InfIuence of wave induced second-order forces in semisubmersible fowt mooring design

The main focus of this paper is on hydrodynamic modelling of a semisubmersible platform (which can support a 1.5MW wind turbine and is composed by three buoyant columns connected by bracings) with especial emphasis on the estimation of the wave drift components and their effects on the design of the mooring system. Indeed, with natural periods of drift around 60 seconds, accurate computation of the low-frequency second-order components is not a straightforward task. As methods usually adopted when dealing with the slow-drifts of deep-water moored systems, such as Newman?s approximation, have their errors increased by the relatively low resonant periods, and as the effects of depth cannot be ignored, the wave diffraction analysis must be based on full Quadratic Transfer Functions (QTF) computations. A discussion on the numerical aspects of performing such computations is presented, making use of the second-order module available with the seakeeping software WAMIT®. Finally, the paper also provides a preliminary verification of the accuracy of the numerical predictions based on the results obtained in a series of model tests with the structure fixed in bichromatic waves.

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period.

Projector Model for Efficient List-Mode Reconstruction in PET Scanners with Parallel Planar Detectors

We have developed a new projector model specifically tailored for fast list-mode tomographic reconstructions in Positron emission tomography (PET) scanners with parallel planar detectors. The model provides an accurate estimation of the probability distribution of coincidence events defined by pairs of scintillating crystals. This distribution is parameterized with 2D elliptical Gaussian functions defined in planes perpendicular to the main axis of the tube of response (TOR). The parameters of these Gaussian functions have been obtained by fitting Monte Carlo simulations that include positron range, acolinearity of gamma rays, as well as detector attenuation and scatter effects. The proposed model has been applied efficiently to list-mode reconstruction algorithms. Evaluation with Monte Carlo simulations over a rotating high resolution PET scanner indicates that this model allows to obtain better recovery to noise ratio in OSEM (ordered-subsets, expectation-maximization) reconstruction, if compared to list-mode reconstruction with symmetric circular Gaussian TOR model, and histogram-based OSEM with precalculated system matrix using Monte Carlo simulated models and symmetries.

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.

Forward micro-inverter with primary-parallel secondary-series multicore transformer

This paper presents a primary-parallel secondary-series multicore forward micro-inverter for photovoltaic AC-module application. The proposed solution changes the number of active phases depending on the grid voltage, thus enabling the usage of low-profile unitary turns ratio transformers. Therefore, the transformers are well coupled and the overall performance of the inverter is improved. Due to the multiphase solution the number of devices increases but, the current stress and losses per device are reduced contributing to an easier thermal management. Furthermore, the decoupling capacitor is split between the phases, contributing to a low-profile solution without electrolytic capacitors suitable to be mounted in the frame of a PV module.

Multiphase Parallel Interleaved And Primary-Parallel Secondary-Series Forward Micro-Inverter Comparison.

Using multiphase technique is interesting in PV AC-module application due to light-load efficiency improvement by applying phase shedding, and the possibility of low-profile implementation. This paper presents a comparison, in terms of size and efficiency, of the parallel interleaved and the parallel-series connected multiphase configurations, as a function of the number of phases, for a forward micro-inverter operated in DCM. 8-phase prototypes of both multiphase configurations are built and compared between them and with the single phase forward micro-inverter, validating the presented analysis.

Advanced Control Strategies for a 6 DoF Hydraulic Parallel Robot Based on the Dynamic Model

Nowadays robots have made their way into real applications that were prohibitive and unthinkable thirty years ago. This is mainly due to the increase in power computations and the evolution in the theoretical field of robotics and control. Even though there is plenty of information in the current literature on this topics, it is not easy to find clear concepts of how to proceed in order to design and implement a controller for a robot. In general, the design of a controller requires of a complete understanding and knowledge of the system to be controlled. Therefore, for advanced control techniques the systems must be first identified. Once again this particular objective is cumbersome and is never straight forward requiring of great expertise and some criteria must be adopted. On the other hand, the particular problem of designing a controller is even more complex when dealing with Parallel Manipulators (PM), since their closed-loop structures give rise to a highly nonlinear system. Under this basis the current work is developed, which intends to resume and gather all the concepts and experiences involve for the control of an Hydraulic Parallel Manipulator. The main objective of this thesis is to provide a guide remarking all the steps involve in the designing of advanced control technique for PMs. The analysis of the PM under study is minced up to the core of the mechanism: the hydraulic actuators. The actuators are modeled and experimental identified. Additionally, some consideration regarding traditional PID controllers are presented and an adaptive controller is finally implemented. From a macro perspective the kinematic and dynamic model of the PM are presented. Based on the model of the system and extending the adaptive controller of the actuator, a control strategy for the PM is developed and its performance is analyzed with simulation.

Generalized optoelectronic model of series-connected multijunction solar cells

The emission of light from each junction in a series-connected multijunction solar cell both complicates and elucidates the understanding of its performance under arbitrary conditions. Bringing together many recent advances in this understanding, we present a general 1-D model to describe luminescent coupling that arises from both voltage-driven electroluminescence and voltage-independent photoluminescence in nonideal junctions that include effects such as Sah-Noyce-Shockley (SNS) recombination with n ≠ 2, Auger recombination, shunt resistance, reverse-bias breakdown, series resistance, and significant dark area losses. The individual junction voltages and currents are experimentally determined from measured optical and electrical inputs and outputs of the device within the context of the model to fit parameters that describe the devices performance under arbitrary input conditions. Techniques to experimentally fit the model are demonstrated for a four-junction inverted metamorphic solar cell, and the predictions of the model are compared with concentrator flash measurements.

Grid-Connected Forward Microinverter With Primary-Parallel Secondary-Series Transformer

This paper presents a primary-parallel secondaryseries multicore forward microinverter for photovoltaic ac-module application. The presented microinverter operates with a constant off-time boundary mode control, providing MPPT capability and unity power factor. The proposed multitransformer solution allows using low-profile unitary turns ratio transformers. Therefore, the transformers are better coupled and the overall performance of the microinverter is improved. Due to the multiphase solution, the number of devices increases but the current stress and losses per device are reduced contributing to an easier thermal management. Furthermore, the decoupling capacitor is split among the phases, contributing to a low-profile solution without electrolytic capacitors suitable to be mounted in the frame of a PV module. The proposed solution is compared to the classical parallel-interleaved approach, showing better efficiency in a wide power range and improving the weighted efficiency.