Vortex Shedding on Combined Bodies at Incidence to a Uniform Air Stream

Vortex-shedding phenomenon of the flow around combined two bodies having various geometries and sizes has been investigated experimentally in the Reynolds number range between 4.1x103 and 1.75x104. To see the effect of the rotation of the bodies on the vortex shedding, the combined bodies were rotated from 0° to 180°. The combined models have a cross section composing of a main circular cylinder and an attached circular or square cylinder. Results have shown that Strouhal numbers for two cases were changed considerably with the angle of incidence, while it was found to be largely independent of Reynolds number at 150. Characteristics of the vortex formation region and location of flow attachments, reattachments, and separations were observed by means of the flow visualizations. Depending on the inclination angle the effects of flow attachment, separation and reattachment on vortex-shedding phenomenon have been discussed.

The Best Efficiency Point of the Performance of Solar Cell Panel System for Pumping Water at Various Lifting Heads Using 100 W Motor- Pump Unit

This study was carried out experimentally and analytically about the performance of solar cell panel system for operating the pump coupled by dc-motor. The solar cell panel with total area 1.9848 m2 consists of three modules of 80 Wp each. The small centrifugal pump powered by dc-motor is operated to lift water from 1m to 7m heads in sequence and gives the amount of water pumped over the whole day from 08.00 to 16.00 h are 11988, 10851, 8874, 7695, 5760, 3600, 2340 L/d respectively. The hourly global solar radiation during the day is an average of 506 W/m2. This study also presents the I-V characteristics of the panel at global radiations 200, 400, 600, 800 and 1000 W/m2 matched with the operation of the pump at the above lifting heads. It proves that the only solar radiations 800 and 1000 W/m2 could provide lifting head from 1m to 7m. The analysis shows the best efficiency point of the performance of solar cell panel system occurs at the pumping head 2.89 m.

Solar Tracking System: More Efficient Use of Solar Panels

This paper shows the potential system benefits of simple tracking solar system using a stepper motor and light sensor. This method is increasing power collection efficiency by developing a device that tracks the sun to keep the panel at a right angle to its rays. A solar tracking system is designed, implemented and experimentally tested. The design details and the experimental results are shown.

Steady State Transpiration Cooling System in Ni-Cr Open-Cellular Porous Plate

The steady-state temperature for one-dimensional transpiration cooling system has been conducted experimentally and numerically to investigate the heat transfer characteristics of combined convection and radiation. The Nickel –Chrome (Ni-Cr) open-cellular porous material having porosity of 0.93 and pores per inch (PPI) of 21.5 was examined. The upper surface of porous plate was heated by the heat flux of incoming radiation varying from 7.7 - 16.6 kW/m2 whereas air injection velocity fed into the lower surface was varied from 0.36 - 1.27 m/s, and was then rearranged as Reynolds number (Re). For the report of the results in the present study, two efficiencies including of temperature and conversion efficiency were presented. Temperature efficiency indicating how close the mean temperature of a porous heat plate to that of inlet air, and increased rapidly with the air injection velocity (Re). It was then saturated and had a constant value at Re higher than 10. The conversion efficiency, which was regarded as the ability of porous material in transferring energy by convection after absorbed from heat radiation, decreased with increasing of the heat flux and air injection velocity. In addition, it was then asymptotic to a constant value at the Re higher than 10. The numerical predictions also agreed with experimental data very well.

Low Air Velocity Measurement Characteristics- Variation Due to Flow Regime

The paper depicts air velocity values, reproduced by laser Doppler anemometer (LDA) and ultrasonic anemometer (UA), relations with calculated ones from flow rate measurements using the gas meter which calibration uncertainty is ± (0.15 – 0.30) %. Investigation had been performed in channel installed in aerodynamical facility used as a part of national standard of air velocity. Relations defined in a research let us confirm the LDA and UA for air velocity reproduction to be the most advantageous measures. The results affirm ultrasonic anemometer to be reliable and favourable instrument for measurement of mean velocity or control of velocity stability in the velocity range of 0.05 m/s – 10 (15) m/s when the LDA used. The main aim of this research is to investigate low velocity regularities, starting from 0.05 m/s, including region of turbulent, laminar and transitional air flows. Theoretical and experimental results and brief analysis of it are given in the paper. Maximum and mean velocity relations for transitional air flow having unique distribution are represented. Transitional flow having distinctive and different from laminar and turbulent flow characteristics experimentally have not yet been analysed.

