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: Experimental investigation has been carried out
towards understanding the complex fluid dynamics involved in the
interaction of vortical structures with zero pressure gradient boundary
layer. A laminar boundary layer is produced on the flat plate placed
in the water flume and the synthetic jet actuator is deployed on top of
the plate at a definite distance from the leading edge. The synthetic
jet actuator has been designed in such a way that the to and fro
motion of the diaphragm is maneuvered at will by varying the
operating parameters to produce the typical streamwise vortical
structures namely hairpin and tilted vortices. PIV measurements are
made on the streamwise plane normal to the plate to evaluate their
interaction with the near wall fluid.
Abstract: The numerical simulation of the slip effect via
vicoelastic fluid for 4:1 contraction problem is investigated with
regard to kinematic behaviors of streamlines and stress tensor by
models of the Navier-Stokes and Oldroyd-B equations. Twodimensional
spatial reference system of incompressible creeping flow
with and without slip velocity is determined and the finite element
method of a semi-implicit Taylor-Galerkin pressure-correction is
applied to compute the problem of this Cartesian coordinate system
including the schemes of velocity gradient recovery method and the
streamline-Upwind / Petrov-Galerkin procedure. The slip effect at
channel wall is added to calculate after each time step in order to
intend the alteration of flow path. The result of stress values and the
vortices are reduced by the optimum slip coefficient of 0.1 with near
the outcome of analytical solution.
Abstract: Cardiovascular diseases, principally atherosclerosis, are responsible for 30% of world deaths. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis.It is increasingly recognized that the initiation and progression of disease and the occurrence of clinical events is a complex interplay between the local biomechanical environment and the local vascular biology. The aim of this study is to investigate the flow behavior through a stenosed artery. A physical experiment was performed using an artery model and blood analogue fluid. An axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. The flow field was measured using particle image velocimetry (PIV). Spherical particles with 20μm diameter were seeded in a water-glycerol-NaCl mixture. Steady flow Reynolds numbers are 250. The area of interest is the region after the stenosis where the flow separation occurs. The velocity field was measured and the velocity gradient was investigated. There was high particle concentration in the recirculation zone. High velocity gradient formed immediately after the stenosis throat created a lift force that enhanced particle migration to the flow separation area.
Abstract: A rigorous two-dimensional model is developed for simulating the operation of a less-investigated type steam reformer having a considerably lower operating Reynolds number, higher tube diameter, and non-availability of extra steam in the feed compared with conventional steam reformers. Simulation results show that reasonable predictions can only be achieved when certain correlations for wall to fluid heat transfer equations are applied. Due to severe operating conditions, in all cases, strong radial temperature gradients inside the reformer tubes have been found. Furthermore, the results show how a certain catalyst loading profile will affect the operation of the reformer.
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 process for predicting the ballistic properties of a liquid rocket engine is based on the quantitative estimation of idealized performance deviations. In this aim, an equilibrium chemistry procedure is firstly developed and implemented in a Fortran routine. The thermodynamic formulation allows for the calculation of the theoretical performances of a rocket thrust chamber. In a second step, a computational fluid dynamic analysis of the turbulent reactive flow within the chamber is performed using a finite volume approach. The obtained values for the “quasi-real" performances account for both turbulent mixing and chemistryturbulence coupling. In the present work, emphasis is made on the combustion efficiency performance for which deviation is mainly due to radial gradients of static temperature and mixture ratio. Numerical values of the characteristic velocity are successfully compared with results from an industry-used code. The results are also confronted with the experimental data of a laboratory-scale rocket engine.
Abstract: The turbulent mixing of coolant streams of different
temperature and density can cause severe temperature fluctuations in
piping systems in nuclear reactors. In certain periodic contraction
cycles these conditions lead to thermal fatigue. The resulting aging
effect prompts investigation in how the mixing of flows over a sharp
temperature/density interface evolves. To study the fundamental
turbulent mixing phenomena in the presence of density gradients,
isokinetic (shear-free) mixing experiments are performed in a square
channel with Reynolds numbers ranging from 2-500 to 60-000.
