Abstract: One of the main research directions in CAD/CAM
machining area is the reducing of machining time.
The feedrate scheduling is one of the advanced techniques that
allows keeping constant the uncut chip area and as sequel to keep
constant the main cutting force. They are two main ways for feedrate
optimization. The first consists in the cutting force monitoring, which
presumes to use complex equipment for the force measurement and
after this, to set the feedrate regarding the cutting force variation. The
second way is to optimize the feedrate by keeping constant the
material removal rate regarding the cutting conditions.
In this paper there is proposed a new approach using an extended
database that replaces the system model.
The feedrate scheduling is determined based on the identification
of the reconfigurable machine tool, and the feed value determination
regarding the uncut chip section area, the contact length between tool
and blank and also regarding the geometrical roughness.
The first stage consists in the blank and tool monitoring for the
determination of actual profiles. The next stage is the determination
of programmed tool path that allows obtaining the piece target
profile.
The graphic representation environment models the tool and blank
regions and, after this, the tool model is positioned regarding the
blank model according to the programmed tool path. For each of
these positions the geometrical roughness value, the uncut chip area
and the contact length between tool and blank are calculated. Each of
these parameters are compared with the admissible values and
according to the result the feed value is established.
We can consider that this approach has the following advantages:
in case of complex cutting processes the prediction of cutting force is
possible; there is considered the real cutting profile which has
deviations from the theoretical profile; the blank-tool contact length
limitation is possible; it is possible to correct the programmed tool
path so that the target profile can be obtained.
Applying this method, there are obtained data sets which allow the
feedrate scheduling so that the uncut chip area is constant and, as a
result, the cutting force is constant, which allows to use more
efficiently the machine tool and to obtain the reduction of machining
time.
Abstract: The aim of this research is to evaluate surface
roughness and develop a multiple regression model for surface roughness as a function of cutting parameters during the turning of
flame hardened medium carbon steel with TiN-Al2O3-TiCN coated inserts. An experimental plan of work and signal-to-noise ratio (S/N)
were used to relate the influence of turning parameters to the
workpiece surface finish utilizing Taguchi methodology. The effects
of turning parameters were studied by using the analysis of variance (ANOVA) method. Evaluated parameters were feed, cutting speed,
and depth of cut. It was found that the most significant interaction among the considered turning parameters was between depth of cut and feed. The average surface roughness (Ra) resulted by TiN-Al2O3-
TiCN coated inserts was about 2.44 μm and minimum value was 0.74 μm. In addition, the regression model was able to predict values for surface roughness in comparison with experimental values within
reasonable limit.
Abstract: The recent drive for use of performance-based methodologies in design and assessment of structures in seismic areas has significantly increased the demand for the development of reliable nonlinear inelastic static pushover analysis tools. As a result, the adaptive pushover methods have been developed during the last decade, which unlike their conventional pushover counterparts, feature the ability to account for the effect that higher modes of vibration and progressive stiffness degradation might have on the distribution of seismic storey forces. Even in advanced pushover methods, little attention has been paid to the Unsymmetric structures. This study evaluates the seismic demands for three dimensional Unsymmetric-Plan buildings determined by the Displacement-based Adaptive Pushover (DAP) analysis, which has been introduced by Antoniou and Pinho [2004]. The capability of DAP procedure in capturing the torsional effects due to the irregularities of the structures, is investigated by comparing its estimates to the exact results, obtained from Incremental Dynamic Analysis (IDA). Also the capability of the procedure in prediction the seismic behaviour of the structure is discussed.
Abstract: The theoretical prediction of the acoustical
polarization effects in the heterogeneous composites, made of thick
elastic solids with thin nematic films, is presented. The numericalanalytical
solution to the problem of the different wave propagation
exhibits some new physical effects in the low frequency domain: the
appearance of the critical frequency and the existence of the narrow
transition zone where the wave rapidly changes its speed. The
associated wave attenuation is highly perturbed in this zone. We also
show the possible appearance of the critical frequencies where the
attenuation changes the sign. The numerical results of parametrical
analysis are presented and discussed.
Abstract: In this research, heat transfer of a poly Ethylene
fluidized bed reactor without reaction were studied experimentally
and computationally at different superficial gas velocities. A multifluid
Eulerian computational model incorporating the kinetic theory
for solid particles was developed and used to simulate the heat
conducting gas–solid flows in a fluidized bed configuration.
