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Slip between layers, material properties of layers and geometric non-linearities largely dictate both the bearing capacity and the ductility of a composite beam. That is why the accuracy of their modelling in the numerical analysis of the composite beams is of utmost importance. In the present paper we present a new strain-based finite element model which considers these issues in a highly effective manner. Each layer of the beam is modelled by geometrically exact Reissner’s beam model. The layers are assumed to stay in the contact during deformation but the relative tangential displacement (slip) is possible. The non-linear load–slip law of the interface is considered. The formulation is found to be accurate, reliable and computationally time-effective. The further objective of the paper is an analysis of the buckling force of axially compressed layered wood columns, being simply supported, fixed–pinned or continuous. We compare the present numerical results with the analytical values of [Girhammar UA, Gopu VKA. Composite beam-columns with interlayer slip–exact analysis, J Struct Engng ASCE 1993;199(4):1265–82] and with the values, recommended by the European code for timber structures [Eurocode 5, Design of timber structures, Part 1-1: General rules and rules for buildings, 1993; ENV 1995-1-1]. The comparisons indicate that the European code for timber structures provides very conservative estimates for the buckling load. [Copyright &y& Elsevier]

In this paper, we present a highly efficient approach for numerically solving the Black–Scholes equation in order to price European and American basket options. Therefore, hardware features of contemporary high performance computer architectures such as non-uniform memory access and hardware-threading are exploited by a hybrid parallelization using MPI and OpenMP which is able to drastically reduce the computing time. In this way, we achieve very good speed-ups and are able to price baskets with up to six underlyings. Our approach is based on a sparse grid discretization with finite elements and makes use of a sophisticated adaption. The resulting linear system is solved by a conjugate gradient method that uses a parallel operator for applying the system matrix implicitly. Since we exploit all levels of the operator's parallelism, we are able to benefit from the compute power of more than 100 cores. Several numerical examples as well as an analysis of the performance for different computer architectures are provided. [ABSTRACT FROM PUBLISHER]