Abstract: A Multi-dimensional computational fluid dynamics
(CFD) two-phase model was developed with the aim to simulate
the in-core coolant circuit of a pressurized heavy water reactor
(PHWR) of a commercial nuclear power plant (NPP). Due to the
fact that this PHWR is a Reactor Pressure Vessel type (RPV),
three-dimensional (3D) detailed modelling of the large reservoirs of
the RPV (the upper and lower plenums and the downcomer) were
coupled with an in-house finite volume one-dimensional (1D) code
in order to model the 451 coolant channels housing the nuclear fuel.
Regarding the 1D code, suitable empirical correlations for taking into
account the in-channel distributed (friction losses) and concentrated
(spacer grids, inlet and outlet throttles) pressure losses were used.
A local power distribution at each one of the coolant channels
was also taken into account. The heat transfer between the coolant
and the surrounding moderator was accurately calculated using a
two-dimensional theoretical model. The implementation of subcooled
boiling and condensation models in the 1D code along with the use
of functions for representing the thermal and dynamic properties of
the coolant and moderator (heavy water) allow to have estimations
of the in-core steam generation under nominal flow conditions for a
generic fission power distribution. The in-core mass flow distribution
results for steady state nominal conditions are in agreement with the
expected from design, thus getting a first assessment of the coupled
1/3D model. Results for nominal condition were compared with
those obtained with a previous 1/3D single-phase model getting more
realistic temperature patterns, also allowing visualize low values of
void fraction inside the upper plenum. It must be mentioned that the
current results were obtained by imposing prescribed fission power
functions from literature. Therefore, results are showed with the aim
of point out the potentiality of the developed model.
Abstract: Non-linear dynamic time history analysis is
considered as the most advanced and comprehensive analytical
method for evaluating the seismic response and performance of
multi-degree-of-freedom building structures under the influence of
earthquake ground motions. However, effective and accurate
application of the method requires the implementation of advanced
hysteretic constitutive models of the various structural components
including masonry infill panels. Sophisticated computational research
tools that incorporate realistic hysteresis models for non-linear
dynamic time-history analysis are not popular among the professional
engineers as they are not only difficult to access but also complex and
time-consuming to use. In addition, commercial computer programs
for structural analysis and design that are acceptable to practicing
engineers do not generally integrate advanced hysteretic models
which can accurately simulate the hysteresis behavior of structural
elements with a realistic representation of strength degradation,
stiffness deterioration, energy dissipation and ‘pinching’ under cyclic
load reversals in the inelastic range of behavior. In this scenario,
push-over or non-linear static analysis methods have gained
significant popularity, as they can be employed to assess the seismic
performance of building structures while avoiding the complexities
and difficulties associated with non-linear dynamic time-history
analysis. “Push-over” or non-linear static analysis offers a practical
and efficient alternative to non-linear dynamic time-history analysis
for rationally evaluating the seismic demands. The present paper is
based on the analytical investigation of the effect of distribution of
masonry infill panels over the elevation of planar masonry infilled
reinforced concrete [R/C] frames on the seismic demands using the
capacity spectrum procedures implementing nonlinear static analysis
[pushover analysis] in conjunction with the response spectrum
concept. An important objective of the present study is to numerically
evaluate the adequacy of the capacity spectrum method using
pushover analysis for performance based design of masonry infilled
R/C frames for near-field earthquake ground motions.
Abstract: This paper addresses the problem of offline path
planning for Unmanned Aerial Vehicles (UAVs) in complex threedimensional
environment with obstacles, which is modelled by 3D
Cartesian grid system. Path planning for UAVs require the
computational intelligence methods to move aerial vehicles along the
flight path effectively to target while avoiding obstacles. In this paper
Modified Particle Swarm Optimization (MPSO) algorithm is applied
to generate the optimal collision free 3D flight path for UAV. The
simulations results clearly demonstrate effectiveness of the proposed
algorithm in guiding UAV to the final destination by providing
optimal feasible path quickly and effectively.
