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This paper proposes an optimisation strategy for the layout design of wave energy converter (WEC) arrays. Optimal layouts are sought so as to maximise the absorbed power given a minimum q-factor, the minimum distance between WECs, and an area of deployment. To guarantee an efficient optimisation, a four-parameter layout description is proposed. Three different optimisation algorithms are further compared in terms of performance and computational cost. These are the covariance matrix adaptation evolution strategy (CMA), a genetic algorithm (GA) and the glowworm swarm optimisation (GSO) algorithm. The results show slightly higher performances for the latter two algorithms; however, the first turns out to be significantly less computationally demanding.

Abstract:The increasing desire for using renewable energy sources throughout the world has resulted in a considerable amount of research into and development of concepts for wave energy converters. By now, many different concepts exist, but still, the wave energy sector is not at a stage that is considered commercial yet, primarily due to the relatively high cost of energy. A considerable amount of the wave energy converters are floating structures, which consequently need mooring systems in order to ensure station keeping. Despite being a well-known concept, mooring in wave energy application has proven to be expensive and has a high rate of failure. Therefore, there is a need for further improvement, investigation into new concepts and sophistication of design procedures. This study uses four Danish wave energy converters, all considered as large floating structures, to investigate a methodology in order to find an inexpensive and reliable mooring solution for each device. The study uses a surrogate-based optimization routine in order to find a feasible solution in only a limited number of evaluations and a constructed cost database for determination of the mooring cost. Based on the outcome, the mooring parameters influencing the cost are identified and the optimum solution determined.

SUMMARYA Lagrangian numerical approach for the simulation of rapid landslide runouts is presented and discussed. The simulation approach is based on the so called Particle Finite Element Method (PFEM). The moving soil mass is assumed to obey a rigid-viscoplastic, non-dilatant Drucker-Prager constitutive law, which is cast in the form of a regularized, pressure sensitive Bingham model. Unlike in classical formulations of computational fluid mechanics, where no-slip boundary conditions are assumed, basal slip boundary conditions are introduced to account for the specific nature of the landslide-basal surface interface. The basal slip conditions are formulated in the form of modified Navier boundary conditions, with a pressure sensitive threshold. A special mixed Eulerian-Lagrangian formulation is used for the elements on the basal interface to accommodate the new slip conditions into the PFEM framework. To avoid inconsistencies in the presence of complex shapes of the basal surface, the no-flux condition through the basal surface is relaxed using a penalty approach. The proposed model is validated by simulating both laboratory tests and a real large scale problem, and the critical role of the basal slip is elucidated.

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