Abstract: The aim of the current study is to develop a numerical
tool that is capable of achieving an optimum shape and design of
hyperbolic cooling towers based on coupling a non-linear finite
element model developed in-house and a genetic algorithm
optimization technique. The objective function is set to be the
minimum weight of the tower. The geometric modeling of the tower
is represented by means of B-spline curves. The finite element
method is applied to model the elastic buckling behaviour of a tower
subjected to wind pressure and dead load. The study is divided into
two main parts. The first part investigates the optimum shape of the
tower corresponding to minimum weight assuming constant
thickness. The study is extended in the second part by introducing the
shell thickness as one of the design variables in order to achieve an
optimum shape and design. Design, functionality and practicality
constraints are applied.
Abstract: In this paper, an efficient local appearance feature
extraction method based the multi-resolution Curvelet transform is
proposed in order to further enhance the performance of the well
known Linear Discriminant Analysis(LDA) method when applied
to face recognition. Each face is described by a subset of band
filtered images containing block-based Curvelet coefficients. These
coefficients characterize the face texture and a set of simple statistical
measures allows us to form compact and meaningful feature vectors.
The proposed method is compared with some related feature extraction
methods such as Principal component analysis (PCA), as well
as Linear Discriminant Analysis LDA, and independent component
Analysis (ICA). Two different muti-resolution transforms, Wavelet
(DWT) and Contourlet, were also compared against the Block Based
Curvelet-LDA algorithm. Experimental results on ORL, YALE and
FERET face databases convince us that the proposed method provides
a better representation of the class information and obtains much
higher recognition accuracies.
Abstract: The pipe inspection operation is the difficult detective
performance. Almost applications are mainly relies on a manual
recognition of defective areas that have carried out detection by an
engineer. Therefore, an automation process task becomes a necessary
in order to avoid the cost incurred in such a manual process. An
automated monitoring method to obtain a complete picture of the
sewer condition is proposed in this work. The focus of the research is
the automated identification and classification of discontinuities in
the internal surface of the pipe. The methodology consists of several
processing stages including image segmentation into the potential
defect regions and geometrical characteristic features. Automatic
recognition and classification of pipe defects are carried out by means
of using an artificial neural network technique (ANN) based on
Radial Basic Function (RBF). Experiments in a realistic environment
have been conducted and results are presented.
Abstract: This paper argues that increased uncertainty, in certain
situations, may actually encourage investment. Since earlier studies
mostly base their arguments on the assumption of geometric Brownian
motion, the study extends the assumption to alternative stochastic
processes, such as mixed diffusion-jump, mean-reverting process, and
jump amplitude process. A general approach of Monte Carlo
simulation is developed to derive optimal investment trigger for the
situation that the closed-form solution could not be readily obtained
under the assumption of alternative process. The main finding is that
the overall effect of uncertainty on investment is interpreted by the
probability of investing, and the relationship appears to be an invested
U-shaped curve between uncertainty and investment. The implication
is that uncertainty does not always discourage investment even under
several sources of uncertainty. Furthermore, high-risk projects are not
always dominated by low-risk projects because the high-risk projects
may have a positive realization effect on encouraging investment.
Abstract: The main objective of this study was to determine if a
minimal increase in road light level (luminance) could lead to
improved driving performance among older adults. Older, middleaged
and younger adults were tested in a driving simulator following
vision and cognitive screening. Comparisons were made for the
performance of simulated night driving under two road light
conditions (0.6 and 2.5 cd/m2). At each light level, the effects of self
reported night driving avoidance were examined along with the
vision/cognitive performance. It was found that increasing road light
level from 0.6 cd/m2 to 2.5 cd/m2 resulted in improved recognition of
signage on straight highway segments. The improvement depends on
different driver-related factors such as vision and cognitive abilities,
and confidence. On curved road sections, the results showed that
driver-s performance worsened. It is concluded that while increasing
road lighting may be helpful to older adults especially for sign
recognition, it may also result in increased driving confidence and
thus reduced attention in some driving situations.
Abstract: In determining the electromagnetic properties of
magnetic materials, hysteresis modeling is of high importance. Many
models are available to investigate those characteristics but they tend
to be complex and difficult to implement. In this paper a new
qualitative hysteresis model for ferromagnetic core is presented,
based on the function approximation capabilities of adaptive neuro
fuzzy inference system (ANFIS). The proposed ANFIS model
combined the neural network adaptive capabilities and the fuzzy
logic qualitative approach can restored the hysteresis curve with a
little RMS error. The model accuracy is good and can be easily
adapted to the requirements of the application by extending or
reducing the network training set and thus the required amount of
measurement data.
