Abstract: The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations.
As a results of this, Computational Fluid Dynamic (CFD) solvers are
widely used in the aeronautical field. These solvers require the correct
selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on
the proper choice of these parameters.
In this paper we create an expert system capable of making an
accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver.
Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time
required for the convergence of a CFD solver.
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 presents the Function Approximation
Technique (FAT) based adaptive impedance control for a robotic
finger. The force based impedance control is developed so that the
robotic finger tracks the desired force while following the reference
position trajectory, under unknown environment position and
uncertainties in finger parameters. The control strategy is divided into
two phases, which are the free and contact phases. Force error
feedback is utilized in updating the uncertain environment position
during contact phase. Computer simulations results are presented to
demonstrate the effectiveness of the proposed technique.
Abstract: In this paper we proposed multistage adaptive
ARQ/HARQ/HARQ scheme. This method combines pure ARQ
(Automatic Repeat reQuest) mode in low channel bit error rate and
hybrid ARQ method using two different Reed-Solomon codes in
middle and high error rate conditions. It follows, that our scheme has
three stages. The main goal is to increase number of states in adaptive
HARQ methods and be able to achieve maximum throughput for
every channel bit error rate. We will prove the proposal by
calculation and then with simulations in land mobile satellite channel
environment. Optimization of scheme system parameters is described
in order to maximize the throughput in the whole defined Signal-to-
Noise Ratio (SNR) range in selected channel environment.
Abstract: This paper presents the averaging model of a buck
converter derived from the generalized state-space averaging method.
The sliding mode control is used to regulate the output voltage of the
converter and taken into account in the model. The proposed model
requires the fast computational time compared with those of the full
topology model. The intensive time-domain simulations via the exact
topology model are used as the comparable model. The results show
that a good agreement between the proposed model and the switching
model is achieved in both transient and steady-state responses. The
reported model is suitable for the optimal controller design by using
the artificial intelligence techniques.
Abstract: As a part of the development of a numerical method of
close capture exhausts systems for machining devices, a test rig
recreating a situation similar to a grinding operation, but in a
perfectly controlled environment, is used. The properties of the
obtained spray of solid particles are initially characterized using
particle tracking velocimetry (PTV), in order to obtain input and
validation parameters for numerical simulations. The dispersion of a
tracer gas (SF6) emitted simultaneously with the particle jet is then
studied experimentally, as the dispersion of such a gas is
representative of that of finer particles, whose aerodynamic response
time is negligible. Finally, complete modeling of the test rig is
achieved to allow comparison with experimental results and thus to
progress towards validation of the models used to describe a twophase
flow generated by machining operation.
Abstract: In this study, a 3D combustion chamber was simulated
using FLUENT 6.32. Aims to obtain accurate information about the
profile of the combustion in the furnace and also check the effect of
oxygen enrichment on the combustion process. Oxygen enrichment is
an effective way to reduce combustion pollutant. The flow rate of air
to fuel ratio is varied as 1.3, 3.2 and 5.1 and the oxygen enriched
flow rates are 28, 54 and 68 lit/min. Combustion simulations
typically involve the solution of the turbulent flows with heat
transfer, species transport and chemical reactions. It is common to
use the Reynolds-averaged form of the governing equation in
conjunction with a suitable turbulence model. The 3D Reynolds
Averaged Navier Stokes (RANS) equations with standard k-ε
turbulence model are solved together by Fluent 6.3 software. First
order upwind scheme is used to model governing equations and the
SIMPLE algorithm is used as pressure velocity coupling. Species
mass fractions at the wall are assumed to have zero normal
gradients.Results show that minimum mole fraction of CO2 happens
when the flow rate ratio of air to fuel is 5.1. Additionally, in a fixed
oxygen enrichment condition, increasing the air to fuel ratio will
increase the temperature peak. As a result, oxygen-enrichment can
reduce the CO2 emission at this kind of furnace in high air to fuel
rates.
Abstract: This paper presents a model for the evaluation of
energy performance and aerodynamic forces acting on a small
straight-bladed Darrieus-type vertical axis wind turbine depending on
blade geometrical section. It consists of an analytical code coupled to
a solid modeling software, capable of generating the desired blade
geometry based on the desired blade design geometric parameters.
Such module is then linked to a finite volume commercial CFD code
for the calculation of rotor performance by integration of the
aerodynamic forces along the perimeter of each blade for a full period
of revolution.After describing and validating the computational
model with experimental data, the results of numerical simulations
are proposed on the bases of two candidate airfoil sections, that is a
classical symmetrical NACA 0021 blade profile and the recently
developed DU 06-W-200 non-symmetric and laminar blade
profile.Through a full CFD campaign of analysis, the effects of blade
geometrical section on angle of attack are first investigated and then
the overall rotor torque and power are analyzed as a function of blade
azimuthal position, achieving a numerical quantification of the
influence of airfoil geometry on overall rotor performance.