Abstract: In this study, the three-dimensional cavitating
turbulent flow in a complete Francis turbine is simulated using
mixture model for cavity/liquid two-phase flows. Numerical analysis
is carried out using ANSYS CFX software release 12, and standard k-ε
turbulence model is adopted for this analysis. The computational
fluid domain consist of spiral casing, stay vanes, guide vanes, runner
and draft tube. The computational domain is discretized with a threedimensional
mesh system of unstructured tetrahedron mesh. The
finite volume method (FVM) is used to solve the governing equations
of the mixture model. Results of cavitation on the runner’s blades
under three different boundary conditions are presented and
discussed. From the numerical results it has been found that the
numerical method was successfully applied to simulate the cavitating
two-phase turbulent flow through a Francis turbine, and also
cavitation is clearly predicted in the form of water vapor formation
inside the turbine. By comparison the numerical prediction results
with a real runner; it’s shown that the region of higher volume
fraction obtained by simulation is consistent with the region of runner
cavitation damage.
Abstract: In this paper genetic based test data compression is
targeted for improving the compression ratio and for reducing the
computation time. The genetic algorithm is based on extended pattern
run-length coding. The test set contains a large number of X value
that can be effectively exploited to improve the test data
compression. In this coding method, a reference pattern is set and its
compatibility is checked. For this process, a genetic algorithm is
proposed to reduce the computation time of encoding algorithm. This
coding technique encodes the 2n compatible pattern or the inversely
compatible pattern into a single test data segment or multiple test data
segment. The experimental result shows that the compression ratio
and computation time is reduced.
Abstract: Obturator Foramen is a specific structure in Pelvic
bone images and recognition of it is a new concept in medical image
processing. Moreover, segmentation of bone structures such as
Obturator Foramen plays an essential role for clinical research in
orthopedics. In this paper, we present a novel method to analyze the
similarity between the substructures of the imaged region and a hand
drawn template as a preprocessing step for computation of Pelvic
bone rotation on hip radiographs. This method consists of integrated
usage of Marker-controlled Watershed segmentation and Zernike
moment feature descriptor and it is used to detect Obturator Foramen
accurately. Marker-controlled Watershed segmentation is applied to
separate Obturator Foramen from the background effectively. Then,
Zernike moment feature descriptor is used to provide matching
between binary template image and the segmented binary image for
final extraction of Obturator Foramens. Finally, Pelvic bone rotation
rate calculation for each hip radiograph is performed automatically to
select and eliminate hip radiographs for further studies which depend
on Pelvic bone angle measurements. The proposed method is tested
on randomly selected 100 hip radiographs. The experimental results
demonstrated that the proposed method is able to segment Obturator
Foramen with 96% accuracy.
Abstract: Presently various computational techniques are used
in modeling and analyzing environmental engineering data. In the
present study, an intra-comparison of polynomial and radial basis
kernel functions based on Support Vector Regression and, in turn, an
inter-comparison with Multi Linear Regression has been attempted in
modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ
multiple plunging jets (varying from 1 to 16 numbers). The data set
used in this study consists of four input parameters with a total of
eighty eight cases, forty four each for vertical and inclined multiple
plunging jets. For testing, tenfold cross validation was used.
Correlation coefficient values of 0.971 and 0.981 along with
corresponding root mean square error values of 0.0025 and 0.0020
were achieved by using polynomial and radial basis kernel functions
based Support Vector Regression respectively. An intra-comparison
suggests improved performance by radial basis function in
comparison to polynomial kernel based Support Vector Regression.
Further, an inter-comparison with Multi Linear Regression
(correlation coefficient = 0.973 and root mean square error = 0.0024)
reveals that radial basis kernel functions based Support Vector
Regression performs better in modeling and estimating mass transfer
by multiple plunging jets.
Abstract: Imperialist Competitive Algorithm (ICA) is a recent
meta-heuristic method that is inspired by the social evolutions for
solving NP-Hard problems. The ICA is a population-based algorithm
which has achieved a great performance in comparison to other metaheuristics.
This study is about developing enhanced ICA approach to
solve the Cell Formation Problem (CFP) using sequence data. In
addition to the conventional ICA, an enhanced version of ICA,
namely EICA, applies local search techniques to add more
intensification aptitude and embed the features of exploration and
intensification more successfully. Suitable performance measures are
used to compare the proposed algorithms with some other powerful
solution approaches in the literature. In the same way, for checking
the proficiency of algorithms, forty test problems are presented. Five
benchmark problems have sequence data, and other ones are based on
0-1 matrices modified to sequence based problems. Computational
results elucidate the efficiency of the EICA in solving CFP problems.
