National Technical University of Athens

About: National Technical University of Athens is a education organization based out in Athens, Attiki, Greece. It is known for research contribution in the topics: Large Hadron Collider & Nonlinear system. The organization has 13445 authors who have published 31259 publications receiving 723504 citations. The organization is also known as: Athens Polytechnic & NTUA.

Natural convection flow in a square cavity revisited: Laminar and turbulent models with wall functions

Abstract: Numerical simulations have been undertaken for the benchmark problem of natural convection flow in a square cavity. The control volume method is used to solve the conservation equations for laminar and turbulent flows for a series of Rayleigh numbers (Ra) reaching values up to 1010. The k-ϵ model has been used for turbulence modelling with and without logarithmic wall functions. Uniform and non-uniform (stretched) grids have been employed with increasing density to guarantee accurate solutions, especially near the walls for high Ra-values. ADI and SIP solvers are implemented to accelerate convergence. Excellent agreement is obtained with previous numerical solutions, while some discrepancies with others for high Ra-values may be due to a possibly different implementation of the wall functions. Comparisons with experimental data for heat transfer (Nusselt number) clearly demonstrates the limitations of the standard k-ϵ model with logarithmic wall functions, which gives significant overpredictions.

Optimizing joins in a map-reduce environment

Abstract: Implementations of map-reduce are being used to perform many operations on very large data. We examine strategies for joining several relations in the map-reduce environment. Our new approach begins by identifying the "map-key," the set of attributes that identify the Reduce process to which a Map process must send a particular tuple. Each attribute of the map-key gets a "share," which is the number of buckets into which its values are hashed, to form a component of the identifier of a Reduce process. Relations have their tuples replicated in limited fashion, the degree of replication depending on the shares for those map-key attributes that are missing from their schema. We study the problem of optimizing the shares, given a fixed number of Reduce processes. An algorithm for detecting and fixing problems where an attribute is "mistakenly" included in the map-key is given. Then, we consider two important special cases: chain joins and star joins. In each case we are able to determine the map-key and determine the shares that yield the least replication. While the method we propose is not always superior to the conventional way of using map-reduce to implement joins, there are some important cases involving large-scale data where our method wins, including: (1) analytic queries in which a very large fact table is joined with smaller dimension tables, and (2) queries involving paths through graphs with high out-degree, such as the Web or a social network.

Quantifying the Impact of Wind Turbine Wakes on Power Output at Offshore Wind Farms

Abstract: There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms. Detailed data ensembles of power losses due to wakes at the large wind farms at Nysted and Horns Rev are presented and analyzed. Differences in turbine spacing (10.5 versus 7 rotor diameters) are not differentiable in wake-related power losses from the two wind farms. This is partly due to the high variability in the data despite careful data screening. A number of ensemble averages are simulated with a range of wind farm and computational fluid dynamics models and compared to observed wake losses. All models were able to capture wake width to some degree, and some models also captured the decrease of power output moving through the wind farm. Root-mean-square errors indicate a generally better model pe...

A benchmark low voltage microgrid network

Abstract: The increasing penetration of distributed generation resources to the low voltage (LV) grids, such as photovoltaics, CHP micro-turbines, small wind turbines in certain areas and possibly fuel cells in the near future, alters the traditional operating principle of the grids. A particularly promising aspect, related to the proliferation of small-scale decentralized generation, is the possibility for parts of the network comprising sufficient generating resources to operate in isolation from the main grid, in a deliberate and controlled way. These are called Microgrids and the study and development of technology to permit their efficient operation has recently started with a great momentum ([1,2]). Microgrids are foreseen within public distribution grids and therefore suitable study case networks are required to perform simulation and analysis tasks. Moreover, standardizing study case grids to provide “benchmark” networks suitable for Microgrid design would further enhance their merit and utility. The objective of this paper is to present and discuss a benchmark LV network developed within the EU project “Microgrids”, Contract ENK5-CT-2002-00610 and later adopted as a benchmark LV system by CIGRE TF C6.04.02: “Computational Tools and Techniques for Analysis, Design and Validation of Distributed Generation Systems”. The network consists of an LV feeder, while a more extended multi-feeder version is also included in the Appendix. The emphasis is placed on the network itself, rather than on the microsources connected and the control concepts applied. The benchmark network maintains the important technical characteristic of real utility grids, whereas, at the same time, it dispenses with the complexity of actual networks, to permit efficient modeling and simulation of microgrid operation.