Abstract: This work was one of the tasks of the
Manufacturing2Client project, whose objective was to develop a
frontal deflector to be commercialized in the automotive industry,
using new project and manufacturing methods. In this task, in
particular, it was proposed to develop the ability to predict
computationally the aerodynamic influence of flow in vehicles, in an
effort to reduce fuel consumption in vehicles from class 3 to 8. With
this aim, two deflector models were developed and their aerodynamic
performance analyzed. The aerodynamic study was done using the
Computational Fluid Dynamics (CFD) software Ansys CFX and
allowed the calculation of the drag coefficient caused by the vehicle
motion for the different configurations considered. Moreover, the
reduction of diesel consumption and carbon dioxide (CO2) emissions
associated with the optimized deflector geometry could be assessed.
Abstract: Axial flow fans, while incapable of developing high
pressures, they are well suitable for handling large volumes of air at
relatively low pressures. In general, they are low in cost and possess
good efficiency, and can have blades of airfoil shape. Axial flow fans
show good efficiencies, and can operate at high static pressures if
such operation is necessary. Our objective is to model and analyze
the flow through AXIAL FANS using CFD Software and draw
inference from the obtained results, so as to get maximum efficiency.
The performance of an axial fan was simulated using CFD and the
effect of variation of different parameters such as the blade number,
noise level, velocity, temperature and pressure distribution on the
blade surface was studied. This paper aims to present a final 3D CAD
model of axial flow fan. Adapting this model to the available
components in the market, the first optimization was done. After this
step, CFX flow solver is used to do the necessary numerical analyses
on the aerodynamic performance of this model. This analysis results
in a final optimization of the proposed 3D model which is presented
in this article.
Abstract: Laplace transformations have wide applications in
engineering and sciences. All previous studies of modified Laplace
transformations depend on differential equation with initial
conditions. The purpose of our paper is to solve the linear differential
equations (not initial value problem) and then find the general
solution (not particular) via the Laplace transformations without
needed any initial condition. The study involves both types of
differential equations, ordinary and partial.
Abstract: Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
Abstract: Machining parameters are very important in
determining the surface quality of any material. In the past decade,
some new engineering materials were developed for the
manufacturing industry which created a need to conduct an
investigation on the impact of the said parameters on their surface
roughness. Polyurethane (PU) block is widely used in the automotive
industry to manufacture parts such as checking fixtures that are used
to verify the dimensional accuracy of automotive parts. In this paper,
the design of experiment (DOE) was used to investigate on the effect
of the milling parameters on the PU block. Furthermore, an analysis
of the machined surface chemical composition was done using
scanning electron microscope (SEM). It was found that the surface
roughness of the PU block is severely affected when PU undergoes a
flood machining process instead of a dry condition. In addition the
stepover and the silicon content were found to be the most significant
parameters that influence the surface quality of the PU block.
Abstract: Rhodamine B (RB) is a toxic dye used extensively in
textile industry, which must be remediated before its drainage to
environment. In the present study, supported gold nanoparticles on
commercially available titania and zincite were successfully prepared
and then their activity on the photodegradation of RB under UV A
light irradiation were evaluated. The synthesized photocatalysts were
characterized by ICP, BET, XRD, and TEM. Kinetic results showed
that Au/TiO2 was an inferior photocatalyst to Au/ZnO. This
observation could be attributed to the strong reflection of UV
irradiation by gold nanoparticles over TiO2 support.
Abstract: Safety is one of the most important considerations
when buying a new car. While active safety aims at avoiding
accidents, passive safety systems such as airbags and seat belts
protect the occupant in case of an accident. In addition to legal
regulations, organizations like Euro NCAP provide consumers with
an independent assessment of the safety performance of cars and
drive the development of safety systems in automobile industry.
Those ratings are mainly based on injury assessment reference values
derived from physical parameters measured in dummies during a car
crash test.
The components and sub-systems of a safety system are designed
to achieve the required restraint performance. Sled tests and other
types of tests are then carried out by car makers and their suppliers
to confirm the protection level of the safety system. A Knowledge
Discovery in Databases (KDD) process is proposed in order to
minimize the number of tests. The KDD process is based on the
data emerging from sled tests according to Euro NCAP specifications.