Abstract: Every 2-3 years the influenza B virus serves
epidemics. Neuraminidase (NA) is an important target for influenza
drug design. Although, oseltamivir, an oral neuraminidase drug, has
been shown good inhibitory efficiency against wild-type of influenza
B virus, the lower susceptibility to the R152K mutation has been
reported. Better understanding of oseltamivir efficiency and
resistance toward the influenza B NA wild-type and R152K mutant,
respectively, could be useful for rational drug design. Here, two
complex systems of wild-type and R152K NAs with oseltamivir
bound were studied using molecular dynamics (MD) simulations.
Based on 5-ns MD simulation, the loss of notable hydrogen bond and
decrease in per-residue decomposition energy from the mutated
residue K152 contributed to drug compared to those of R152 in wildtype
were found to be a primary source of high-level of oseltamivir
resistance due to the R152K mutation.
Abstract: This work aims to test the application of computational fluid dynamics (CFD) modeling to fixed bed catalytic cracking reactors. Studies of CFD with a fixed bed design commonly use a regular packing with N=2 to define bed geometry. CFD allows us to obtain a more accurate view of the fluid flow and heat transfer mechanisms present in fixed bed equipment. Naphtha was used as feedstock and the reactor length was 80cm. It is divided in three sections that catalyst bed packed in the middle section of the reactor. The reaction scheme was involved one primary reaction and 24 secondary reactions. Because of high CPU times in these simulations, parallel processing have been used. In this study the coke formation process in fixed bed and empty tube reactor was simulated and coke in these reactors are compared. In addition, the effect of steam ratio and feed flow rate on coke formation was investigated.
Abstract: In this paper, a post processing scheme is suggested
for improvement of Bit Error-Rate (BER) in optical fiber
transmission receivers. The developed scheme has been tested on
optical fiber systems operating with a non-return-to-zero (NRZ)
format at transmission rates of up to 10Gbps. The transmission
system considered is based on well known transmitters and receivers
blocks operating at wavelengths in the region of 1550 nm using a
standard single mode fiber. Performance of improved detected
signals has been evaluated via the analysis of quality factor and
computed bit error rates. Numerical simulations have shown a
noticeable improvement of the system BER after implementation of
the suggested post processing operation on the detected electrical
signals.
Abstract: Increasing demand on the performance of Subsea
Production Systems (SPS) suggests a need for more detailed
investigation of fluid behavior taking place in subsea equipment.
Complete CFD cool down analyses of subsea equipment are very
time demanding. The objective of this paper is to investigate a
Locked CFD approach, which enables significant reduction of the
computational time and at the same time maintains sufficient
accuracy during thermal cool down simulations. The result
comparison of a dead leg simulation using the Full CFD and the three
LCFD-methods confirms the validity of the locked flow field
assumption for the selected case. For the tested case the LCFD
simulation speed up by factor of 200 results in the absolute thermal
error of 0.5 °C (3% relative error), speed up by factor of 10 keeps the
LCFD results within 0.1 °C (0.5 % relative error) comparing to the
Full CFD.
Abstract: In the closed quantum system, if the control system is
strongly regular and all other eigenstates are directly coupled to the
target state, the control system can be asymptotically stabilized at the
target eigenstate by the Lyapunov control based on the state error.
However, if the control system is not strongly regular or as long as
there is one eigenstate not directly coupled to the target state, the
situations will become complicated. In this paper, we propose an
implicit Lyapunov control method based on the state error to solve the
convergence problems for these two degenerate cases. And at the same
time, we expand the target state from the eigenstate to the arbitrary
pure state. Especially, the proposed method is also applicable in the
control system with multi-control Hamiltonians. On this basis, the
convergence of the control systems is analyzed using the LaSalle
invariance principle. Furthermore, the relation between the implicit
Lyapunov functions of the state distance and the state error is
investigated. Finally, numerical simulations are carried out to verify
the effectiveness of the proposed implicit Lyapunov control method.
The comparisons of the control effect using the implicit Lyapunov
control method based on the state distance with that of the state error
are given.
