Abstract: The Spalart and Allmaras turbulence model has been
implemented in a numerical code to study the compressible turbulent
flows, which the system of governing equations is solved with a
finite volume approach using a structured grid. The AUSM+ scheme
is used to calculate the inviscid fluxes. Different benchmark
problems have been computed to validate the implementation and
numerical results are shown. A special Attention is paid to wall jet
applications. In this study, the jet is submitted to various wall
boundary conditions (adiabatic or uniform heat flux) in forced
convection regime and both two-dimensional and axisymmetric wall
jets are considered. The comparison between the numerical results
and experimental data has given the validity of this turbulence model
to study the turbulent wall jets especially in engineering applications.
Abstract: Grid computing provides a virtual framework for
controlled sharing of resources across institutional boundaries.
Recently, trust has been recognised as an important factor for
selection of optimal resources in a grid. We introduce a new method
that provides a quantitative trust value, based on the past interactions
and present environment characteristics. This quantitative trust value
is used to select a suitable resource for a job and eliminates run time
failures arising from incompatible user-resource pairs. The proposed
work will act as a tool to calculate the trust values of the various
components of the grid and there by improves the success rate of the
jobs submitted to the resource on the grid. The access to a resource
not only depend on the identity and behaviour of the resource but
also upon its context of transaction, time of transaction, connectivity
bandwidth, availability of the resource and load on the resource. The
quality of the recommender is also evaluated based on the accuracy
of the feedback provided about a resource. The jobs are submitted for
execution to the selected resource after finding the overall trust value
of the resource. The overall trust value is computed with respect to
the subjective and objective parameters.
Abstract: Resource discovery is one of the chief services of a grid. A new approach to discover the provenances in grid through learning automata has been propounded in this article. The objective of the aforementioned resource-discovery service is to select the resource based upon the user-s applications and the mercantile yardsticks that is to say opting for an originator which can accomplish the user-s tasks in the most economic manner. This novel service is submitted in two phases. We proffered an applicationbased categorization by means of an intelligent nerve-prone plexus. The user in question sets his or her application as the input vector of the nerve-prone nexus. The output vector of the aforesaid network limns the appropriateness of any one of the resource for the presented executive procedure. The most scrimping option out of those put forward in the previous stage which can be coped with to fulfill the task in question is picked out. Te resource choice is carried out by means of the presented algorithm based upon the learning automata.
Abstract: A typical definition of the Computer Aided Diagnosis
(CAD), found in literature, can be: A diagnosis made by a radiologist
using the output of a computerized scheme for automated image
analysis as a diagnostic aid. Often it is possible to find the expression
Computer Aided Detection (CAD or CADe): this definition
emphasizes the intent of CAD to support rather than substitute the
human observer in the analysis of radiographic images. In this article
we will illustrate the application of CAD systems and the aim of
these definitions.
Commercially available CAD systems use computerized
algorithms for identifying suspicious regions of interest. In this paper
are described the general CAD systems as an expert system
constituted of the following components: segmentation / detection,
feature extraction, and classification / decision making.
As example, in this work is shown the realization of a Computer-
Aided Detection system that is able to assist the radiologist in
identifying types of mammary tumor lesions. Furthermore this
prototype of station uses a GRID configuration to work on a large
distributed database of digitized mammographic images.
Abstract: This paper is a numerical investigation of a laminar
isothermal plane two dimensional wall jet. Special attention has been
paid to the effect of the inlet conditions at the nozzle exit on the
hydrodynamic and thermal characteristics of the flow. The
behaviour of various fluids evolving in both forced and mixed
convection regimes near a vertical plate plane is carried out. The
system of governing equations is solved with an implicit finite
difference scheme. For numerical stability we use a staggered non
uniform grid. The obtained results show that the effect of the Prandtl
number is significant in the plume region in which the jet flow is
governed by buoyant forces. Further for ascending X values, the
buoyancy forces become dominating, and a certain agreement
between the temperature profiles are observed, which shows that the
velocity profile has no longer influence on the wall temperature
evolution in this region. Fluids with low Prandtl number warm up
more importantly, because for such fluids the effect of heat diffusion
is higher.
Abstract: This paper focuses on developing an integrated
reliable and sophisticated model for ultra large wind turbines And to
study the performance and analysis of vector control on large wind
turbines. With the advance of power electronics technology, direct
driven multi-pole radial flux PMSG (Permanent Magnet Synchronous
Generator) has proven to be a good choice for wind turbines
manufacturers. To study the wind energy conversion systems, it is
important to develop a wind turbine simulator that is able to produce
realistic and validated conditions that occur in real ultra MW wind
turbines. Three different packages are used to simulate this model,
namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind
simulator developed by National Renewable Energy Laboratory
(NREL). The wind turbine mechanical parts are modeled by FAST
(Fatigue, Aerodynamics, Structures and Turbulence) code which is
also developed by NREL. Simulink is used to model the PMSG, full
scale back to back IGBT converters, and the grid.
Abstract: This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.