About 30 parameters of the passive safety systems from different data
sources (crash data, dummy protocol) are first analysed together with
experts opinions. A procedure is proposed to manage missing data
and validated on real data sets. Finally, a procedure is developed to
estimate a set of rough initial parameters of the passive system before
testing aiming at reducing the number of tests.
Abstract: Metal matrix composites (MMCs) attract considerable
attention as a result from its ability in providing a high strength, high
modulus, high toughness, high impact properties, improving wear
resistance and providing good corrosion resistance compared to
unreinforced alloy. Aluminium Silicon (Al/Si) alloy MMC has been
widely used in various industrial sectors such as in transportation,
domestic equipment, aerospace, military, construction, etc.
Aluminium silicon alloy is an MMC that had been reinforced with
aluminium nitrate (AlN) particle and become a new generation
material use in automotive and aerospace sector. The AlN is one of
the advance material that have a bright prospect in future since it has
features such as lightweight, high strength, high hardness and
stiffness quality. However, the high degree of ceramic particle
reinforcement and the irregular nature of the particles along the
matrix material that contribute to its low density is the main problem
which leads to difficulties in machining process. This paper examined
the tool wear when milling AlSi/AlN Metal Matrix Composite using
a TiB2 (Titanium diboride) coated carbide cutting tool. The volume
of the AlN reinforced particle was 10% and milling process was
carried out under dry cutting condition. The TiB2 coated carbide
insert parameters used were at the cutting speed of (230, 300 and
370m/min, feed rate of 0.8, Depth of Cut (DoC) at 0.4m). The
Sometech SV-35 video microscope system used to quantify of the
tool wear. The result shown that tool life span increasing with the
cutting speeds at (370m/min, feed rate of 0.8mm/tooth and DoC at
0.4mm) which constituted an optimum condition for longer tool life
lasted until 123.2 mins. Meanwhile, at medium cutting speed which
at 300m/m, feed rate of 0.8mm/tooth and depth of cut at 0.4mm we
found that tool life span lasted until 119.86 mins while at low cutting
speed it lasted in 119.66 mins. High cutting speed will give the best
parameter in cutting AlSi/AlN MMCs material. The result will help
manufacturers in machining process of AlSi/AlN MMCs materials.
Abstract: Red blood cells (RBC) are the most common types of
blood cells and are the most intensively studied in cell biology. The
lack of RBCs is a condition in which the amount of hemoglobin level
is lower than normal and is referred to as “anemia”. Abnormalities in
RBCs will affect the exchange of oxygen. This paper presents a
comparative study for various techniques for classifying the RBCs as
normal or abnormal (anemic) using WEKA. WEKA is an open
source consists of different machine learning algorithms for data
mining applications. The algorithms tested are Radial Basis Function
neural network, Support vector machine, and K-Nearest Neighbors
algorithm. Two sets of combined features were utilized for
classification of blood cells images. The first set, exclusively consist
of geometrical features, was used to identify whether the tested blood
cell has a spherical shape or non-spherical cells. While the second
set, consist mainly of textural features was used to recognize the
types of the spherical cells. We have provided an evaluation based on
applying these classification methods to our RBCs image dataset
which were obtained from Serdang Hospital - Malaysia, and
measuring the accuracy of test results. The best achieved
classification rates are 97%, 98%, and 79% for Support vector
machines, Radial Basis Function neural network, and K-Nearest
Neighbors algorithm respectively.
Abstract: Solar air heater is a type of heat exchanger which
transforms solar radiation into heat energy. The thermal performance
of conventional solar air heater has been found to be poor because of
the low convective heat transfer coefficient from the absorber plate to
the air. It is attributed to the formation of a very thin boundary layer
at the absorber plate surface commonly known as viscous sub-layer.
Thermal efficiency of solar air heater can be improved by providing
the artificial roughness on absorber plate is the most efficient
technique. In this paper an attempt is made to provide artificial
roughness by incorporating inclined multiple V-ribs in the underside
of the absorber plate. 60˚V – ribs are arranged inclined to the
direction of air flow. Performance of collector estimated theoretically
and experimentally. Results of the investigation reveal that thermal
efficiency of collector with multiple V-ribs increased by 14%.
