CFD Simulations to Validate Two and Three Phase Up-flow in Bubble Columns

Bubble columns have a variety of applications in absorption, bio-reactions, catalytic slurry reactions, and coal liquefaction; because they are simple to operate, provide good heat and mass transfer, having less operational cost. The use of Computational Fluid Dynamics (CFD) for bubble column becomes important, since it can describe the fluid hydrodynamics on both local and global scale. Euler- Euler two-phase fluid model has been used to simulate two-phase (air and water) transient up-flow in bubble column (15cm diameter) using FLUENT6.3. These simulations and experiments were operated over a range of superficial gas velocities in the bubbly flow and churn turbulent regime (1 to16 cm/s) at ambient conditions. Liquid velocity was varied from 0 to 16cm/s. The turbulence in the liquid phase is described using the standard k-ε model. The interactions between the two phases are described through drag coefficient formulations (Schiller Neumann). The objectives are to validate CFD simulations with experimental data, and to obtain grid-independent numerical solutions. Quantitatively good agreements are obtained between experimental data for hold-up and simulation values. Axial liquid velocity profiles and gas holdup profiles were also obtained for the simulation.

Modeling and Simulation of Photovoltaic based LED Lighting System

Although lighting systems powered by Photovoltaic (PV) cells have existed for many years, they are not widely used, especially in lighting for buildings, due to their high initial cost and low conversion efficiency. One of the technical challenges facing PV powered lighting systems has been how to use dc power generated by the PV module to energize common light sources that are designed to operate efficiently under ac power. Usually, the efficiency of the dc light sources is very poor compared to ac light sources. Rapid developments in LED lighting systems have made this technology a potential candidate for PV powered lighting systems. This study analyzed the efficiency of each component of PV powered lighting systems to identify optimum system configurations for different applications.

Fast Extraction of Edge Histogram in DCT Domain based on MPEG7

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

An Improved Model for Prediction of the Effective Thermal Conductivity of Nanofluids

Thermal conductivity is an important characteristic of a nanofluid in laminar flow heat transfer. This paper presents an improved model for the prediction of the effective thermal conductivity of nanofluids based on dimensionless groups. The model expresses the thermal conductivity of a nanofluid as a function of the thermal conductivity of the solid and liquid, their volume fractions and particle size. The proposed model includes a parameter which accounts for the interfacial shell, brownian motion, and aggregation of particle. The validation of the model is verified by applying the results obtained by the experiments of Tio2-water and Al2o3-water nanofluids.

Optimal Generation Expansion Planning Strategy with Carbon Trading

Fossil fuel-firing power plants dominate electric power generation in Taiwan, which are also the major contributor to Green House gases (GHG). CO2 is the most important greenhouse gas that cause global warming. This paper penetrates the relationship between carbon trading for GHG reduction and power generation expansion planning (GEP) problem for the electrical utility. The Particle Swarm Optimization (PSO) Algorithm is presented to deal with the generation expansion planning strategy of the utility with independent power providers (IPPs). The utility has to take both the IPPs- participation and environment impact into account when a new generation unit is considering expanded from view of supply side.

Measuring Pressure Wave Velocity in a Hydraulic System

Pressure wave velocity in a hydraulic system was determined using piezo pressure sensors without removing fluid from the system. The measurements were carried out in a low pressure range (0.2 – 6 bar) and the results were compared with the results of other studies. This method is not as accurate as measurement with separate measurement equipment, but the fluid is in the actual machine the whole time and the effect of air is taken into consideration if air is present in the system. The amount of air is estimated by calculations and comparisons between other studies. This measurement equipment can also be installed in an existing machine and it can be programmed so that it measures in real time. Thus, it could be used e.g. to control dampers.

