Abstract: There was a high rate of corrosion in Pyrolysis
Gasoline Hydrogenation (PGH) unit of Arak Petrochemical Company
(ARPC), and it caused some operational problem in this plant. A
commercial chemical had been used as anti-corrosion in the
depentanizer column overhead in order to control the corrosion rate.
Injection of commercial corrosion inhibitor caused some
operational problems such as fouling in some heat exchangers. It was
proposed to replace this commercial material with another more
effective trouble free, and well-known additive by R&D and
operation specialists.
At first, the system was simulated by commercial simulation
software in electrolytic system to specify low pH points inside the
plant. After a very comprehensive study of the situation and technical
investigations ,ammonia / monoethanol amine solution was proposed
as neutralizer or corrosion inhibitor to be injected in a suitable point
of the plant. For this purpose, the depentanizer column and its
accessories system was simulated again in case of this solution
injection.
According to the simulation results, injection of new anticorrosion
substance has no any side effect on C5 cut product and
operating conditions of the column. The corrosion rate will be
cotrolled, if the pH remains at the range of 6.5 to 8 . Aactual plant
test run was also carried out by injection of ammonia / monoethanol
amine solution at the rate of 0.6 Kg/hr and the results of iron content
of water samples and corrosion test coupons confirmed the
simulation results.
Now, ammonia / monoethanol amine solution is injected to a
suitable pint inside the plant and corrosion rate has decreased
significantly.
Abstract: In this researcha particle swarm optimization (PSO)
algorithm is proposedfor no-wait flowshopsequence dependent
setuptime scheduling problem with weighted earliness-tardiness
penalties as the criterion (|,
|Σ
"
).The
smallestposition value (SPV) rule is applied to convert the continuous
value of position vector of particles in PSO to job permutations.A
timing algorithm is generated to find the optimal schedule and
calculate the objective function value of a given sequence in PSO
algorithm. Twodifferent neighborhood structures are applied to
improve the solution quality of PSO algorithm.The first one is based
on variable neighborhood search (VNS) and the second one is a
simple one with invariable structure. In order to compare the
performance of two neighborhood structures, random test problems
are generated and solved by both neighborhood
approaches.Computational results show that the VNS algorithmhas
better performance than the other one especially for the large sized
problems.
Abstract: Utilization of bagasse ash for silica sources is one of
the most common application for agricultural wastes and valuable
biomass byproducts in sugar milling. The high percentage silica
content from bagasse ash was used as silica source for sodium
silicate solution. Different heating temperature, time and acid
treatment were studies for silica extraction. The silica was
characterized using various techniques including X-ray fluorescence,
X-ray diffraction, Scanning electron microscopy, and Fourier
Transform Infrared Spectroscopy method,. The synthesis conditions
were optimized to obtain the bagasse ash with the maximum silica
content. The silica content of 91.57 percent was achieved from
heating of bagasse ash at 600°C for 3 hours under oxygen feeding
and HCl treatment. The result can be used as value added for bagasse
ash utilization and minimize the environmental impact of disposal
problems.
Abstract: The software system goes through a number of stages
during its life and a software process model gives a standard format
for planning, organizing and running a project. The article presents a
new software development process model named as “Divide and
Conquer Process Model", based on the idea first it divides the things
to make them simple and then gathered them to get the whole work
done. The article begins with the backgrounds of different software
process models and problems in these models. This is followed by a
new divide and conquer process model, explanation of its different
stages and at the end edge over other models is shown.
Abstract: The conventional production of biodiesel from crude
palm oil which contains large amounts of free fatty acids in the
presence of a homogeneous base catalyst confronts the problems of
soap formation and very low yield of biodiesel. To overcome these
problems, free fatty acids must be esterified to their esters in the
presence of an acid catalyst prior to alkaline-catalyzed
transesterification. Sulfated metal oxides are a promising group of
catalysts due to their very high acidity. In this research, aluminadoped
sulfated tin oxide (SO4
2-/Al2O3-SnO2) catalysts were prepared
and used for esterification of free fatty acids in crude palm oil in a
batch reactor. The SO4
2-/Al2O3-SnO2 catalysts were prepared from
different Al precursors. The results showed that different Al
precursors gave different activities of the SO4
2-/Al2O3-SnO2 catalysts.
The esterification of free fatty acids in crude palm oil with methanol
in the presence of SO4
2-/Al2O3-SnO2 catalysts followed first-order
kinetics.
Abstract: A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper.
