Abstract: Modelling techniques for a fluid coupling taken from
published literature have been extended to include the effects of the
filling and emptying of the coupling with oil and the variation in
losses when the coupling is partially full. In the model, the fluid flow
inside the coupling is considered to have two principal velocity
components; one circumferentially about the coupling axis
(centrifugal head) and the other representing the secondary vortex
within the coupling itself (vortex head). The calculation of liquid
mass flow rate circulating between the two halves of the coupling is
based on: the assumption of a linear velocity variation in the
circulating vortex flow; the head differential in the fluid due to the
speed difference between the two shafts; and the losses in the
circulating vortex flow as a result of the impingement of the flow
with the blades in the coupling and friction within the passages
between the blades.
Abstract: Property investment in the real estate industry has a
high risk due to the uncertainty factors that will affect the decisions
made and high cost. Analytic hierarchy process has existed for some
time in which referred to an expert-s opinion to measure the
uncertainty of the risk factors for the risk analysis. Therefore,
different level of experts- experiences will create different opinion
and lead to the conflict among the experts in the field. The objective
of this paper is to propose a new technique to measure the uncertainty
of the risk factors based on multidimensional data model and data
mining techniques as deterministic approach. The propose technique
consist of a basic framework which includes four modules: user,
technology, end-user access tools and applications. The property
investment risk analysis defines as a micro level analysis as the
features of the property will be considered in the analysis in this
paper.
Abstract: This paper has been investigated a technique that predicts the performance of a bar-type unimorph piezoelectric vibration actuator depending on the frequency. This paper has been proposed an equivalent circuit that can be easily analyzed for the bar-type unimorph piezoelectric vibration actuator. In the dynamic analysis, rigidity and resonance frequency, which are important mechanical elements, were derived using the basic beam theory. In the equivalent circuit analysis, the displacement and bandwidth of the piezoelectric vibration actuator depending on the frequency were predicted. Also, for the reliability of the derived equations, the predicted performance depending on the shape change was compared with the result of a finite element analysis program.
Abstract: Ramadan requires individuals to abstain from food and fluid intake between sunrise and sunset; physiological considerations predict that poorer mood, physical performance and mental performance will result. In addition, any difficulties will be worsened because preparations for fasting and recovery from it often mean that nocturnal sleep is decreased in length, and this independently affects mood and performance.
A difficulty of interpretation in many studies is that the observed changes could be due to fasting but also to the decreased length of sleep and altered food and fluid intakes before and after the daytime fasting. These factors were separated in this study, which took place over three separate days and compared the effects of different durations of fasting (4, 8 or 16h) upon a wide variety of measures (including subjective and objective assessments of performance, body composition, dehydration and responses to a short bout of exercise) - but with an unchanged amount of nocturnal sleep, controlled supper the previous evening, controlled intakes at breakfast and daytime naps not being allowed. Many of the negative effects of fasting observed in previous studies were present in this experiment also. These findings indicate that fasting was responsible for many of the changes previously observed, though some effect of sleep loss, particularly if occurring on successive days (as would occur in Ramadan) cannot be excluded.
Abstract: Numerical analysis for the aerodynamic characteristics
of the WIG (wing-in ground effect) craft with highly cambered and
aspect ratio of one is performed to predict the ground effect for the
case of with- and without- lower-extension endplate. The analysis is
included varying angles of attack from 0 to10 deg. and ground
clearances from 5% of chord to 50%. Due to the ground effect, the lift
by rising in pressure on the lower surface is increased and the
influence of wing-tip vortices is decreased. These two significant
effects improve the lift-drag ratio. On the other hand, the endplate
prevents the high-pressure air escaping from the air cushion at the
wing tip and causes to increase the lift and lift-drag ratio further. It is
found from the visualization of computation results that two wing-tip
vortices are generated from each surface of the wing tip and their
strength are weak and diminished rapidly. Irodov-s criteria are also
evaluated to investigate the static height stability. The comparison of
Irodov-s criteria shows that the endplate improves the deviation of the
static height stability with respect to pitch angles and heights. As the
results, the endplate can improve the aerodynamic characteristics and
static height stability of wings in ground effect, simultaneously.