Momentum exchange coefficients were evaluated using the Syamlal–
O-Brien drag functions. Temperature distributions of different phases
in the reactor were also computed. Good agreement was found
between the model predictions and the experimentally obtained data
for the bed expansion ratio as well as the qualitative gas–solid flow
patterns. The simulation and experimental results showed that the gas
temperature decreases as it moves upward in the reactor, while the
solid particle temperature increases. Pressure drop and temperature
distribution predicted by the simulations were in good agreement
with the experimental measurements at superficial gas velocities
higher than the minimum fluidization velocity. Also, the predicted
time-average local voidage profiles were in reasonable agreement
with the experimental results. The study showed that the
computational model was capable of predicting the heat transfer and
the hydrodynamic behavior of gas-solid fluidized bed flows with
reasonable accuracy.
Abstract: End milling process is one of the common metal
cutting operations used for machining parts in manufacturing
industry. It is usually performed at the final stage in manufacturing a
product and surface roughness of the produced job plays an
important role. In general, the surface roughness affects wear
resistance, ductility, tensile, fatigue strength, etc., for machined parts
and cannot be neglected in design. In the present work an
experimental investigation of end milling of aluminium alloy with
carbide tool is carried out and the effect of different cutting
parameters on the response are studied with three-dimensional
surface plots. An artificial neural network (ANN) is used to establish
the relationship between the surface roughness and the input cutting
parameters (i.e., spindle speed, feed, and depth of cut). The Matlab
ANN toolbox works on feed forward back propagation algorithm is
used for modeling purpose. 3-12-1 network structure having
minimum average prediction error found as best network architecture
for predicting surface roughness value. The network predicts surface
roughness for unseen data and found that the result/prediction is
better. For desired surface finish of the component to be produced
there are many different combination of cutting parameters are
available. The optimum cutting parameter for obtaining desired
surface finish, to maximize tool life is predicted. The methodology is
demonstrated, number of problems are solved and algorithm is coded
in Matlab®.
Abstract: Analytical procedure was carried out in this paper to
calculate the ultimate load capacity of reinforced concrete corbels
strengthened or repaired externally with CFRP sheets. Strut and tie
method and shear friction method proposed earlier for analyzing
reinforced concrete corbels were modified to incorporate the effect of
external CFRP sheets bonded to the corbel. The points of weakness
of any method that lead to an inaccuracy, especially when
overestimating test results were checked and discussed. Comparison
of prediction with the test data indicates that the ratio of test /
calculated ultimate load is 0.82 and 1.17 using strut and tie method
and shear friction method, respectively. If the limits of maximum
shear stress is followed, the calculated ultimate load capacity using
shear friction method was found to underestimates test data
considerably.
Abstract: The measurement of aerodynamic forces and moments
acting on an aircraft model is important for the development of wind
tunnel measurement technology to predict the performance of the full
scale vehicle. The potentials of an aircraft model with and without
winglet and aerodynamic characteristics with NACA wing No. 65-3-
218 have been studied using subsonic wind tunnel of 1 m × 1 m
rectangular test section and 2.5 m long of Aerodynamics Laboratory
Faculty of Engineering (University Putra Malaysia). Focusing on
analyzing the aerodynamic characteristics of the aircraft model, two
main issues are studied in this paper. First, a six component wind
tunnel external balance is used for measuring lift, drag and pitching
moment. Secondly, Tests are conducted on the aircraft model with
and without winglet of two configurations at Reynolds numbers
1.7×105, 2.1×105, and 2.5×105 for different angle of attacks. Fuzzy
logic approach is found as efficient for the representation,
manipulation and utilization of aerodynamic characteristics.
Therefore, the primary purpose of this work was to investigate the
relationship between lift and drag coefficients, with free-stream
velocities and angle of attacks, and to illustrate how fuzzy logic
might play an important role in study of lift aerodynamic
characteristics of an aircraft model with the addition of certain
winglet configurations. Results of the developed fuzzy logic were
compared with the experimental results. For lift coefficient analysis,
the mean of actual and predicted values were 0.62 and 0.60
respectively. The coreelation between actual and predicted values
(from FLS model) of lift coefficient in different angle of attack was
found as 0.99. The mean relative error of actual and predicted valus
was found as 5.18% for the velocity of 26.36 m/s which was found to
be less than the acceptable limits (10%). The goodness of fit of
prediction value was 0.95 which was close to 1.0.
