Abstract: In recent years asymmetric cross section aluminum
alloy stock has been finding increasing use in various industrial manufacturing areas such as general structures and automotive
components. In these areas, components are generally required to have
complex curved configuration and, as such, a bending process is required during manufacture. Undesirable deformation in bending
processes such as flattening or wrinkling can easily occur when thin-walled sections are bent. Hence, a thorough understanding of the
bending behavior of such sections is needed to prevent these undesirable deformations. In this study, the bending behavior of
asymmetric channel section was examined using finite element analysis (FEA). Typical methods of preventing undesirable
deformation, such as asymmetric laminated elastic mandrels were included in FEA model of draw bending. Additionally, axial tension
was applied to prevent wrinkling. By utilizing the FE simulations effect of restriction dies and axial tension on undesirable deformation during the process was clarified.
Abstract: Computing and maintaining network structures for efficient
data aggregation incurs high overhead for dynamic events
where the set of nodes sensing an event changes with time. Moreover,
structured approaches are sensitive to the waiting time that is used
by nodes to wait for packets from their children before forwarding
the packet to the sink. An optimal routing and data aggregation
scheme for wireless sensor networks is proposed in this paper. We
propose Tree on DAG (ToD), a semistructured approach that uses
Dynamic Forwarding on an implicitly constructed structure composed
of multiple shortest path trees to support network scalability. The key
principle behind ToD is that adjacent nodes in a graph will have
low stretch in one of these trees in ToD, thus resulting in early
aggregation of packets. Based on simulations on a 2,000-node Mica2-
based network, we conclude that efficient aggregation in large-scale
networks can be achieved by our semistructured approach.
Abstract: This paper proposes, implements and evaluates an original discretization method for continuous random variables, in order to estimate the reliability of systems for which stress and strength are defined as complex functions, and whose reliability is not derivable through analytic techniques. This method is compared to other two discretizing approaches appeared in literature, also through a comparative study involving four engineering applications. The results show that the proposal is very efficient in terms of closeness of the estimates to the true (simulated) reliability. In the study we analyzed both a normal and a non-normal distribution for the random variables: this method is theoretically suitable for each parametric family.
Abstract: In literatures, many researches proposed various
methods to reduce PAPR (Peak to Average Power Ratio). Among
those, DSI (Dummy Sequence Insertion) is one of the most attractive
methods for WiMAX systems because it does not require side
information transmitted along with user data. However, the
conventional DSI methods find dummy sequence by performing an
iterative procedure until achieving PAPR under a desired threshold.
This causes a significant delay on finding dummy sequence and also
effects to the overall performances in WiMAX systems. In this paper,
the new method based on DSI is proposed by finding dummy
sequence without the need of iterative procedure. The fast DSI
method can reduce PAPR without either delays or required side
information. The simulation results confirm that the proposed method
is able to carry out PAPR performances as similar to the other
methods without any delays. In addition, the simulations of WiMAX
system with adaptive modulations are also investigated to realize the
use of proposed methods on various fading schemes. The results
suggest the WiMAX designers to modify a new Signal to Noise Ratio
(SNR) criteria for adaptation.
Abstract: In this paper, a generalized synchronization scheme, which is called function synchronization, for chaotic systems is studied. Based on Lyapunov method and active control method, we design the synchronization controller for the system such that the error dynamics between master and slave chaotic systems is asymptotically stable. For verification of our theory, computer and circuit simulations for a specific chaotic system is conducted.
Abstract: A new robust nonlinear control scheme of a manipulator is proposed in this paper which is robust against modeling errors and unknown disturbances. It is based on the principle of variable structure control, with sliding mode control (SMC) method. The variable structure control method is a robust method that appears to be well suited for robotic manipulators because it requers only bounds on the robotic arm parameters. But there is no single systematic procedure that is guaranteed to produce a suitable control law. Also, to reduce chattring of the control signal, we replaced the sgn function in the control law by a continuous approximation such as tangant function. We can compute the maximum load with regard to applied torque into joints. The effectivness of the proposed approach has been evaluated analitically demonstrated through computer simulations for the cases of variable load and robot arm parameters.