Sucrose is used to create the density difference. A Wire Mesh Sensor
(WMS) is used to determine the concentration map of the flow in the
cross section. The mean interface width as a function of velocity,
density difference and distance from the mixing point are analyzed
based on traditional methods chosen for the purposes of
atmospheric/oceanic stratification analyses. A definition of the
mixing layer thickness more appropriate to thermal fatigue and based
on mixedness is devised. This definition shows that the thermal
fatigue risk assessed using simple mixing layer growth can be
misleading and why an approach that separates the effects of large
scale (turbulent) and small scale (molecular) mixing is necessary.
Abstract: Rockfall is a kind of irregular geological disaster. Its
destruction time, space and movements are highly random. The impact
force is determined by the way and velocity rocks move. The
movement velocity of a rockfall depends on slope gradient of its
moving paths, height, slope surface roughness and rock shapes. For
effectively mitigate and prevent disasters brought by rockfalls, it is
required to precisely calculate the moving paths of a rockfall so as to
provide the best protective design. This paper applies Colorado
Rockfall Simulation Program (CRSP) as our study tool to discuss the
impact of slope shape and surface roughness on the moving paths of a
single rockfall. The analytical results showed that the slope, m=1:1,
acted as the threshold for rockfall bounce height on a monoclinal slight
slope. When JRC ´╝£ 1.2, movement velocity reduced and bounce
height increased as JCR increased. If slope fixed and JRC increased,
the bounce height of rocks increased gradually with reducing
movement velocity. Therefore, the analysis on the moving paths of
rockfalls with CRSP could simulate bouncing of falling rocks. By
analyzing moving paths, velocity, and bounce height of falling rocks,
we could effectively locate impact points of falling rocks on a slope.
Such analysis can be served as a reference for future disaster
prevention and control.
Abstract: In this paper are illustrated the principal aspects
connected with the numerical evaluation of thermal stress induced by high gradient temperature in the concrete beam. The reinforced concrete beam has many advantages over steel
beam, such as high resistance to high temperature, high resistance to thermal shock, Better resistance to fatigue and buckling, strong
resistance against, fire, explosion, etc.
The main drawback of the reinforced concrete beam is its poor resistance to tensile stresses. In order to investigate the thermal
induced tensile stresses, a numerical model of a transient thermal
analysis is presented for the evaluation of thermo-mechanical
response of concrete beam to the high temperature, taking into account the temperature dependence of the thermo physical properties of the concrete like thermal conductivity and specific heat.
Abstract: The Linear discriminant analysis (LDA) can be
generalized into a nonlinear form - kernel LDA (KLDA) expediently
by using the kernel functions. But KLDA is often referred to a general
eigenvalue problem in singular case. To avoid this complication, this
paper proposes an iterative algorithm for the two-class KLDA. The
proposed KLDA is used as a nonlinear discriminant classifier, and the
experiments show that it has a comparable performance with SVM.
Abstract: This paper focuses on a technique for identifying the geological boundary of the ground strata in front of a tunnel excavation site using the first order adjoint method based on the optimal control theory. The geological boundary is defined as the boundary which is different layers of elastic modulus. At tunnel excavations, it is important to presume the ground situation ahead of the cutting face beforehand. Excavating into weak strata or fault fracture zones may cause extension of the construction work and human suffering. A theory for determining the geological boundary of the ground in a numerical manner is investigated, employing excavating blasts and its vibration waves as the observation references. According to the optimal control theory, the performance function described by the square sum of the residuals between computed and observed velocities is minimized. The boundary layer is determined by minimizing the performance function. The elastic analysis governed by the Navier equation is carried out, assuming the ground as an elastic body with linear viscous damping. To identify the boundary, the gradient of the performance function with respect to the geological boundary can be calculated using the adjoint equation. The weighed gradient method is effectively applied to the minimization algorithm. To solve the governing and adjoint equations, the Galerkin finite element method and the average acceleration method are employed for the spatial and temporal discretizations, respectively. Based on the method presented in this paper, the different boundary of three strata can be identified. For the numerical studies, the Suemune tunnel excavation site is employed. At first, the blasting force is identified in order to perform the accuracy improvement of analysis. We identify the geological boundary after the estimation of blasting force. With this identification procedure, the numerical analysis results which almost correspond with the observation data were provided.
