Abstract: This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines.
Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the
dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the
effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN.
Abstract: Energy generated by the force of water in hydropower
can provide a more sustainable, non-polluting alternative to fossil
fuels, along with other renewable sources of energy, such as wind,
solar and tidal power, bio energy and geothermal energy. Small scale
hydroelectricity in Iran is well suited for “off-grid" rural electricity
applications, while other renewable energy sources, such as wind,
solar and biomass, can be beneficially used as fuel for pumping
groundwater for drinking and small scale irrigation in remote rural
areas or small villages. Small Hydro Power plants in Iran have very
low operating and maintenance costs because they consume no fossil
or nuclear fuel and do not involve high temperature processes. The
equipment is relatively simple to operate and maintain. Hydropower
equipment can adjust rapidly to load changes. The extended
equipment life provides significant economic advantages. Some
hydroelectric plants installed 100 years ago still operate reliably. The
Polkolo river is located on Karun basin at southwest of Iran. Situation
and conditions of Polkolo river are evaluated for construction of
small hydropower in this article. The topographical conditions and
the existence of permanent water from springs provide the suitability
to install hydroelectric power plants on the river Polkolo. The
cascade plant consists of 9 power plants connected with each other
and is having the total head as 1100m and discharge about 2.5cubic
meter per second. The annual production of energy is 105.5 million
kwh.
Abstract: Various methods of geofield parameters restoration (by algebraic polynoms; filters; rational fractions; interpolation splines; geostatistical methods – kriging; search methods of nearest points – inverse distance, minimum curvature, local – polynomial interpolation; neural networks) have been analyzed and some possible mistakes arising during geofield surface modeling have been presented.
Abstract: An important step in three-dimensional reconstruction
and computer vision is camera calibration, whose objective is to
estimate the intrinsic and extrinsic parameters of each camera. In this
paper, two linear methods based on the different planes are given. In
both methods, the general plane is used to replace the calibration
object with very good precision. In the first method, after controlling
the camera to undergo five times- translation movements and taking
pictures of the orthogonal planes, a set of linear constraints of the
camera intrinsic parameters is then derived by means of homography
matrix. The second method is to get all camera parameters by taking
only one picture of a given radius circle. experiments on simulated
data and real images,indicate that our method is reasonable and is a
good supplement to camera calibration.
Abstract: In this paper, the 1-D conduction-radiation problem is solved by the lattice Boltzmann method. The effects of various parameters such as the scattering albedo, the conduction–radiation parameter and the wall emissivity are studied. In order to check on the accuracy of the numerical technique employed for the solution of the considered problem, the present numerical code was validated with the published study. The found results are in good agreement with those published
Abstract: Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.
Abstract: This paper studies the application of a variety of
sawdust materials in the production of lightweight insulating bricks.
First, the mineralogical and chemical composition of clays was determined. Next, ceramic bricks were fabricated with different
quantities of materials (3–6 and 9 wt. % for sawdust, 65 wt. % for grey clay, 24–27 and 30 wt. % for yellow clay and 2 wt% of tuff).
These bricks were fired at 800 and 950 °C. The effect of adding this sawdust on the technological behaviour of the brick was assessed by
drying and firing shrinkage, water absorption, porosity, bulk density
and compressive strength. The results have shown that the optimum
sintering temperature is 950 °C. Below this temperature, at 950 °C,
increased open porosity was observed, which decreased the compressive strength of the bricks. Based on the results obtained, the
optimum amounts of waste were 9 wt. % sawdust of eucalyptus, 24 wt. % shaping moisture and 1.6 particle size diameter. These percentages produced bricks whose mechanical properties were
suitable for use as secondary raw materials in ceramic brick
production.
Abstract: Turbulent forced convection flow in a 2-dimensional channel over periodic grooves is numerically investigated. Finite volume method is used to study the effect of turbulence model. The range of Reynolds number varied from 10000 to 30000 for the ribheight to channel-height ratio (B/H) of 2. The downstream wall is heated by a uniform heat flux while the upstream wall is insulated. The investigation is analyzed with different types of nanoparticles such as SiO2, Al2O3, and ZnO, with water as a base fluid are used. The volume fraction is varied from 1% to 4% and the nanoparticle diameter is utilized between 20nm to 50nm. The results revealed 114% heat transfer enhancement compared to the water in a grooved channel by using SiO2 nanoparticle with volume fraction and nanoparticle diameter of 4% and 20nm respectively.
