Abstract: The most severe damage of the turbine rotor is its
distortion. The rotor straightening process must lead, at the first
stage, to removal of the stresses from the material by annealing and
next, to straightening of the plastic distortion without leaving any
stress by hot spotting. The straightening method does not produce
stress accumulations and the heating technique, developed
specifically for solid forged rotors and disks, enables to avoid local
overheating and structural changes in the material. This process also
does not leave stresses in the shaft material. An experimental study
of hot spotting is carried out on a large turbine rotor and some of the
most important effective parameters that must be considered on
annealing and hot spotting processes are investigated in this paper.
Abstract: The paper presents a one-dimensional transient
mathematical model of compressible thermal multi-component gas
mixture flows in pipes. The set of the mass, momentum and enthalpy
conservation equations for gas phase is solved. Thermo-physical
properties of multi-component gas mixture are calculated by solving
the Equation of State (EOS) model. The Soave-Redlich-Kwong
(SRK-EOS) model is chosen. Gas mixture viscosity is calculated on
the basis of the Lee-Gonzales-Eakin (LGE) correlation. Numerical
analysis on rapid decompression in conventional dry gases is
performed by using the proposed mathematical model. The model is
validated on measured values of the decompression wave speed in
dry natural gas mixtures. All predictions show excellent agreement
with the experimental data at high and low pressure. The presented
model predicts the decompression in dry natural gas mixtures much
better than GASDECOM and OLGA codes, which are the most
frequently-used codes in oil and gas pipeline transport service.
Abstract: In the present work an investigation of the effects of
the air frontal velocity, relative humidity and dry air temperature on
the heat transfer characteristics of plain finned tube evaporator has
been conducted. Using an appropriate correlation for the air side heat
transfer coefficient the temperature distribution along the fin surface
was calculated using a dimensionless temperature distribution. For a
constant relative humidity and bulb temperature, it is found that the
temperature distribution decreases with increasing air frontal
velocity. Apparently, it is attributed to the condensate water film
flowing over the fin surface. When dry air temperature and face
velocity are being kept constant, the temperature distribution
decreases with the increase of inlet relative humidity. An increase in
the inlet relative humidity is accompanied by a higher amount of
moisture on the fin surface. This results in a higher amount of latent
heat transfer which involves higher fin surface temperature. For the
influence of dry air temperature, the results here show an increase in
the dimensionless temperature parameter with a decrease in bulb
temperature. Increasing bulb temperature leads to higher amount of
sensible and latent heat transfer when other conditions remain
constant.
Abstract: Batch fermentation of 5, 10 and 25 g/L biodiesel
derived crude glycerol was carried out at 30, 37 and 450C by
Clostridium pasteurianum cells immobilized on silica. Maximum
yield of 1,3-propanediol (PDO) (0.60 mol/mol), and ethanol (0.26
mol/mol) were obtained from 10 g/L crude glycerol at 30 and 370C
respectively. Maximum yield of butanol (0.28 mol/mol substrate
added) was obtained at 370C with 25 g/L substrate. None of the three
products were detected at 45oC even after 10 days of fermentation.
Only traces of ethanol (0.01 mol/mol) were detected at 450C with 5
g/L substrate. The results obtained for 25 g/L substrate utilization
were fitted in first order rate equation to obtain the values of rate
constant at three different temperatures for bioconversion of glycerol.
First order rate constants for bioconversion of glycerol at 30, 37 and
45oC were found to be 0.198, 0.294 and 0.029/day respectively.
Activation energy (Ea) for crude glycerol bioconversion was
calculated to be 57.62 kcal/mol.
Abstract: A supervisory scheme is proposed that implements Stepwise Safe Switching Logic. The functionality of the supervisory scheme is organized in the following eight functional units: Step- Wise Safe Switching unit, Common controllers design unit, Experimentation unit, Simulation unit, Identification unit, Trajectory cruise unit, Operating points unit and Expert system unit. The supervisory scheme orchestrates both the off-line preparative actions, as well as the on-line actions that implement the Stepwise Safe Switching Logic. The proposed scheme is a generic tool, that may be easily applied for a variety of industrial control processes and may be implemented as an automation software system, with the use of a high level programming environment, like Matlab.
Abstract: In this paper we propose the study of a centrifugal pump control system driven by a three-phase induction motor, which is supplied by a PhotoVoltaic PV generator. The system includes solar panel, a DC / DC converter equipped with its MPPT control, a voltage inverter to three-phase Pulse Width Modulation - PWM and a centrifugal pump driven by a three phase induction motor. In order to control the flow of the centrifugal pump, a Direct Torque Control - DTC of the induction machine is used. To illustrate the performances of the control, simulation results are carried out using Matlab/Simulink.
