Modeling of Gas Turbine Cooled Blades

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.

Inter-Phase Magnetic Coupling Effects on Sensorless SR Motor Control

Control of commutation of switched reluctance (SR) motor has been an area of interest for researchers for sometime now with mixed successes in addressing the inherent challenges. New technologies, processing schemes and methods have been adopted to make sensorless SR drive a reality. There are a number of conceptual, offline, analytical and online solutions in literature that have varying complexities and achieved equally varying degree of robustness and accuracies depending on the method used to address the challenges and the SR drive application. Magnetic coupling is one such challenge when using active probing techniques to determine rotor position of a SR motor from stator winding. This paper studies the effect of back-of-core saturation on the detected rotor position and presents results on measurement made on a 4- phase SR motor. The results shows that even for a four phase motor which is excited one phase at a time and using the electrically opposite phase for active position probing, the back-of-core saturation effects should not be ignored.

Microstructure and Mechanical Behaviuor of Rotary Friction Welded Titanium Alloys

Ti-6Al-4V alloy has demonstrated a high strength to weight ratio as well as good properties at high temperature. The successful application of the alloy in some important areas depends on suitable joining techniques. Friction welding has many advantageous features to be chosen for joining Titanium alloys. The present work investigates the feasibility of producing similar metal joints of this Titanium alloy by rotary friction welding method. The joints are produced at three different speeds and the performances of the welded joints are evaluated by conducting microstructure studies, Vickers Hardness and tensile tests at the joints. It is found that the weld joints produced are sound and the ductile fractures in the tensile weld specimens occur at locations away from the welded joints. It is also found that a rotational speed of 1500 RPM can produce a very good weld, with other parameters kept constant.

Numerical Simulation of Wall Treatment Effects on the Micro-Scale Combustion

To understand working features of a micro combustor, a computer code has been developed to study combustion of hydrogen–air mixture in a series of chambers with same shape aspect ratio but various dimensions from millimeter to micrometer level. The prepared algorithm and the computer code are capable of modeling mixture effects in different fluid flows including chemical reactions, viscous and mass diffusion effects. The effect of various heat transfer conditions at chamber wall, e.g. adiabatic wall, with heat loss and heat conduction within the wall, on the combustion is analyzed. These thermal conditions have strong effects on the combustion especially when the chamber dimension goes smaller and the ratio of surface area to volume becomes larger. Both factors, such as larger heat loss through the chamber wall and smaller chamber dimension size, may lead to the thermal quenching of micro-scale combustion. Through such systematic numerical analysis, a proper operation space for the micro-combustor is suggested, which may be used as the guideline for microcombustor design. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the micro-combustor design, optimization and performance analysis.

Reactive Neural Control for Phototaxis and Obstacle Avoidance Behavior of Walking Machines

This paper describes reactive neural control used to generate phototaxis and obstacle avoidance behavior of walking machines. It utilizes discrete-time neurodynamics and consists of two main neural modules: neural preprocessing and modular neural control. The neural preprocessing network acts as a sensory fusion unit. It filters sensory noise and shapes sensory data to drive the corresponding reactive behavior. On the other hand, modular neural control based on a central pattern generator is applied for locomotion of walking machines. It coordinates leg movements and can generate omnidirectional walking. As a result, through a sensorimotor loop this reactive neural controller enables the machines to explore a dynamic environment by avoiding obstacles, turn toward a light source, and then stop near to it.

Performance Evaluation and Modeling of a Conical Plunging Jet Aerator

Aeration by a plunging water jet is an energetically attractive way to effect oxygen-transfer than conventional oxygenation systems. In the present study, a new type of conical shaped plunging aeration device is fabricated to generate hollow inclined ined plunging jets (jet plunge angle of π/3 ) to investigate its oxygen transfer capacity. The results suggest that the volumetric oxygen-transfer coefficient and oxygen-transfer efficiency of the conical plunging jet aerator are competitive with other types of aeration systems. Relationships of volumetric oxygen-transfer coefficient with jet power per unit volume and jet parameters are also proposed. The suggested relationships predict the volumetric oxygentransfer coefficient within a scatter of ± 15% . Further, the application of Support Vector Machines on the experimental data revealed its utility in the prediction of volumetric oxygen-transfer coefficient and development of conical plunging jet aerators.

