Direct numerical simulations have been carried out for a fully developed turbulent channel flow with a smooth upper wall and a lower wall consisting of square bars separated by a rectangular cavity. A wide range of w/k, the cavity width to roughness height ratio, was considered. For w/k > 7, recirculation zones occur immediately upstream and downstream of each element while mean streamlines and spatial distributions of the skin frictional drag indicate that each element is virtually isolated. The maximum form drag occurs at w/k = 7 and coincides with the minimum skin frictional drag. The dependence on w/k of the Clauser roughness function reflects that of the form drag.

In this work, we present results of a large-eddy simulation of the 48 multi-megawatt turbines composing the Lillgrund wind plant. Turbulent inflow wind is created by performing an atmospheric boundary layer precursor simulation, and turbines are modeled using a rotating, variable-speed actuator line representation. The motivation for this work is that few others have done large-eddy simulations of wind plants with a substantial number of turbines, and the methods for carrying out the simulations are varied. We wish to draw upon the strengths of the existing simulations and our growing atmospheric large-eddy simulation capability to create a sound methodology for performing this type of simulation. We used the OpenFOAM CFD toolbox to create our solver.The simulated time-averaged power production of the turbines in the plant agrees well with field observations, except with the sixth turbine and beyond in each wind-aligned. The power produced by each of those turbines is overpredicted by 25-40%. A direct comparison between simulated and field data is difficult because we simulate one wind direction with a speed and turbulence intensity characteristic of Lillgrund, but the field observations were taken over a year of varying conditions. The simulation shows the significant 60-70% decrease in the performance of the turbines behind the front row in this plant that has a spacing of 4.3 rotor diameters in this direction. The overall plant efficiency is well predicted. This work shows the importance of using local grid refinement to simultaneously capture the meter-scale details of the turbine wake and the kilometer-scale turbulent atmospheric structures. Although this work illustrates the power of large-eddy simulation in producing a time-accurate solution, it required about one million processor-hours, showing the significant cost of large-eddy simulation.

We present an analysis of the statistical properties and growth of the free on-line encyclopedia Wikipedia. By describing topics by vertices and hyperlinks between them as edges, we can represent this encyclopedia as a directed graph. The topological properties of this graph are in close analogy with those of the World Wide Web, despite the very different growth mechanism. In particular, we measure a scale-invariant distribution of the in and out degree and we are able to reproduce these features by means of a simple statistical model. As a major consequence, Wikipedia growth can be described by local rules such as the preferential attachment mechanism, though users, who are responsible of its evolution, can act globally on the network.

Computations of channel flow with rough walls comprising staggered arrays of cubes having various plan area densities are presented and discussed. The cube height h is 12.5 % of the channel half-depth and Reynolds numbers (u τ h/ν) are typically around 700 -well into the fully rough regime. A direct numerical simulation technique, using an immersed boundary method for the obstacles, was employed with typically 35 million cells. It is shown that the surface drag is predominantly form drag, which is greatest at an area coverage around 15 %. The height variation of the axial pressure force across the obstacles weakens significantly as the area coverage decreases, but is always largest near the top of the obstacles. Mean flow velocity and pressure data allow precise determination of the zero-plane displacement (defined as the height at which the axial surface drag force acts) and this leads to noticeably better fits to the log-law region than can be obtained by using the zero-plane displacement merely as a fitting parameter. There are consequent implications for the value of von Kármán's constant. As the effective roughness of the surface increases, it is also shown that there are significant changes to the structure of the turbulence field around the bottom boundary of the inertial sublayer. In distinct contrast to twodimensional roughness (longitudinal or transverse bars), increasing the area density of this three-dimensional roughness leads to a monotonic decrease in normalized vertical stress around the top of the roughness elements. Normalized turbulence stresses in the outer part of the flows are nonetheless very similar to those in smooth-wall flows.