Abstract: We present an analytical model for the calculation of
the sensitivity, the spectral current noise and the detective parameter
for an optically illuminated In0.53Ga0.47As n+nn+ diode. The
photocurrent due to the excess carrier is obtained by solving the
continuity equation. Moreover, the current noise level is evaluated at
room temperature and under a constant voltage applied between the
diode terminals. The analytical calculation of the current noise in the
n+nn+ structure is developed by considering the free carries
fluctuations. The responsivity and the detection parameter are
discussed as functions of the doping concentrations and the emitter
layer thickness in one-dimensional homogeneous n+nn+ structure.
Abstract: In this work, we propose and analyze a model of
Phytoplankton-Zooplankton interaction with harvesting considering
that some species are exploited commercially for food. Criteria for
local stability, instability and global stability are derived and some
threshold harvesting levels are explored to maintain the population
at an appropriate equilibrium level even if the species are exploited
continuously.Further,biological and bionomic equilibria of the system
are obtained and an optimal harvesting policy is also analysed using
the Pantryagin’s Maximum Principle.Finally analytical findings are
also supported by some numerical simulations.
Abstract: Several of the practical industrial control processes are
multivariable processes. Due to the relation amid the variables
(interaction), delay in the loops, it is very intricate to design a
controller directly for these processes. So first, the interaction of the
variables is analyzed using Relative Normalized Gain Array
(RNGA), which considers the time constant, static gain and delay
time of the processes. Based on the effect of RNGA, relative gain
array (RGA) and NI, the pair (control configuration) of variables to
be controlled by decentralized control is selected. The equivalent
transfer function (ETF) of the process model is estimated as first
order process with delay using the corresponding elements in the
Relative gain array and Relative average residence time array
(RARTA) of the processes. Secondly, a decentralized Proportional-
Integral (PI) controller is designed for each ETF simply using
frequency response specifications. Finally, the performance and
robustness of the algorithm is comparing with existing related
approaches to validate the effectiveness of the projected algorithm.
Abstract: Image spam is a kind of email spam where the spam
text is embedded with an image. It is a new spamming technique
being used by spammers to send their messages to bulk of internet
users. Spam email has become a big problem in the lives of internet
users, causing time consumption and economic losses. The main
objective of this paper is to detect the image spam by using histogram
properties of an image. Though there are many techniques to
automatically detect and avoid this problem, spammers employing
new tricks to bypass those techniques, as a result those techniques are
inefficient to detect the spam mails. In this paper we have proposed a
new method to detect the image spam. Here the image features are
extracted by using RGB histogram, HSV histogram and combination
of both RGB and HSV histogram. Based on the optimized image
feature set classification is done by using k- Nearest Neighbor(k-NN)
algorithm. Experimental result shows that our method has achieved
better accuracy. From the result it is known that combination of RGB
and HSV histogram with k-NN algorithm gives the best accuracy in
spam detection.
Abstract: The demand of high quality services has fueled
dimensional research and development in wireless communications
and networking. As a result, different wireless technologies like
Wireless LAN, CDMA, GSM, UMTS, MANET, Bluetooth and
satellite networks etc. have emerged in the last two decades. Future
networks capable of carrying multimedia traffic need IP convergence,
portability, seamless roaming and scalability among the existing
networking technologies without changing the core part of the
existing communications networks. To fulfill these goals, the present
networking systems are required to work in cooperation to ensure
technological independence, seamless roaming, high security and
authentication, guaranteed Quality of Services (QoS). In this paper, a
conceptual framework for a cooperative network (CN) is proposed
for integration of heterogeneous existing networks to meet out the
requirements of the next generation wireless networks.
Abstract: Heavy rare earth (HRE) oxalate concentrates were
prepared from the Egyptian crude monazite sand (graded about 47%).