T-DOF PI Controller Design for a Speed Control of Induction Motor

This paper presents design and implements the T-DOF PI controller design for a speed control of induction motor. The voltage source inverter type space vector pulse width modulation technique is used the drive system. This scheme leads to be able to adjust the speed of the motor by control the frequency and amplitude of the input voltage. The ratio of input stator voltage to frequency should be kept constant. The T-DOF PI controller design by root locus technique is also introduced to the system for regulates and tracking speed response. The experimental results in testing the 120 watt induction motor from no-load condition to rated condition show the effectiveness of the proposed control scheme.

Predicting Extrusion Process Parameters Using Neural Networks

The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

A Fiber Optic Interferometric Sensor for Dynamic Measurement

An optical fiber Fabry-Perot interferometer (FFPI) is proposed and demonstrated for dynamic measurements in a mechanical vibrating target. A polishing metal with a low reflectance value adhered to a mechanical vibrator was excited via a function generator at various excitation frequencies. Output interference fringes were generated by modulating the reference and sensing signal at the output arm. A fringe-counting technique was used for interpreting the displacement information on the dedicated computer. The fiber interferometer has been found the capability of the displacement measurements of 1.28 μm – 96.01 μm. A commercial displacement sensor was employed as a reference sensor for investigating the measurement errors from the fiber sensor. A maximum percentage measurement error of approximately 1.59 % was obtained.

An Analysis of Activity-Based Costing in a Manufacturing System

Activity-Based Costing (ABC) represents an alternative paradigm to traditional cost accounting system and it often provides more accurate cost information for decision making such as product pricing, product mix, and make-orbuy decisions. ABC models the causal relationships between products and the resources used in their production and traces the cost of products according to the activities through the use of appropriate cost drivers. In this paper, the implementation of the ABC in a manufacturing system is analyzed and a comparison with the traditional cost based system in terms of the effects on the product costs are carried out to highlight the difference between two costing methodologies. By using this methodology, a valuable insight into the factors that cause the cost is provided, helping to better manage the activities of the company.

Using Fuzzy Controller in Induction Motor Speed Control with Constant Flux

Variable speed drives are growing and varying. Drives expanse depend on progress in different part of science like power system, microelectronic, control methods, and so on. Artificial intelligent contains hard computation and soft computation. Artificial intelligent has found high application in most nonlinear systems same as motors drive. Because it has intelligence like human but there are no sentimental against human like angriness and.... Artificial intelligent is used for various points like approximation, control, and monitoring. Because artificial intelligent techniques can use as controller for any system without requirement to system mathematical model, it has been used in electrical drive control. With this manner, efficiency and reliability of drives increase and volume, weight and cost of them decrease.

Multi Objective Micro Genetic Algorithm for Combine and Reroute Problem

Several approaches such as linear programming, network modeling, greedy heuristic and decision support system are well-known approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Micro Genetic Algorithm. The aim of this research is to introduce the concept of Multi Objective Micro Genetic Algorithm as a tool to solve irregular airline operation, combine and reroute problem. The experiment result indicated that the model could obtain optimal solutions within a few second.

An Analysis of Collapse Mechanism of Thin- Walled Circular Tubes Subjected to Bending

Circular tubes have been widely used as structural members in engineering application. Therefore, its collapse behavior has been studied for many decades, focusing on its energy absorption characteristics. In order to predict the collapse behavior of members, one could rely on the use of finite element codes or experiments. These tools are helpful and high accuracy but costly and require extensive running time. Therefore, an approximating model of tubes collapse mechanism is an alternative for early step of design. This paper is also aimed to develop a closed-form solution of thin-walled circular tube subjected to bending. It has extended the Elchalakani et al.-s model (Int. J. Mech. Sci.2002; 44:1117-1143) to include the rate of energy dissipation of rolling hinge in the circumferential direction. The 3-D geometrical collapse mechanism was analyzed by adding the oblique hinge lines along the longitudinal tube within the length of plastically deforming zone. The model was based on the principal of energy rate conservation. Therefore, the rates of internal energy dissipation were calculated for each hinge lines which are defined in term of velocity field. Inextensional deformation and perfect plastic material behavior was assumed in the derivation of deformation energy rate. The analytical result was compared with experimental result. The experiment was conducted with a number of tubes having various D/t ratios. Good agreement between analytical and experiment was achieved.

A Method for Quality Inspection of Motors by Detecting Abnormal Sound

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Complex Condition Monitoring System of Aircraft Gas Turbine Engine

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.