Abstract: Environmental awareness and the recent
environmental policies have forced many electric utilities to
restructure their operational practices to account for their emission
impacts. One way to accomplish this is by reformulating the
traditional economic dispatch problem such that emission effects are
included in the mathematical model. This paper presents a Particle
Swarm Optimization (PSO) algorithm to solve the Economic-
Emission Dispatch problem (EED) which gained recent attention due
to the deregulation of the power industry and strict environmental
regulations. The problem is formulated as a multi-objective one with
two competing functions, namely economic cost and emission
functions, subject to different constraints. The inequality constraints
considered are the generating unit capacity limits while the equality
constraint is generation-demand balance. A novel equality constraint
handling mechanism is proposed in this paper. PSO algorithm is
tested on a 30-bus standard test system. Results obtained show that
PSO algorithm has a great potential in handling multi-objective
optimization problems and is capable of capturing Pareto optimal
solution set under different loading conditions.
Abstract: With deep development of software reuse, componentrelated
technologies have been widely applied in the development of
large-scale complex applications. Component identification (CI) is
one of the primary research problems in software reuse, by analyzing
domain business models to get a set of business components with high
reuse value and good reuse performance to support effective reuse.
Based on the concept and classification of CI, its technical stack is
briefly discussed from four views, i.e., form of input business models,
identification goals, identification strategies, and identification
process. Then various CI methods presented in literatures are
classified into four types, i.e., domain analysis based methods,
cohesion-coupling based clustering methods, CRUD matrix based
methods, and other methods, with the comparisons between these
methods for their advantages and disadvantages. Additionally, some
insufficiencies of study on CI are discussed, and the causes are
explained subsequently. Finally, it is concluded with some
significantly promising tendency about research on this problem.
Abstract: Imperfect transmission conditions modeling a thin reactive 2D interphases layer between two dissimilar bonded strips have been extracted. In this paper, the soundness of these transmission conditions for heat conduction problems are examined by the finite element method for a strong temperature-dependent source or sink and non-monotonic temperature distributions around the faces..
Abstract: Cell formation is the first step in the design of cellular
manufacturing systems. In this study, a general purpose
computational scheme employing a hybrid tabu search algorithm as
the core is proposed to solve the cell formation problem and its
variants. In the proposed scheme, great flexibilities are left to the
users. The core solution searching algorithm embedded in the scheme
can be easily changed to any other meta-heuristic algorithms, such as
the simulated annealing, genetic algorithm, etc., based on the
characteristics of the problems to be solved or the preferences the
users might have. In addition, several counters are designed to control
the timing of conducting intensified solution searching and diversified
solution searching strategies interactively.
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: The paper deals with cartographic visualisation of
results of transport accessibility monitoring with the use of a semiautomated
method of unipolar anamorphosis, developed by the
authors in the GIS environment. The method is based on
transformation of distance in the map to values of a geographical
phenomenon. In the case of time accessibility it is based on
transformation of isochrones converted into the form of concentric
circles, taking into account selected topographic and thematic
elements in the map. The method is most suitable for analyses of
accessibility to or from a centre and for modelling its long-term
context.
The paper provides a detailed analysis of the procedures and
functionality of the method, discussing the issues of coordinates,
transformation, scale and visualisation. It also offers a discussion of
possible problems and inaccuracies. A practical application of the
method is illustrated by previous research results by the authors in
the filed of accessibility in Czechia.
Abstract: The objectives of this research are to search the
management pattern of Nakhon Pathom lodging entrepreneurs for
sufficient economy ways, to know the threat that affects this sector
and design fit arrangement model to sustain their business with
Nakhon Pathom style. What will happen if they do not use this
approach? Will they have a financial crisis? The data and
information are collected by informal discussions with 12 managers
and 400 questionnaires. A mixed method of both qualitative research
and quantitative research are used. Bent Flyvbjerg’s phronesis is
utilized for this analysis. Our research will prove that sufficient
economy can help small business firms to solve their problems. We
think that the results of our research will be a financial model to
solve many problems of the entrepreneurs and this way will can be a
model for other provinces of Thailand.
Abstract: Disparity in India has been persisting since independence causing many socioeconomic problems and its removal has become the most prime objective of the planned development in India. Hence the paper attempts to study the disparity at State and Regional level and gives inclusive planning guidelines to achieve balanced regional development. At State level, the relative socioeconomic backwardness of Vidarbha Region based on Interregional analysis using selected indicators like Foreign Direct Investment, Human Development Index, Per Capita District Domestic Product has been assessed and broad guidelines have been proposed. In the later part at Regional level, the relative backwardness of districts based on Intraregional analysis using socioeconomic indicators has been assessed within Nagpur sub region and factors responsible for backwardness & disparity have been indicated. The policy guidelines for Identified sub region have been proposed based on the most significant factor and their extent of relationship explaining backwardness Nagpur sub region.
