Abstract: An Australian manufacturer has fabricated an
innovative GFRP sandwich panel made from E-glass fiber skin and a
modified phenolic core for structural applications. Debonding, which
refers to separation of skin from the core material in composite
sandwiches, is one of the most common types of damage in
composites. The presence of debonding is of great concern because it
not only severely affects the stiffness but also modifies the dynamic
behaviour of the structure. Generally it is seen that the majority of
research carried out has been concerned about the delamination of
laminated structures whereas skin-core debonding has received
relatively minor attention. Furthermore it is observed that research
done on composite slabs having multiple skin-core debonding is very
limited. To address this gap, a comprehensive research investigating
dynamic behaviour of composite panels with single and multiple
debonding is presented. The study uses finite-element modelling and
analyses for investigating the influence of debonding on free
vibration behaviour of single and multilayer composite sandwich
panels. A broad parametric investigation has been carried out by
varying debonding locations, debonding sizes and support conditions
of the panels in view of both single and multiple debonding.
Numerical models were developed with Strand7 finite element
package by innovatively selecting the suitable elements to diligently
represent their actual behavior. Three-dimensional finite element
models were employed to simulate the physically real situation as
close as possible, with the use of an experimentally and numerically
validated finite element model. Comparative results and conclusions
based on the analyses are presented. For similar extents and locations
of debonding, the effect of debonding on natural frequencies appears
greatly dependent on the end conditions of the panel, giving greater
decrease in natural frequency when the panels are more restrained.
Some modes are more sensitive to debonding and this sensitivity
seems to be related to their vibration mode shapes. The fundamental
mode seems generally the least sensitive mode to debonding with
respect to the variation in free vibration characteristics. The results
indicate the effectiveness of the developed three dimensional finite
element models in assessing debonding damage in composite
sandwich panels.
Abstract: The main objective of incorporating natural fibers such as Henequen microfibers (NF) into the High Density Polyethylene (HDPE) polymer matrix is to reduce the cost and to enhance the mechanical as well as other properties. The Henequen microfibers were chopped manually to 5-7mm in length and added into the polymer matrix at the optimized concentration of 8 wt %. In order to facilitate the link between Henequen microfibers (NF) and HDPE matrix, coupling agent such as Glycidoxy (Epoxy) Functional Methoxy Silane (GPTS) at various concentrations from 0.1%, 0.3%, 0.5%, 0.7%, 0.9% and 1% by weight to the total fibers were added. The tensile strength of the composite increased marginally while % elongation at break of the composites decreased with increase in silane loading by wt %. Tensile modulus and stiffness observed increased at 0.9 wt % GPTS loading. Flexural as well as impact strength of the composite decreased with increase in GPTS loading by weight %. Dielectric strength of the composite also found increased marginally up to 0.5wt % silane loading and thereafter remained constant.
Abstract: Reflux condensation occurs in vertical channels and tubes when there is an upward core flow of vapour (or gas-vapour mixture) and a downward flow of the liquid film. The understanding of this condensation configuration is crucial in the design of reflux condensers, distillation columns, and in loss-of-coolant safety analyses in nuclear power plant steam generators. The unique feature of this flow is the upward flow of the vapour-gas mixture (or pure vapour) that retards the liquid flow via shear at the liquid-mixture interface. The present model solves the full, elliptic governing equations in both the film and the gas-vapour core flow. The computational mesh is non-orthogonal and adapts dynamically the phase interface, thus produces a sharp and accurate interface. Shear forces and heat and mass transfer at the interface are accounted for fundamentally. This modeling is a big step ahead of current capabilities by removing the limitations of previous reflux condensation models which inherently cannot account for the detailed local balances of shear, mass, and heat transfer at the interface. Discretisation has been done based on finite volume method and co-located variable storage scheme. An in-house computer code was developed to implement the numerical solution scheme. Detailed results are presented for laminar reflux condensation from steam-air mixtures flowing in vertical parallel plate channels. The results include velocity and gas mass fraction profiles, as well as axial variations of film thickness.
Abstract: This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design.
Abstract: The article deals with the tool in Matlab GUI form
that is designed to analyse a mechatronic system sensitivity and
tolerance. In the analysed mechatronic system, a torque is transferred
from the drive to the load through a coupling containing flexible
elements. Different methods of control system design are used. The
classic form of the feedback control is proposed using Naslin method,
modulus optimum criterion and inverse dynamics method. The
cascade form of the control is proposed based on combination of
modulus optimum criterion and symmetric optimum criterion. The
sensitivity is analysed on the basis of absolute and relative sensitivity
of system function to the change of chosen parameter value of the
mechatronic system, as well as the control subsystem. The tolerance
is analysed in the form of determining the range of allowed relative
changes of selected system parameters in the field of system stability.
