Abstract: The sea waves carry thousands of GWs of power
globally. Although there are a number of different approaches to
harness offshore energy, they are likely to be expensive, practically
challenging, and vulnerable to storms. Therefore, this paper considers
using the near shore waves for generating mechanical and electrical
power. It introduces two new approaches, the wave manipulation and
using a variable duct turbine, for intercepting very wide wave fronts
and coping with the fluctuations of the wave height and the sea level,
respectively. The first approach effectively allows capturing much
more energy yet with a much narrower turbine rotor. The second
approach allows using a rotor with a smaller radius but captures
energy of higher wave fronts at higher sea levels yet preventing it
from totally submerging. To illustrate the effectiveness of the first
approach, the paper contains a description and the simulation results
of a scale model of a wave manipulator. Then, it includes the results
of testing a physical model of the manipulator and a single duct, axial
flow turbine in a wave flume in the laboratory. The paper also
includes comparisons of theoretical predictions, simulation results,
and wave flume tests with respect to the incident energy, loss in wave
manipulation, minimal loss, brake torque, and the angular velocity.
Abstract: There is not much effective guideline on development of design parameters selection on spring back for advanced high strength steel sheet metal in U-channel process during cold forming process. This paper presents the development of predictive model for spring back in U-channel process on advanced high strength steel sheet employing Response Surface Methodology (RSM). The experimental was performed on dual phase steel sheet, DP590 in Uchannel forming process while design of experiment (DoE) approach was used to investigates the effects of four factors namely blank holder force (BHF), clearance (C) and punch travel (Tp) and rolling direction (R) were used as input parameters using two level values by applying Full Factorial design (24 ). From a statistical analysis of variant (ANOVA), result showed that blank holder force (BHF), clearance (C) and punch travel (Tp) displayed significant effect on spring back of flange angle (β2 ) and wall opening angle (β1 ), while rolling direction (R) factor is insignificant. The significant parameters are optimized in order to reduce the spring back behavior using Central Composite Design (CCD) in RSM and the optimum parameters were determined. A regression model for spring back was developed. The effect of individual parameters and their response was also evaluated. The results obtained from optimum model are in agreement with the experimental values.
Abstract: Based on an indoor environmental quality (IEQ) index established by previous work that indicates the overall IEQ acceptance from the prospect of an occupant in residential buildings in terms of four IEQ factors - thermal comfort, indoor air quality, visual and aural comforts, this study develops a user-friendly IEQ calculator for iOS and Android users to calculate the occupant acceptance and compare the relative performance of IEQ in apartments. “IEQ calculator” is easy to use and it preliminarily illustrates the overall indoor environmental quality on the spot. Users simply input indoor parameters such as temperature, number of people and windows are opened or closed for the mobile application to calculate the scores in four areas: the comforts of temperature, brightness, noise and indoor air quality. The calculator allows the prediction of the best IEQ scenario on a quantitative scale. Any indoor environments under the specific IEQ conditions can be benchmarked against the predicted IEQ acceptance range. This calculator can also suggest how to achieve the best IEQ acceptance among a group of residents.
Abstract: Complex lifting entry was selected for precise landing
performance during the Mars Science Laboratory entry. This study
aims to develop the three-dimensional numerical method for precise
computation and the surface panel method for rapid engineering
prediction. Detailed flow field analysis for Mars exploration mission
was performed by carrying on a series of fully three-dimensional
Navier-Stokes computations. The static aerodynamic performance was
then discussed, including the surface pressure, lift and drag coefficient,
lift-to-drag ratio with the numerical and engineering method.
Computation results shown that the shock layer is thin because of
lower effective specific heat ratio, and that calculated results from both
methods agree well with each other, and is consistent with the
reference data. Aerodynamic performance analysis shows that CG
location determines trim characteristics and pitch stability, and certain
radially and axially shift of the CG location can alter the capsule lifting
entry performance, which is of vital significance for the aerodynamic
configuration design and inner instrument layout of the Mars entry
capsule.
