Abstract: In this paper, a robust fault detection and isolation
(FDI) scheme is developed to monitor a multivariable nonlinear
chemical process called the Chylla-Haase polymerization reactor,
when it is under the cascade PI control. The scheme employs a radial
basis function neural network (RBFNN) in an independent mode to
model the process dynamics, and using the weighted sum-squared
prediction error as the residual. The Recursive Orthogonal Least
Squares algorithm (ROLS) is employed to train the model to
overcome the training difficulty of the independent mode of the
network. Then, another RBFNN is used as a fault classifier to isolate
faults from different features involved in the residual vector. Several
actuator and sensor faults are simulated in a nonlinear simulation of
the reactor in Simulink. The scheme is used to detect and isolate the
faults on-line. The simulation results show the effectiveness of the
scheme even the process is subjected to disturbances and
uncertainties including significant changes in the monomer feed rate,
fouling factor, impurity factor, ambient temperature, and
measurement noise. The simulation results are presented to illustrate
the effectiveness and robustness of the proposed method.
Abstract: A model to predict the plastic zone size for material
under plane stress condition has been developed and verified
experimentally. The developed model is a function of crack size,
crack angle and material property (dislocation density). Simulation
and validation results show that the model developed show good
agreement with experimental results. Samples of low carbon steel
(0.035%C) with included surface crack angles of 45o, 50o, 60o, 70o
and 90o and crack depths of 2mm and 4mm were subjected to low
strain rate between 0.48 x 10-3 s-1 – 2.38 x 10-3 s-1. The mechanical
properties studied were ductility, tensile strength, modulus of
elasticity, yield strength, yield strain, stress at fracture and fracture
toughness. The experimental study shows that strain rate has no
appreciable effect on the size of plastic zone while crack depth and
crack angle plays an imperative role in determining the size of the
plastic zone of mild steel materials.
Abstract: Concurrent planning of project scheduling and
material ordering has been increasingly addressed within last decades
as an approach to improve the project execution costs. Therefore, we
have taken the problem into consideration in this paper, aiming to
maximize schedules quality robustness, in addition to minimize the
relevant costs. In this regard, a bi-objective mathematical model is
developed to formulate the problem. Moreover, it is possible to
utilize the all-unit discount for materials purchasing. The problem is
then solved by the E-constraint method, and the Pareto front is
obtained for a variety of robustness values. The applicability and
efficiency of the proposed model is tested by different numerical
instances, finally.
Abstract: Production fluids are transported from the platform to
tankers or process facilities through transfer pipelines. Water being
one of the heavier phases tends to settle at the bottom of pipelines
especially at low flow velocities and this has adverse consequences
for pipeline integrity. On restart after a shutdown, this could result in
corrosion and issues for process equipment, thus the need to have the
heavier liquid dispersed into the flowing lighter fluid. This study
looked at the flow regime of low water cut and low flow velocity oil
and water flow using conductive film thickness probes in a large
diameter 4-inch pipe to obtain oil and water interface height and the
interface structural velocity. A wide range of 0.1–1.0 m/s oil and
water mixture velocities was investigated for 0.5–5% water cut. Two
fluid model predictions were used to compare with the experimental
results.
Abstract: The modelling of physical phenomena, such as the
earth’s free oscillations, the vibration of strings, the interaction of
atomic particles, or the steady state flow in a bar give rise to Sturm-
Liouville (SL) eigenvalue problems. The boundary applications of
some systems like the convection-diffusion equation, electromagnetic
and heat transfer problems requires the combination of Dirichlet and
Neumann boundary conditions. Hence, the incorporation of Robin
boundary condition in the analyses of Sturm-Liouville problem. This
paper deals with the computation of the eigenvalues and
eigenfunction of generalized Sturm-Liouville problems with Robin
boundary condition using the finite element method. Numerical
solution of classical Sturm–Liouville problem is presented. The
results show an agreement with the exact solution. High results
precision is achieved with higher number of elements.