The tool allows to analyse an influence of torsion stiffness, torsion
damping, inertia moments of the motor and the load and controller(s)
parameters. The sensitivity and tolerance are monitored in terms of
the impact of parameter change on the response in the form of system
step response and system frequency-response logarithmic
characteristics. The Symbolic Math Toolbox for expression of the
final shape of analysed system functions was used. The sensitivity
and tolerance are graphically represented as 2D graph of sensitivity
or tolerance of the system function and 3D/2D static/interactive graph
of step/frequency response.
Abstract: This work proposes a data-driven multiscale based
quantitative measures to reveal the underlying complexity of
electroencephalogram (EEG), applying to a rodent model of
hypoxic-ischemic brain injury and recovery. Motivated by that real
EEG recording is nonlinear and non-stationary over different
frequencies or scales, there is a need of more suitable approach over
the conventional single scale based tools for analyzing the EEG data.
Here, we present a new framework of complexity measures
considering changing dynamics over multiple oscillatory scales. The
proposed multiscale complexity is obtained by calculating entropies of
the probability distributions of the intrinsic mode functions extracted
by the empirical mode decomposition (EMD) of EEG. To quantify
EEG recording of a rat model of hypoxic-ischemic brain injury
following cardiac arrest, the multiscale version of Tsallis entropy is
examined. To validate the proposed complexity measure, actual EEG
recordings from rats (n=9) experiencing 7 min cardiac arrest followed
by resuscitation were analyzed. Experimental results demonstrate that
the use of the multiscale Tsallis entropy leads to better discrimination
of the injury levels and improved correlations with the neurological
deficit evaluation after 72 hours after cardiac arrest, thus suggesting an
effective metric as a prognostic tool.
Abstract: Scrubbing by a liquid spraying is one of the most
effective processes used for removal of fine particles and soluble
gas pollutants (such as SO2, HCl, HF) from the flue gas. There are
many configurations of scrubbers designed to provide contact
between the liquid and gas stream for effectively capturing
particles or soluble gas pollutants, such as spray plates, packed bed
towers, jet scrubbers, cyclones, vortex and venturi scrubbers. The
primary function of venturi scrubber is the capture of fine particles
as well as HCl, HF or SO2 removal with effect of the flue gas
temperature decrease before input to the absorption column. In this
paper, sulfur dioxide (SO2) from flue gas was captured using new
design replacing venturi scrubber (1st degree of wet scrubbing).
The flue gas was prepared by the combustion of the carbon
disulfide solution in toluene (1:1 vol.) in the flame in the reactor.
Such prepared flue gas with temperature around 150°C was
processed in designed laboratory O-element scrubber. Water was
used as absorbent liquid. The efficiency of SO2 removal, pressure
drop and temperature drop were measured on our experimental
device. The dependence of these variables on liquid-gas ratio was
observed. The average temperature drop was in the range from
150°C to 40°C. The pressure drop was increased with increasing of
a liquid-gas ratio, but no too much as for the common venturi
scrubber designs. The efficiency of SO2 removal was up to 70 %.
The pressure drop of our new designed wet scrubber is similar to
commonly used venturi scrubbers; nevertheless the influence of
amount of the liquid on pressure drop is not so significant.
Abstract: This paper is concerned with knowledge representation
and extraction of fuzzy if-then rules using Interval Type-2
Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of
fuzzy granulation. This proposed clustering algorithm is based on
information granulation in the form of IT2 based Fuzzy C-Means
(IT2-FCM) clustering and estimates the cluster centers by preserving
the homogeneity between the clustered patterns from the IT2 contexts
produced in the output space. Furthermore, we can obtain the
automatic knowledge representation in the design of Radial Basis
Function Networks (RBFN), Linguistic Model (LM), and Adaptive
Neuro-Fuzzy Networks (ANFN) from the numerical input-output data
pairs. We shall focus on a design of ANFN in this paper. The
experimental results on an estimation problem of energy performance
reveal that the proposed method showed a good knowledge
representation and performance in comparison with the previous
works.