Abstract: This research presents the design and analysis of solar
air-conditioning systems particularly solar chimney which is a
passive strategy for natural ventilation, and demonstrates the
structures of these systems’ using Computational Fluid Dynamic
(CFD) and finally compares the results with several examples, which
have been studied experimentally and carried out previously. In order
to improve the performance of solar chimney system, highly efficient
sub-system components are considered for the design. The general
purpose of the research is to understand how efficiently solar
chimney systems generate cooling, and is to improve the efficient of
such systems for integration with existing and future domestic
buildings.
Abstract: This paper develops a multiple channel assignment
model, which allows to take advantage of spectrum opportunities in
cognitive radio networks in the most efficient way. The developed
scheme allows making several assignments of available and
frequency adjacent channel, which require a bigger bandwidth, under
an equality environment. The hybrid assignment model it is made by
two algorithms, one that makes the ranking and selects available
frequency channels and the other one in charge of establishing the
Max-Min Fairness for not restrict the spectrum opportunities for all
the other secondary users, who also claim to make transmissions.
Measurements made were done for average bandwidth, average
delay, as well as fairness computation for several channel
assignments. Reached results were evaluated with experimental
spectrum occupational data from captured GSM frequency band. The
developed model shows evidence of improvement in spectrum
opportunity use and a wider average transmission bandwidth for each
secondary user, maintaining equality criteria in channel assignment.
Abstract: This paper integrates Octagon and Square Search
pattern (OCTSS) motion estimation algorithm into H.264/AVC
(Advanced Video Coding) video codec in Adaptive Group of Pictures
(AGOP) mode. AGOP structure is computed based on scene change
in the video sequence. Octagon and square search pattern block-based
motion estimation method is implemented in inter-prediction process
of H.264/AVC. Both these methods reduce bit rate and computational
complexity while maintaining the quality of the video sequence
respectively. Experiments are conducted for different types of video
sequence. The results substantially proved that the bit rate,
computation time and PSNR gain achieved by the proposed method
is better than the existing H.264/AVC with fixed GOP and AGOP.
With a marginal gain in quality of 0.28dB and average gain in bitrate
of 132.87kbps, the proposed method reduces the average computation
time by 27.31 minutes when compared to the existing state-of-art
H.264/AVC video codec.
Abstract: This article presents the main results of a numerical
investigation on the uncertainty of dynamic response of structures
with statistically correlated random damping Gamma distributed. A
computational method based on a Linear Statistical Model (LSM) is
implemented to predict second order statistics for the response of a
typical industrial building structure. The significance of random
damping with correlated parameters and its implications on the
sensitivity of structural peak response in the neighborhood of a
resonant frequency are discussed in light of considerable ranges of
damping uncertainties and correlation coefficients. The results are
compared to those generated using Monte Carlo simulation
techniques. The numerical results obtained show the importance of
damping uncertainty and statistical correlation of damping
coefficients when obtaining accurate probabilistic estimates of
dynamic response of structures. Furthermore, the effectiveness of the
LSM model to efficiently predict uncertainty propagation for
structural dynamic problems with correlated damping parameters is
demonstrated.
Abstract: The present study focused on the investigation of the
effects of roughness elements on heat transfer during natural
convection in a rectangular cavity using numerical technique.
Roughness elements were introduced on the bottom hot wall with a
normalized amplitude (A*/H) of 0.1. Thermal and hydrodynamic
behaviors were studied using computational method based on Lattice
Boltzmann method (LBM). Numerical studies were performed for a
laminar flow in the range of Rayleigh number (Ra) from 103 to 106
for a rectangular cavity of aspect ratio (L/H) 2.0 with a fluid of
Prandtl number (Pr) 1.0. The presence of the sinusoidal roughness
elements caused a minimum to maximum decrease in the heat
transfer as 7% to 17% respectively compared to smooth enclosure.
The results are presented for mean Nusselt number (Nu), isotherms
and streamlines.
Abstract: This paper describes a subarray based low
computational design method of multiuser massive multiple
input multiple output (MIMO) system. In our previous works, use of
large array is assumed only in transmitter, but this study considers
the case both of transmitter and receiver sides are equipped with
large array antennas. For this aim, receive arrays are also divided
into several subarrays, and the former proposed method is modified
for the synthesis of a large array from subarrays in both ends.
Through computer simulations, it is verified that the performance
of the proposed method is degraded compared with the original
approach, but it can achieve the improvement in the aspect of
complexity, namely, significant reduction of the computational load
to the practical level.
