Modeling and Simulation of Switched Reluctance Motor with Three-Phase and Four- Phase Configurations

The reluctance motor is an electric motor in which torque is produced by the tendency of its moveable part to move to a position where the inductance of the excited winding is maximized. In this paper switched reluctance motors (SRMs) with two different configurations(3-phase SRM with 4rotor poles and 6 stator poles, 4- phase SRM with 6rotor poles and 8 stator poles) is designed by RMxprt, and performance of them is analyzed. Efficiency and torque of SRM for different configurations in full-load condition have been presented. The results indicate that with correct choosing of motor applications, maximum efficiency can be found.

Parametric Modeling Approach for Call Holding Times for IP based Public Safety Networks via EM Algorithm

This paper presents parametric probability density models for call holding times (CHTs) into emergency call center based on the actual data collected for over a week in the public Emergency Information Network (EIN) in Mongolia. When the set of chosen candidates of Gamma distribution family is fitted to the call holding time data, it is observed that the whole area in the CHT empirical histogram is underestimated due to spikes of higher probability and long tails of lower probability in the histogram. Therefore, we provide the Gaussian parametric model of a mixture of lognormal distributions with explicit analytical expressions for the modeling of CHTs of PSNs. Finally, we show that the CHTs for PSNs are fitted reasonably by a mixture of lognormal distributions via the simulation of expectation maximization algorithm. This result is significant as it expresses a useful mathematical tool in an explicit manner of a mixture of lognormal distributions.

Flight Control of a Trirotor Mini-UAV for Enhanced Situational Awareness

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for an unmanned aerial vehicle (UAV). Autonomous vertical flight is a challenging but important task for tactical UAVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a two stage flight control procedure using two autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for a nontrivial nonlinear trirotor mini-UAV model. This control strategy for chosen mini-UAV model has been verified by simulation of hovering maneuvers using software package Simulink and demonstrated good performance for fast SA in realtime search-and-rescue operations.

Space Vector PWM Simulation for Three Phase DC/AC Inverter

Space Vector Pulse Width Modulation SVPWM is one of the most used techniques to generate sinusoidal voltage and current due to its facility and efficiency with low harmonics distortion. This algorithm is specially used in power electronic applications. This paper describes simulation algorithm of SVPWM & SPWM using MatLab/simulink environment. It also implements a closed loop three phases DC-AC converter controlling its outputs voltages amplitude and frequency using MatLab. Also comparison between SVPWM & SPWM results is given.

Portfolio Simulation in GSM Cellular Telecommunication Industry for Company's Decision and Policies Making

The rising growth of the GSM cellular phone industry has tightening competition level between providers in making strategies enhancing the market shares in Indonesia. Tsel, as one of those companies, has to determine the proper strategy to sustain as well as improve the market share without reducing its operational income level. Portfolio simulation model is designed with a dynamic system approach. The result of this research is a recommendation to the company by optimizing its technological policies, services, and promotions. The tariff policies and the signal quality should not be the main focus because this company has had a large number of customers and a good infrastructural condition.

Schmitt Trigger Based SRAM Using Finfet Technology- Shorted Gate Mode

The most widely used semiconductor memory types are the Dynamic Random Access Memory (DRAM) and Static Random Access memory (SRAM). Competition among memory manufacturers drives the need to decrease power consumption and reduce the probability of read failure. A technology that is relatively new and has not been explored is the FinFET technology. In this paper, a single cell Schmitt Trigger Based Static RAM using FinFET technology is proposed and analyzed. The accuracy of the result is validated by means of HSPICE simulations with 32nm FinFET technology and the results are then compared with 6T SRAM using the same technology.

MATLAB/SIMULINK Based Model of Single- Machine Infinite-Bus with TCSC for Stability Studies and Tuning Employing GA

With constraints on data availability and for study of power system stability it is adequate to model the synchronous generator with field circuit and one equivalent damper on q-axis known as the model 1.1. This paper presents a systematic procedure for modelling and simulation of a single-machine infinite-bus power system installed with a thyristor controlled series compensator (TCSC) where the synchronous generator is represented by model 1.1, so that impact of TCSC on power system stability can be more reasonably evaluated. The model of the example power system is developed using MATLAB/SIMULINK which can be can be used for teaching the power system stability phenomena, and also for research works especially to develop generator controllers using advanced technologies. Further, the parameters of the TCSC controller are optimized using genetic algorithm. The non-linear simulation results are presented to validate the effectiveness of the proposed approach.