Abstract: In a liberalized electricity market, it is not surprising
that different customers require different power quality (PQ) levels at
different price. Power quality related to several power disturbances is
described by many parameters, so how to define a comprehensive
hierarchy evaluation system of power quality (PQCHES) has become
a concerned issue. In this paper, based on four electromagnetic
compatibility (EMC) levels, the numerical range of each power
disturbance is divided into five grades (Grade I –Grade V), and the
“barrel principle" of power quality is used for the assessment of
overall PQ performance with only one grade indicator. A case study
based on actual monitored data of PQ shows that the site PQ grade
indicates the electromagnetic environment level and also expresses the
characteristics of loads served by the site.
The shortest plank principle of PQ barrel is an incentive
mechanism, which can combine with the rewards/penalty mechanism
(RPM) of consumed energy “on quality demand", to stimulate utilities
to improve the overall PQ level and also stimulate end-user more
“smart" under the infrastructure of future SmartGrid..
Abstract: We provide a maximum norm analysis of a finite
element Schwarz alternating method for a nonlinear elliptic boundary
value problem of the form -Δu = f(u), on two overlapping sub
domains with non matching grids. We consider a domain which is
the union of two overlapping sub domains where each sub domain
has its own independently generated grid. The two meshes being
mutually independent on the overlap region, a triangle belonging to
one triangulation does not necessarily belong to the other one. Under
a Lipschitz assumption on the nonlinearity, we establish, on each sub
domain, an optimal L∞ error estimate between the discrete Schwarz
sequence and the exact solution of the boundary value problem.
Abstract: Querying a data source and routing data towards sink
becomes a serious challenge in static wireless sensor networks if sink
and/or data source are mobile. Many a times the event to be observed
either moves or spreads across wide area making maintenance of
continuous path between source and sink a challenge. Also, sink can
move while query is being issued or data is on its way towards sink.
In this paper, we extend our already proposed Grid Based Data
Dissemination (GBDD) scheme which is a virtual grid based
topology management scheme restricting impact of movement of
sink(s) and event(s) to some specific cells of a grid. This obviates the
need for frequent path modifications and hence maintains continuous
flow of data while minimizing the network energy consumptions.
Simulation experiments show significant improvements in network
energy savings and average packet delay for a packet to reach at sink.
Abstract: Grid computing is a group of clusters connected over
high-speed networks that involves coordinating and sharing
computational power, data storage and network resources operating
across dynamic and geographically dispersed locations. Resource
management and job scheduling are critical tasks in grid computing.
Resource selection becomes challenging due to heterogeneity and
dynamic availability of resources. Job scheduling is a NP-complete
problem and different heuristics may be used to reach an optimal or
near optimal solution. This paper proposes a model for resource and
job scheduling in dynamic grid environment. The main focus is to
maximize the resource utilization and minimize processing time of
jobs. Grid resource selection strategy is based on Max Heap Tree
(MHT) that best suits for large scale application and root node of
MHT is selected for job submission. Job grouping concept is used to
maximize resource utilization for scheduling of jobs in grid
computing. Proposed resource selection model and job grouping
concept are used to enhance scalability, robustness, efficiency and
load balancing ability of the grid.
Abstract: Cosmic showers, during the transit through space, produce
sub - products as a result of interactions with the intergalactic
or interstellar medium which after entering earth generate secondary
particles called Extensive Air Shower (EAS). Detection and analysis
of High Energy Particle Showers involve a plethora of theoretical and
experimental works with a host of constraints resulting in inaccuracies
in measurements. Therefore, there exist a necessity to develop a
readily available system based on soft-computational approaches
which can be used for EAS analysis. This is due to the fact that soft
computational tools such as Artificial Neural Network (ANN)s can be
trained as classifiers to adapt and learn the surrounding variations. But
single classifiers fail to reach optimality of decision making in many
situations for which Multiple Classifier System (MCS) are preferred
to enhance the ability of the system to make decisions adjusting
to finer variations. This work describes the formation of an MCS
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN) with data inputs
from correlation mapping Self Organizing Map (SOM) blocks and
the output optimized by another SOM. The results show that the setup
can be adopted for real time practical applications for prediction
of primary energy and location of EAS from density values captured
using detectors in a circular grid.
Abstract: The deficit of power for electricity demand reaches
almost 30% for consumers in the last few years. This reflects with
continually increasing the price of electricity, and today the price for
small industry is almost 110Euro/MWh. The high price is additional
problem for the owners in the economy crisis which is reflected with
higher price of the goods.
The paper gives analyses of the energy needs for real agro
complex in Macedonia, private vinery with capacity of over 2 million
liters in a year and with self grapes and fruits fields. The existing
power supply is from grid with 10/04 kV transformer. The
geographical and meteorological condition of the vinery location
gives opportunity for including renewable as a power supply option
for the vinery complex.
After observation of the monthly energy needs for the vinery, the
base scenario is the existing power supply from the distribution grid.
The electricity bill in small industry has three factors: electricity in
high and low tariffs in kWh and the power engaged for the
technological process of production in kW. These three factors make
the total electricity bill and it is over 110 Euro/MWh which is the
price near competitive for renewable option. On the other side
investments in renewable (especially photovoltaic (PV)) has tendency
of decreasing with price of near 1,5 Euro/W. This means that
renewable with PV can be real option for power supply for small
industry capacities (under 500kW installed power).