Concrete Mix Design Using Neural Network

Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

A Study on the Location and Range of Obstacle Region in Robot's Point Placement Task based on the Vision Control Algorithm

This paper is concerned with the application of the vision control algorithm for robot's point placement task in discontinuous trajectory caused by obstacle. The presented vision control algorithm consists of four models, which are the robot kinematic model, vision system model, parameters estimation model, and robot joint angle estimation model.When the robot moves toward a target along discontinuous trajectory, several types of obstacles appear in two obstacle regions. Then, this study is to investigate how these changes will affect the presented vision control algorithm.Thus, the practicality of the vision control algorithm is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.

A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks

Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.

Autonomous Underwater Vehicle (AUV) Dynamics Modeling and Performance Evaluation

A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.

Two Different Solutions for Gigabit Ethernet Transmission over POF

Two completely different approaches for a Gigabit Ethernet compliant stream transmission over 50m of 1mm PMMA SI-POF have been experimentally demonstrated and are compared in this paper. The first solution is based on a commercial RC-LED transmission and a careful optimization of the physical layer architecture, realized during the POF-PLUS EU Project. The second solution exploits the performance of an edge-emitting laser at the transmitter side in order to avoid any sort of electrical equalization at the receiver side.

Experimental Investigation of Combustion Chamber Dimensions Effects on Pollutant Emission and Combustion Efficiency

The combustion chamber dimensions have important effects on pollutant emission in furnaces as a direct result of temperature distribution and maximum temperature value. In this paper the pollutant emission and the temperature distribution in two cylindrical furnaces with different dimensions (with similar length to diameter ratio) in similar condition have been investigated experimentally. The furnace fuel is gas oil that is used with three different flow rates. The results show that in these two cases the temperature increases to its maximum value quickly, and then decreases slowly. The results also show that increase in fuel flow rate cause to increase in NOx emission in each case, but this increase is greater in small furnace. With increase in fuel flow rate, CO emission decreases firstly, and then it increases. Combustion efficiency reduces with increase in fuel flow rate but the rate of reduction in small furnace is greater than large furnace. The results of axial temperature distribution have been compared with those have been obtained numerically and experimentally by Moghiman.

Energy Systems and Crushing Behavior of Fiber Reinforced Composite Materials

Effect of geometry on crushing behavior, energy absorption and failure mode of woven roving jute fiber/epoxy laminated composite tubes were experimentally studied. Investigations were carried out on three different geometrical types of composite tubes (circular, square and radial corrugated) subjected to axial compressive loading. It was observed in axial crushing study that the load bearing capability is significantly influenced by corrugation geometry. The influence of geometries of specimens was supported by the plotted load – displacement curves of the tests.

Visual Study on Flow Patterns and Heat Transfer during Convective Boiling Inside Horizontal Smooth and Microfin Tubes

Evaporator is an important and widely used heat exchanger in air conditioning and refrigeration industries. Different methods have been used by investigators to increase the heat transfer rates in evaporators. One of the passive techniques to enhance heat transfer coefficient is the application of microfin tubes. The mechanism of heat transfer augmentation in microfin tubes is dependent on the flow regime of two-phase flow. Therefore many investigations of the flow patterns for in-tube evaporation have been reported in literatures. The gravitational force, surface tension and the vapor-liquid interfacial shear stress are known as three dominant factors controlling the vapor and liquid distribution inside the tube. A review of the existing literature reveals that the previous investigations were concerned with the two-phase flow pattern for flow boiling in horizontal tubes [12], [9]. Therefore, the objective of the present investigation is to obtain information about the two-phase flow patterns for evaporation of R-134a inside horizontal smooth and microfin tubes. Also Investigation of heat transfer during flow boiling of R-134a inside horizontal microfin and smooth tube have been carried out experimentally The heat transfer coefficients for annular flow in the smooth tube is shown to agree well with Gungor and Winterton-s correlation [4]. All the flow patterns occurred in the test can be divided into three dominant regimes, i.e., stratified-wavy flow, wavy-annular flow and annular flow. Experimental data are plotted in two kinds of flow maps, i.e., Weber number for the vapor versus weber number for the liquid flow map and mass flux versus vapor quality flow map. The transition from wavy-annular flow to annular or stratified-wavy flow is identified in the flow maps.

Can Nipple Be Used as a Good Indicator of Breast in Breast Motion Research?