Abstract: In this study the elastic-plastic stress distribution in
weld-bonded joint, fabricated from austenitic stainless steel (AISI
304) sheet of 1.00 mm thickness and Epoxy adhesive Araldite 2011,
subjected to axial loading is investigated. This is needed to improve
design procedures and welding codes, and saving efforts in the
cumbersome experiments and analysis. Therefore, a complete 3-D
finite element modelling and analysis of spot welded, bonded and
weld-bonded joints under axial loading conditions is carried out. A
comprehensive systematic experimental program is conducted to
determine many properties and quantities, of the base metals and the
adhesive, needed for FE modelling, such like the elastic – plastic
properties, modulus of elasticity, fracture limit, the nugget and heat
affected zones (HAZ) properties, etc. Consequently, the finite
element models developed, for each case, are used to evaluate
stresses distributions across the entire joint, in both the elastic and
plastic regions. The stress distribution curves are obtained,
particularly in the elastic regions and found to be consistent and in
excellent agreement with the published data. Furthermore, the
stresses distributions are obtained in the weld-bonded joint and
display the best results with almost uniform smooth distribution
compared to spot and bonded cases. The stress concentration peaks at
the edges of the weld-bonded region, are almost eliminated resulting
in achieving the strongest joint of all processes.
Abstract: This work is focused on the numerical prediction of the fracture resistance of a flat stiffened panel made of the aluminium alloy 2024 T3 under a monotonic traction condition. The performed numerical simulations have been based on the micromechanical Gurson-Tvergaard (GT) model for ductile damage. The applicability of the GT model to this kind of structural problems has been studied and assessed by comparing numerical results, obtained by using the WARP 3D finite element code, with experimental data available in literature. In the sequel a home-made procedure is presented, which aims to increase the residual strength of a cracked stiffened aluminum panel and which is based on the stochastic design improvement (SDI) technique; a whole application example is then given to illustrate the said technique.
Abstract: In this work, we consider the number of integer solutions
of Diophantine equation D : y2 - 2yx - 3 = 0 over Z and
also over finite fields Fp for primes p ≥ 5. Later we determine the
number of rational points on curves Ep : y2 = Pp(x) = yp
1 + yp
2
over Fp, where y1 and y2 are the roots of D. Also we give a formula
for the sum of x- and y-coordinates of all rational points (x, y) on
Ep over Fp.
Abstract: Nondestructive testing in engineering is an inverse
Cauchy problem for Laplace equation. In this paper the problem
of nondestructive testing is expressed by a Laplace-s equation with
third-kind boundary conditions. In order to find unknown values on
the boundary, the method of fundamental solution is introduced and
realized. Because of the ill-posedness of studied problems, the TSVD
regularization technique in combination with L-curve criteria and
Generalized Cross Validation criteria is employed. Numerical results
are shown that the TSVD method combined with L-curve criteria is
more efficient than the TSVD method combined with GCV criteria.
The abstract goes here.
Abstract: As the global climate changes, the threat from
landslides and debris flows increases. Learning how a watershed
initiates landslides under abnormal rainfall conditions and predicting
landslide magnitude and frequency distribution is thus important.
Landslides show a power-law distribution in the frequency-area
distribution. The distribution curve shows an exponent gradient 1.0 in
the Sandpile model test. Will the landslide frequency-area statistics
show a distribution similar to the Sandpile model under extreme
rainfall conditions? The purpose of the study is to identify the extreme
rainfall-induced landslide frequency-area distribution in the Laonong
River Basin in southern Taiwan. Results of the analysis show that a
lower gradient of landslide frequency-area distribution could be
attributed to the transportation and deposition of debris flow areas that
are included in the landslide area.
Abstract: The behavior of three phase five leg transformer under voltage sag is studied in this paper. This paper proposes a simple, practical model of a three phase-five leg, saturated transformer with accurate performance. Transformer saturation is produced when the voltage sag is recovered and it causes inrush current in transformer. Effects of voltage sag depth, duration and initial point on wave have been analyzed in this paper. Initial point on wave can produce maximum inrush current in five leg transformers while comparing with three leg transformers. The magnetic circuit symmetry of five leg transformer produces the more symmetrical shape of inrush current curves versus initial point on wave and sag duration than three leg transformer. The simulations show that current peak has a periodical dependence on sag duration and linear dependence on sag depth. Inrush current that is produced in three phase five leg transformer is higher than three phase three leg transformer.
Abstract: Time series analysis often requires data that represents
the evolution of an observed variable in equidistant time steps. In
order to collect this data sampling is applied. While continuous
signals may be sampled, analyzed and reconstructed applying
Shannon-s sampling theorem, time-discrete signals have to be dealt
with differently. In this article we consider the discrete-event
simulation (DES) of job-shop-systems and study the effects of
different sampling rates on data quality regarding completeness and
accuracy of reconstructed inventory evolutions. At this we discuss
deterministic as well as non-deterministic behavior of system
variables. Error curves are deployed to illustrate and discuss the
sampling rate-s impact and to derive recommendations for its wellfounded
choice.