The concentrates were specified quantitatively for their constituents
of individual rare earth elements using ion chromatograph (IC) and
qualitatively by scanning electron microscope (SEM) for the other
major constituents. The 1st concentrate was composed of 10.5%
HREE where 7.25% of them represented yttrium. The 2nd concentrate
contained about 41.7% LREE, 17.5% HREE and 13.6% Th. The
LREE involved 18.3% Ce, 10.5% La and 8% Nd while the HREE
were 8.7% Y, 3.5% Gd and 2.9% Dy. The 3rd concentrate was
containing about 8.0% LREE (3.7% Ce, 2.0% La and 1.5% Nd),
10.2% HREE (6.4% yttrium and 2.0% Dy) and 2.1% uranium. The
final concentrate comprised 0.84% uranium beside iron, chromium
and traces of REE.
Abstract: The effect of a 3-dimensional (3D) blade on the turbine
characteristics of Wells turbine for wave energy conversion has been
investigated experimentally by model testing under steady flow
conditions in this study, in order to improve the peak efficiency and
stall characteristics. The aim of use of 3D blade is to prevent flow
separation on the suction surface near the tip. The chord length is
constant with radius and the blade profile changes gradually from the
mean radius to tip. The proposed blade profiles in the study are
NACA0015 from the hub to mean radius and NACA0025 at the tip.
The performances of Wells turbine with 3D blades has been compared
with those of the original Wells turbine, i.e., the turbine with
2-dimensional (2D) blades. As a result, it was concluded that although
the peak efficiency of Wells turbine can be improved by the use of the
proposed 3D blade, its blade does not overcome the weakness of
stalling.
Abstract: The paper presents a plastic analysis procedure based
on the energy balance concept for performance based seismic retrofit
of multi-story multi-bay masonry infilled reinforced concrete (R/C)
frames with a ‘soft’ ground story using passive energy dissipation
(PED) devices with the objective of achieving a target performance
level of the retrofitted R/C frame for a given seismic hazard level at
the building site. The proposed energy based plastic analysis
procedure was employed for developing performance based design
(PBD) formulations for PED devices for a simulated application in
seismic retrofit of existing frame structures designed in compliance
with the prevalent standard codes of practice. The PBD formulations
developed for PED devices were implemented for simulated seismic
retrofit of a representative code-compliant masonry infilled R/C
frame with a ‘soft’ ground story using friction dampers as the PED
device. Non-linear dynamic analyses of the retrofitted masonry
infilled R/C frames is performed to investigate the efficacy and
accuracy of the proposed energy based plastic analysis procedure in
achieving the target performance level under design level
earthquakes. Results of non-linear dynamic analyses demonstrate that
the maximum inter-story drifts in the masonry infilled R/C frames
with a ‘soft’ ground story that is retrofitted with the friction dampers
designed using the proposed PBD formulations are controlled within
the target drifts under near-field as well far-field earthquakes.
Abstract: In this paper a comprehensive review on various
factory layouts has been carried out for designing a lucrative process
layout for medium scale industries. Industry data base reveals that the
end product rejection rate is on the order of 10% amounting large
profit loss. In order to avoid these rejection rates and to increase the
quality product production an intermediate non-destructive testing
facility (INDTF) has been recommended for increasing the overall
profit. We observed through detailed case studies that while
introducing INDTF to medium scale industries the expensive
production process can be avoided to the defective products well
before its final shape. Additionally, the defective products identified
during the intermediate stage can be effectively utilized for other
applications or recycling; thereby the overall wastage of the raw
materials can be reduced and profit can be increased. We concluded
that the prudent design of a factory layout through critical path
method facilitating with INDTF will warrant profitable outcome.
Abstract: In this paper, Fuzzy C-Means clustering with
Expectation Maximization-Gaussian Mixture Model based hybrid
modeling algorithm is proposed for Continuous Tamil Speech
Recognition. The speech sentences from various speakers are used
for training and testing phase and objective measures are between the
proposed and existing Continuous Speech Recognition algorithms.
From the simulated results, it is observed that the proposed algorithm
improves the recognition accuracy and F-measure up to 3% as
compared to that of the existing algorithms for the speech signal from
various speakers. In addition, it reduces the Word Error Rate, Error
Rate and Error up to 4% as compared to that of the existing
algorithms. In all aspects, the proposed hybrid modeling for Tamil
speech recognition provides the significant improvements for speechto-
text conversion in various applications.