Abstract: Moving into a new era of healthcare, new tools and
devices are developed to extend and improve health services, such as
remote patient monitoring and risk prevention. In this concept,
Internet of Things (IoT) and Cloud Computing present great
advantages by providing remote and efficient services, as well as
cooperation between patients, clinicians, researchers and other health
professionals. This paper focuses on patients suffering from bipolar
disorder, a brain disorder that belongs to a group of conditions
called affective disorders, which is characterized by great mood
swings. We exploit the advantages of Semantic Web and Cloud
Technologies to develop a patient monitoring system to support
clinicians. Based on intelligently filtering of evidence-knowledge and
individual-specific information we aim to provide treatment
notifications and recommended function tests at appropriate times or
concluding into alerts for serious mood changes and patient’s nonresponse
to treatment. We propose an architecture as the back-end
part of a cloud platform for IoT, intertwining intelligence devices
with patients’ daily routine and clinicians’ support.
Abstract: We have conducted the optimal synthesis of rootmean-
squared objective filter to estimate the state vector in the case if
within the observation channel with memory the anomalous noises
with unknown mathematical expectation are complement in the
function of the regular noises. The synthesis has been carried out for
linear stochastic systems of continuous - time.
Abstract: The capability of exploiting the electronic charge and
spin properties simultaneously in a single material has made diluted
magnetic semiconductors (DMS) remarkable in the field of
spintronics. We report the designing of DMS based on zinc-blend
ZnO doped with Cr impurity. The full potential linearized augmented
plane wave plus local orbital FP-L(APW+lo) method in density
functional theory (DFT) has been adapted to carry out these
investigations. For treatment of exchange and correlation energy,
generalized gradient approximations have been used. Introducing Cr
atoms in the matrix of ZnO has induced strong magnetic moment
with ferromagnetic ordering at stable ground state. Cr:ZnO was found
to favor the short range magnetic interaction that
reflect tendency of Cr clustering. The electronic structure of ZnO is
strongly influenced in the presence of Cr impurity atoms where
impurity bands appear in the band gap.
Abstract: The quality and condition of perishable products
delivered to the market and their subsequent selling prices are
directly affected by the care taken during harvesting and handling.
Mechanical injury, in fact, occurs at all stages, from pre-harvest
operations through post-harvest handling, packing and transport to
the market. The main implications of this damage are the reduction of
the product’s quality and economical losses related to the shelf life
diminution. For most perishable products, the shelf life is relatively
short and it is typically dictated by microbial growth related to the
application of dynamic and static loads during transportation. This
paper presents the correlation between vibration levels and
microbiological growth on strawberries and woodland strawberries
and detects the presence of volatile organic compounds (VOC) in
order to develop an intelligent logistic unit capable of monitoring
VOCs using a specific sensor system. Fresh fruits were exposed to
vibrations by means of a vibrating table in a temperature-controlled
environment. Microbiological analyses were conducted on samples,
taken at different positions along the column of the crates. The values
obtained were compared with control samples not exposed to
vibrations and the results show that different positions along the
column influence the development of bacteria, yeasts and filamentous
fungi.
Abstract: All the software engineering researches and best
industry practices aim at providing software products with high
degree of quality and functionality at low cost and less time. These
requirements are addressed by the Component Based Software
Engineering (CBSE) as well. CBSE, which deals with the software
construction by components’ assembly, is a revolutionary extension
of Software Engineering. CBSE must define and describe processes
to assure timely completion of high quality software systems that are
composed of a variety of pre built software components. Though
these features provide distinct and visible benefits in software design
and programming, they also raise some challenging problems. The
aim of this work is to summarize the pertinent issues and
considerations in CBSE to make an understanding in forms of
concepts and observations that may lead to development of newer
ways of dealing with the problems and challenges in CBSE.
Abstract: The main objective of this paper is to provide a new
methodology for road safety assessment in Oman through the
development of suitable accident prediction models. GLM technique
with Poisson or NBR using SAS package was carried out to develop
these models. The paper utilized the accidents data of 31 un-signalized
T-intersections during three years. Five goodness-of-fit
measures were used to assess the overall quality of the developed
models. Two types of models were developed separately; the flow-based
models including only traffic exposure functions, and the full
models containing both exposure functions and other significant
geometry and traffic variables.
The results show that, traffic exposure functions produced much
better fit to the accident data. The most effective geometric variables
were major-road mean speed, minor-road 85th percentile speed,
major-road lane width, distance to the nearest junction, and right-turn
curb radius.
The developed models can be used for intersection treatment or
upgrading and specify the appropriate design parameters of T-intersections.
Finally, the models presented in this thesis reflect the intersection
conditions in Oman and could represent the typical conditions in
several countries in the middle east area, especially gulf countries.
