Abstract: The overall objective of this research is a strain
improvement technology for efficient pectinase production. A novel
cells cultivation technology by immobilization of fungal cells has
been studied in long time continuous fermentations. Immobilization
was achieved by using of new material for absorption of stores of
immobilized cultures which was for the first time used for
immobilization of microorganisms. Effects of various conditions of
nitrogen and carbon nutrition on the biosynthesis of pectolytic
enzymes in Aspergillus awamori 1-8 strain were studied. Proposed
cultivation technology along with optimization of media components
for pectinase overproduction led to increased pectinase productivity
in Aspergillus awamori 1-8 from 7 to 8 times. Proposed technology
can be applied successfully for production of major industrial
enzymes such as α-amylase, protease, collagenase etc.
Abstract: Starting from a biologically inspired framework, Gabor filters were built up from retinal filters via LMSE algorithms. Asubset of retinal filter kernels was chosen to form a particular Gabor filter by using a weighted sum. One-dimensional optimization approaches were shown to be inappropriate for the problem. All model parameters were fixed with biological or image processing constraints. Detailed analysis of the optimization procedure led to the introduction of a minimization constraint. Finally, quantization of weighting factors was investigated. This resulted in an optimized cascaded structure of a Gabor filter bank implementation with lower computational cost.
Abstract: This article considers the positional buckling of
composite thick plates under thermal loading . For this purpose , the
complex finite strip method is used . In analysis of complex finite
strip, harmonic complex function in longitudinal direction , cubic
functions in transversal direction and parabola distribution of
transverse shear strain in thickness of thick plate based on higherorder
shear deformation theory are used . In given examples , the
effect of angles of stratification , number of layers , dimensions ratio
and length – to – thick ratio across critical temperature are
considered.
Abstract: Calibration estimation is a method of adjusting the
original design weights to improve the survey estimates by using
auxiliary information such as the known population total (or mean)
of the auxiliary variables. A calibration estimator uses calibrated
weights that are determined to minimize a given distance measure to
the original design weights while satisfying a set of constraints
related to the auxiliary information. In this paper, we propose a new
multivariate calibration estimator for the population mean in the
stratified sampling design, which incorporates information available
for more than one auxiliary variable. The problem of determining the
optimum calibrated weights is formulated as a Mathematical
Programming Problem (MPP) that is solved using the Lagrange
multiplier technique.
Abstract: This paper deals with wireless relay communication
systems in which multiple sources transmit information to the
destination node by the help of multiple relays. We consider a
signal forwarding technique based on the minimum mean-square
error (MMSE) approach with multiple antennas for each relay. A
source-relay-destination joint design strategy is proposed with power
constraints at the destination and the source nodes. Simulation results
confirm that the proposed joint design method improves the average
MSE performance compared with that of conventional MMSE relaying
schemes.
Abstract: A minimal complexity version of component mode
synthesis is presented that requires simplified computer
programming, but still provides adequate accuracy for modeling
lower eigenproperties of large structures and their transient
responses. The novelty is that a structural separation into components
is done along a plane/surface that exhibits rigid-like behavior, thus
only normal modes of each component is sufficient to use, without
computing any constraint, attachment, or residual-attachment modes.
The approach requires only such input information as a few (lower)
natural frequencies and corresponding undamped normal modes of
each component. A novel technique is shown for formulation of
equations of motion, where a double transformation to generalized
coordinates is employed and formulation of nonproportional damping
matrix in generalized coordinates is shown.
Abstract: In this paper we develop an efficient numerical method for the finite-element model updating of damped gyroscopic systems based on incomplete complex modal measured data. It is assumed that the analytical mass and stiffness matrices are correct and only the damping and gyroscopic matrices need to be updated. By solving a constrained optimization problem, the optimal corrected symmetric damping matrix and skew-symmetric gyroscopic matrix complied with the required eigenvalue equation are found under a weighted Frobenius norm sense.
Abstract: This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.
Abstract: Project managers are the ultimate responsible for the
overall characteristics of a project, i.e. they should deliver the project
on time with minimum cost and with maximum quality. It is vital for
any manager to decide a trade-off between these conflicting
objectives and they will be benefited of any scientific decision
support tool. Our work will try to determine optimal solutions (rather
than a single optimal solution) from which the project manager will
select his desirable choice to run the project. In this paper, the
problem in project scheduling notated as
(1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The
problem is multi-objective and the purpose is finding the Pareto
optimal front of time, cost and quality of a project
(curve:quality,time,cost), whose activities belong to a start to finish
activity relationship network (cpm) and they can be done in different
possible modes (mu) which are non-continuous or discrete (disc), and
each mode has a different cost, time and quality . The project is
constrained to a non-renewable resource i.e. money (1,T). Because
the problem is NP-Hard, to solve the problem, a meta-heuristic is
developed based on a version of genetic algorithm specially adapted
to solve multi-objective problems namely FastPGA. A sample project
with 30 activities is generated and then solved by the proposed
method.
