Abstract: This paper deals with the steady and unsteady flow behavior on the separation bubble occurring on the rear portion of the suction side of T106A blade. The first phase was to implement the steady condition capturing the separation bubble. To accurately predict the separated region, the effects of three different turbulence models and computational grids were separately investigated. The results of Large Eddy Simulation (LES) model on the finest grid structure are acceptably in a good agreement with its relevant experimental results. The second phase is mainly to address the effects of wake entrance on bubble disappearance in unsteady situation. In the current simulations, from what was suggested in an experiment, simulating the flow unsteadiness, with concentrations on small scale disturbances instead of simulating a complete oncoming wake, is the key issue. Subsequently, the results from the current strategy to apply the effects of the wake and two other experimental work were compared to be in a good agreement. Between the two experiments, one of them deals with wake passing unsteady flow, and the other one implements experimentally the same approach as the current Computational Fluid Dynamics (CFD) simulation.
Abstract: Multi-modal film boiling simulations are carried out on adaptive octree grids. The liquid-vapor interface is captured using the volume-of-fluid framework adjusted to account for exchanges of mass, momentum, and energy across the interface. Surface tension effects are included using a volumetric source term in the momentum equations. The phase change calculations are conducted based on the exact location and orientation of the interface; however, the source terms are calculated using the mixture variables to be consistent with the one field formulation used to represent the entire fluid domain. The numerical model on octree representation of the computational grid is first verified using test cases including advection tests in severely deforming velocity fields, gravity-based instabilities and bubble growth in uniformly superheated liquid under zero gravity. The model is then used to simulate both single and multi-modal film boiling simulations. The octree grid is dynamically adapted in order to maintain the highest grid resolution on the instability fronts using markers of interface location, volume fraction, and thermal gradients. The method thus provides an efficient platform to simulate fluid instabilities with or without phase change in the presence of body forces like gravity or shear layer instabilities.
Abstract: Grid is an environment with millions of resources
which are dynamic and heterogeneous in nature. A computational
grid is one in which the resources are computing nodes and is meant
for applications that involves larger computations. A scheduling
algorithm is said to be efficient if and only if it performs better
resource allocation even in case of resource failure. Resource
allocation is a tedious issue since it has to consider several
requirements such as system load, processing cost and time, user’s
deadline and resource failure. This work attempts in designing a
resource allocation algorithm which is cost-effective and also targets
at load balancing, fault tolerance and user satisfaction by considering
the above requirements. The proposed Budget Constrained Load
Balancing Fault Tolerant algorithm with user satisfaction (BLBFT)
reduces the schedule makespan, schedule cost and task failure rate
and improves resource utilization. Evaluation of the proposed
BLBFT algorithm is done using Gridsim toolkit and the results are
compared with the algorithms which separately concentrates on all
these factors. The comparison results ensure that the proposed
algorithm works better than its counterparts.
Abstract: The indoor airflow with a mixed natural/forced convection
was numerically calculated using the laminar and turbulent
approach. The Boussinesq approximation was considered for a simplification
of the mathematical model and calculations. The results
obtained, such as mean velocity fields, were successfully compared
with experimental PIV flow visualizations. The effect of the distance
between the cooled wall and the heat exchanger on the temperature
and velocity distributions was calculated. In a room with a simple
shape, the computational code OpenFOAM demonstrated an ability to
numerically predict flow patterns. Furthermore, numerical techniques,
boundary type conditions and the computational grid quality were
examined. Calculations using the turbulence model k-omega had a
significant effect on the results influencing temperature and velocity
distributions.
Abstract: In this paper, fully developed flow and heat transfer of
viscoelastic materials in curved ducts with square cross section under
constant heat flux have been investigated. Here, staggered mesh is
used as computational grids and flow and heat transfer parameters
have been allocated in this mesh with marker and cell method.
Numerical solution of governing equations has being performed with
FTCS finite difference method. Furthermore, Criminale-Eriksen-
Filbey (CEF) constitutive equation has being used as viscoelastic
model. CEF constitutive equation is a suitable model for studying
steady shear flow of viscoelastic materials which is able to model
both effects of the first and second normal stress differences. Here, it
is shown that the first and second normal stresses differences have
noticeable and inverse effect on secondary flows intensity and mean
Nusselt number which is the main novelty of current research.
Abstract: This paper presents a study of laminar to turbulent transition on a profile specifically designed for wind turbine blades, the DU91-W2-250, which belongs to a class of wind turbine dedicated airfoils, developed by Delft University of Technology. A comparison between the experimental behavior of the airfoil studied at Delft wind tunnel and the numerical predictions of the commercial CFD solver ANSYS FLUENT® has been performed. The prediction capabilities of the Spalart-Allmaras turbulence model and of the γ-θ Transitional model have been tested. A sensitivity analysis of the numerical results to the spatial domain discretization has also been performed using four different computational grids, which have been created using the mesher GAMBIT®. The comparison between experimental measurements and CFD results have allowed to determine the importance of the numerical prediction of the laminar to turbulent transition, in order not to overestimate airfoil friction drag due to a fully turbulent-regime flow computation.