Abstract: Latvia is the fourth in the world by means of broadband internet speed. The total number of internet users in Latvia exceeds 70% of its population. The number of active mailboxes of the local internet e-mail service Inbox.lv accounts for 68% of the population and 97.6% of the total number of internet users. The Latvian portal Draugiem.lv is a phenomenon of social media, because 58.4 % of the population and 83.5% of internet users use it. A majority of Latvian company profiles are available on social networks, the most popular being Twitter.com. These and other parameters prove the fact consumers and companies are actively using the Internet.
However, after the authors in a number of studies analyzed how enterprises are employing the e-environment, namely, e-environment tools, they arrived to the conclusions that are not as flattering as the aforementioned statistics. There is an obvious contradiction between the statistical data and the actual studies. As a result, the authors have posed a question: Why are entrepreneurs resistant to e-tools? In order to answer this question, the authors have addressed the Technology Acceptance Model (TAM). The authors analyzed each phase and determined several factors affecting the use of e-environment, reaching the main conclusion that entrepreneurs do not have a sufficient level of e-literacy (digital literacy).
The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistic method, factor analysis in SPSS 20 environment etc.
The theoretical and methodological background of the research is formed by, scientific researches and publications, that from the mass media and professional literature, statistical information from legal institutions as well as information collected by the author during the survey.
Abstract: This research aims to create a model for analysis of student motivation behavior on e-Learning based on association rule mining techniques in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The model was created under association rules, one of the data mining techniques with minimum confidence. The results showed that the student motivation behavior model by using association rule technique can indicate the important variables that influence the student motivation behavior on e-Learning.
Abstract: In this paper, a novel contrast enhancement technique
for contrast enhancement of a low-contrast satellite image has been
proposed based on the singular value decomposition (SVD) and
discrete cosine transform (DCT). The singular value matrix
represents the intensity information of the given image and any
change on the singular values change the intensity of the input image.
The proposed technique converts the image into the SVD-DCT
domain and after normalizing the singular value matrix; the enhanced
image is reconstructed by using inverse DCT. The visual and
quantitative results suggest that the proposed SVD-DCT method
clearly shows the increased efficiency and flexibility of the proposed
method over the exiting methods such as Linear Contrast Stretching
technique, GHE technique, DWT-SVD technique, DWT technique,
Decorrelation Stretching technique, Gamma Correction method
based techniques.
Abstract: One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.
Abstract: In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.
Abstract: The paper deals with the analysis of triggering
conditions and evolution processes of piping phenomena, in relation
to both mechanical and hydraulic aspects. In particular, the aim of
the study is to predict slope instabilities triggered by piping,
analysing the conditions necessary for a flow failure to occur. Really,
the mechanical effect involved in the loads redistribution around the
pipe is coupled to the drainage process arising from higher
permeability of the pipe. If after the pipe formation, the drainage
goes prevented for pipe clogging, the porewater pressure increase can
lead to the failure or even the liquefaction, with a subsequent flow
slide. To simulate the piping evolution and to verify relevant stability
conditions, a iterative coupled modelling approach has been pointed
out. As example, the proposed tool has been applied to the Stava
Valley disaster (July, 1985), demonstrating that piping might be one
of triggering phenomena of the tailings dams collapse.
Abstract: Twelve lactating Etawah Crossedbred goats were used
in this study. Goat feed consisted of Cally andra callothyrsus,
Pennisetum purpureum, wheat bran and dried fermented cassava
peel. The cassava peels were fermented with a traditional culture
called “ragi tape" (mixed culture of Saccharomyces cerevisae,
Aspergillus sp, Candida, Hasnula and Acetobacter). The goats were
divided into 2 groups (Control and Treated) of six does. The
experimental diet of the Control group consisted of 70% of roughage
(fresh Callyandra callothyrsus and Pennisetum purpureum 60:40)
and 30% of wheat bran on dry matter (DM) base. In the Treated
group 30% of wheat bran was replaced with dried fermented cassava
peels. Data were statistically analyzed using analysis of variance
followed SPSS program. The concentration of HCN in fermented
cassava peel decreased to non toxic level. Nutrient composition of
dried fermented cassava peel consisted of 85.75% dry matter;
5.80% crude protein and 82.51% total digestible nutrien (TDN).
Substitution of 30% of wheat bran with dried fermented cassava peel
in the diet had no effect on dry matter and organic matter intake but
significantly (P< 0.05) decreased crude protein and TDN
consumption as well as milk yields and milk composition. The study
recommended to reduced the level of substitution to less than 30% of
concentrates in the diet in order to avoid low nutrient intake and milk
production of goats.
