Abstract: Spherical shaped magnetite (Fe3O4) and Au@Fe3O4
nanoparticles were successfully synthesized from Fe electrodes
immersed in water with CTAB surfactant and HAuCl4 solution using
simple method-pulsed plasma in liquid, without the use of dopants or
special conditions for stabilization. Vibrating sample magnetometer
indicated ferromagnetic behavior of particles at room temperature with
coercivity and saturation magnetization of (Hc=105 Oe, Ms=6.83
emu/g) for Fe3O4 and (Hc=175, Ms=3.56emu/g) for Au@Fe3O4
nanoparticles. Structure and morphology of nanoparticles were
characterized by X-ray Diffraction analysis and HR-TEM
measurements. The cytotoxicity of nanoparticles was indicated using a
XTT assay to be very low (cell viability: 98-89% with Fe3O4 and
99-91% for Au@Fe3O4 NPs).
Abstract: This paper presents a method of model selection and
identification of Hammerstein systems by hybridization of the genetic
algorithm (GA) and particle swarm optimization (PSO). An unknown
nonlinear static part to be estimated is approximately represented
by an automatic choosing function (ACF) model. The weighting
parameters of the ACF and the system parameters of the linear
dynamic part are estimated by the linear least-squares method. On
the other hand, the adjusting parameters of the ACF model structure
are properly selected by the hybrid algorithm of the GA and PSO,
where the Akaike information criterion is utilized as the evaluation
value function. Simulation results are shown to demonstrate the
effectiveness of the proposed hybrid algorithm.
Abstract: Fluid flow and heat transfer of vertical full cone
embedded in porous media is studied in this paper. Nonlinear
differential equation arising from similarity solution of inverted cone
(subjected to wall temperature boundary conditions) embedded in
porous medium is solved using a hybrid neural network- particle
swarm optimization method.
To aim this purpose, a trial solution of the differential equation is
defined as sum of two parts. The first part satisfies the initial/
boundary conditions and does contain an adjustable parameter and
the second part which is constructed so as not to affect the
initial/boundary conditions and involves adjustable parameters (the
weights and biases) for a multi-layer perceptron neural network.
Particle swarm optimization (PSO) is applied to find adjustable
parameters of trial solution (in first and second part). The obtained
solution in comparison with the numerical ones represents a
remarkable accuracy.
Abstract: The results of the two-phase gas-solid jet in pneumatic
powder injection process analysis were presented in the paper. The
researches were conducted on model set-up with high speed camera
jet movement recording. Then the recorded material was analyzed to
estimate main particles movement parameters. The values obtained
from this direct measurement were compared to those calculated with
the use of the well-known formulas for the two-phase flows
(pneumatic conveying). Moreover, they were compared to
experimental results previously achieved by authors. The analysis led
to conclusions which to some extent changed the assumptions used
even by authors, regarding the two-phase jet in pneumatic powder
injection process. Additionally, the visual analysis of the recorded
clips supplied data to make a more complete evaluation of the jet
behavior in the lance outlet than before.
Abstract: The present contribution deals with the
thermophoretic deposition of nanoparticles over a rapidly rotating
permeable disk in the presence of partial slip, magnetic field, thermal
radiation, thermal-diffusion, and diffusion-thermo effects. The
governing nonlinear partial differential equations such as continuity,
momentum, energy and concentration are transformed into nonlinear
ordinary differential equations using similarity analysis, and the
solutions are obtained through the very efficient computer algebra
software MATLAB. Graphical results for non-dimensional
concentration and temperature profiles including thermophoretic
deposition velocity and Stanton number (thermophoretic deposition
flux) in tabular forms are presented for a range of values of the
parameters characterizing the flow field. It is observed that slip
mechanism, thermal-diffusion, diffusion-thermo, magnetic field and
radiation significantly control the thermophoretic particles deposition
rate. The obtained results may be useful to many industrial and
engineering applications.
Abstract: Natural gas flow contains undesirable solid particles,
liquid condensation, and/or oil droplets and requires reliable
removing equipment to perform filtration. Recent natural gas
processing applications are demanded compactness and reliability of
process equipment. Since conventional means are sophisticated in
design, poor in efficiency, and continue lacking robust, a supersonic
nozzle has been introduced as an alternative means to meet such
demands.
A 3-D Convergent-Divergent Nozzle is simulated using
commercial Code for pressure ratio (NPR) varies from 1.2 to 2. Six
different shapes of nozzle are numerically examined to illustrate the
position of shock-wave as such spot could be considered as a
benchmark of particle separation. Rectangle, triangle, circular,
elliptical, pentagon, and hexagon nozzles are simulated using Fluent
Code with all have same cross-sectional area.
The simple one-dimensional inviscid theory does not describe the
actual features of fluid flow precisely as it ignores the impact of
nozzle configuration on the flow properties. CFD Simulation results,
however, show that nozzle geometry influences the flow structures
including location of shock wave.