Abstract: The recent development of Information and Communication Technology (ICT) enables new ways of "democratic" decision-making such as a page-ranking system, which estimates the importance of a web page based on indirect trust on that page shared by diverse group of unorganized individuals. These kinds of "democracy" have not been acclaimed yet in the world of real politics. On the other hand, a large amount of data about personal relations including trust, norms of reciprocity, and networks of civic engagement has been accumulated in a computer-readable form by computer systems (e.g., social networking systems). We can use these relations as a new type of social capital to construct a new democratic decision-making system based on a delegation network. In this paper, we propose an effective decision-making support system, which is based on empowering someone's vote whom you trust. For this purpose, we propose two new techniques: the first is for estimating entire vote distribution from a small number of votes, and the second is for estimating active voter choice to promote voting using a delegation network. We show that these techniques could increase the voting ratio and credibility of the whole decision by agent-based simulations.
Abstract: This paper deals with the synthesis of fuzzy controller
applied to a permanent magnet synchronous machine (PMSM) with a
guaranteed H∞ performance. To design this fuzzy controller,
nonlinear model of the PMSM is approximated by Takagi-Sugeno
fuzzy model (T-S fuzzy model), then the so-called parallel
distributed compensation (PDC) is employed. Next, we derive the
property of the H∞ norm. The latter is cast in terms of linear matrix
inequalities (LMI-s) while minimizing the H∞ norm of the transfer
function between the disturbance and the error ( ) ev T . The
experimental and simulations results were conducted on a permanent
magnet synchronous machine to illustrate the effects of the fuzzy
modelling and the controller design via the PDC.
Abstract: This study assesses the vulnerability of Bulgarian
agriculture to drought using the WINISAREG model and seasonal
standard precipitation index SPI(2) for the period 1951-2004. This
model was previously validated for maize on soils of different water
holding capacity (TAW) in various locations. Simulations are
performed for Plovdiv, Stara Zagora and Sofia. Results relative to
Plovdiv show that in soils of large TAW (180 mm m-1) net irrigation
requirements (NIRs) range 0-40 mm in wet years and 350-380 mm in
dry years. In soils of small TAW (116 mm m-1), NIRs reach 440 mm
in the very dry year. NIRs in Sofia are about 80 mm smaller. Rainfed
maize is associated with great yield variability (29%
Abstract: This article is based on the technique which is called
Discrete Parameter Tracking (DPT). First introduced by A. A. Azab
[8] which is applicable for less order reference model. The order of
the reference model is (n-l) and n is the number of the adjustable
parameters in the physical plant.
The technique utilizes a modified gradient method [9] where the
knowledge of the exact order of the nonadaptive system is not
required, so, as to eliminate the identification problem. The
applicability of the mentioned technique (DPT) was examined
through the solution of several problems.
This article introduces the solution of a third order system with
three adjustable parameters, controlled according to second order
reference model. The adjustable parameters have great initial error
which represent condition.
Computer simulations for the solution and analysis are provided
to demonstrate the simplicity and feasibility of the technique.
Abstract: The most widely used semiconductor memory types
are the Dynamic Random Access Memory (DRAM) and Static
Random Access memory (SRAM). Competition among memory
manufacturers drives the need to decrease power consumption and
reduce the probability of read failure. A technology that is relatively
new and has not been explored is the FinFET technology. In this
paper, a single cell Schmitt Trigger Based Static RAM using FinFET
technology is proposed and analyzed. The accuracy of the result is
validated by means of HSPICE simulations with 32nm FinFET
technology and the results are then compared with 6T SRAM using
the same technology.
Abstract: A straightforward and intuitive combination of single simulations into an aggregated master-simulation is not trivial. There are lots of problems, which trigger-specific difficulties during the modeling and execution of such a simulation. In this paper we identify these problems and aim to solve them by mapping the task to the field of multi agent systems. The solution is a new meta-model named AGENTMAP, which is able to mitigate most of the problems and to support intuitive modeling at the same time. This meta-model will be introduced and explained on basis of an example from the e-commerce domain.
Abstract: Collateralized Debt Obligations are not as widely used
nowadays as they were before 2007 Subprime crisis. Nonetheless
there remains an enthralling challenge to optimize cash flows
associated with synthetic CDOs. A Gaussian-based model is used
here in which default correlation and unconditional probabilities of
default are highlighted. Then numerous simulations are performed
based on this model for different scenarios in order to evaluate the
associated cash flows given a specific number of defaults at different
periods of time. Cash flows are not solely calculated on a single
bought or sold tranche but rather on a combination of bought and
sold tranches. With some assumptions, the simplex algorithm gives
a way to find the maximum cash flow according to correlation of
defaults and maturities. The used Gaussian model is not realistic in
crisis situations. Besides present system does not handle buying or
selling a portion of a tranche but only the whole tranche. However the
work provides the investor with relevant elements on how to know
what and when to buy and sell.