Vibration Base Identification of Impact Force Using Genetic Algorithm

This paper presents the identification of the impact force acting on a simply supported beam. The force identification is an inverse problem in which the measured response of the structure is used to determine the applied force. The identification problem is formulated as an optimization problem and the genetic algorithm is utilized to solve the optimization problem. The objective function is calculated on the difference between analytical and measured responses and the decision variables are the location and magnitude of the applied force. The results from simulation show the effectiveness of the approach and its robustness vs. the measurement noise and sensor location.

AGENTMAP: A Conceptual Meta-Model of Interacting Simulations

A straightforward and intuitive combination of single simulations into an aggregated master-simulation is not trivial. There are lots of problems, which trigger-specific difficulties during the modeling and execution of such a simulation. In this paper we identify these problems and aim to solve them by mapping the task to the field of multi agent systems. The solution is a new meta-model named AGENTMAP, which is able to mitigate most of the problems and to support intuitive modeling at the same time. This meta-model will be introduced and explained on basis of an example from the e-commerce domain.

An Enhance of the Energy Effectiveness of the Convectors Used for Heating or Cooling

The objective of this paper is to present a research study of the convectors that are used for heating or cooling of the living room or industrial halls. The key points are experimental measurement and comprehensive numerical simulation of the flow coming throughout the part of the convector such as heat exchanger, input from the fan etc.. From the obtained results, the components of the convector are optimized in sense to increase thermal power efficiency due to improvement of heat convection or reduction of air drag friction. Both optimized aspects are leading to the more effective service conditions and to energy saving. The significant part of the convector research is a design of the unique measurement laboratory and adopting measure techniques. The new laboratory provides possibility to measure thermal power efficiency and other relevant parameters under specific service conditions of the convectors.

Adaptive Kernel Principal Analysis for Online Feature Extraction

The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard KPCA.This formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.

Cash Flow Optimization on Synthetic CDOs

Collateralized Debt Obligations are not as widely used nowadays as they were before 2007 Subprime crisis. Nonetheless there remains an enthralling challenge to optimize cash flows associated with synthetic CDOs. A Gaussian-based model is used here in which default correlation and unconditional probabilities of default are highlighted. Then numerous simulations are performed based on this model for different scenarios in order to evaluate the associated cash flows given a specific number of defaults at different periods of time. Cash flows are not solely calculated on a single bought or sold tranche but rather on a combination of bought and sold tranches. With some assumptions, the simplex algorithm gives a way to find the maximum cash flow according to correlation of defaults and maturities. The used Gaussian model is not realistic in crisis situations. Besides present system does not handle buying or selling a portion of a tranche but only the whole tranche. However the work provides the investor with relevant elements on how to know what and when to buy and sell.

High Precision Draw Bending of Asymmetric Channel Section with Restriction Dies and Axial Tension

In recent years asymmetric cross section aluminum alloy stock has been finding increasing use in various industrial manufacturing areas such as general structures and automotive components. In these areas, components are generally required to have complex curved configuration and, as such, a bending process is required during manufacture. Undesirable deformation in bending processes such as flattening or wrinkling can easily occur when thin-walled sections are bent. Hence, a thorough understanding of the bending behavior of such sections is needed to prevent these undesirable deformations. In this study, the bending behavior of asymmetric channel section was examined using finite element analysis (FEA). Typical methods of preventing undesirable deformation, such as asymmetric laminated elastic mandrels were included in FEA model of draw bending. Additionally, axial tension was applied to prevent wrinkling. By utilizing the FE simulations effect of restriction dies and axial tension on undesirable deformation during the process was clarified.