Abstract: Steady three-dimensional and two free surface waves
generated by moving bodies are presented, the flow problem to be
simulated is rich in complexity and poses many modeling challenges
because of the existence of breaking waves around the ship hull, and
because of the interaction of the two-phase flow with the turbulent
boundary layer. The results of several simulations are reported. The
first study was performed for NACA0012 of hydrofoil with different
meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second
simulation a mathematically defined Wigley hull form is used to
investigate the application of a commercial CFD code in prediction of
the total resistance and its components from tangential and normal
forces on the hull wetted surface. The computed resistance and wave
profiles are used to estimate the coefficient of the total resistance for
Wigley hull advancing in calm water under steady conditions. The
commercial CFD software FLUENT version 12 is used for the
computations in the present study. The calculated grid is established
using the code computer GAMBIT 2.3.26. The shear stress k-ωSST
model is used for turbulence modeling and the volume of fluid
technique is employed to simulate the free-surface motion. The
second order upwind scheme is used for discretizing the convection
terms in the momentum transport equations, the Modified HRIC
scheme for VOF discretization. The results obtained compare well
with the experimental data.
Abstract: Steady three-dimensional and two free surface waves
generated by moving bodies are presented, the flow problem to be
simulated is rich in complexity and poses many modeling challenges
because of the existence of breaking waves around the ship hull, and
because of the interaction of the two-phase flow with the turbulent
boundary layer. The results of several simulations are reported. The
first study was performed for NACA0012 of hydrofoil with different
meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second
simulation a mathematically defined Wigley hull form is used to
investigate the application of a commercial CFD code in prediction of
the total resistance and its components from tangential and normal
forces on the hull wetted surface. The computed resistance and wave
profiles are used to estimate the coefficient of the total resistance for
Wigley hull advancing in calm water under steady conditions. The
commercial CFD software FLUENT version 12 is used for the
computations in the present study. The calculated grid is established
using the code computer GAMBIT 2.3.26. The shear stress k-ωSST
model is used for turbulence modeling and the volume of fluid
technique is employed to simulate the free-surface motion. The
second order upwind scheme is used for discretizing the convection
terms in the momentum transport equations, the Modified HRIC
scheme for VOF discretization. The results obtained compare well
with the experimental data.
Abstract: Atmospheric carbon dioxide emissions are considered
as the greatest environmental challenge the world is facing today.
The tasks to control the emissions include the recovery of CO2 from
flue gas. This concern has been improved due to recent advances in
materials process engineering resulting in the development of
inorganic gas separation membranes with excellent thermal and
mechanical stability required for most gas separations. This paper,
therefore, evaluates the performance of a highly selective inorganic
membrane for CO2 recovery applications. Analysis of results
obtained is in agreement with experimental literature data. Further
results show the prediction performance of the membranes for gas
separation and the future direction of research. The materials
selection and the membrane preparation techniques are discussed.
Method of improving the interface defects in the membrane and its
effect on the separation performance has also been reviewed and in
addition advances to totally exploit the potential usage of this
innovative membrane.
Abstract: Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while e was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching e of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.
Abstract: This paper presents a method of evaluating the effect
of aggregate angularity on hot mix asphalt (HMA) properties and its
relationship to the Permanent Deformation resistance. The research
concluded that aggregate particle angularity had a significant effect
on the Permanent Deformation performance, and also that with an
increase in coarse aggregate angularity there was an increase in the
resistance of mixes to Permanent Deformation. A comparison
between the measured data and predictive data of permanent
deformation predictive models showed the limits of existing
prediction models. The numerical analysis described the permanent
deformation zones and concluded that angularity has an effect of the
onset of these zones. Prediction of permanent deformation help road
agencies and by extension economists and engineers determine the
best approach for maintenance, rehabilitation, and new construction
works of the road infrastructure.