Abstract: The aim of this work was to study the in vitro effects
of δ-lactam 1 and its 4-chlorophenyl derivative 2, on the proliferative
responses of human lymphocytes and Th1 and Th2 cytokine
secretion. The possible protective role of vitamin E on intracellular
stress oxidative induced by these compounds was also investigated.
Peripheral blood lymphocytes were isolated using differential
centrifugation on a density gradient of Histopaque. They were
cultured with mitogen concanavalin A, vitamin E (10 μM) and with
different concentrations of the compounds 1 and 2 (0.1 to 10 μM).
Proliferation (MTT assay), IL-2, INFγ and IL-4 (Elisa kits),
intracellular superoxide anion were determined. 1 and 2 were
immunostimulant and increased cytokine secretion with a shift away
from Th1 response to Th2. These properties were however
accompanied by an increase in intracellular oxidative stress. The
presence of vitamin E exhibited protective effects by reducing δ-
lactam-induced superoxide anion generation in lymphocytes.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: An enhanced particle swarm optimization algorithm
(PSO) is presented in this work to solve the non-convex OPF
problem that has both discrete and continuous optimization variables.
The objective functions considered are the conventional quadratic
function and the augmented quadratic function. The latter model
presents non-differentiable and non-convex regions that challenge
most gradient-based optimization algorithms. The optimization
variables to be optimized are the generator real power outputs and
voltage magnitudes, discrete transformer tap settings, and discrete
reactive power injections due to capacitor banks. The set of equality
constraints taken into account are the power flow equations while the
inequality ones are the limits of the real and reactive power of the
generators, voltage magnitude at each bus, transformer tap settings,
and capacitor banks reactive power injections. The proposed
algorithm combines PSO with Newton-Raphson algorithm to
minimize the fuel cost function. The IEEE 30-bus system with six
generating units is used to test the proposed algorithm. Several cases
were investigated to test and validate the consistency of detecting
optimal or near optimal solution for each objective. Results are
compared to solutions obtained using sequential quadratic
programming and Genetic Algorithms.
Abstract: Segmentation techniques based on Active Contour
Models have been strongly benefited from the use of prior information
during their evolution. Shape prior information is captured from
a training set and is introduced in the optimization procedure to
restrict the evolution into allowable shapes. In this way, the evolution
converges onto regions even with weak boundaries. Although
significant effort has been devoted on different ways of capturing
and analyzing prior information, very little thought has been devoted
on the way of combining image information with prior information.
This paper focuses on a more natural way of incorporating the
prior information in the level set framework. For proof of concept
the method is applied on hippocampus segmentation in T1-MR
images. Hippocampus segmentation is a very challenging task, due
to the multivariate surrounding region and the missing boundary
with the neighboring amygdala, whose intensities are identical. The
proposed method, mimics the human segmentation way and thus
shows enhancements in the segmentation accuracy.
Abstract: this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.
Abstract: A numerical study on the heat transfer in the thermal
barrier coatings and the substrates of a parallel-plate enclosure is
carried out. Some of the thermal barrier coatings, such as ceramics, are
semitransparent and are of interest for high-temperature applications
where radiation effects are significant. The radiative transfer equations
and the energy equations are solved by using the discrete ordinates
method and the finite difference method. Illustrative results are
presented for temperature distributions in the coatings and the opaque
walls under various heating conditions. The results show that the
temperature distribution is more uniform in the interior portion of each
coating away from its boundary for the case with a larger average of
varying refractive index and a positive gradient of refractive index
enhances radiative transfer to the substrates.
Abstract: Equilibrium and stability equations of a thin rectangular plate with length a, width b, and thickness h(x)=C1x+C2, made of functionally graded materials under thermal loads are derived based on the first order shear deformation theory. It is assumed that the material properties vary as a power form of thickness coordinate variable z. The derived equilibrium and buckling equations are then solved analytically for a plate with simply supported boundary conditions. One type of thermal loading, uniform temperature rise and gradient through the thickness are considered, and the buckling temperatures are derived. The influences of the plate aspect ratio, the relative thickness, the gradient index and the transverse shear on buckling temperature difference are all discussed.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.