The CFD analysis predicts shock appearance when p01/pa>1.2 for
almost all geometry and locates at the lower area ratio (Ae/At).
Simulation results showed that shock wave in Elliptical nozzle has
the farthest distance from the throat among the others at relatively
small NPR. As NPR increases, hexagon would be the farthest. The
numerical result is compared with available experimental data and
has shown good agreement in terms of shock location and flow
structure.
Abstract: A method to determine experimentally the melting
rate, rm, and the heat transfer coefficients, αv (W/(m3K)), at
convective melting in a fixed bed of particles under adiabatic regime
is established in this paper. The method lies in the determining of the
melting rate by measuring the fixed bed height in time. Experimental
values of rm, α and α v were determined using cylindrical particles of
ice (d = 6.8 mm, h = 5.5 mm) and, as a melting agent, aqueous NaCl
solution with a temperature of 283 K at different values of the liquid
flow rate (11.63·10-6, 28.83·10-6, 38.83·10-6 m3/s).
Our experimental results were compared with those existing in
literature being noticed a good agreement for Re values higher than
50.
Abstract: In this paper, the Lennard -Jones potential is applied
to molecules of liquid argon as well as its vapor and platinum as solid
surface in order to perform a non-equilibrium molecular dynamics
simulation to study the microscopic aspects of liquid-vapor-solid
interactions. The channel is periodic in x and y directions and along z
direction it is bounded by atomic walls. It was found that density of
the liquids near the solid walls fluctuated greatly and that the
structure was more like a solid than a liquid. This indicates that the
interactions of solid and liquid molecules are very strong. The
resultant surface tension, liquid density and vapor density are found
to be well predicted when compared with the experimental data for
argon. Liquid and vapor densities were found to depend on the cutoff
radius which induces the use of P3M (particle-particle particle-mesh)
method which was implemented for evaluation of force and surface
tension.
Abstract: Using steelmaking slag as a raw material, aragonite superstructure product had been synthesized via an indirect CO2 mineral sequestration rout. It mainly involved two separate steps, in which the element of calcium is first selectively leached from steelmaking slag by a novel leaching media consisting of organic solvent Tributyl phosphate (TBP), acetic acid, and ultra-purity water, followed by enhanced carbonation in a separate step for aragonite superstructure production as well as efficiency recovery of leaching media. Based on the different leaching medium employed in the steelmaking slag leaching process, two typical products were collected from the enhanced carbonation step. The products were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), respectively. It reveals that the needle-like aragonite crystals self-organized into aragonite superstructure particles including aragonite microspheres as well as dumbbell-like spherical particles, can be obtained from the steelmaking slag with the purity over 99%.
Abstract: This research is part of a broad program aimed at
advancing the science and technology involved in the rescue and
rehabilitation of oiled wildlife. One aspect of this research involves
the use of oil-sequestering magnetic particles for the removal of
contaminants from plumage – so-called “magnetic cleansing". This
treatment offers a number of advantages over conventional
detergent-based methods including portability - which offers the
possibility of providing a “quick clean" to the animal upon first
encounter in the field. This could be particularly advantageous
when the contaminant is toxic and/or corrosive and/or where there
is a delay in transporting the victim to a treatment centre. The
method could also be useful as part of a stabilization protocol when
large numbers of affected animals are awaiting treatment. This
presentation describes the design, development and testing of a
prototype field kit for providing a “quick clean" to contaminated
wildlife in the field.
Abstract: An enhanced particle swarm optimization algorithm
(PSO) is presented in this work to solve the non-convex OPF
problem that has both discrete and continuous optimization variables.
The objective functions considered are the conventional quadratic
function and the augmented quadratic function. The latter model
presents non-differentiable and non-convex regions that challenge
most gradient-based optimization algorithms. The optimization
variables to be optimized are the generator real power outputs and
voltage magnitudes, discrete transformer tap settings, and discrete
reactive power injections due to capacitor banks. The set of equality
constraints taken into account are the power flow equations while the
inequality ones are the limits of the real and reactive power of the
generators, voltage magnitude at each bus, transformer tap settings,
and capacitor banks reactive power injections. The proposed
algorithm combines PSO with Newton-Raphson algorithm to
minimize the fuel cost function. The IEEE 30-bus system with six
generating units is used to test the proposed algorithm. Several cases
were investigated to test and validate the consistency of detecting
optimal or near optimal solution for each objective. Results are
compared to solutions obtained using sequential quadratic
programming and Genetic Algorithms.
Abstract: The application of a Static Synchronous Series Compensator (SSSC) controller to improve the transient stability performance of a power system is thoroughly investigated in this paper. The design problem of SSSC controller is formulated as an optimization problem and Particle Swarm Optimization (PSO) Technique is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor angle of the generator is involved; transient stability performance of the system is improved. The proposed controller is tested on a weakly connected power system subjected to different severe disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and its ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances.
