of electric power. W2Power platform combines offshore wind and wave energy in a semi-submersible floating platform. In this work we present a preliminary study of platform W2Power carried by UCA and collaboration with EnerOcean. A first step of the study, is presented, in this first step the platform and the wave converter are separately studied. A model of these components is created in the software SeaFEM and they are calibrated in the software using previous experimental test tank results. Taking into account this preliminary work, a study of a complete fully coupled model of the W2Power including wind and WECs under different control laws [11] platform will be made in future works.

Many investigations led to show that no crack begins to propagate to an increase of stress intensity factor. The life of the components of a structure containing premature cracks, can be governed by the degree of subcritical crack propagation. Thus, knowledge of crack propagation to determine the fatigue of the structure is necessary. One problem of steels of high resilience is their low toughness in the HAZ, when they are welded with a high heat input. In this work we have studied nine specimens that have been welded under a submerged arc welding process controlling the welding parameters and checking in the HAZ of such specimens, critical tensions at the ends of the cracks, the critical cracks lengths and stress intensity factors. It is intended to check that the parameters that indicate the values of fracture mechanics in the HAZ, after heat cycle to which the steel has undergone, under a process with a maximum heat input of 2.327kJ /mm, they are still valid, with the welding parameters applied. It is checked a correlation between the theoretical and experimental values.

The global population is growing and the demand for food and energy is steadily increasing. Coastal space all over the world becomes increasingly limited and near-shore resources are often already heavily exploited. The use of offshore regions may provide new opportunities, but also involves major challenges such as the development of designs and technologies suitable for offshore condition. The floating TROPOS ‘Green & Blue’ modular multi-use platform concept introduced in this chapter is especially designed for offshore conditions and provides solutions for the problems and obstacles involved in “moving offshore”. The Green & Blue platform concept integrates fish and algae aquaculture with a wind farm. The floating multi-use approach allows for platform operation in deep waters and the promotion of synergies such as joint logistics, shared infrastructure and services, thereby making the use of offshore resources viable and profitable.

The first part of this study (Carnero et al., Mechanical Systems and Signal Processing, 24:1138–1160, 2010) analysed the influence of the process variables and work cycles on the quality of the bearings manufactured in an automotive bearing plant. The study was focused on the analysis of the overall vibration reading produced by the contact between the tool and the part. An analysis of variance was conducted on the overall vibration readings, which reflected that high-frequency vibration displacements are sensitive to process setup variables as well as the quality of products manufactured. Nevertheless, it was also observed that overall vibration values are not sufficient to analyse the relationship between the mechanical behaviour (vibration) and final quality obtained from high-precision machining processes. In this article, therefore, a new study is conducted based on spectral vibration measurements. A new experiment has been designed taking as input variables the diameter and the rotating speed of the tool. The selection criterion is based on the strong influence of these two variables on high-frequency vibration displacement and quality of parts (chattering, measured in terms of Lob A and Lob B). Two identical grinding machine tools were used during the experimental phase. Output variables are high-frequency displacements and high- and low-frequency chattering. The statistical analysis used in the new experiments determines spectral bands of the process in which vibrations induced by tool–part contact relates to development of lobes in the part to be identified. The study allows identification of vibration bands that are suitable for control in order to guarantee quality of the parts produced. To achieve that goal, the concept of spectral identity of the processes has been introduced to incorporate vibration induced by the process itself in the spectrums and to differentiate that process vibration from other mechanical vibration sources.

The present study introduces the concept of statistical quality control in automotive wheel bearings manufacturing processes. Defects on products under analysis can have a direct influence on passengers’ safety and comfort. At present, the use of vibration analysis on machine tools for quality control purposes is not very extensive in manufacturing facilities. Noise and vibration are common quality problems in bearings. These failure modes likely occur under certain operating conditions and do not require high vibration amplitudes but relate to certain vibration frequencies. The vibration frequencies are affected by the type of surface problems (chattering) of ball races that are generated through grinding processes. The purpose of this paper is to identify grinding process variables that affect the quality of bearings by using statistical principles in the field of machine tools. In addition, an evaluation of the quality results of the finished parts under different combinations of process variables is assessed. This paper intends to establish the foundations to predict the quality of the products through the analysis of self-induced vibrations during the contact between the grinding wheel and the parts. To achieve this goal, the overall self-induced vibration readings under different combinations of process variables are analysed using statistical tools. The analysis of data and design of experiments follows a classical approach, considering all potential interactions between variables. The analysis of data is conducted through analysis of variance (ANOVA) for data sets that meet normality and homoscedasticity criteria. This paper utilizes different statistical tools to support the conclusions such as chi squared, Shapiro–Wilks, symmetry, Kurtosis, Cochran, Hartlett, and Hartley and Krushal–Wallis. The analysis presented is the starting point to extend the use of predictive techniques (vibration analysis) for quality control. This paper demonstrates the existence of predictive variables (high-frequency vibration displacements) that are sensible to the processes setup and the quality of the products obtained. Based on the result of this overall vibration analysis, a second paper will analyse self-induced vibration spectrums in order to define limit vibration bands, controllable every cycle or connected to permanent vibration-monitoring systems able to adjust sensible process variables identified by ANOVA, once the vibration readings exceed established quality limits.