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: In Virtual organization, Knowledge Discovery (KD)
service contains distributed data resources and computing grid nodes.
Computational grid is integrated with data grid to form Knowledge
Grid, which implements Apriori algorithm for mining association
rule on grid network. This paper describes development of parallel
and distributed version of Apriori algorithm on Globus Toolkit using
Message Passing Interface extended with Grid Services (MPICHG2).
The creation of Knowledge Grid on top of data and
computational grid is to support decision making in real time
applications. In this paper, the case study describes design and
implementation of local and global mining of frequent item sets. The
experiments were conducted on different configurations of grid
network and computation time was recorded for each operation. We
analyzed our result with various grid configurations and it shows
speedup of computation time is almost superlinear.
Abstract: Large scale systems such as computational Grid is
a distributed computing infrastructure that can provide globally
available network resources. The evolution of information processing
systems in Data Grid is characterized by a strong decentralization of
data in several fields whose objective is to ensure the availability and
the reliability of the data in the reason to provide a fault tolerance
and scalability, which cannot be possible only with the use of the
techniques of replication. Unfortunately the use of these techniques
has a height cost, because it is necessary to maintain consistency
between the distributed data. Nevertheless, to agree to live with
certain imperfections can improve the performance of the system by
improving competition. In this paper, we propose a multi-layer protocol
combining the pessimistic and optimistic approaches conceived
for the data consistency maintenance in large scale systems. Our
approach is based on a hierarchical representation model with tree
layers, whose objective is with double vocation, because it initially
makes it possible to reduce response times compared to completely
pessimistic approach and it the second time to improve the quality
of service compared to an optimistic approach.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.
Abstract: The problem of mapping tasks onto a computational grid with the aim to minimize the power consumption and the makespan subject to the constraints of deadlines and architectural requirements is considered in this paper. To solve this problem, we propose a solution from cooperative game theory based on the concept of Nash Bargaining Solution. The proposed game theoretical technique is compared against several traditional techniques. The experimental results show that when the deadline constraints are tight, the proposed technique achieves superior performance and reports competitive performance relative to the optimal solution.
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: Market based models are frequently used in the resource
allocation on the computational grid. However, as the size of
the grid grows, it becomes difficult for the customer to negotiate
directly with all the providers. Middle agents are introduced to
mediate between the providers and customers and facilitate the
resource allocation process. The most frequently deployed middle
agents are the matchmakers and the brokers. The matchmaking agent
finds possible candidate providers who can satisfy the requirements
of the consumers, after which the customer directly negotiates with
the candidates. The broker agents are mediating the negotiation with
the providers in real time.
In this paper we present a new type of middle agent, the marketmaker.
Its operation is based on two parallel operations - through
the investment process the marketmaker is acquiring resources and
resource reservations in large quantities, while through the resale process
it sells them to the customers. The operation of the marketmaker
is based on the fact that through its global view of the grid it can
perform a more efficient resource allocation than the one possible in
one-to-one negotiations between the customers and providers.
We present the operation and algorithms governing the operation
of the marketmaker agent, contrasting it with the matchmaker and
broker agents. Through a series of simulations in the task oriented
domain we compare the operation of the three agents types. We find
that the use of marketmaker agent leads to a better performance in the
allocation of large tasks and a significant reduction of the messaging
overhead.
Abstract: Phase-Contrast MR imaging methods are widely used
for measurement of blood flow velocity components. Also there are
some other tools such as CT and Ultrasound for velocity map
detection in intravascular studies. These data are used in deriving
flow characteristics. Some clinical applications are investigated
which use pressure distribution in diagnosis of intravascular disorders
such as vascular stenosis. In this paper an approach to the problem of
measurement of intravascular pressure field by using velocity field
obtained from flow images is proposed. The method presented in this
paper uses an algorithm to calculate nonlinear equations of Navier-
Stokes, assuming blood as an incompressible and Newtonian fluid.
Flow images usually suffer the lack of spatial resolution. Our
attempt is to consider the effect of spatial resolution on the pressure
distribution estimated from this method. In order to achieve this aim,
velocity map of a numerical phantom is derived at six different
spatial resolutions. To determine the effects of vascular stenoses on
pressure distribution, a stenotic phantom geometry is considered. A
comparison between the pressure distribution obtained from the
phantom and the pressure resulted from the algorithm is presented. In
this regard we also compared the effects of collocated and staggered
computational grids on the pressure distribution resulted from this
algorithm.
Abstract: Some meta-schedulers query the information system of individual supercomputers in order to submit jobs to the least busy supercomputer on a computational Grid. However, this information can become outdated by the time a job starts due to changes in scheduling priorities. The MSR scheme is based on Multiple Simultaneous Requests and can take advantage of opportunities resulting from these priorities changes. This paper presents the SWARM meta-scheduler, which can speed up the execution of large sets of tasks by minimizing the job queuing time through the submission of multiple requests. Performance tests have shown that this new meta-scheduler is faster than an implementation of the MSR scheme and the gLite meta-scheduler. SWARM has been used through the GridQTL project beta-testing portal during the past year. Statistics are provided for this usage and demonstrate its capacity to achieve reliably a substantial reduction of the execution time in production conditions.