Abstract: Six Sigma is a well known discipline that reduces
variation using complex statistical tools and the DMAIC model. By
integrating Goldratts-s Theory of Constraints, the Five Focusing
Points and System Thinking tools, Six Sigma projects can be selected
where it can cause more impact in the company. This research
defines an integrated model of six sigma and constraint management
that shows a step-by-step guide using the original methodologies
from each discipline and is evaluated in a case study from the
production line of a Automobile engine monoblock V8, resulting in
an increase in the line capacity from 18.7 pieces per hour to 22.4
pieces per hour, a reduction of 60% of Work-In-Process and a
variation decrease of 0.73%.
Abstract: To support mobility in ATM networks, a number of
technical challenges need to be resolved. The impact of handoff
schemes in terms of service disruption, handoff latency, cost
implications and excess resources required during handoffs needs to
be addressed. In this paper, a one phase handoff and route
optimization solution using reserved PVCs between adjacent ATM
switches to reroute connections during inter-switch handoff is
studied. In the second phase, a distributed optimization process is
initiated to optimally reroute handoff connections. The main
objective is to find the optimal operating point at which to perform
optimization subject to cost constraint with the purpose of reducing
blocking probability of inter-switch handoff calls for delay tolerant
traffic. We examine the relation between the required bandwidth
resources and optimization rate. Also we calculate and study the
handoff blocking probability due to lack of bandwidth for resources
reserved to facilitate the rapid rerouting.
Abstract: The present experimental investigation brings about
a comparative study of lactic acid production by pure strains of
Lactobacilli (1) L. delbreuckii (NCIM2025), (2) L. pentosus (NCIM
2912), (3) Lactobacillus sp.(NCIM 2734, (4) Lactobacillus sp.
(NCIM2084) and coculture of strain-1 and Stain-2 in solid bed of
wheat bran, under the influence of different nitrogen sources such as
baker-s yeast, meat extract and proteose peptone. Among the pure
cultures, strain-3 attained lowest pH value of 3.44, hence highest acid
formation 46.41 g/L, while the coculture attained an overall
maximum value 47.56 g/L lactic acid (pH 3.38) at 15 g/L and 20 g/L
level of baker-s yeast, respectively.
Abstract: The current methods of predictive controllers are
utilized for those processes in which the rate of output variations is
not high. For such processes, therefore, stability can be achieved by
implementing the constrained predictive controller or applying
infinite prediction horizon. When the rate of the output growth is
high (e.g. for unstable nonminimum phase process) the stabilization
seems to be problematic. In order to avoid this, it is suggested to
change the method in the way that: first, the prediction error growth
should be decreased at the early stage of the prediction horizon, and
second, the rate of the error variation should be penalized. The
growth of the error is decreased through adjusting its weighting
coefficients in the cost function. Reduction in the error variation is
possible by adding the first order derivate of the error into the cost
function. By studying different examples it is shown that using these
two remedies together, the closed-loop stability of unstable
nonminimum phase process can be achieved.
Abstract: Topology Optimization is a defined as the method of
determining optimal distribution of material for the assumed design
space with functionality, loads and boundary conditions [1].
Topology optimization can be used to optimize shape for the
purposes of weight reduction, minimizing material requirements or
selecting cost effective materials [2]. Topology optimization has been
implemented through the use of finite element methods for the
analysis, and optimization techniques based on the method of moving
asymptotes, genetic algorithms, optimality criteria method, level sets
and topological derivatives. Case study of Typical “Fuselage design"
is considered for this paper to explain the benefits of Topology
Optimization in the design cycle. A cylindrical shell is assumed as
the design space and aerospace standard pay loads were applied on
the fuselage with wing attachments as constraints. Then topological
optimization is done using Finite Element (FE) based software. This
optimization results in the structural concept design which satisfies
all the design constraints using minimum material.
Abstract: Nanostructured materials have attracted many
researchers due to their outstanding mechanical and physical
properties. For example, carbon nanotubes (CNTs) or carbon
nanofibres (CNFs) are considered to be attractive reinforcement
materials for light weight and high strength metal matrix composites.
These composites are being projected for use in structural
applications for their high specific strength as well as functional
materials for their exciting thermal and electrical characteristics. The
critical issues of CNT-reinforced MMCs include processing
techniques, nanotube dispersion, interface, strengthening mechanisms
and mechanical properties. One of the major obstacles to the effective
use of carbon nanotubes as reinforcements in metal matrix
composites is their agglomeration and poor distribution/dispersion
within the metallic matrix. In order to tap into the advantages of the
properties of CNTs (or CNFs) in composites, the high dispersion of
CNTs (or CNFs) and strong interfacial bonding are the key issues
which are still challenging. Processing techniques used for synthesis
of the composites have been studied with an objective to achieve
homogeneous distribution of carbon nanotubes in the matrix.