Abstract: Many studies have focused on the nonlinear analysis
of electroencephalography (EEG) mainly for the characterization of
epileptic brain states. It is assumed that at least two states of the
epileptic brain are possible: the interictal state characterized by a
normal apparently random, steady-state EEG ongoing activity; and
the ictal state that is characterized by paroxysmal occurrence of
synchronous oscillations and is generally called in neurology, a
seizure.
The spatial and temporal dynamics of the epileptogenic process is
still not clear completely especially the most challenging aspects of
epileptology which is the anticipation of the seizure. Despite all the
efforts we still don-t know how and when and why the seizure
occurs. However actual studies bring strong evidence that the
interictal-ictal state transition is not an abrupt phenomena. Findings
also indicate that it is possible to detect a preseizure phase.
Our approach is to use the neural network tool to detect interictal
states and to predict from those states the upcoming seizure ( ictal
state). Analysis of the EEG signal based on neural networks is used
for the classification of EEG as either seizure or non-seizure. By
applying prediction methods it will be possible to predict the
upcoming seizure from non-seizure EEG.
We will study the patients admitted to the epilepsy monitoring
unit for the purpose of recording their seizures. Preictal, ictal, and
post ictal EEG recordings are available on such patients for analysis
The system will be induced by taking a body of samples then
validate it using another. Distinct from the two first ones a third body
of samples is taken to test the network for the achievement of
optimum prediction. Several methods will be tried 'Backpropagation
ANN' and 'RBF'.
Abstract: Cosmic showers, during the transit through space, produce
sub - products as a result of interactions with the intergalactic
or interstellar medium which after entering earth generate secondary
particles called Extensive Air Shower (EAS). Detection and analysis
of High Energy Particle Showers involve a plethora of theoretical and
experimental works with a host of constraints resulting in inaccuracies
in measurements. Therefore, there exist a necessity to develop a
readily available system based on soft-computational approaches
which can be used for EAS analysis. This is due to the fact that soft
computational tools such as Artificial Neural Network (ANN)s can be
trained as classifiers to adapt and learn the surrounding variations. But
single classifiers fail to reach optimality of decision making in many
situations for which Multiple Classifier System (MCS) are preferred
to enhance the ability of the system to make decisions adjusting
to finer variations. This work describes the formation of an MCS
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN) with data inputs
from correlation mapping Self Organizing Map (SOM) blocks and
the output optimized by another SOM. The results show that the setup
can be adopted for real time practical applications for prediction
of primary energy and location of EAS from density values captured
using detectors in a circular grid.
Abstract: Tubular linear induction motor (TLIM) can be used as a capsule pump in a large pneumatic capsule pipeline (PCP) system. Parametric performance evaluation of the designed 1-meter diameter PCP-TLIM system yields encouraging results for practical implementation. The capsule thrust and speed inside the TLIM pump can be calculated from the combination of the PCP fluid mechanics and the TLIM equations. The TLIM equivalent circuits derived from those of the conventional three-phase induction motor are used as a model to predict the static test results of a small-scale PCP-TLIM system. In this paper, additional dynamic tests are performed on the same small-scale PCP-TLIM system with two capsules of different diameters. The behaviors of the capsule inside the pump are observed and analyzed. The dynamic performances from the dynamic tests are compared with the theoretical predictions based on the TLIM equivalent circuit model.
Abstract: Since primary school trips usually start from home,
attention by many scholars have been focused on the home end for
data gathering. Thereafter category analysis has often been relied
upon when predicting school travel demands. In this paper, school
end was relied on for data gathering and multivariate regression for
future travel demand prediction. 9859 pupils were surveyed by way
of questionnaires at 21 primary schools. The town was divided into 5
zones. The study was carried out in Skudai Town, Malaysia. Based
on the hypothesis that the number of primary school trip ends are
expected to be the same because school trips are fixed, the choice of
trip end would have inconsequential effect on the outcome. The
study compared empirical data for home and school trip end
productions and attractions. Variance from both data results was
insignificant, although some claims from home based family survey
were found to be grossly exaggerated. Data from the school trip ends
was relied on for travel demand prediction because of its
completeness. Accessibility, trip attraction and trip production were
then related to school trip rates under daylight and dry weather
conditions. The paper concluded that, accessibility is an important
parameter when predicting demand for future school trip rates.