There were many studies on how to alleviate breast discomfort by reducing breast motion, in which nipple motion was used to represent breast motion. However, this assumption had not been experimentally validated. The aim of this paper was to experimentally validate if nipple can be used as a good indicator of breast. Seven participants (average of 24.4 years old) were recruited to walk and run on the treadmill at 5km h-1 and 10km h-1 respectively. Six markers were pasted on their bodies to collect motion data of different parts of breasts. The results of Friedman test combined with the relationship among the five markers on the same breast revealed that nipple could be used as a good indicator of breast. Wilcoxon test showed that there was no significant (P

Propagation of Viscous Waves and Activation Energy of Hydrocarbon Fluids

The Euler-s equation of motion is extended to include the viscosity stress tensor leading to the formulation of Navier– Stokes type equation. The latter is linearized and applied to investigate the rotational motion or vorticity in a viscous fluid. Relations for the velocity of viscous waves and attenuation parameter are obtained in terms of viscosity (μ) and the density (¤ü) of the fluid. μ and ¤ü are measured experimentally as a function of temperature for two different samples of light and heavy crude oil. These data facilitated to determine the activation energy, velocity of viscous wave and the attenuation parameter. Shear wave velocity in heavy oil is found to be much larger than the light oil, whereas the attenuation parameter in heavy oil is quite low in comparison to light one. The activation energy of heavy oil is three times larger than light oil.

Design Optimization of Cutting Parameters when Turning Inconel 718 with Cermet Inserts

Inconel 718, a nickel based super-alloy is an extensively used alloy, accounting for about 50% by weight of materials used in an aerospace engine, mainly in the gas turbine compartment. This is owing to their outstanding strength and oxidation resistance at elevated temperatures in excess of 5500 C. Machining is a requisite operation in the aircraft industries for the manufacture of the components especially for gas turbines. This paper is concerned with optimization of the surface roughness when turning Inconel 718 with cermet inserts. Optimization of turning operation is very useful to reduce cost and time for machining. The approach is based on Response Surface Method (RSM). In this work, second-order quadratic models are developed for surface roughness, considering the cutting speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models are used to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in reasonable agreement with the predicted values.

An Investigation into Turbine Blade Tip Leakage Flows at High Speeds

The effect of the blade tip geometry of a high pressure gas turbine is studied experimentally and computationally for high speed leakage flows. For this purpose two simplified models are constructed, one models a flat tip of the blade and the second models a cavity tip of the blade. Experimental results are obtained from a transonic wind tunnel to show the static pressure distribution along the tip wall and provide flow visualization. RANS computations were carried to provide further insight into the mean flow behavior and to calculate the discharge coefficient which is a measure of the flow leaking over the tip. It is shown that in both geometries of tip the flow separates over the tip to form a separation bubble. The bubble is higher for the cavity tip while a complete shock wave system of oblique waves ending with a normal wave can be seen for the flat tip. The discharge coefficient for the flat tip shows less dependence on the pressure ratio over the blade tip than the cavity tip. However, the discharge coefficient for the cavity tip is lower than that of the flat tip, showing a better ability to reduce the leakage flow and thus increase the turbine efficiency.

Operational risks Classification for Information Systems with Service-Oriented Architecture (Including Loss Calculation Example)

This article presents the results of a study conducted to identify operational risks for information systems (IS) with service-oriented architecture (SOA). Analysis of current approaches to risk and system error classifications revealed that the system error classes were never used for SOA risk estimation. Additionally system error classes are not normallyexperimentally supported with realenterprise error data. Through the study several categories of various existing error classifications systems are applied and three new error categories with sub-categories are identified. As a part of operational risks a new error classification scheme is proposed for SOA applications. It is based on errors of real information systems which are service providers for application with service-oriented architecture. The proposed classification approach has been used to classify SOA system errors for two different enterprises (oil and gas industry, metal and mining industry). In addition we have conducted a research to identify possible losses from operational risks.

An Autonomous Collaborative Forecasting System Implementation – The First Step towards Successful CPFR System

In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Investigation of Drying Kinetics of Viscose Yarn Bobbins

This study is concerned with the investigation of the suitability of several empirical and semi-empirical drying models available in the literature to define drying behavior of viscose yarn bobbins. For this purpose, firstly, experimental drying behaviour of viscose bobbins was determined on an experimental dryer setup which was designed and manufactured based on hot-air bobbin dryers used in textile industry. Afterwards, drying models considered were fitted to the experimentally obtained moisture ratios. Drying parameters were drying temperature and bobbin diameter. The fit was performed by selecting the values for constants in the models in such a way that these values make the sum of the squared differences between the experimental and the model results for moisture ratio minimum. Suitability of fitting was specified as comparing the correlation coefficient, standard error and mean square deviation. The results show that the most appropriate model in describing the drying curves of viscose bobbins is the Page model.