1,722,394 research outputs found

    The evolution of the approach to Scientific Computing: a Survey

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    This article surveys relevant present and promising future methods for scientific computing. General concepts, like scalability, latency, saturation, and fault tolerance are recalled. A scientific application of distributed heterogeneous computing to the numerical solution of certain partial differential equations problems is given. Basing on the idea of grid computing, we outline mainstream distributed and parallel environments such as GPU computing and cloud computing. CUDA and OpenCL languages, used to implement algorithms on GPU systems, are also briefly described and compared. The main advantages and potential issues of leveraging such resources for scientific computing are described. In addition, a few novel promising approaches are outlined, such as crowd computing, quantum computing, and frequency-fractal computing. The latter, for instance, can indeed be considered a new paradigm for computing

    Evaluation of gpr frequency and polarisation for underground concrete tunnels assessment

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    This paper presents the results from a Ground Penetrating Radar experimental campaign aiming at characterising the thickness of principal concrete elements of a subway tunnel, following relevant water infiltration phenomena that might have affected their integrity and possibly have degraded their structural stability. Given the requirements of penetration and image quality, the main purpose of the study was to identify an optimal equipment design capable of accurately determine thickness variations of the subsurface structures by the joint analysis of different operational frequency, particularly a 200 MHz and a 600 MHz equipment, and antenna polarisation. While suitable depth performance has been achieved for both frequency bands, the image quality is notably higher when the interference from the metallic elements is minimised, and hence the 600 MHz equipment oriented perpendicular to the armour level has proven to be the best option. Obtained results allow a centimetric characterisation of the vertical extension of the investigated structures, and confirm their deterioration

    SELF-ADAPTIVE BOUNDARY ELEMENTS WITH H-HIERARCHICAL SHAPE FUNCTIONS

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    A self-adaptive boundary element method as implemented in the new computer program SHERPA is presented. Error indicators are obtained by comparing two BEM solutions obtained from exactly the same discretization but with (partly) different sets of collocation points. The code SHERPA has some advanced features, including fully automatic mesh refinement and user-friendly interfaces. h-hierarchical quadratic shape functions are employed to improve the computational efficiency. Numerical results for elastic problems are presented. Pointwise as well as global convergence is always reached in a few adaptive steps

    QCA Memory

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    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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