Abstract: Software fault prediction models are created by using
the source code, processed metrics from the same or previous version
of code and related fault data. Some company do not store and keep
track of all artifacts which are required for software fault prediction.
To construct fault prediction model for such company, the training
data from the other projects can be one potential solution. Earlier we
predicted the fault the less cost it requires to correct. The training
data consists of metrics data and related fault data at function/module
level. This paper investigates fault predictions at early stage using the
cross-project data focusing on the design metrics. In this study,
empirical analysis is carried out to validate design metrics for cross
project fault prediction. The machine learning techniques used for
evaluation is Naïve Bayes. The design phase metrics of other projects
can be used as initial guideline for the projects where no previous
fault data is available. We analyze seven datasets from NASA
Metrics Data Program which offer design as well as code metrics.
Overall, the results of cross project is comparable to the within
company data learning.
Abstract: Heat transfer due to forced convection of copper water
based nanofluid has been predicted by Artificial Neural network
(ANN). The present nanofluid is formed by mixing copper
nanoparticles in water and the volume fractions are considered here
are 0% to 15% and the Reynolds number are kept constant at 100.
The back propagation algorithm is used to train the network. The
present ANN is trained by the input and output data which has been
obtained from the numerical simulation, performed in finite volume
based Computational Fluid Dynamics (CFD) commercial software
Ansys Fluent. The numerical simulation based results are compared
with the back propagation based ANN results. It is found that the
forced convection heat transfer of water based nanofluid can be
predicted correctly by ANN. It is also observed that the back
propagation ANN can predict the heat transfer characteristics of
nanofluid very quickly compared to standard CFD method.
Abstract: Plasmin plays an important role in the human
circulatory system owing to its catalytic ability of fibrinolysis. The
immediate injection of plasmin in patients of strokes has intrigued
many scientists to design vectors that can transport plasmin to the
desired location in human body. Here we predict the structure of
human plasmin and investigate the interaction of plasmin with the
gold-nanoparticle.
Because the crystal structure of plasminogen has been solved, we
deleted N-terminal domain (Pan-apple domain) of plasminogen and
generate a mimic of the active form of this enzyme (plasmin). We
conducted a simulated annealing process on plasmin and discovered a
very large conformation occurs. Kringle domains 1, 4 and 5 had been
observed to leave its original location relative to the main body of the
enzyme and the original doughnut shape of this enzyme has been
transformed to a V-shaped by opening its two arms. This observation
of conformational change is consistent with the experimental results of
neutron scattering and centrifugation.
We subsequently docked the plasmin on the simulated gold surface
to predict their interaction. The V-shaped plasmin could utilize its
Kringle domain and catalytic domain to contact the gold surface.
Our findings not only reveal the flexibility of plasmin structure but
also provide a guide for the design of a plasmin-gold nanoparticle.
Abstract: In the present study, RBF neural networks were used
for predicting the performance and emission parameters of a
biodiesel engine. Engine experiments were carried out in a 4 stroke
diesel engine using blends of diesel and Honge methyl ester as the
fuel. Performance parameters like BTE, BSEC, Tex and emissions
from the engine were measured. These experimental results were
used for ANN modeling.
RBF center initialization was done by random selection and by
using Clustered techniques. Network was trained by using fixed and
varying widths for the RBF units. It was observed that RBF results
were having a good agreement with the experimental results.
Networks trained by using clustering technique gave better results
than using random selection of centers in terms of reduced MRE and
increased prediction accuracy. The average MRE for the performance
parameters was 3.25% with the prediction accuracy of 98% and for
emissions it was 10.4% with a prediction accuracy of 80%.