Abstract: Deep cold rolling (DCR) is a cold working process, which easily produces a smooth and work-hardened surface by plastic deformation of surface irregularities. In the present study, the influence of main deep cold rolling process parameters on the surface roughness and the hardness of AISI 4140 steel were studied by using fractional factorial design of experiments. The assessment of the surface integrity aspects on work material was done, in terms of identifying the predominant factor amongst the selected parameters, their order of significance and setting the levels of the factors for minimizing surface roughness and/or maximizing surface hardness. It was found that the ball diameter, rolling force, initial surface roughness and number of tool passes are the most pronounced parameters, which have great effects on the work piece-s surface during the deep cold rolling process. A simple, inexpensive and newly developed DCR tool, with interchangeable collet for using different ball diameters, was used throughout the experimental work presented in this paper.
Abstract: Numerical calculations of flow around a square cylinder are presented using the multi-relaxation-time lattice Boltzmann method at Reynolds number 150. The effects of upstream locations, downstream locations and blockage are investigated systematically. A detail analysis are given in terms of time-trace analysis of drag and lift coefficients, power spectra analysis of lift coefficient, vorticity contours visualizations and phase diagrams. A number of physical quantities mean drag coefficient, drag coefficient, Strouhal number and root-mean-square values of drag and lift coefficients are calculated and compared with the well resolved experimental data and numerical results available in open literature. The results had shown that the upstream, downstream and height of the computational domain are at least 7.5, 37.5 and 12 diameters of the cylinder, respectively.
Abstract: The aim of this work is to analyze a viscous flow in
the axisymmetric nozzle taken into account the mesh size both in the
free stream and into the boundary layer. The resolution of the Navier-
Stokes equations is realized by using the finite volume method to
determine the supersonic flow parameters at the exit of convergingdiverging
nozzle. The numerical technique uses the Flux Vector
Splitting method of Van Leer. Here, adequate time stepping
parameter, along with CFL coefficient and mesh size level is selected
to ensure numerical convergence. The effect of the boundary layer
thickness is significant at the exit of the nozzle. The best solution is
obtained with using a very fine grid, especially near the wall, where
we have a strong variation of velocity, temperature and shear stress.
This study enabled us to confirm that the determination of boundary
layer thickness can be obtained only if the size of the mesh is lower
than a certain value limits given by our calculations.
Abstract: The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.
Abstract: An inflation–extension test with human vena cava
inferior was performed with the aim to fit a material model. The vein
was modeled as a thick–walled tube loaded by internal pressure and
axial force. The material was assumed to be an incompressible
hyperelastic fiber reinforced continuum. Fibers are supposed to be
arranged in two families of anti–symmetric helices. Considered
anisotropy corresponds to local orthotropy. Used strain energy
density function was based on a concept of limiting strain
extensibility. The pressurization was comprised by four pre–cycles
under physiological venous loading (0 – 4kPa) and four cycles under
nonphysiological loading (0 – 21kPa). Each overloading cycle was
performed with different value of axial weight. Overloading data
were used in regression analysis to fit material model. Considered
model did not fit experimental data so good. Especially predictions
of axial force failed. It was hypothesized that due to
nonphysiological values of loading pressure and different values of
axial weight the material was not preconditioned enough and some
damage occurred inside the wall. A limiting fiber extensibility
parameter Jm was assumed to be in relation to supposed damage.
Each of overloading cycles was fitted separately with different values
of Jm. Other parameters were held the same. This approach turned out
to be successful. Variable value of Jm can describe changes in the
axial force – axial stretch response and satisfy pressure – radius
dependence simultaneously.
Abstract: The experimental and theoretical results of a ZVS
(Zero Voltage Switching) isolated flyback DC-DC converter using
multilayered coreless PCB step down 2:1 transformer are presented.
The performance characteristics of the transformer are shown which
are useful for the parameters extraction. The measured energy
efficiency of the transformer is found to be more than 94% with the
sinusoidal input voltage excitation. The designed flyback converter
has been tested successfully upto the output power level of 10W,
with a switching frequency in the range of 2.7MHz-4.3MHz. The
input voltage of the converter is varied from 25V-40V DC.
Frequency modulation technique is employed by maintaining
constant off time to regulate the output voltage of the converter. The
energy efficiency of the isolated flyback converter circuit under ZVS
condition in the MHz frequency region is found to be approximately
in the range of 72-84%. This paper gives the comparative results in
terms of the energy efficiency of the hard switched and soft switched
flyback converter in the MHz frequency region.
Abstract: In the micro and nano-technology industry, the
«clean-rooms» dedicated to manufacturing chip, are equipped with
the most sophisticated equipment-tools. There use a large number of
resources in according to strict specifications for an optimum
working and result. The distribution of «utilities» to the production is
assured by teams who use a supervision tool.