Abstract: In this paper multivariable predictive PID controller has
been implemented on a multi-inputs multi-outputs control problem
i.e., quadruple tank system, in comparison with a simple multiloop
PI controller. One of the salient feature of this system is an
adjustable transmission zero which can be adjust to operate in both
minimum and non-minimum phase configuration, through the flow
distribution to upper and lower tanks in quadruple tank system.
Stability and performance analysis has also been carried out for this
highly interactive two input two output system, both in minimum
and non-minimum phases. Simulations of control system revealed
that better performance are obtained in predictive PID design.
Abstract: This paper employs a new approach to regulate the
blood glucose level of type I diabetic patient under an intensive
insulin treatment. The closed-loop control scheme incorporates
expert knowledge about treatment by using reinforcement learning
theory to maintain the normoglycemic average of 80 mg/dl and the
normal condition for free plasma insulin concentration in severe
initial state. The insulin delivery rate is obtained off-line by using Qlearning
algorithm, without requiring an explicit model of the
environment dynamics. The implementation of the insulin delivery
rate, therefore, requires simple function evaluation and minimal
online computations. Controller performance is assessed in terms of
its ability to reject the effect of meal disturbance and to overcome the
variability in the glucose-insulin dynamics from patient to patient.
Computer simulations are used to evaluate the effectiveness of the
proposed technique and to show its superiority in controlling
hyperglycemia over other existing algorithms
Abstract: Numerical simulations are performed for laminar
continuous and pulsed jets impinging on a surface in order to
investigate the effects of pulsing frequency on the heat transfer
characteristics. The time-averaged Nusselt number of pulsed jets is
larger in the impinging jet region as compared to the continuous jet,
while it is smaller in the outer wall jet region. At the stagnation point,
the mean and RMS Nusselt numbers become larger and smaller,
respectively, as the pulsing frequency increases. Unsteady behaviors
of vortical fluid motions and temperature field are also investigated to
understand the underlying mechanisms of heat transfer enhancement.
Abstract: This paper presents the impact study of GTO Controlled Series Capacitor (GCSC) parameters on measured impedance (Zseen) by MHO distance relays for single transmission line high voltage 220 kV in the presence of single phase to earth fault with fault resistance (RF). The study deals with a 220 kV single electrical transmission line of Eastern Algerian transmission networks at Group Sonelgaz (Algerian Company of Electrical and Gas) compensated by series Flexible AC Transmission System (FACTS) i.e. GCSC connected at midpoint of the transmission line. The transmitted active and reactive powers are controlled by three GCSC-s. The effects of maximum reactive power injected as well as injected maximum voltage by GCSC on distance relays measured impedance is treated. The simulations results investigate the effects of GCSC injected parameters: variable reactance (XGCSC), variable voltage (VGCSC) and reactive power injected (QGCSC) on measured resistance and reactance in the presence of earth fault with resistance fault varied between 5 to 50 Ω for three cases study.
Abstract: Today with the rapid growth of telecommunications equipment, electronic and developing more and more networks of power, influence of electromagnetic waves on one another has become hot topic discussions. So in this article, this issue and appropriate mechanisms for EMC operations have been presented. First, impact of high voltage lines on the surrounding environment especially on the control room has been investigated, then to reduce electromagnetic radiation, various methods of shielding are provided and shielding effectiveness of them has been compared. It should be expressed that simulations have been done by the finite element method (FEM).
Abstract: Using neural network we try to model the unknown function f for given input-output data pairs. The connection strength of each neuron is updated through learning. Repeated simulations of crisp neural network produce different values of weight factors that are directly affected by the change of different parameters. We propose the idea that for each neuron in the network, we can obtain quasi-fuzzy weight sets (QFWS) using repeated simulation of the crisp neural network. Such type of fuzzy weight functions may be applied where we have multivariate crisp input that needs to be adjusted after iterative learning, like claim amount distribution analysis. As real data is subjected to noise and uncertainty, therefore, QFWS may be helpful in the simplification of such complex problems. Secondly, these QFWS provide good initial solution for training of fuzzy neural networks with reduced computational complexity.
Abstract: In this paper back-propagation artificial neural
network (BPANN) with Levenberg–Marquardt algorithm is
employed to predict the limiting drawing ratio (LDR) of the deep
drawing process. To prepare a training set for BPANN, some finite
element simulations were carried out. die and punch radius, die arc
radius, friction coefficient, thickness, yield strength of sheet and
strain hardening exponent were used as the input data and the LDR
as the specified output used in the training of neural network. As a
result of the specified parameters, the program will be able to
estimate the LDR for any new given condition. Comparing FEM and
BPANN results, an acceptable correlation was found.
