Abstract: Foundation of tower crane serves to ensure stability
against vertical and horizontal forces. If foundation stress is not
sufficient, tower crane may be subject to overturning, shearing or
foundation settlement. Therefore, engineering review of stable support
is a highly critical part of foundation design. However, there are not
many professionals who can conduct engineering review of tower
crane foundation and, if any, they have information only on a small
number of cranes in which they have hands-on experience. It is also
customary to rely on empirical knowledge and tower crane renter-s
recommendations rather than designing foundation on the basis of
engineering knowledge. Therefore, a foundation design automation
system considering not only lifting conditions but also overturning
risk, shearing and vertical force may facilitate production of foolproof
foundation design for experts and enable even non-experts to utilize
professional knowledge that only experts can access now. This study
proposes Automatic Design Algorithm for the Tower Crane
Foundations considering load and horizontal force.
Abstract: The bypass exhaust system of a 160 MW combined cycle has been modeled and analyzed using numerical simulation in 2D prospective. Analysis was carried out using the commercial numerical simulation software, FLUENT 6.2. All inputs were based on the technical data gathered from working conditions of a Siemens V94.2 gas turbine, installed in the Yazd power plant. This paper deals with reduction of pressure drop in bypass exhaust system using turning vanes mounted in diverter box in order to alleviate turbulent energy dissipation rate above diverter box. The geometry of such turning vanes has been optimized based on the flow pattern at diverter box inlet. The results show that the use of optimized turning vanes in diverter box can improve the flow pattern and eliminate vortices around sharp edges just before the silencer. Furthermore, this optimization could decrease the pressure drop in bypass exhaust system and leads to higher plant efficiency.
Abstract: Environmental pollution problems have been globally
main concern in all fields including economy, society and culture into
the 21st century. Beginning with the Kyoto Protocol, the reduction on
the emissions of greenhouse gas such as CO2 and SOX has been a
principal challenge of our day. As most buildings unlike durable goods
in other industries have a characteristic and long life cycle, they
consume energy in quantity and emit much CO2. Thus, for green
building construction, more research is needed to reduce the CO2
emissions at each stage in the life cycle. However, recent studies are
focused on the use and maintenance phase. Also, there is a lack of
research on the initial design stage, especially the structure design.
Therefore, in this study, we propose an optimal design plan
considering CO2 emissions and cost in composite buildings
simultaneously by applying to the structural design of actual building.
Abstract: In this paper, an improved ant colony optimization
(ACO) algorithm is proposed to enhance the performance of global
optimum search. The strategy of the proposed algorithm has the
capability of fuzzy pheromone updating, adaptive parameter tuning,
and mechanism resetting. The proposed method is utilized to tune the
parameters of the fuzzy controller for a real beam and ball system.
Simulation and experimental results indicate that better performance
can be achieved compared to the conventional ACO algorithms in the
aspect of convergence speed and accuracy.
Abstract: Rapid economic development and population growth
in Malaysia had accelerated the generation of solid waste. This issue
gives pressure for effective management of municipal solid waste
(MSW) to take place in Malaysia due to the increased cost of landfill.
This paper discusses optimal planning of waste-to-energy (WTE)
using a combinatorial simulation and optimization model through
mixed integer linear programming (MILP) approach. The proposed
multi-period model is tested in Iskandar Malaysia (IM) as case study
for a period of 12 years (2011 -2025) to illustrate the economic
potential and tradeoffs involved in this study. In this paper, 3
scenarios have been used to demonstrate the applicability of the
model: (1) Incineration scenario (2) Landfill scenario (3) Optimal
scenario. The model revealed that the minimum cost of electricity
generation from 9,995,855 tonnes of MSW is estimated as USD
387million with a total electricity generation of 50MW /yr in the
optimal scenario.