Abstract: Rapid urbanization, industrialization and population
growth have led to an increase in number of automobiles that cause
air pollution. It is estimated that road traffic contributes 60% of air
pollution in urban areas. A case by case assessment is required to
predict the air quality in urban situations, so as to evolve certain
traffic management measures to maintain the air quality levels with
in the tolerable limits. Calicut city in the state of Kerala, India has
been chosen as the study area. Carbon Monoxide (CO) concentration
was monitored at 15 links in Calicut city and air quality performance
was evaluated over each link. The CO pollutant concentration values
were compared with the National Ambient Air Quality Standards
(NAAQS), and the CO values were predicted by using CALINE4 and
IITLS and Linear regression models. The study has revealed that
linear regression model performs better than the CALINE4 and
IITLS models. The possible association between CO pollutant
concentration and traffic parameters like traffic flow, type of vehicle,
and traffic stream speed was also evaluated.
Abstract: The performance and the plasma created by a pulsed
magnetoplasmadynamic thruster for small satellite application is
studied to understand better the ablation and plasma propagation
processes occurring during the short-time discharge. The results can
be applied to improve the quality of the thruster in terms of efficiency,
and to tune the propulsion system to the needs required by the satellite
mission. Therefore, plasma measurements with a high-speed camera
and induction probes, and performance measurements of mass bit
and impulse bit were conducted. Values for current sheet propagation
speed, mean exhaust velocity and thrust efficiency were derived from
these experimental data. A maximum in current sheet propagation
was found by the high-speed camera measurements for a medium
energy input and confirmed by the induction probes. A quasilinear
tendency between the mass bit and the energy input, the current
action integral respectively, was found, as well as a linear tendency
between the created impulse and the discharge energy. The highest
mean exhaust velocity and thrust efficiency was found for the highest
energy input.
Abstract: A cross sectional survey design was used to collect
data from 370 diabetic patients. Two instruments were used in
obtaining data; in-depth interview guide and researchers- developed
questionnaire. Fisher's exact test was used to investigate association
between the identified factors and nonadherence. Factors identified
were: socio-demographic factors such as: gender, age, marital status,
educational level and occupation; psychosocial obstacles such as:
non-affordability of prescribed diet, frustration due to the restriction,
limited spousal support, feelings of deprivation, feeling that
temptation is inevitable, difficulty in adhering in social gatherings
and difficulty in revealing to host that one is diabetic; health care
providers obstacles were: poor attitude of health workers, irregular
diabetes education in clinics , limited number of nutrition education
sessions/ inability of the patients to estimate the desired quantity of
food, no reminder post cards or phone calls about upcoming patient
appointments and delayed start of appointment / time wasting in
clinics.
Abstract: Economically transformers constitute one of the largest investments in a Power system. For this reason, transformer condition assessment and management is a high priority task. If a transformer fails, it would have a significant negative impact on revenue and service reliability. Monitoring the state of health of power transformers has traditionally been carried out using laboratory Dissolved Gas Analysis (DGA) tests performed at periodic intervals on the oil sample, collected from the transformers. DGA of transformer oil is the single best indicator of a transformer-s overall condition and is a universal practice today, which started somewhere in the 1960s. Failure can occur in a transformer due to different reasons. Some failures can be limited or prevented by maintenance. Oil filtration is one of the methods to remove the dissolve gases and prevent the deterioration of the oil. In this paper we analysis the DGA data by regression method and predict the gas concentration in the oil in the future. We bring about a comparative study of different traditional methods of regression and the errors generated out of their predictions. With the help of these data we can deduce the health of the transformer by finding the type of fault if it has occurred or will occur in future. Additional in this paper effect of filtration on the transformer health is highlight by calculating the probability of failure of a transformer with and without oil filtrating.
Abstract: A catastrophic earthquake measuring 6.3 on the
Richter scale struck the Christchurch, New Zealand Central Business
District on February 22, 2012, abruptly disrupting the business of
teaching and learning at Christchurch Polytechnic Institute of
Technology. This paper presents the findings from a study
undertaken about the complexity of delivering an educational
programme in the face of this traumatic natural event. Nine
interconnected themes emerged from this multiple method study:
communication, decision making, leader- and follower-ship,
balancing personal and professional responsibilities, taking action,
preparedness and thinking ahead, all within a disruptive and uncertain
context. Sustainable responses that maximise business continuity, and
provide solutions to practical challenges, are among the study-s
recommendations.