The studies show the interest to control the various parameters of
production or/and distribution, in real time, through a reliable and
effective supervision tool. This document looks at a large part of the
functions that the supervisor must assure, with complementary
functionalities to help the diagnosis and simulation that prove very
useful in our case where the supervised installations are complexed
and in constant evolution.
Abstract: A comparative evaluation of acute toxicity of
synthesized nano silvers using two different procedures (biological
and chemical reduction methods) and silver ions on bacteria
Vibrio fischeri was investigated. The bacterial light inhibition test as
a toxicological endpoint was used by applying of a homemade
luminometer. To compare the toxicity effects as a quantitative
parameter, a nominal effective concentrations (EC) of chemicals and
a susceptibility constant (Z-value) of bacteria, after 5 min and 30 min
exposure times, were calculated. After 5 and 30 min contact times,
the EC50 values of two silver nanoparticles and the EC20 values were
about similar. It demonstrates that toxicity of silvers was independent
of their procedure. The EC values of nanoparticles were larger than
those of the silver ions. The susceptibilities(Z- Values) of V.fischeri
(L/mg) to the silver ions were greater than those of the nano silvers.
According to the EC and Z values, the toxicity of silvers decreased in
the following order: Silver ions >> silver nanoparticles from
chemical reduction method ~ silver nanoparticles from biological
method.
Abstract: In this paper, a novel method using Bees Algorithm is proposed to determine the optimal allocation of FACTS devices for maximizing the Available Transfer Capability (ATC) of power transactions between source and sink areas in the deregulated power system. The algorithm simultaneously searches the FACTS location, FACTS parameters and FACTS types. Two types of FACTS are simulated in this study namely Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC). A Repeated Power Flow with FACTS devices including ATC is used to evaluate the feasible ATC value within real and reactive power generation limits, line thermal limits, voltage limits and FACTS operation limits. An IEEE30 bus system is used to demonstrate the effectiveness of the algorithm as an optimization tool to enhance ATC. A Genetic Algorithm technique is used for validation purposes. The results clearly indicate that the introduction of FACTS devices in a right combination of location and parameters could enhance ATC and Bees Algorithm can be efficiently used for this kind of nonlinear integer optimization.
Abstract: Routing in MANET is extremely challenging because
of MANETs dynamic features, its limited bandwidth, frequent
topology changes caused by node mobility and power energy
consumption. In order to efficiently transmit data to destinations, the
applicable routing algorithms must be implemented in mobile ad-hoc
networks. Thus we can increase the efficiency of the routing by
satisfying the Quality of Service (QoS) parameters by developing
routing algorithms for MANETs. The algorithms that are inspired by
the principles of natural biological evolution and distributed
collective behavior of social colonies have shown excellence in
dealing with complex optimization problems and are becoming more
popular. This paper presents a survey on few meta-heuristic
algorithms and naturally-inspired algorithms.
Abstract: Manufacturing components of fiber-reinforced
thermoplastics requires three steps: heating the matrix, forming and
consolidation of the composite and terminal cooling the matrix. For
the heating process a pre-determined temperature distribution through
the layers and the thickness of the pre-consolidated sheets is
recommended to enable forming mechanism. Thus, a design for the
heating process for forming composites with thermoplastic matrices
is necessary. To obtain a constant temperature through thickness and
width of the sheet, the heating process was analyzed by the help of
the finite element method. The simulation models were validated by
experiments with resistance thermometers as well as with an infrared
camera. Based on the finite element simulation, heating methods for
infrared radiators have been developed. Using the numeric
simulation many iteration loops are required to determine the process
parameters. Hence, the initiation of a model for calculating relevant
process parameters started applying regression functions.
Abstract: Methods of clustering which were developed in the
data mining theory can be successfully applied to the investigation of
different kinds of dependencies between the conditions of
environment and human activities. It is known, that environmental
parameters such as temperature, relative humidity, atmospheric
pressure and illumination have significant effects on the human
mental performance. To investigate these parameters effect, data
mining technique of clustering using entropy and Information Gain
Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where
H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of
clusters. It is shown that the information gain ratio (IGR) grows
monotonically and simultaneously with degree of connectivity
between two variables. This approach has some preferences if
compared, for example, with correlation analysis due to relatively
smaller sensitivity to shape of functional dependencies. Variant of an
algorithm to implement the proposed method with some analysis of
above problem of environmental effects is also presented. It was
shown that proposed method converges with finite number of steps.