Modified mechanical alloying (ball milling) techniques have emerged
as promising routes for the fabrication of carbon nanotube (CNT)
reinforced metal matrix composites. In order to obtain a
homogeneous product, good control of the milling process, in
particular control of the ball movement, is essential. The control of
the ball motion during the milling leads to a reduction in grinding
energy and a more homogeneous product. Also, the critical inner
diameter of the milling container at a particular rotational speed can
be calculated. In the present work, we use conventional and modified
mechanical alloying to generate a homogenous distribution of 2 wt.
% CNT within Al powders. 99% purity Aluminium powder (Acros,
200mesh) was used along with two different types of multiwall
carbon nanotube (MWCNTs) having different aspect ratios to
produce Al-CNT composites. The composite powders were processed
into bulk material by compaction, and sintering using a cylindrical
compaction and tube furnace. Field Emission Scanning electron
microscopy (FESEM), X-Ray diffraction (XRD), Raman
spectroscopy and Vickers macro hardness tester were used to
evaluate CNT dispersion, powder morphology, CNT damage, phase
analysis, mechanical properties and crystal size determination.
Despite the success of ball milling in dispersing CNTs in Al powder,
it is often accompanied with considerable strain hardening of the Al
powder, which may have implications on the final properties of the
composite. The results show that particle size and morphology vary
with milling time. Also, by using the mixing process and sonication
before mechanical alloying and modified ball mill, dispersion of the
CNTs in Al matrix improves.
Abstract: In present work, prediction the effect of nose radius, rz (mm) on the equivalent strain (PEEQ) and surface finish during the machining of titanium alloy (Ti-6Al-4V) through orthogonal cutting process. The results were performed at several of the nose radiuses, rz (mm) while the cutting speed, vc (m/min), feed rate, f (mm/tooth) and depth of cut, d (mm) were remained constant. The equivalent plastic strain (PEEQ) was estimated by using finite element modeling (FEM) and applied through ABAQUS/EXPLICIT software. The simulation results led to conclude that the equivalent plastic strain (PEEQ) was increased and surface roughness (Ra) decreased when increasing nose radius, rz (mm) during the machining of titanium alloy (Ti–6Al–4V) in dry cutting conditions.
Abstract: To investigates the effect of fiberglass clamping
process improvement on drape simulation prediction. This has
great effect on the mould and the fiber during manufacturing
process. This also, improves the fiber strain, the quality of the
fiber orientation in the area of folding and wrinkles formation
during the press-forming process. Drape simulation software
tool was used to digitalize the process, noting the formation
problems on the contour sensitive part. This was compared
with the real life clamping processes using single and double
frame set-ups to observe the effects. Also, restrains are
introduced by using clips, and the G-clamps with predetermine
revolution to; restrain the fabric deformation during the
forming process.The incorporation of clamping and fabric
restrain deformation improved on the prediction of the
simulation tool. Therefore, for effective forming process,
incorporation of clamping process into the drape simulation
process will assist in the development of fiberglass application
in manufacturing process.
Abstract: The sand production problem has led researchers into making various attempts to understand the phenomenon. The generally accepted concept is that the occurrence of sanding is due to the in-situ stress conditions and the induced changes in stress that results in the failure of the reservoir sandstone during hydrocarbon production from wellbores. By using a hypothetical cased (perforated) well, an approach to the problem is presented here by using Finite Element numerical modelling techniques. In addition to the examination of the erosion problem, the influence of certain key parameters is studied in order to ascertain their effect on the failure and subsequent erosion process. The major variables investigated include: drawdown, perforation depth, and the erosion criterion. Also included is the determination of the optimal mud pressure for given operational and reservoir conditions. The improved understanding between parameters enables the choice of optimal values to minimize sanding during oil production.
Abstract: The paper deals with calculation of the parameters of
ceramic material from a set of destruction tests of ceramic heads of
total hip joint endoprosthesis. The standard way of calculation of the
material parameters consists in carrying out a set of 3 or 4 point
bending tests of specimens cut out from parts of the ceramic material
to be analysed. In case of ceramic heads, it is not possible to cut out
specimens of required dimensions because the heads are too small (if
the cut out specimens were smaller than the normalised ones, the
material parameters derived from them would exhibit higher strength
values than those which the given ceramic material really has). On
that score, a special testing jig was made, in which 40 heads were
destructed. From the measured values of circumferential strains of the
head-s external spherical surface under destruction, the state of stress
in the head under destruction was established using the final elements
method (FEM). From the values obtained, the sought for parameters
of the ceramic material were calculated using Weibull-s weakest-link
theory.
Abstract: In this paper the neural network-based controller is
designed for motion control of a mobile robot. This paper treats the
problems of trajectory following and posture stabilization of the
mobile robot with nonholonomic constraints. For this purpose the
recurrent neural network with one hidden layer is used. It learns
relationship between linear velocities and error positions of the
mobile robot. This neural network is trained on-line using the
backpropagation optimization algorithm with an adaptive learning
rate. The optimization algorithm is performed at each sample time to
compute the optimal control inputs. The performance of the proposed
system is investigated using a kinematic model of the mobile robot.