Abstract: Wind energy is rapidly emerging as the primary
source of electricity in the Philippines, although developing an
accurate wind resource model is difficult. In this study, Weather
Research and Forecasting (WRF) Model, an open source mesoscale
Numerical Weather Prediction (NWP) model, was used to produce a
1-year atmospheric simulation with 4 km resolution on the Ilocos
Region of the Philippines. The WRF output (netCDF) extracts the
annual mean wind speed data using a Python-based Graphical User
Interface. Lastly, wind resource assessment was produced using a
GIS software. Results of the study showed that it is more flexible to
use Python scripts than using other post-processing tools in dealing
with netCDF files. Using WRF Model, Python, and Geographic
Information Systems, a reliable wind resource map is produced.
Abstract: The underutilization of biomass resources in the
Philippines, combined with its growing population and the rise in
fossil fuel prices confirms demand for alternative energy sources. The
goal of this paper is to provide a comparison of MODIS-based and
Landsat-based agricultural land cover maps when used in the
estimation of rice hull’s available energy potential. Biomass resource
assessment was done using mathematical models and remote sensing
techniques employed in a GIS platform.
Abstract: Finding the optimal 3D path of an aerial vehicle under
flight mechanics constraints is a major challenge, especially when
the algorithm has to produce real time results in flight. Kinematics
models and Pythagorian Hodograph curves have been widely used
in mobile robotics to solve this problematic. The level of difficulty
is mainly driven by the number of constraints to be saturated at the
same time while minimizing the total length of the path. In this paper,
we suggest a pragmatic algorithm capable of saturating at the same
time most of dimensioning helicopter 3D trajectories’ constraints
like: curvature, curvature derivative, torsion, torsion derivative, climb
angle, climb angle derivative, positions. The trajectories generation
algorithm is able to generate versatile complex 3D motion primitives
feasible by a helicopter with parameterization of the curvature and the
climb angle. An upper ”motion primitives’ concatenation” algorithm
is presented based. In this article we introduce a new way of designing
three-dimensional trajectories based on what we call the ”Dubins
gliding symmetry conjecture”. This extremely performing algorithm
will be soon integrated to a real-time decisional system dealing with
inflight safety issues.
Abstract: Geological and tectonic framework indicates that
Bangladesh is one of the most seismically active regions in the world.
The Bengal Basin is at the junction of three major interacting plates:
the Indian, Eurasian, and Burma Plates. Besides there are many
active faults within the region, e.g. the large Dauki fault in the north.
The country has experienced a number of destructive earthquakes due
to the movement of these active faults. Current seismic provisions of
Bangladesh are mostly based on earthquake data prior to the 1990.
Given the record of earthquakes post 1990, there is a need to revisit
the design provisions of the code. This paper compares the base shear
demand of three major cities in Bangladesh: Dhaka (the capital city),
Sylhet, and Chittagong for earthquake scenarios of magnitudes
7.0MW, 7.5MW, 8.0MW, and 8.5MW using a stochastic model. In
particular, the stochastic model allows the flexibility to input region
specific parameters such as shear wave velocity profile (that were
developed from Global Crustal Model CRUST2.0) and include the
effects of attenuation as individual components. Effects of soil
amplification were analysed using the Extended Component
Attenuation Model (ECAM). Results show that the estimated base
shear demand is higher in comparison with code provisions leading to
the suggestion of additional seismic design consideration in the study
regions.
Abstract: In this study, the time-dependent behavior of damaged
reinforced concrete shear wall structures strengthened with composite
plates having variable fibers spacing was investigated to analyze their
seismic response. In the analytical formulation, the adherent and the
adhesive layers are all modeled as shear walls, using the mixed Finite
Element Method (FEM). The anisotropic damage model is adopted to
describe the damage extent of the Reinforced Concrete shear walls.
The phenomenon of creep and shrinkage of concrete has been
determined by Eurocode 2. Large earthquakes recorded in Algeria
(El-Asnam and Boumerdes) have been tested to demonstrate the
accuracy of the proposed method. Numerical results are obtained for non-uniform distributions of
carbon fibers in epoxy matrices. The effects of damage extent and the
delay mechanism creep and shrinkage of concrete are highlighted.
Prospects are being studied.