Abstract: Detection and tracking of the lip contour is an important
issue in speechreading. While there are solutions for lip tracking
once a good contour initialization in the first frame is available,
the problem of finding such a good initialization is not yet solved
automatically, but done manually. We have developed a new tracking
solution for lip contour detection using only few landmarks (15
to 25) and applying the well known Active Shape Models (ASM).
The proposed method is a new LMS-like adaptive scheme based on
an Auto regressive (AR) model that has been fit on the landmark
variations in successive video frames. Moreover, we propose an extra
motion compensation model to address more general cases in lip
tracking. Computer simulations demonstrate a fair match between
the true and the estimated spatial pixels. Significant improvements
related to the well known LMS approach has been obtained via a
defined Frobenius norm index.
Abstract: Generally speaking, the mobile robot is capable of
sensing its surrounding environment, interpreting the sensed
information to obtain the knowledge of its location and the
environment, planning a real-time trajectory to reach the object. In
this process, the issue of obstacle avoidance is a fundamental topic to
be challenged. Thus, an adaptive path-planning control scheme is
designed without detailed environmental information, large memory
size and heavy computation burden in this study for the obstacle
avoidance of a mobile robot. In this scheme, the robot can gradually
approach its object according to the motion tracking mode, obstacle
avoidance mode, self-rotation mode, and robot state selection. The
effectiveness of the proposed adaptive path-planning control scheme
is verified by numerical simulations of a differential-driving mobile
robot under the possible occurrence of obstacle shapes.
Abstract: This study deals with Computational Fluid Dynamics
(CFD) studies of the interactions between the air flow and louvered
fins which equipped the automotive heat exchangers. 3D numerical
simulation results are obtained by using the ANSYS Fluent 13.0 code
and compared to experimental data. The paper studies the effect of
louver angle and louver pitch geometrical parameters, on overall
thermal hydraulic performances of louvered fins.
The comparison between CFD simulations and experimental data
show that established 3-D CFD model gives a good agreement. The
validation agrees, with about 7% of deviation respectively of friction
and Colburn factors to experimental results. As first, it is found that
the louver angle has a strong influence on the heat transfer rate. Then,
louver angle and louver pitch variation of the louvers and their effects
on thermal hydraulic performances are studied. In addition to this
study, it is shown that the second half of the fin takes has a
significant contribution on pressure drop increase without any
increase in heat transfer.
Abstract: A 3D industrial computed tomography (CT)
manufactured based on a first generation CT systems, single-source
– single-detector, was evaluated. Operation accuracy assessment of
the manufactured system was achieved using simulation in
comparison with experimental tests. 137Cs and 60Co were used as a gamma source. Simulations were achieved using MCNP4C code.
Experimental tests of 137Cs were in good agreement with the simulations
Abstract: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: This paper considers the problem of Null-Steering beamforming using Neural Network (NN) approach for antenna array system. Two cases are presented. First, unlike the other authors, the estimated Direction Of Arrivals (DOAs) are used for antenna array weights NN-based determination and the imprecise DOAs estimations are taken into account. Second, the blind null-steering beamforming is presented. In this case the antenna array outputs are presented at the input of the NN without DOAs estimation. The results of computer simulations will show much better relative mean error performances of the first NN approach compared to the NNbased blind beamforming.
Abstract: Serious games have proven to be a useful instrument
to engage learners and increase motivation. Nevertheless, a broadly
accepted, practical instructional design approach to serious games
does not exist. In this paper, we introduce the use of an instructional
design model that has not been applied to serious games yet, and has
some advantages compared to other design approaches. We present
the case of mechanics mechatronics education to illustrate the close
match with timing and role of knowledge and information that the
instructional design model prescribes and how this has been
translated to a rigidly structured game design. The structured
approach answers the learning needs of applicable knowledge within
the target group. It combines advantages of simulations with
strengths of entertainment games to foster learner-s motivation in the
best possible way. A prototype of the game will be evaluated along a
well-respected evaluation method within an advanced test setting
including test and control group.