Abstract: The polymer foil used for manufacturing of
laminated glass members behaves in a viscoelastic manner with
temperature dependance. This contribution aims at incorporating
the time/temperature-dependent behavior of interlayer to our earlier
elastic finite element model for laminated glass beams. The model
is based on a refined beam theory: each layer behaves according
to the finite-strain shear deformable formulation by Reissner and
the adjacent layers are connected via the Lagrange multipliers
ensuring the inter-layer compatibility of a laminated unit. The
time/temperature-dependent behavior of the interlayer is accounted
for by the generalized Maxwell model and by the time-temperature
superposition principle due to the Williams, Landel, and Ferry.
The resulting system is solved by the Newton method with
consistent linearization and the viscoelastic response is determined
incrementally by the exponential algorithm. By comparing the model
predictions against available experimental data, we demonstrate that
the proposed formulation is reliable and accurately reproduces the
behavior of the laminated glass units.
Abstract: Structural Equation Modeling (SEM) was used to test
a hypothesized model explaining Malaysian hypermarket customers’
perceptions of brand trust (BT), customer perceived value (CPV) and
perceived service quality (PSQ) on building their brand loyalty
(CBL) and generating positive word-of-mouth communication
(WOM). Self-administered questionnaires were used to collect data
from 374 Malaysian hypermarket customers from Mydin, Tesco,
Aeon Big and Giant in Kuala Lumpur, a metropolitan city of
Malaysia. The data strongly supported the model exhibiting that BT,
CPV and PSQ are prerequisite factors in building customer brand
loyalty, while PSQ has the strongest effect on prediction of customer
brand loyalty compared to other factors. Besides, the present study
suggests the effect of the aforementioned factors via customer brand
loyalty strongly contributes to generate positive word of mouth
communication.
Abstract: Cloud computing is the innovative and leading
information technology model for enabling convenient, on-demand
network access to a shared pool of configurable computing resources
that can be rapidly provisioned and released with minimal
management effort. In this paper, we aim at the development of
workflow management system for cloud computing platforms based
on our previous research on the dynamic allocation of the cloud
computing resources and its workflow process. We took advantage of
the HTML5 technology and developed web-based workflow interface.
In order to enable the combination of many tasks running on the cloud
platform in sequence, we designed a mechanism and developed an
execution engine for workflow management on clouds. We also
established a prediction model which was integrated with job queuing
system to estimate the waiting time and cost of the individual tasks on
different computing nodes, therefore helping users achieve maximum
performance at lowest payment. This proposed effort has the potential
to positively provide an efficient, resilience and elastic environment
for cloud computing platform. This development also helps boost user
productivity by promoting a flexible workflow interface that lets users
design and control their tasks' flow from anywhere.
Abstract: Latin hypercube designs (LHDs) have been applied in
many computer experiments among the space-filling designs found in
the literature. A LHD can be randomly generated but a randomly
chosen LHD may have bad properties and thus act poorly in
estimation and prediction. There is a connection between Latin
squares and orthogonal arrays (OAs). A Latin square of order s
involves an arrangement of s symbols in s rows and s columns, such
that every symbol occurs once in each row and once in each column
and this exists for every non-negative integer s. In this paper, a
computer program was written to construct orthogonal array-based
Latin hypercube designs (OA-LHDs). Orthogonal arrays (OAs) were
constructed from Latin square of order s and the OAs constructed
were afterward used to construct the desired Latin hypercube designs
for three input variables for use in computer experiments. The LHDs
constructed have better space-filling properties and they can be used
in computer experiments that involve only three input factors.
MATLAB 2012a computer package (www.mathworks.com/) was
used for the development of the program that constructs the designs.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: Rainfall runoff models play important role in
hydrological predictions. However, the model is only one part of the
process for creation of flood prediction. The aim of this paper is to
show the process of successful prediction for flood event (May 15 –
May 18 2014). Prediction was performed by rainfall runoff model
HEC–HMS, one of the models computed within Floreon+ system.
The paper briefly evaluates the results of automatic hydrologic
prediction on the river Olše catchment and its gages Český Těšín and
Věřňovice.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.