Abstract: Design and modeling of nonlinear systems require the
knowledge of all inside acting parameters and effects. An empirical
alternative is to identify the system-s transfer function from input and
output data as a black box model. This paper presents a procedure
using least squares algorithm for the identification of a feed drive
system coefficients in time domain using a reduced model based on
windowed input and output data. The command and response of the
axis are first measured in the first 4 ms, and then least squares are
applied to predict the transfer function coefficients for this
displacement segment. From the identified coefficients, the next
command response segments are estimated. The obtained results
reveal a considerable potential of least squares method to identify the
system-s time-based coefficients and predict accurately the command
response as compared to measurements.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.
Abstract: The performance of schedules released to a shop floor may greatly be affected by unexpected disruptions. Thus, this paper considers the flexible job shop scheduling problem when processing times of some operations are represented by a uniform distribution with given lower and upper bounds. The objective is to find a predictive schedule that can deal with this uncertainty. The paper compares two genetic approaches to obtain predictive schedule. To determine the performance of the predictive schedules obtained by both approaches, an experimental study is conducted on a number of benchmark problems.
Abstract: This study investigated the seasonal prevalence of
Aedes aegypti and Ae. albopictus larvae in three topographical areas
(i.e. mangrove, rice paddy and mountainous areas). Samples were
collected from 300 households in both wet and dry seasons in nine
districts in Nakhon Si Thammarat province. Ae. aegypti and Ae.
albopictus were found in 21 out of 29 types of water containers in
mangrove, rice paddy and mountainous areas. Ae. aegypti and Ae.
albopictus laid eggs in different container types depending on season
and topographical areas. Ae. aegypti larvae were found most in metal
box in mangrove and mountainous areas in wet season. Ae.
albopictus larvae were also found most in metal box in mangrove and
mountainous areas in both wet and dry seasons. All Ae. albopictus
larval indices were higher than Ae. aegypti larval indices in all three
topographical areas and both seasons. HI and BI did not differ in
three topographical areas but differed between Aedes sp. HI for both
Ae. aegypti and Ae. albopictus in all three topographical areas in both
seasons were greater than 10 %, except Aedes aegypti in rice paddy
area in wet season. This indicated high risks of DHF transmission in
these areas.
Abstract: The approach of subset selection in polynomial
regression model building assumes that the chosen fixed full set of
predefined basis functions contains a subset that is sufficient to
describe the target relation sufficiently well. However, in most cases
the necessary set of basis functions is not known and needs to be
guessed – a potentially non-trivial (and long) trial and error process.
In our research we consider a potentially more efficient approach –
Adaptive Basis Function Construction (ABFC). It lets the model
building method itself construct the basis functions necessary for
creating a model of arbitrary complexity with adequate predictive
performance. However, there are two issues that to some extent
plague the methods of both the subset selection and the ABFC,
especially when working with relatively small data samples: the
selection bias and the selection instability. We try to correct these
issues by model post-evaluation using Cross-Validation and model
ensembling. To evaluate the proposed method, we empirically
compare it to ABFC methods without ensembling, to a widely used
method of subset selection, as well as to some other well-known
regression modeling methods, using publicly available data sets.
Abstract: Due to the stringent legislation for emission of diesel
engines and also increasing demand on fuel consumption, the
importance of detailed 3D simulation of fuel injection, mixing and
combustion have been increased in the recent years. In the present
work, FIRE code has been used to study the detailed modeling of
spray and mixture formation in a Caterpillar heavy-duty diesel
engine. The paper provides an overview of the submodels
implemented, which account for liquid spray atomization, droplet
secondary break-up, droplet collision, impingement, turbulent
dispersion and evaporation. The simulation was performed from
intake valve closing (IVC) to exhaust valve opening (EVO). The
predicted in-cylinder pressure is validated by comparing with
existing experimental data. A good agreement between the predicted
and experimental values ensures the accuracy of the numerical
predictions collected with the present work. Predictions of engine
emissions were also performed and a good quantitative agreement
between measured and predicted NOx and soot emission data were
obtained with the use of the present Zeldowich mechanism and
Hiroyasu model. In addition, the results reported in this paper
illustrate that the numerical simulation can be one of the most
powerful and beneficial tools for the internal combustion engine
design, optimization and performance analysis.
Abstract: In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.
Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.
Abstract: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.
Abstract: For numerical prediction of the NOX in the exhaust of
a compression ignition engine a model was developed by considering
the parameter equivalence ratio. This model was validated by
comparing the predicted results of NOX with experimental ones. The
ultimate aim of the work was to access the applicability, robustness
and performance of the improved NOX model against other NOX
models.