Towards Security in Virtualization of SDN

In this paper, the potential security issues brought by the virtualization of a Software Defined Networks (SDN) would be analyzed. The virtualization of SDN is achieved by FlowVisor (FV). With FV, a physical network is divided into multiple isolated logical networks while the underlying resources are still shared by different slices (isolated logical networks). However, along with the benefits brought by network virtualization, it also presents some issues regarding security. By examining security issues existing in an OpenFlow network, which uses FlowVisor to slice it into multiple virtual networks, we hope we can get some significant results and also can get furtherdiscussions among the security of SDN virtualization.

Effects of Catalyst Tubes Characteristics on a Steam Reforming Process in Ammonia

The tubes in an Ammonia primary reformer furnace operate close to the limits of materials technology in terms of the stress induced as a result of very high temperatures, combined with large differential pressures across the tube wall. Operation at tube wall temperatures significantly above design can result in a rapid increase in the number of tube failures, since tube life is very sensitive to the absolute operating temperature of the tube. Clearly it is important to measure tube wall temperatures accurately in order to prevent premature tube failure by overheating.. In the present study, the catalyst tubes in an Ammonia primary reformer has been modeled taking into consideration heat, mass and momentum transfer as well as reformer characteristics.. The investigations concern the effects of tube characteristics and superficial tube wall temperatures on of the percentage of heat flux, unconverted methane and production of Hydrogen for various values of steam to carbon ratios. The results show the impact of catalyst tubes length and diameters on the performance of operating parameters in ammonia primary reformers.

Fatigue Properties and Strength Degradation of Carbon Fibber Reinforced Composites

A two-parameter fatigue model explicitly accounting for the cyclic as well as the mean stress was used to fit static and fatigue data available in literature concerning carbon fiber reinforced composite laminates subjected tension-tension fatigue. The model confirms the strength–life equal rank assumption and predicts reasonably the probability of failure under cyclic loading. The model parameters were found by best fitting procedures and required a minimum of experimental tests.

Environmental Analysis of Springs in Urban Areas–A Methodological Proposal

The springs located in urban areas are the outpouring of surface water, which can serve as water supply, effluent receptors and important local macro-drainage elements. With unplanned occupation, non-compliance with environmental legislation and the importance of these water bodies, it is vital to analyze the springs within urban areas, considering the Brazilian forest code. This paper submits an analysis and discussion methodology proposal of environmental compliance functions of urban springs, by means of G.I.S. - Geographic Information System analysis - and in situ analysis. The case study included two springs which exhibit a history of occupation along its length, with different degrees of impact. The proposed method is effective and easy to apply, representing a powerful tool for analyzing the environmental conditions of springs in urban areas.

Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process

In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Fabrication of Microfluidic Device for Quantitative Monitoring of Algal Cell Behavior Using X-ray LIGA Technology

In this paper, a simple microfluidic device for monitoring algal cell behavior is proposed. An array of algal microwells is fabricated by PDMS soft-lithography using X-ray LIGA mold, placed on a glass substrate. Two layers of replicated PDMS and substrate are attached by oxygen plasma bonding, creating a microchannel for the microfluidic system. Algal cell are loaded into the microfluidic device, which provides positive charge on the bottom surface of wells. Algal cells, which are negative charged, can be attracted to the bottom of the wells via electrostatic interaction. By varying the concentration of algal cells in the loading suspension, it is possible to obtain wells with a single cell. Liquid medium for cells monitoring are flown continuously over the wells, providing nutrient and waste exchange between the well and the main flow. This device could lead to the uncovering of the quantitative biology of the algae, which is a key to effective and extensive algal utilizations in the field of biotechnology, food industry and bioenergy research and developments.

Cross Layer Optimization for Fairness Balancing Based on Adaptively Weighted Utility Functions in OFDMA Systems

Cross layer optimization based on utility functions has been recently studied extensively, meanwhile, numerous types of utility functions have been examined in the corresponding literature. However, a major drawback is that most utility functions take a fixed mathematical form or are based on simple combining, which can not fully exploit available information. In this paper, we formulate a framework of cross layer optimization based on Adaptively Weighted Utility Functions (AWUF) for fairness balancing in OFDMA networks. Under this framework, a two-step allocation algorithm is provided as a sub-optimal solution, whose control parameters can be updated in real-time to accommodate instantaneous QoS constrains. The simulation results show that the proposed algorithm achieves high throughput while balancing the fairness among multiple users.