Abstract: Transmission network expansion planning (TNEP) is
a basic part of power system planning that determines where, when
and how many new transmission lines should be added to the
network. Up till now, various methods have been presented to solve
the static transmission network expansion planning (STNEP)
problem. But in all of these methods, transmission expansion
planning considering network adequacy restriction has not been
investigated. Thus, in this paper, STNEP problem is being studied
considering network adequacy restriction using discrete particle
swarm optimization (DPSO) algorithm. The goal of this paper is
obtaining a configuration for network expansion with lowest
expansion cost and a specific adequacy. The proposed idea has been
tested on the Garvers network and compared with the decimal
codification genetic algorithm (DCGA). The results show that the
network will possess maximum efficiency economically. Also, it is
shown that precision and convergence speed of the proposed DPSO
based method for the solution of the STNEP problem is more than
DCGA approach.
Abstract: In this paper we proposed multistage adaptive
ARQ/HARQ/HARQ scheme. This method combines pure ARQ
(Automatic Repeat reQuest) mode in low channel bit error rate and
hybrid ARQ method using two different Reed-Solomon codes in
middle and high error rate conditions. It follows, that our scheme has
three stages. The main goal is to increase number of states in adaptive
HARQ methods and be able to achieve maximum throughput for
every channel bit error rate. We will prove the proposal by
calculation and then with simulations in land mobile satellite channel
environment. Optimization of scheme system parameters is described
in order to maximize the throughput in the whole defined Signal-to-
Noise Ratio (SNR) range in selected channel environment.
Abstract: This paper presents the optimum design for a double
stator, cup rotor machine; a novel type of BLDC PM Machine. The optimization approach is divided into two stages: the first stage is
calculating the machine configuration using Matlab, and the second stage is the optimization of the machine using Finite Element
Modeling (FEM). Under the design specifications, the machine
model will be selected from three pole numbers, namely, 8, 10 and 12 with an appropriate slot number. A double stator brushless DC
permanent magnet machine is designed to achieve low cogging torque; high electromagnetic torque and low ripple torque.
Abstract: Coronary artery bypass grafts (CABG) are widely
studied with respect to hemodynamic conditions which play
important role in presence of a restenosis. However, papers which
concern with constitutive modeling of CABG are lacking in the
literature. The purpose of this study is to find a constitutive model for
CABG tissue. A sample of the CABG obtained within an autopsy
underwent an inflation–extension test. Displacements were
recoredered by CCD cameras and subsequently evaluated by digital
image correlation. Pressure – radius and axial force – elongation
data were used to fit material model. The tissue was modeled as onelayered
composite reinforced by two families of helical fibers. The
material is assumed to be locally orthotropic, nonlinear,
incompressible and hyperelastic. Material parameters are estimated
for two strain energy functions (SEF). The first is classical
exponential. The second SEF is logarithmic which allows
interpretation by means of limiting (finite) strain extensibility.
Presented material parameters are estimated by optimization based
on radial and axial equilibrium equation in a thick-walled tube. Both
material models fit experimental data successfully. The exponential
model fits significantly better relationship between axial force and
axial strain than logarithmic one.
Abstract: Main Memory Database systems (MMDB) store their
data in main physical memory and provide very high-speed access.
Conventional database systems are optimized for the particular
characteristics of disk storage mechanisms. Memory resident
systems, on the other hand, use different optimizations to structure
and organize data, as well as to make it reliable.
This paper provides a brief overview on MMDBs and one of the
memory resident systems named FastDB and compares the
processing time of this system with a typical disc resident database
based on the results of the implementation of TPC benchmarks
environment on both.
Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: In this paper, a decision aid method for preoptimization
is presented. The method is called “negotiation", and it
is based on the identification, formulation, modeling and use of
indicators defined as “negotiation indicators". These negotiation
indicators are used to explore the solution space by means of a classbased
approach. The classes are subdomains for the negotiation
indicators domain. They represent equivalent cognitive solutions in
terms of the negotiation indictors being used. By this method, we
reduced the size of the solution space and the criteria, thus aiding the
optimization methods. We present an example to show the method.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: Optimization plays an important role in most real
world applications that support decision makers to take the right
decision regarding the strategic directions and operations of the
system they manage. Solutions for traffic management and traffic
congestion problems are considered major problems that most
decision making authorities for cities around the world are looking
for. This review paper gives a full description of the traffic problem
as part of the transportation planning process and present a view as a
framework of urban transportation system analysis where the core of
the system is a transportation network equilibrium model that is
based on optimization techniques and that can also be used for
evaluating an alternative solution or a combination of alternative
solutions for the traffic congestion. Different transportation network
equilibrium models are reviewed from the sequential approach to the
multiclass combining trip generation, trip distribution, modal split,
trip assignment and departure time model. A GIS-Based intelligent
decision support system framework for urban transportation system
analysis is suggested for implementation where the selection of
optimized alternative solutions, single or packages, will be based on
an intelligent agent rather than human being which would lead to
reduction in time, cost and the elimination of the difficulty, by
human being, for finding the best solution to the traffic congestion
problem.
Abstract: This paper aims at overviewing the topics of a research project (CARDIOSENSOR) on the field of health sciences (biomaterials and biomedical engineering). The project has focused on the development of a nanosensor for the assessment of the risk of cardiovascular diseases by the monitoring of C-reactive protein (CRP), which has been currently considered as the best validated inflammatory biomarker associated to cardiovascular diseases. The project involves tasks such as: 1) the development of sensor devices based on field effect transistors (FET): assembly, optimization and validation; 2) application of sensors to the detection of CRP in standard solutions and comparison with enzyme-linked immunosorbent assay (ELISA); and 3) application of sensors to real samples such as blood and saliva and evaluation of their ability to predict the risk of cardiovascular disease.
Abstract: Minor problems arising from optimizations by
welding of fixed prostheses frameworks can be identified by
macroscopic and microscopic visual inspection. The purpose of this
study was to highlight the visible discontinuities present in the laser
welds of dental Ni-Cr alloys. Ni-Cr base metal alloys designated for
fixed prostheses manufacture were selected for the experiments.
Using cast plates, preliminary tests were conducted by laser welding.
Macroscopic visual inspection was done carefully to assess the
defects of the welding rib. Electron microscopy images allowed
visualization of small discontinuities, which escapes visual
inspection. Making comparison to Ni-Cr alloys taken in the
experiment and laser welded, after visual analysis, the best welds
appear for Heraenium NA alloy.
Abstract: With the advent of DSL services, high data rates are now available over phone lines, yet higher rates are in demand. In this paper, we optimize the transmit filters that can be used over wireline channels. Results showing the bit error rates when optimized filters are used, and with a decision feedback equalizer (DFE) employed in the receiver, are given. We then show that significantly higher throughput can be achieved by modeling the channel as a multiple input multiple output (MIMO) channel. A receiver that employs a MIMO-DFE that deals jointly with several users is proposed and shown to provide significant improvement over the conventional DFE.
Abstract: Very Large and/or computationally complex optimization problems sometimes require parallel or highperformance computing for achieving a reasonable time for computation. One of the most popular and most complicate problems of this family is “Traveling Salesman Problem". In this paper we have introduced a Branch & Bound based algorithm for the solution of such complicated problems. The main focus of the algorithm is to solve the “symmetric traveling salesman problem". We reviewed some of already available algorithms and felt that there is need of new algorithm which should give optimal solution or near to the optimal solution. On the basis of the use of logarithmic sampling, it was found that the proposed algorithm produced a relatively optimal solution for the problem and results excellent performance as compared with the traditional algorithms of this series.
Abstract: The paper presents the virtual model of the active
suspension system used for improving the dynamic behavior of a
motor vehicle. The study is focused on the design of the control
system, the purpose being to minimize the effect of the road
disturbances (which are considered as perturbations for the control
system). The analysis is performed for a quarter-car model, which
corresponds to the suspension system of the front wheel, by using the
DFC (Design for Control) software solution EASY5 (Engineering
Analysis Systems) of MSC Software. The controller, which is a PIDbased
device, is designed through a parametric optimization with the
Matrix Algebra Tool (MAT), considering the gain factors as design
variables, while the design objective is to minimize the overshoot of
the indicial response.
Abstract: Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.