Abstract: Spherical shaped magnetite (Fe3O4) and Au@Fe3O4
nanoparticles were successfully synthesized from Fe electrodes
immersed in water with CTAB surfactant and HAuCl4 solution using
simple method-pulsed plasma in liquid, without the use of dopants or
special conditions for stabilization. Vibrating sample magnetometer
indicated ferromagnetic behavior of particles at room temperature with
coercivity and saturation magnetization of (Hc=105 Oe, Ms=6.83
emu/g) for Fe3O4 and (Hc=175, Ms=3.56emu/g) for Au@Fe3O4
nanoparticles. Structure and morphology of nanoparticles were
characterized by X-ray Diffraction analysis and HR-TEM
measurements. The cytotoxicity of nanoparticles was indicated using a
XTT assay to be very low (cell viability: 98-89% with Fe3O4 and
99-91% for Au@Fe3O4 NPs).
Abstract: Physical and mechanical properties of Russian olive
fruits were measured at moisture content of 14.43% w.b. The results
revealed that the mean length, width and thickness of Russian olive
fruits were 20.72, 15.73 and 14.69mm, respectively. Mean mass and
volume of Russian olive fruits were measured as 1.45 g and 2.55 cm3,
respectively. The sphericity, aspect ratio and surface area were
calculated as 0.81, 0.72 and 8.96 cm2, respectively, while arithmetic
mean diameter, geometric mean diameter and equivalent diameter of
Russian olive fruits were 17.05, 16.83 and 16.84 mm, respectively.
Whole fruit density, bulk density and porosity of jujube fruits were
measured and found to be 1.01 g/cm3, 0.29 g/cm3 and 69.5%,
respectively. The values of static coefficient of friction on three
surfaces of glass, galvanized iron and plywood were 0.35, 0.36 and
0.43, respectively. The skin color (L*, a*, b*) varied from 9.92 to
16.08; 2.04 to 3.91 and 1.12 to 3.83, respectively. The values of
rupture force, deformation, energy absorbed and hardness were found
to be between 12.14-16.85 N, 2.16-4.25 mm, 3.42-6.99 N mm and
17.1-23.85 N/mm.
Abstract: Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.
Abstract: The paper compares the treatment of fractions in a
typical undergraduate college curriculum and in abstract algebra
textbooks. It stresses that the main difference is that the
undergraduate curriculum treats equivalent fractions as equal, and
this treatment eventually leads to paradoxes and impairs the students-
ability to perceive ratios, proportions, radicals and rational exponents
adequately. The paper suggests a simplified version of rigorous
theory of fractions suitable for regular college curriculum.
Abstract: This paper presents a method of model selection and
identification of Hammerstein systems by hybridization of the genetic
algorithm (GA) and particle swarm optimization (PSO). An unknown
nonlinear static part to be estimated is approximately represented
by an automatic choosing function (ACF) model. The weighting
parameters of the ACF and the system parameters of the linear
dynamic part are estimated by the linear least-squares method. On
the other hand, the adjusting parameters of the ACF model structure
are properly selected by the hybrid algorithm of the GA and PSO,
where the Akaike information criterion is utilized as the evaluation
value function. Simulation results are shown to demonstrate the
effectiveness of the proposed hybrid algorithm.
Abstract: Water is the key of national development. Wherever a spring has been dried out or a river has changed its course, the area-s people have migrated and have been scattered and the area-s civilization has lost its brilliance. Today, air pollution, global warming and ozone layer damage are as the problems of countries, but certainly in the next decade the shortage and pollution of waters will be important issues of the world. The polluted waters are more dangerous in when they are used in agriculture. Because they infect plants and these plants are used in human and livestock consumption in food chain. With the increasing population growth and after that, the increase need to facilities and raw materials, human beings has started to do haste actions and wanted or unwanted destroyed his life basin. They try to overuse and capture his environment extremely, instead of having futurism approach in sustainable use of nature. This process includes Zayanderood recession, and caused its pollution after the transition from industrial and urban areas. Zayandehrood River in Isfahan is a vital artery of a living ecosystem. Now is the location of disposal waste water of many cities, villages and existing industries. The central area of the province is an important industrial place, and its environmental situation has reached a critical stage. Not only a large number of pollution-generating industries are active in the city limits, but outside of the city and adjacent districts Zayandehrood River, heavy industries like steel, Mobarakeh Steel and other tens great units pollute wild life. This article tries to study contaminant sources of Zayanderood and their severity, and determine and discuss the share of each of these resources by major industrial centers located in areas. At the end, we represent suitable strategy.
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.