Dimensionality Reduction of PSSM Matrix and its Influence on Secondary Structure and Relative Solvent Accessibility Predictions

State-of-the-art methods for secondary structure (Porter, Psi-PRED, SAM-T99sec, Sable) and solvent accessibility (Sable, ACCpro) predictions use evolutionary profiles represented by the position specific scoring matrix (PSSM). It has been demonstrated that evolutionary profiles are the most important features in the feature space for these predictions. Unfortunately applying PSSM matrix leads to high dimensional feature spaces that may create problems with parameter optimization and generalization. Several recently published suggested that applying feature extraction for the PSSM matrix may result in improvements in secondary structure predictions. However, none of the top performing methods considered here utilizes dimensionality reduction to improve generalization. In the present study, we used simple and fast methods for features selection (t-statistics, information gain) that allow us to decrease the dimensionality of PSSM matrix by 75% and improve generalization in the case of secondary structure prediction compared to the Sable server.

On Optimum Stratification

In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique.

Totally Integrated Smart Energy System through Data Acquisition via Remote Location

This paper discusses the approach of real-time controlling of the energy management system using the data acquisition tool of LabVIEW. The main idea of this inspiration was to interface the Station (PC) with the system and publish the data on internet using LabVIEW. In this venture, controlling and switching of 3 phase AC loads are effectively and efficiently done. The phases are also sensed through devices. In case of any failure the attached generator starts functioning automatically. The computer sends command to the system and system respond to the request. The modern feature is to access and control the system world-wide using world wide web (internet). This controlling can be done at any time from anywhere to effectively use the energy especially in developing countries where energy management is a big problem. In this system totally integrated devices are used to operate via remote location.

Application of Feed-Forward Neural Networks Autoregressive Models with Genetic Algorithm in Gross Domestic Product Prediction

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Simulation of Loss-of-Flow Transient in a Radiant Steam Boiler with Relap5/Mod3.2

loss of feedwater accident is one of the frequently sever accidents in steam boiler facilities. It threatens the system structural integrity and generates serious hazards and economic loses. The safety analysis of the thermal installations, based extensively on the numeric simulation. The simulation analysis using realistic computer codes like Relap5/Mod3.2 will help understand steam boiler thermal-hydraulic behavior during normal and abnormal conditions. In this study, we are interested on the evaluation of the radiant steam boiler assessment and response to loss-of-feedwater accident. Pressure, temperature and flow rate profiles are presented in various steam boiler system components. The obtained results demonstrate the importance and capability of the Relap5/Mod3.2 code in the thermal-hydraulic analysis of the steam boiler facilities.

The Decentralized Nonlinear Controller of Robot Manipulator with External Load Compensation

This paper describes a newly designed decentralized nonlinear control strategy to control a robot manipulator. Based on the concept of the nonlinear state feedback theory and decentralized concept is developed to improve the drawbacks in previous works concerned with complicate intelligent control and low cost effective sensor. The control methodology is derived in the sense of Lyapunov theorem so that the stability of the control system is guaranteed. The decentralized algorithm does not require other joint angle and velocity information. Individual Joint controller is implemented using a digital processor with nearly actuator to make it possible to achieve good dynamics and modular. Computer simulation result has been conducted to validate the effectiveness of the proposed control scheme under the occurrence of possible uncertainties and different reference trajectories. The merit of the proposed control system is indicated in comparison with a classical control system.

Implementation of RSA Blind Signature on CryptO-0N2 Protocol

Blind Signature were introduced by Chaum. In this scheme, a signer can “sign” a document without knowing the document contain. This is particularly important in electronic voting. CryptO-0N2 is an electronic voting protocol which is development of CryptO-0N. During its development this protocol has not been furnished with the requirement of blind signature, so the choice of voters can be determined by counting center. In this paper will be presented of implementation of blind signature using RSA algorithm.