Abstract: The effects of dynamic subgrid scale (SGS) models are
investigated in variational multiscale (VMS) LES simulations of bluff
body flows. The spatial discretization is based on a mixed finite
element/finite volume formulation on unstructured grids. In the VMS
approach used in this work, the separation between the largest and the
smallest resolved scales is obtained through a variational projection
operator and a finite volume cell agglomeration. The dynamic version
of Smagorinsky and WALE SGS models are used to account for
the effects of the unresolved scales. In the VMS approach, these
effects are only modeled in the smallest resolved scales. The dynamic
VMS-LES approach is applied to the simulation of the flow around a
circular cylinder at Reynolds numbers 3900 and 20000 and to the flow
around a square cylinder at Reynolds numbers 22000 and 175000. It
is observed as in previous studies that the dynamic SGS procedure
has a smaller impact on the results within the VMS approach than in
LES. But improvements are demonstrated for important feature like
recirculating part of the flow. The global prediction is improved for
a small computational extra cost.
Abstract: The connection between solar activity and adverse phenomena in the Earth’s environment that can affect space and ground based technologies has spurred interest in Space Weather (SW) research. A great effort has been put on the development of suitable models that can provide advanced forecast of SW events. With the progress in computational technology, it is becoming possible to develop operational large scale physics based models which can incorporate the most important physical processes and domains of the Sun-Earth system. In order to enhance our SW prediction capabilities we are developing advanced numerical tools. With operational requirements in mind, our goal is to develop a modular simulation framework of propagation of the disturbances from the Sun through interplanetary space to the Earth. Here, we report and discuss on the development of coronal field and solar wind components for a large scale MHD code. The model for these components is based on a potential field source surface model and an empirical Wang-Sheeley-Arge solar wind relation.
Abstract: On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.
Abstract: In this paper, for the first time, a two-dimensional
(2D) analytical drain current model for sub-100 nm multi-layered
gate material engineered trapezoidal recessed channel (MLGMETRC)
MOSFET: a novel design is presented and investigated using
ATLAS and DEVEDIT device simulators, to mitigate the large gate
leakages and increased standby power consumption that arise due to
continued scaling of SiO2-based gate dielectrics. The twodimensional
(2D) analytical model based on solution of Poisson-s
equation in cylindrical coordinates, utilizing the cylindrical
approximation, has been developed which evaluate the surface
potential, electric field, drain current, switching metric: ION/IOFF
ratio and transconductance for the proposed design. A good
agreement between the model predictions and device simulation
results is obtained, verifying the accuracy of the proposed analytical
model.
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: One of the most important parts of a cement factory is
the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral
movement of air and materials, together with chemical reactions take
place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only
in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was
presented instead. This issue caused many problems for designing a
cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using
nonlinear identification technique on the Locally Linear Neuro-
Fuzzy (LLNF) model. For the first time, a simulator model as well as
a predictor one with a precise fifteen minute prediction horizon for a
cement rotary kiln is presented. These models are trained by
LOLIMOT algorithm which is an incremental tree-structure
algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these
models. The data collected from White Saveh Cement Company is used for modeling.
Abstract: A transient heat transfer mathematical model for the
prediction of temperature distribution in the car body during primer
baking has been developed by considering the thermal radiation and
convection in the furnace chamber and transient heat conduction
governing equations in the car framework. The car cockpit is
considered like a structure with six flat plates, four vertical plates
representing the car doors and the rear and front panels. The other
two flat plates are the car roof and floor. The transient heat
conduction in each flat plate is modeled by the lumped capacitance
method. Comparison with the experimental data shows that the heat
transfer model works well for the prediction of thermal behavior of
the car body in the curing furnace, with deviations below 5%.
Abstract: Loop detectors report traffic characteristics in real
time. They are at the core of traffic control process. Intuitively,
one would expect that as density of detection increases, so would
the quality of estimates derived from detector data. However, as
detector deployment increases, the associated operating and
maintenance cost increases. Thus, traffic agencies often need to
decide where to add new detectors and which detectors should
continue receiving maintenance, given their resource constraints.
This paper evaluates the effect of detector spacing on freeway
travel time estimation. A freeway section (Interstate-15) in Salt
Lake City metropolitan region is examined. The research reveals
that travel time accuracy does not necessarily deteriorate with
increased detector spacing. Rather, the actual location of detectors
has far greater influence on the quality of travel time estimates.
The study presents an innovative computational approach that
delivers optimal detector locations through a process that relies on
Genetic Algorithm formulation.