Abstract: The scalar wave equation for a potential in a curved space time, i.e., the Laplace-Beltrami equation has been studied in this work. An action principle is used to derive a finite element algorithm for determining the modes of propagation inside a waveguide of arbitrary shape. Generalizing this idea, the Maxwell theory in a curved space time determines a set of linear partial differential equations for the four electromagnetic potentials given by the metric of space-time. Similar to the Einstein-s formulation of the field equations of gravitation, these equations are also derived from an action principle. In this paper, the expressions for the action functional of the electromagnetic field have been derived in the presence of gravitational field.
Abstract: This paper presents an improved image segmentation
model with edge preserving regularization based on the
piecewise-smooth Mumford-Shah functional. A level set formulation
is considered for the Mumford-Shah functional minimization in
segmentation, and the corresponding partial difference equations are
solved by the backward Euler discretization. Aiming at encouraging
edge preserving regularization, a new edge indicator function is
introduced at level set frame. In which all the grid points which is used
to locate the level set curve are considered to avoid blurring the edges
and a nonlinear smooth constraint function as regularization term is
applied to smooth the image in the isophote direction instead of the
gradient direction. In implementation, some strategies such as a new
scheme for extension of u+ and u- computation of the grid points and
speedup of the convergence are studied to improve the efficacy of the
algorithm. The resulting algorithm has been implemented and
compared with the previous methods, and has been proved efficiently
by several cases.
Abstract: In this paper back-propagation artificial neural network
(BPANN) is employed to predict the deformation of the upsetting
process. To prepare a training set for BPANN, some finite element
simulations were carried out. The input data for the artificial neural
network are a set of parameters generated randomly (aspect ratio d/h,
material properties, temperature and coefficient of friction). The
output data are the coefficient of polynomial that fitted on barreling
curves. Neural network was trained using barreling curves generated
by finite element simulations of the upsetting and the corresponding
material parameters. This technique was tested for three different
specimens and can be successfully employed to predict the
deformation of the upsetting process
Abstract: This paper reports the fatigue crack growth behaviour
of gas tungsten arc, electron beam and laser beam welded Ti-6Al-4V
titanium alloy. Centre cracked tensile specimens were prepared to
evaluate the fatigue crack growth behaviour. A 100kN servo
hydraulic controlled fatigue testing machine was used under constant
amplitude uniaxial tensile load (stress ratio of 0.1 and frequency of
10 Hz). Crack growth curves were plotted and crack growth
parameters (exponent and intercept) were evaluated. Critical and
threshold stress intensity factor ranges were also evaluated. Fatigue
crack growth behaviour of welds was correlated with mechanical
properties and microstructural characteristics of welds. Of the three
joints, the joint fabricated by laser beam welding exhibited higher
fatigue crack growth resistance due to the presence of fine lamellar
microstructure in the weld metal.
Abstract: The data measurement of mean velocity has been
taken for the wake of single circular cylinder with three different diameters for two different velocities. The effects of change in
diameter and in velocity are studied in self-similar coordinate system.
The spatial variations of velocity defect and that of the half-width
have been investigated. The results are compared with those
published by H.Schlichting. In the normalized coordinates, it is also observed that all cases except for the first station are self-similar. By attention to self-similarity profiles of mean velocity, it is observed for all the cases at the each station curves tend to zero at a same point.
Abstract: Mammography is the most effective procedure for an
early diagnosis of the breast cancer. Nowadays, people are trying to
find a way or method to support as much as possible to the
radiologists in diagnosis process. The most popular way is now being
developed is using Computer-Aided Detection (CAD) system to
process the digital mammograms and prompt the suspicious region to
radiologist. In this paper, an automated CAD system for detection
and classification of massive lesions in mammographic images is
presented. The system consists of three processing steps: Regions-Of-
Interest detection, feature extraction and classification. Our CAD
system was evaluated on Mini-MIAS database consisting 322
digitalized mammograms. The CAD system-s performance is
evaluated using Receiver Operating Characteristics (ROC) and Freeresponse
ROC (FROC) curves. The archived results are 3.47 false
positives per image (FPpI) and sensitivity of 85%.
Abstract: We report the size dependence of 1D superconductivity in ultrathin (10-130 nm) nanowires produced by coating suspended carbon nanotubes with a superconducting NbN thin film. The resistance-temperature characteristic curves for samples with ≧25 nm wire width show the superconducting transition. On the other hand, for the samples with 10-nm width, the superconducting transition is not exhibited owing to the quantum size effect. The differential resistance vs. current density characteristic curves show some peak, indicating that Josephson junctions are formed in nanowires. The presence of the Josephson junctions is well explained by the measurement of the magnetic field dependence of the critical current. These understanding allow for the further expansion of the potential application of NbN, which is utilized for single photon detectors and so on.