We study the problem of online team formation. We consider a setting in which people possess different skills and compatibility among potential team members is modeled by a social network. A sequence of tasks arrives in an online fashion, and each task requires a specific set of skills. The goal is to form a new team upon arrival of each task, so that (i) each team possesses all skills required by the task, (ii) each team has small communication overhead, and (iii) the workload of performing the tasks is balanced among people in the fairest possible way.We propose efficient algorithms that address all these requirements: our algorithms form teams that always satisfy the required skills, provide approximation guarantees with respect to team communication overhead, and they are online-competitive with respect to load balancing. Experiments performed on collaboration networks among film actors and scientists, confirm that our algorithms are successful at balancing these conflicting requirements. This is the first paper that simultaneously addresses all these aspects. Previous work has either focused on minimizing coordination for a single task or balancing the workload neglecting coordination costs.

Large eddy simulations of the flow through wind turbines have been carried out using actuator disk and actuator line models for the turbine rotor aerodynamics. In this study, we compare the performance of these two models in producing wind turbine wakes. We also examine parameters that strongly affect the performance of these models, namely, grid resolution and the way in which the actuator force is projected onto the flow field. The proper choice of these two parameters has not been adequately addressed in previous works. We see that as the grid is coarsened, the predicted power decreases. As the width of the body force projection function is increased, the predicted power increases. The actuator disk and actuator line models produce similar wake profiles and predict power within 1% of one another when subject to the same uniform inflow. The actuator line model is able to generate flow structures near the blades such as root and tip vortices which the actuator disk model does not, but in the far wake, the predicted mean wakes are very similar. In order to perform validation against experimental data, the actuator line model output was compared with data from the wind tunnel experiment conducted at the Norwegian University of Science and Technology, Trondheim. Agreement between measured and predicted power, wake profiles, and turbulent kinetic energy has been observed for most tip speed ratios; larger discrepancies in power and thrust coefficient, though, have been found for tip speed ratios of 9 and 12. Copyright © 2014 John Wiley & Sons, Ltd.

We present two space bounded random sampling algorithms that compute an approximation of the number of triangles in an undirected graph given as a stream of edges. Our first algorithm does not make any assumptions on the order of edges in the stream. It uses space that is inversely related to the ratio between the number of triangles and the number of triples with at least one edge in the induced subgraph, and constant expected update time per edge. Our second algorithm is designed for incidence streams (all edges incident to the same vertex appear consecutively). It uses space that is inversely related to the ratio between the number of triangles and length 2 paths in the graph and expected update time O(log |V | · (1 + s · |V |/|E|)), where s is the space requirement of the algorithm. These results significantly improve over previous work [20,8]. Since the space complexity depends only on the structure of the input graph and not on the number of nodes, our algorithms scale very well with increasing graph size and so they provide a basic tool to analyze the structure of large graphs. They have many applications, for example, in the discovery of Web communities, the computa- * This work was partially supported by the EU within the 6th Framework Programme under contract 001907 "Dynamically Evolving, Large Scale Information Systems" (DELIS) * Part of this work was done while the author was post-doc at Universitá degli Studi di Roma "La Sapienza" † Part of this work was done while the author was visiting the School of Computer Science at Carnegie Mellon UniversityPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. tion of clustering and transitivity coefficient, and discovery of frequent patterns in large graphs.We have implemented both algorithms and evaluated their performance on networks from different application domains. The sizes of the considered graphs varied from about 8, 000 nodes and 40, 000 edges to 135 million nodes and more than 1 billion edges. For both algorithms we run experiments with parameter s = 1, 000, 10, 000, 100, 000, 1, 000, 000 to evaluate running time and approximation guarantee. Both algorithms appear to be time efficient for these sample sizes. The approximation quality of the first algorithm was varying significantly and even for s = 1, 000, 000 we had more than 10% deviation for more than half of the instances. The second algorithm performed much better and even for s = 10, 000 we had an average deviation of less than 6% (taken over all but the largest instance for which we could not compute the number of triangles exactly).

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