Abstract: Strong anthropogenic impact has uncontrolled
consequences on the nature of the soil. Hence, up-to-date sustainable
methods of soil state improvement are essential. Investigators provide
the evidence that biochar can positively effects physical, chemical,
and biological soil properties and the abundance of mycorrhizal fungi
which are in the focus of this study. The main aim of the present
investigation is to demonstrate the effect of two types of plant growth
promoting bacteria (PGPB) inoculums along with the beech wood
biochar and mineral N additives on mycorrhizal colonization.
Experiment has been set up in laboratory conditions with containers
filled with arable soil from the protection zone of the main water
source “Brezova nad Svitavou”. Lactuca sativa (lettuce) has been
selected as a model plant. Based on the obtained data, it can be
concluded that mycorrhizal colonization increased as the result of
combined influence of biochar and PGPB inoculums amendment. In
addition, correlation analyses showed that the numbers of main
groups of cultivated bacteria were dependent on the degree of
mycorrhizal colonization.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: The Com-Poisson (CMP) model is one of the most
popular discrete generalized linear models (GLMS) that handles
both equi-, over- and under-dispersed data. In longitudinal context,
an integer-valued autoregressive (INAR(1)) process that incorporates
covariate specification has been developed to model longitudinal
CMP counts. However, the joint likelihood CMP function is
difficult to specify and thus restricts the likelihood-based estimating
methodology. The joint generalized quasi-likelihood approach
(GQL-I) was instead considered but is rather computationally
intensive and may not even estimate the regression effects due
to a complex and frequently ill-conditioned covariance structure.
This paper proposes a new GQL approach for estimating the
regression parameters (GQL-III) that is based on a single score vector
representation. The performance of GQL-III is compared with GQL-I
and separate marginal GQLs (GQL-II) through some simulation
experiments and is proved to yield equally efficient estimates as
GQL-I and is far more computationally stable.
Abstract: The application of ESS (Energy Storage Systems) in
the future grids has been the solution of the microgrid. However, high
investment costs necessitate accurate modeling and control strategy of
ESS to justify its economic viability and further underutilization.
Therefore, the reasonable control strategy for ESS which is subjected
to generator and usage helps to curtail the cost of investment and
operation costs. The rated frequency in power system is decreased
when the load is increasing unexpectedly; hence the thermal power is
operated at the capacity of only its 95% for the Governor Free (GF) to
adjust the frequency as reserve (5%) in practice. The ESS can be
utilized with governor at the same time for the frequency response due
to characteristic of its fast response speed and moreover, the cost of
ESS is declined rapidly to the reasonable price. This paper presents the
ESS control strategy to extend usage of the ESS taken account into
governor’s ramp rate and reduce the governor’s intervention as well.
All results in this paper are simulated by MATLAB.
Abstract: A theoretical study of a humidification
dehumidification solar desalination unit has been carried out to
increase understanding the effect of weather conditions on the unit
productivity. A humidification-dehumidification (HD) solar
desalination unit has been designed to provide fresh water for
population in remote arid areas. It consists of solar water collector
and air collector; to provide the hot water and air to the desalination
chamber. The desalination chamber is divided into humidification
and dehumidification towers. The circulation of air between the two
towers is maintained by the forced convection. A mathematical
model has been formulated, in which the thermodynamic relations
were used to study the flow, heat and mass transfer inside the
humidifier and dehumidifier. The present technique is performed in
order to increase the unit performance. Heat and mass balance has
been done and a set of governing equations has been solved using the
finite difference technique. The unit productivity has been calculated
along the working day during the summer and winter sessions and
has compared with the available experimental results. The average
accumulative productivity of the system in winter has been ranged
between 2.5 to 4 (kg/m2)/day, while the average summer productivity
has been found between 8 to 12 (kg/m2)/day.
Abstract: The Petri nets are the first standard for business
process modeling. Most probably, it is one of the core reasons why
all new standards created afterwards have to be so reformed as to
reach the stage of mapping the new standard onto Petri nets. The paper presents a business process repository based on a
universal database. The repository provides the possibility the data
about a given process to be stored in three different ways. Business
process repository is developed with regard to the reformation of a
given model to a Petri net in order to be easily simulated. Two different techniques for business process simulation based on
Petri nets - Yasper and Woflan are discussed. Their advantages and
drawbacks are outlined. The way of simulating business process
models, stored in the Business process repository is shown.