Linear systems with tridiagonal structures are very common in problems related not only to engineering, but chemistry, biomedical or finance, for example, real time cubic B-Spline interpolation of ND-images, real time processing of Electrocardiography (ECG) and hand drawing recognition. In those problems which the matrix is positive definite, it is possible to optimize the solution in O(n) time. This paper describes such systems whose size grows over time and proposes an approximation in O(1) time of such systems based on a series of previous approximations. In addition, it is described the development of the method and is proved that the proposed solution converges linearly to the optimal. A real-time cubic B-Spline interpolation of an ECG is computed with this proposal, for this application the proposed method shows a global relative error near to 10-6 and its computation is faster than traditional methods, as shown in the experiments.

Machine vision methods to provide spatial coordinates measurement has developed in a wide range of technologies for multiples fields of applications such as robot navigation, medical scanning, and structural monitoring. Each technology with specified properties that could be categorized as advantage and disadvantage according its utility to the application purpose. This paper presents the photodiode and charge coupled device sensors fusion as the base for those systems with non-lineal behavior supported by artificial intelligence techniques, which require the use of information from various sensors for pattern recognition to produce an enhanced output.

Nowadays, different devices are used for traffic control and accidents prevention in urban junctions. The most popular systems for vehicles detection are: inductive loop vehicle detector systems and camera detector systems. However, these systems have some weaknesses. Basically, in installation and maintenance for the first one and complex processing algorithms for the second one. This paper presents an alternative method to vehicles detection and speed estimation using an infrared emitter and a photodiode as visualization system. The main advantage lies in that it is a non-intrusive method and installation does not requires pavement cut. Possible measuring errors can be compensated with different techniques as artificial intelligence - and other mathematic models. In this application we used functions defined by parts.

The paper presents the state of development of the W2Power hybrid, combining offshore wind and wave energy in a large but lightweight semi-submersible floating platform. Results of design optimisation and proof-of-concept experiments by tank testing are reviewed. Modelled hydrodynamic performance of the floating structure at full scale are compared with results of scaled validation tests in further tank experiments. Business cases for the hybrid are analysed using a simplified cost/revenue model, taking into account both CAPEX, OPEX and lifetime revenues from both wind- and wave-generated electricity.

In external grinding processes, vibrations induced by the process itself can lead to defects that affect the quality of the parts. The literature offers models that cannot include all process variables in the analysis. This research applies theoretical models and experimental analysis to determine their suitability for predicting the chatter profile of parts in a plunge grinding process. The application of variance analysis to overall vibration value induced by grinding wheel-workpiece contact allows us to show that high frequency displacements vibration are sensitive to the process setup as well as to the quality of the products manufactured. The final statistical analysis has provided a determination of the spectral bands of the process in which the vibrations causes by grinding wheel-workpiece contact influence the existence of flaws in the workpieces. The methodology described can contribute to increasing the environmental sustainability of an industrial organization.

Predictive maintenance has a significant impact on the environmental sustainability of an organization, by means of the increase in quality of the product, which allows the consumption of raw materials to be reduced. Vibration analysis is a predictive technique especially suitable for reciprocating and rotary machines; it consists of periodically recording the vibration level of the machine, as it increases when there are anomalies such as misalignment, unbalance, etc. In the manufacture of bearings for vehicles, the final vibration of the assembled bearing is one of the quality parameters analysed to ensure that the quality of the bearings are as desired. In external grinding processes vibrations appear which are generated by the process itself and not by flaws in the machine tool. These vibrations can cause defects which affect the quality of the workpieces produced. Nevertheless, analysis of process-induced vibrations is little studied in the literature. Vibration spectra are applied to distinguish problematic vibration frequencies from those that are not. Intercomparison of spectra between similar machines and studies of the change over time of spectra or waterfall plots are used. This method considers the possible of establishing separate vibration limits in the machining of components so as to guarantee the quality of the final assembled product. The methodology exposed can contribute to increase the environmental sustainability of an industrial organization due that contribute to a more efficient use of resources.

A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom–up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.

The difficulty of the inspection tasks along electric transmission lines in order to ensure the safety of the line workers, combined with the interests to reduce the operation costs, makes the automation of the process to become interesting. The goal is to develop an autonomous robot which should run along the conductors while making the inspection. This robot needs energy. Several sources are considered but the line energy itself is selected as the best option. A system to take profit of the electromagnetic fields generated by the high voltage transmission lines is introduced in this paper. Experimental results have been obtained validating the viability of this kind of power supply system.

Presentación en webinar de SOCLIMPACT el 21/09/2020 para la comunidad online Principales temas: EnerOcean Profile. EnerOcean and W2Power. Offshore wind: Spreading success. Offshore wind: Islands, Climate Change and Marine Energy Main floater types and depth ranges W2Power: The lowest-cost floating solution Key technical specifications Key technology advantages: Lower energy cost Easy and cost-efficient maintenance Systematic step by stepdevelopment W2Power prototype at sea Excellent results of prototype sea testing W2Power: Wind Energy and Aquaculture W2Power with fish farming, benefits. Summary

Presentación en webinar de SOCLIMPACT el 21/09/2020 para la comunidad online Principales temas: EnerOcean Profile. EnerOcean and W2Power. Offshore wind: Spreading success. Offshore wind: Islands, Climate Change and Marine Energy Main floater types and depth ranges W2Power: The lowest-cost floating solution Key technical specifications Key technology advantages: Lower energy cost Easy and cost-efficient maintenance Systematic step by step development W2Power prototype at sea Excellent results of prototype sea testing W2Power: Wind Energy and Aquaculture W2Power with fish farming, benefits. Summary