Therefore, the other scenarios give the option with PV and the last
one includes wind option. The paper presents some scenarios for
power supply of the vinery as the followings:
• Base scenario of existing conventional power supply from the
grid
• Scenario with implementation of renewable of Photovoltaic
• Scenario with implementation of renewable of Photovoltaic and
Wind power
The total power installed in a vinery is near 570 kW, but the
maximum needs are around 250kW. At the end of the full paper some
of the results from scenarios will be presented. The paper also
includes the environmental impacts of the renewable scenarios, as
well as financial needs for investments and revenues from renewable.
Abstract: Clustering algorithms help to understand the hidden
information present in datasets. A dataset may contain intrinsic and
nested clusters, the detection of which is of utmost importance. This
paper presents a Distributed Grid-based Density Clustering algorithm
capable of identifying arbitrary shaped embedded clusters as well as
multi-density clusters over large spatial datasets. For handling
massive datasets, we implemented our method using a 'sharednothing'
architecture where multiple computers are interconnected
over a network. Experimental results are reported to establish the
superiority of the technique in terms of scale-up, speedup as well as
cluster quality.
Abstract: This paper present a circular patch microstrip array antenna operate in KU-band (10.9GHz – 17.25GHz). The proposed circular patch array antenna will be in light weight, flexible, slim and compact unit compare with current antenna used in KU-band. The paper also presents the detail steps of designing the circular patch microstrip array antenna. An Advance Design System (ADS) software is used to compute the gain, power, radiation pattern, and S11 of the antenna. The proposed Circular patch microstrip array antenna basically is a phased array consisting of 'n' elements (circular patch antennas) arranged in a rectangular grid. The size of each element is determined by the operating frequency. The incident wave from satellite arrives at the plane of the antenna with equal phase across the surface of the array. Each 'n' element receives a small amount of power in phase with the others. There are feed network connects each element to the microstrip lines with an equal length, thus the signals reaching the circular patches are all combined in phase and the voltages add up. The significant difference of the circular patch array antenna is not come in the phase across the surface but in the magnitude distribution.
Abstract: On a such wide-area environment as a Grid, data
placement is an important aspect of distributed database systems. In
this paper, we address the problem of initial placement of database
no-replicated fragments in Grid architecture. We propose a graph
based approach that considers resource restrictions. The goal is to
optimize the use of computing, storage and communication
resources. The proposed approach is developed in two phases: in the
first phase, we perform fragment grouping using knowledge about
fragments dependency and, in the second phase, we determine an
efficient placement of the fragment groups on the Grid. We also
show, via experimental analysis that our approach gives solutions
that are close to being optimal for different databases and Grid
configurations.
Abstract: A major requirement for Grid application developers is ensuring performance and scalability of their applications. Predicting the performance of an application demands understanding its specific features. This paper discusses performance modeling and prediction of multi-agent based simulation (MABS) applications on the Grid. An experiment conducted using a synthetic MABS workload explains the key features to be included in the performance model. The results obtained from the experiment show that the prediction model developed for the synthetic workload can be used as a guideline to understand to estimate the performance characteristics of real world simulation applications.
Abstract: This study presents the numerical simulation of
optimum pin-fin heat sink with air impinging cooling by using
Taguchi method. 9 L ( 4 3 ) orthogonal array is selected as a plan for
the four design-parameters with three levels. The governing
equations are discretized by using the
control-volume-based-finite-difference method with a power-law
scheme on the non-uniform staggered grid. We solved the coupling of
the velocity and the pressure terms of momentum equations using
SIMPLEC algorithm. We employ the k −ε two-equations
turbulence model to describe the turbulent behavior. The parameters
studied include fin height H (35mm-45mm), inter-fin spacing a , b ,
and c (2 mm-6.4 mm), and Reynolds number ( Re = 10000- 25000).
The objective of this study is to examine the effects of the fin
spacings and fin height on the thermal resistance and to find the
optimum group by using the Taguchi method. We found that the fin
spacings from the center to the edge of the heat sink gradually
extended, and the longer the fin’s height the better the results. The
optimum group is 3 1 2 3 H a b c . In addition, the effects of parameters are
ranked by importance as a , H , c , and b .
Abstract: Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.
Abstract: This paper presents a method for the optimal
allocation of Distributed generation in distribution systems. In this
paper, our aim would be optimal distributed generation allocation for
voltage profile improvement and loss reduction in distribution
network. Genetic Algorithm (GA) was used as the solving tool,
which referring two determined aim; the problem is defined and
objective function is introduced. Considering to fitness values
sensitivity in genetic algorithm process, there is needed to apply load
flow for decision-making. Load flow algorithm is combined
appropriately with GA, till access to acceptable results of this
operation. We used MATPOWER package for load flow algorithm
and composed it with our Genetic Algorithm. The suggested method
is programmed under MATLAB software and applied ETAP
software for evaluating of results correctness. It was implemented on
part of Tehran electricity distributing grid. The resulting operation of
this method on some testing system is illuminated improvement of
voltage profile and loss reduction indexes.