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This paper presents performance requirements for a real-time hybrid testing system to be suitable for scale-model floating wind turbine experiments. In the wave basin, real-time hybrid testing could be used to replace the model wind turbine with an actuation mechanism, driven by a wind turbine simulation running in parallel with, and reacting to, the experiment. The actuation mechanism, attached to the floating platform, would provide the full range of forces normally provided by the model wind turbine. This arrangement could resolve scaling incompatibilities that currently challenge scale-model floating wind turbine experiments. In this paper, published experimental results and a collection of full-scale simulations are used to determine what performance specifications such a system would need to meet. First, an analysis of full-scale numerical simulations and published 1:50-scale experimental results is presented. This analysis indicates the required operating envelope of the actuation system in terms of displacements, velocities, accelerations, and forces. Next, a sensitivity study using a customization of the floating wind turbine simulator FAST is described. Errors in the coupling between the wind turbine and the floating platform are used to represent the various inaccuracies and delays that could be introduced by a real-time hybrid testing system. Results of this sensitivity study indicate the requirements — in terms of motion-tracking accuracy, force actuation accuracy, and system latency — for maintaining an acceptable level of accuracy in 1:50-scale floating wind turbine experiments using real-time hybrid testing.

Many Pareto-based multi-objective evolutionary algorithms require to rank the solutions of the population in each iteration according to the dominance principle, what can become a costly operation particularly in the case of dealing with manyobjective optimization problems. In this paper, we present a new efficient algorithm for computing the non-dominated sorting procedure, called Merge Non-Dominated Sorting (MNDS), which has a best computational complexity of Θ(N logN ) and a worst computational complexity of Θ(M N 2 ). Our approach is based on the computation of the dominance set of each solution by taking advantage of the characteristics of the merge sort algorithm. We compare the MNDS against four well-known techniques that can be considered as the state-of-the-art. The results indicate that the MNDS algorithm outperforms the other techniques in terms of number of comparisons as well as the total running time.

Abstract-To study any electromagnetic system, the geometry model must be discretized into elements with an appropriate size for the working frequency. The discretization of a system must be transparent to the user of electromagnetic computing tools. A mesher is presented based on the paving algorithm. The algorithm has been modified to allow triangular elements and has been accelerated by distributing the load on multiple processors simultaneously. Also, a multilevel mode has been implemented. With this tool, any geometry defined by NURBS (Non Uniform Rational B-Spline) surfaces can be decomposed into triangular and quadrangular curved elements.

This document presents a technique for the generation of Sparse Inverse Preconditioners based on the near field coupling matrices of Method of Moments simulations where the geometry has been partitioned in terms of regions. A distance parameter is used to determine the sparsity pattern of the preconditioner. The rows of the preconditioner are computed in groups at a time, according to the number of unknowns contained in each region of the geometry. Two filtering thresholds allow considering only the coupling terms with a significant weight for a faster generation of the preconditioner and storing only the most significant preconditioner coefficients in order to decrease the memory required. The generation of the preconditioner involves the computation of as many independent linear least square problems as the number of regions in which the geometry is partitioned, resulting in very good scalability properties regarding its parallelization.