Abstract: The floor beams of steel buildings, cold-formed steel
floor joists in particular, often require large web openings, which may
affect their shear capacities. A cost effective way to mitigate the
detrimental effects of such openings is to weld/fasten reinforcements.
A difficulty associated with an experimental investigation to establish
suitable reinforcement schemes for openings in shear zone is that
moment always coexists with the shear, and thus, it is impossible to
create pure shear state in experiments, resulting in moment
influenced results. However, Finite Element Method (FEM) based
analysis can be conveniently used to investigate the pure shear
behaviour of webs including webs with reinforced openings. This
paper presents the details associated with the finite element analysis
of thick/thin-plates (representing the web of hot-rolled steel beam,
and the web of a cold-formed steel member) having a large
reinforced opening. The study considered simply-supported
rectangular plates subjected to in-plane shear loadings until failure
(including post-buckling behaviour). The plate was modelled using
geometrically non-linear quadrilateral shell elements, and non-linear
stress-strain relationship based on experiments. Total Langrangian
with large displacement/small strain formulation was used for such
analyses. The model also considered the initial geometric
imperfections. This study considered three reinforcement schemes,
namely, flat, lip, and angle reinforcements. This paper discusses the
modelling considerations and presents the results associated with the
various reinforcement schemes under consideration.
Abstract: The rapid development technology and widespread
Internet make business environment changing a lot. In order to stand in
the global market and to keep subsistence, “changing” is unspoken
rule for the company’s survival. The purpose of this paper is building
up change model by using SWOT, strategy map, KPI and change
management theory. The research findings indicate that the company
needs to deal with employee’s resistance emotion firstly before
building up change model. The ways of providing performance
appraisal reward, consulting and counseling mechanisms that will
great help to achieve reducing staff negative emotions and motivate
staff’s efficiencies also. To revise strategy map, modify corporate
culture, and improve internal operational processes which is based on
change model. Through the change model, the increasing growth rate
of net income helps company to achieve the goals and be a leading
brand of precision machinery industry.
Abstract: For the last decade, researchers have started to focus
their interest on Multicast Group Key Management Framework. The
central research challenge is secure and efficient group key
distribution. The present paper is based on the Bit model based
Secure Multicast Group key distribution scheme using the most
popular absolute encoder output type code named Gray Code. The
focus is of two folds. The first fold deals with the reduction of
computation complexity which is achieved in our scheme by
performing fewer multiplication operations during the key updating
process. To optimize the number of multiplication operations, an
O(1) time algorithm to multiply two N-bit binary numbers which
could be used in an N x N bit-model of reconfigurable mesh is used
in this proposed work. The second fold aims at reducing the amount
of information stored in the Group Center and group members while
performing the update operation in the key content. Comparative
analysis to illustrate the performance of various key distribution
schemes is shown in this paper and it has been observed that this
proposed algorithm reduces the computation and storage complexity
significantly. Our proposed algorithm is suitable for high
performance computing environment.
Abstract: Liver segmentation from medical images poses more
challenges than analogous segmentations of other organs. This
contribution introduces a liver segmentation method from a series of
computer tomography images. Overall, we present a novel method for
segmenting liver by coupling density matching with shape priors.
Density matching signifies a tracking method which operates via
maximizing the Bhattacharyya similarity measure between the
photometric distribution from an estimated image region and a model
photometric distribution. Density matching controls the direction of
the evolution process and slows down the evolving contour in regions
with weak edges. The shape prior improves the robustness of density
matching and discourages the evolving contour from exceeding liver’s
boundaries at regions with weak boundaries. The model is
implemented using a modified distance regularized level set (DRLS)
model. The experimental results show that the method achieves a
satisfactory result. By comparing with the original DRLS model, it is
evident that the proposed model herein is more effective in addressing
the over segmentation problem. Finally, we gauge our performance of
our model against matrices comprising of accuracy, sensitivity, and
specificity.