Mathematical Simulation of Bubble Column Slurry Reactor for Direct Dimethyl Ether Synthesis Process from Syngas

Based on a global kinetics of direct dimethyl ether (DME) synthesis process from syngas, a steady-state one-dimensional mathematical model for the bubble column slurry reactor (BCSR) has been established. It was built on the assumption of plug flow of gas phase, sedimentation-dispersion model of catalyst grains and isothermal chamber regardless of reaction heats and rates for the design of an industrial scale bubble column slurry reactor. The simulation results indicate that higher pressure and lower temperature were favorable to the increase of CO conversion, DME selectivity, products yield and the height of slurry bed, which has a coincidence with the characteristic of DME synthesis reaction system, and that the height of slurry bed is lessen with the increasing of operation temperature in the range of 220-260℃. CO conversion, the optimal operation conditions in BCSR were proposed. 

An Improved ICI Self-Cancellation Scheme for Multi-Carrier Communication Systems

For broadband wireless mobile communication systems the orthogonal frequency division multiplexing (OFDM) is a suitable modulation scheme. The frequency offset between transmitter and receiver local oscillator is main drawback of OFDM systems, which causes intercarrier interference (ICI) in the subcarriers of the OFDM system. This ICI degrades the bit error rate (BER) performance of the system. In this paper an improved self-ICI cancellation scheme is proposed to improve the system performance. The proposed scheme is based on discrete Fourier transform-inverse discrete Fourier transform (DFT-IDFT). The simulation results show that there is satisfactory improvement in the bit error rate (BER) performance of the present scheme.

Tree-on-DAG for Data Aggregation in Sensor Networks

Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.

Impacts of Global Warming on the World Food Market According to SRES Scenarios

This research examines possible effects of climatic change focusing on global warming and its impacts on world agricultural product markets, by using a world food model developed to consider climate changes. GDP and population for each scenario were constructed by IPCC and climate data for each scenario was reported by the Hadley Center and are used in this research to consider results in different contexts. Production and consumption of primary agriculture crops of the world for each socio-economic scenario are obtained and investigated by using the modified world food model. Simulation results show that crop production in some countries or regions will have different trends depending on the context. These alternative contexts depend on the rate of GDP growth, population, temperature, and rainfall. Results suggest that the development of environment friendly technologies lead to more consumption of food in many developing countries. Relationships among environmental policy, clean energy development, and poverty elimination warrant further investigation.

A Discretizing Method for Reliability Computation in Complex Stress-strength Models

This paper proposes, implements and evaluates an original discretization method for continuous random variables, in order to estimate the reliability of systems for which stress and strength are defined as complex functions, and whose reliability is not derivable through analytic techniques. This method is compared to other two discretizing approaches appeared in literature, also through a comparative study involving four engineering applications. The results show that the proposal is very efficient in terms of closeness of the estimates to the true (simulated) reliability. In the study we analyzed both a normal and a non-normal distribution for the random variables: this method is theoretically suitable for each parametric family.

A Robust Frequency Offset Estimation Scheme for OFDM System with Cyclic Delay Diversity

Cyclic delay diversity (CDD) is a simple technique to intentionally increase frequency selectivity of channels for orthogonal frequency division multiplexing (OFDM).This paper proposes a residual carrier frequency offset (RFO) estimation scheme for OFDMbased broadcasting system using CDD. In order to improve the RFO estimation, this paper addresses a decision scheme of the amount of cyclic delay and pilot pattern used to estimate the RFO. By computer simulation, the proposed estimator is shown to benefit form propoerly chosen delay parameter and perform robustly.

PID Controller Design for Following Control of Hard Disk Drive by Characteristic Ratio Assignment Method

The author present PID controller design for following control of hard disk drive by characteristic ratio assignment method. The study in this paper concerns design of a PID controller which sufficiently robust to the disturbances and plant perturbations on following control of hard disk drive. Characteristic Ratio Assignment (CRA) is shown to be an efficient control technique to serve this requirement. The controller design by CRA is based on the choice of the coefficients of the characteristic polynomial of the closed loop system according to the convenient performance criteria such as equivalent time constant and ration of characteristic coefficient. Hence, in this study, CRA method is applied in PID controller design for following control of hard disk drive. Matlab simulation results shown that CRA design is fairly stable and robust whilst giving the convenience in controller-s parameters adjustment.