Abstract: Active Power Filters (APFs) are today the most
widely used systems to eliminate harmonics compensate power
factor and correct unbalanced problems in industrial power plants.
We propose to improve the performances of conventional APFs by
using artificial neural networks (ANNs) for harmonics estimation.
This new method combines both the strategies for extracting the
three-phase reference currents for active power filters and DC link
voltage control method. The ANNs learning capabilities to
adaptively choose the power system parameters for both to compute
the reference currents and to recharge the capacitor value requested
by VDC voltage in order to ensure suitable transit of powers to
supply the inverter. To investigate the performance of this
identification method, the study has been accomplished using
simulation with the MATLAB Simulink Power System Toolbox. The
simulation study results of the new (SAPF) identification technique
compared to other similar methods are found quite satisfactory by
assuring good filtering characteristics and high system stability.
Abstract: Steel surface defect detection is essentially one of
pattern recognition problems. Support Vector Machines (SVMs) are
known as one of the most proper classifiers in this application. In this
paper, we introduce a more accurate classification method by using
SVMs as our final classifier of the inspection system. In this scheme,
multiclass classification task is performed based on the "one-againstone"
method and different kernels are utilized for each pair of the
classes in multiclass classification of the different defects.
In the proposed system, a decision tree is employed in the first
stage for two-class classification of the steel surfaces to "defect" and
"non-defect", in order to decrease the time complexity. Based on
the experimental results, generated from over one thousand images,
the proposed multiclass classification scheme is more accurate than
the conventional methods and the overall system yields a sufficient
performance which can meet the requirements in steel manufacturing.
Abstract: Does the spatial perspective provide a common thread for rural sociology? Have rural sociologists succeeded in bringing order to their data using spatial analysis models and techniques? A trial answer to such questions, as touchstones of theoretical and applied sociological studies in rural areas, is the point at issue in the present paper. Spatial analyses have changed the way rural sociologists approach scientific problems. Rural sociology is spatial by nature because much, if not most, of its research topics has a spatial “awareness." However, such spatial awareness is not quite the same as spatial analysis because it is not typically associated with underlying theories and hypotheses about spatial patterns that are designed to be tested for their specific spatial content. This paper presents pressing issues for future research to reintroduce mainstream rural sociology to the concept of space.
Abstract: The quick training algorithms and accurate solution
procedure for incremental learning aim at improving the efficiency of
training of SVR, whereas there are some disadvantages for them, i.e.
the nonconvergence of the formers for changeable training set and
the inefficiency of the latter for a massive dataset. In order to handle
the problems, a new training algorithm for a changeable training
set, named Approximation Incremental Training Algorithm (AITA),
was proposed. This paper explored the reason of nonconvergence
theoretically and discussed the realization of AITA, and finally
demonstrated the benefits of AITA both on precision and efficiency.
Abstract: Genetic Folding (GF) a new class of EA named as is
introduced for the first time. It is based on chromosomes composed
of floating genes structurally organized in a parent form and
separated by dots. Although, the genotype/phenotype system of GF
generates a kernel expression, which is the objective function of
superior classifier. In this work the question of the satisfying
mapping-s rules in evolving populations is addressed by analyzing
populations undergoing either Mercer-s or none Mercer-s rule. The
results presented here show that populations undergoing Mercer-s
rules improve practically models selection of Support Vector
Machine (SVM). The experiment is trained multi-classification
problem and tested on nonlinear Ionosphere dataset. The target of this
paper is to answer the question of evolving Mercer-s rule in SVM
addressed using either genetic folding satisfied kernel-s rules or not
applied to complicated domains and problems.
Abstract: In this paper, we consider a new particle filter inspired
by biological evolution. In the standard particle filter, a resampling
scheme is used to decrease the degeneracy phenomenon and improve
estimation performance. Unfortunately, however, it could cause the
undesired the particle deprivation problem, as well. In order to
overcome this problem of the particle filter, we propose a novel
filtering method called the genetic filter. In the proposed filter, we
embed the genetic algorithm into the particle filter and overcome the
problems of the standard particle filter. The validity of the proposed
method is demonstrated by computer simulation.