Abstract: The mechanisms underlying the association between
obesity and asthma may be related to a decreased immunological
tolerance induced by a defective function of regulatory T cells
(Tregs). The aim of this study is to establish the potential link
between these diseases and CD4+, CD25+ FoxP3+ Tregs as well as T
helper cells (Ths) in children. This is a prospective case control
study. Obese (n:40), asthmatic (n:40), asthmatic obese (n:40) and
healthy children (n:40), who don't have any acute or chronic diseases,
were included in this study. Obese children were evaluated according
to WHO criteria. Asthmatic patients were chosen based on GINA
criteria. Parents were asked to fill up the questionnaire. Informed
consent forms were taken. Blood samples were marked with CD4+,
CD25+ and FoxP3+ in order to determine Tregs and Ths by flow
cytometric method. Statistical analyses were performed. p≤0.05 was
chosen as meaningful threshold. Tregs exhibiting anti-inflammatory
nature were significantly lower in obese (0,16%; p≤0,001), asthmatic
(0,25%; p≤0,01) and asthmatic obese (0,29%; p≤0,05) groups than
the control group (0,38%). Ths were counted higher in asthma group
than the control (p≤0,01) and obese (p≤0,001) groups. T cell
immunity plays important roles in obesity and asthma pathogeneses.
Decreased numbers of Tregs found in obese, asthmatic and asthmatic
obese children may help to elucidate some questions in
pathophysiology of these diseases. For HOMA-IR levels, any
significant difference was not noted between control and obese
groups, but statistically higher values were found for obese
asthmatics. The values obtained in all groups were found to be below
the critical cut off points. This finding has made the statistically
significant difference observed between Tregs of obese, asthmatic,
obese asthmatic and control groups much more valuable. These
findings will be useful in diagnosis and treatment of these disorders
and future studies are needed. The production and propagation of
Tregs may be promising in alternative asthma and obesity treatments.
Abstract: This paper describes the issues relating to the role of
the flash flood early warning system provided by the Malaysian
Government to the communities in Malaysia, specifically during the
flash flood disaster in the Cameron Highlands, Malaysia. Normally,
flash flood disasters can occur as a result of heavy rainfall in an area,
and that water may possibly cause flooding via streams or narrow
channels. The focus of this study is the flash flood disaster which
occurred on 23 October 2013 in the Cameron Highlands, and as a
result the Sungai Bertam overflowed after the release of water from
the Sultan Abu Bakar Dam. This release of water from the dam
caused flash flooding which led to damage to properties and also the
death of residents and livestock in the area. Therefore, the effort of
this study is to identify the perceptions of the flash flood victims on
the role of the flash flood early warning system. For the purposes of
this study, data were gathered through face-to-face interviews from
those flood victims who were willing to participate in this study. This
approach helped the researcher to glean in-depth information about
their feelings and perceptions of the role of the flash flood early
warning system offered by the government. The data were analysed
descriptively and the findings show that the respondents of 22 flood
victims believe strongly that the flash flood early warning system was
confusing and dysfunctional, and communities had failed to response
positively to it. Therefore, most of the communities were not well
prepared for the releasing of water from the dam which caused
property damage, and 3 people were killed in the Cameron Highland
flash flood disaster.
Abstract: In this paper, we introduced a gradient-based inverse
solver to obtain the missing boundary conditions based on the
readings of internal thermocouples. The results show that the method
is very sensitive to measurement errors, and becomes unstable when
small time steps are used. The artificial neural networks are shown to
be capable of capturing the whole thermal history on the run-out
table, but are not very effective in restoring the detailed behavior of
the boundary conditions. Also, they behave poorly in nonlinear cases
and where the boundary condition profile is different.
GA and PSO are more effective in finding a detailed
representation of the time-varying boundary conditions, as well as in
nonlinear cases. However, their convergence takes longer. A
variation of the basic PSO, called CRPSO, showed the best
performance among the three versions. Also, PSO proved to be
effective in handling noisy data, especially when its performance
parameters were tuned. An increase in the self-confidence parameter
was also found to be effective, as it increased the global search
capabilities of the algorithm. RPSO was the most effective variation
in dealing with noise, closely followed by CRPSO. The latter
variation is recommended for inverse heat conduction problems, as it
combines the efficiency and effectiveness required by these
problems.
Abstract: In this paper, the problem of steady laminar boundary
layer flow and heat transfer over a permeable exponentially
stretching/shrinking sheet with generalized slip velocity is
considered. The similarity transformations are used to transform the
governing nonlinear partial differential equations to a system of
nonlinear ordinary differential equations. The transformed equations
are then solved numerically using the bvp4c function in MATLAB.
Dual solutions are found for a certain range of the suction and
stretching/shrinking parameters. The effects of the suction parameter,
stretching/shrinking parameter, velocity slip parameter, critical shear
rate and Prandtl number on the skin friction and heat transfer
coefficients as well as the velocity and temperature profiles are
presented and discussed.
Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.