Abstract: Radiative heat transfer in participating medium was
carried out using the finite volume method. The radiative transfer
equations are formulated for absorbing and anisotropically scattering
and emitting medium. The solution strategy is discussed and the
conditions for computational stability are conferred. The equations
have been solved for transient radiative medium and transient
radiation incorporated with transient conduction. Results have been
obtained for irradiation and corresponding heat fluxes for both the
cases. The solutions can be used to conclude incident energy and
surface heat flux. Transient solutions were obtained for a slab of heat
conducting in slab and by thermal radiation. The effect of heat
conduction during the transient phase is to partially equalize the
internal temperature distribution. The solution procedure provides
accurate temperature distributions in these regions. A finite volume
procedure with variable space and time increments is used to solve
the transient radiation equation. The medium in the enclosure
absorbs, emits, and anisotropically scatters radiative energy. The
incident radiations and the radiative heat fluxes are presented in
graphical forms. The phase function anisotropy plays a significant
role in the radiation heat transfer when the boundary condition is
non-symmetric.
Abstract: In recent years, new techniques for solving complex
problems in engineering are proposed. One of these techniques is
JPSO algorithm. With innovative changes in the nature of the jump
algorithm JPSO, it is possible to construct a graph-based solution
with a new algorithm called G-JPSO. In this paper, a new algorithm
to solve the optimal control problem Fletcher-Powell and optimal
control of pumps in water distribution network was evaluated.
Optimal control of pumps comprise of optimum timetable operation
(status on and off) for each of the pumps at the desired time interval.
Maximum number of status on and off for each pumps imposed to the
objective function as another constraint. To determine the optimal
operation of pumps, a model-based optimization-simulation
algorithm was developed based on G-JPSO and JPSO algorithms.
The proposed algorithm results were compared well with the ant
colony algorithm, genetic and JPSO results. This shows the
robustness of proposed algorithm in finding near optimum solutions
with reasonable computational cost.
Abstract: This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for the jobs and the advance/tardiness for the maintenance activities. To solve the problem, a genetic algorithm was developed and successfully tested and validated on many problem instances. The computational results showed that the new genetic algorithm outperforms another earlier proposed algorithm.
Abstract: This paper addresses minimizing the makespan of the
distributed permutation flow shop scheduling problem. In this
problem, there are several parallel identical factories or flowshops
each with series of similar machines. Each job should be allocated to
one of the factories and all of the operations of the jobs should be
performed in the allocated factory. This problem has recently gained
attention and due to NP-Hard nature of the problem, metaheuristic
algorithms have been proposed to tackle it. Majority of the proposed
algorithms require large computational time which is the main
drawback. In this study, a general variable neighborhood search
algorithm (GVNS) is proposed where several time-saving schemes
have been incorporated into it. Also, the GVNS uses the sophisticated
method to change the shaking procedure or perturbation depending
on the progress of the incumbent solution to prevent stagnation of the
search. The performance of the proposed algorithm is compared to
the state-of-the-art algorithms based on standard benchmark
instances.
Abstract: Space Vector Pulse Width Modulation is popular for
variable frequency drives. The method has several advantages over
carried based PWM and is computation intensive. The
implementation of SVPWM for multilevel inverter requires special
attention and at the same time consumes considerable resources. Due
to faster processing power and reduced over all computational
burden, FPGAs are being investigated as an alternative for other
controllers. In this paper, a space vector PWM algorithm is
implemented using FPGA which requires less computational area and
is modular in structure. The algorithm is verified experimentally for
Neutral Point Clamped inverter using FPGA development board
xc3s5000-4fg900.
Abstract: Ecological systems are exposed and are influenced by
various natural and anthropogenic disturbances. They produce
various effects and states seeking response symmetry to a state of
global phase coherence or stability and balance of their food webs.
This research project addresses the development of a computational
methodology for modeling plankton food webs. The use of
algorithms to establish connections, the generation of representative
fuzzy multigraphs and application of technical analysis of complex
networks provide a set of tools for defining, analyzing and evaluating
community structure of coastal aquatic ecosystems, beyond the
estimate of possible external impacts to the networks. Thus, this
study aims to develop computational systems and data models to
assess how these ecological networks are structurally and
functionally organized, to analyze the types and degree of
compartmentalization and synchronization between oscillatory and
interconnected elements network and the influence of disturbances on
the overall pattern of rhythmicity of the system.