Abstract: A new multi inner stage (MIS) cyclone was designed to
remove the acidic gas and fine particles produced from electronic
industry. To characterize gas flow in MIS cyclone, pressure and
velocity distribution were calculated by means of CFD program. Also,
the flow locus of fine particles and particle removal efficiency were
analyzed by Lagrangian method. When outlet pressure condition was
–100mmAq, the efficiency was the best in this study.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.
Abstract: Estimation of voltage stability based on optimal
filtering method is presented. PV curve is used as a tool for voltage stability analysis. Dynamic voltage stability estimation is done by
using particle filter method. Optimum value (nose point) of PV curve can be estimated by estimating parameter of PV curve equation
optimal value represents critical voltage and
condition at specified point of measurement. Voltage stability is then estimated by analyzing loading margin condition c stimating equation. This
maximum loading
ecified dynamically.
Abstract: This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.
Abstract: The utilization of renewable energy sources in electric
power systems is increasing quickly because of public apprehensions
for unpleasant environmental impacts and increase in the energy
costs involved with the use of conventional energy sources. Despite
the application of these energy sources can considerably diminish the
system fuel costs, they can also have significant influence on the
system reliability. Therefore an appropriate combination of the
system reliability indices level and capital investment costs of system
is vital. This paper presents a hybrid wind/photovoltaic plant, with
the aim of supplying IEEE reliability test system load pattern while
the plant capital investment costs is minimized by applying a hybrid
particle swarm optimization (PSO) / harmony search (HS) approach,
and the system fulfills the appropriate level of reliability.
Abstract: In this paper spatial variability of some chemical and
physical soil properties were investigated in mountain rangelands of
Nesho, Mazandaran province, Iran. 110 soil samples from 0-30 cm
depth were taken with systematic method on grid 30×30 m2 in
regions with different vegetation cover and transported to laboratory.
Then soil chemical and physical parameters including Acidity (pH),
Electrical conductivity, Caco3, Bulk density, Particle density, total
phosphorus, total Nitrogen, available potassium, Organic matter,
Saturation moisture, Soil texture (percentage of sand, silt and clay),
Sodium, Calcium, magnesium were measured in laboratory. Data
normalization was performed then was done statistical analysis for
description of soil properties and geostatistical analysis for indication
spatial correlation between these properties and were perpetrated
maps of spatial distribution of soil properties using Kriging method.
Results indicated that in the study area Saturation moisture and
percentage of Sand had highest and lowest spatial correlation
respectively.
Abstract: The systematic manipulations of shapes and sizes of
inorganic compounds greatly benefit the various application fields
including optics, magnetic, electronics, catalysis and medicine.
However shape control has been much more difficult to achieve.
Hence exploration of novel method for the preparation of differently
shaped nanoparticles is challenging research area. II-VI group of
semiconductor cadmium sulphide (CdS) nanostructure with different
morphologies (such as, acicular like, mesoporous, spherical shapes)
and of crystallite sizes vary from 11 to 16 nm were successfully
synthesized by chemical aqueous precipitation of Cd2+ ions with
homogeneously released S2- ions from decomposition of cadmium
sulphate (CdSO4) and thioacetamide (CH3CSNH2) by annealing at
different radiations (microwave, ultrasonic and sunlight) with matter
and systematic research has been done for various factors affecting
the controlled growth rate of CdS nanoparticles. The obtained
nanomaterials have been characterized by X-ray Diffraction (XRD),
Fourier Transform Infrared Spectroscopy (FTIR),
Thermogravometric (DSC-TGA) analysis and Scanning Electron
Microscopy (SEM). The result indicates that on increasing the
reaction time particle size increases but on increasing the molar ratios
grain size decreases.
Abstract: In this paper the combination of thermal oxidation and
electrochemical anodizing processes is used to produce titanium
oxide layers. The response of titanium alloy Ti6Al4V to oxidation
processes at various temperatures and electrochemical anodizing in
various voltages are investigated. Scanning electron microscopy
(SEM); X-Ray Diffraction (XRD) and porosity determination have
been used to characterize the oxide layer thickness, surface
morphology, oxide layer-substrate adhesion and porosity. In the first
experiment, samples modified by thermal oxidation process then
followed by electrochemical anodizing. Second experiment consists
of surfaces modified by electrochemical anodizing process and then
followed by thermal oxidation. The first method shows better
properties than other one. In second experiment, Surfaces modified
were achieved by thicker and more adherent thick oxide layers on
titanium surface. The existence of an electrochemical anodized oxide
layer did not improve the adhesion of thermal oxide layer. The high
temperature, thermal formation of an oxide layer leads to a coarse
oxide grain morphology and a complete oxidative particle. In
addition, in high temperature oxidation porosity content is increased.
The oxide layer of thermal oxidation and electrochemical anodizing
processes; on Ti–6Al–4V substrate was covered with different
colored oxide layers.