Search results for: radial distribution system
9749 Analytical Solution of Stress Distribution ona Hollow Cylindrical Fiber of a Composite with Cylindrical Volume Element under Axial Loading
Authors: M. H. Kargarnovin, K. Momeni
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The study of the stress distribution on a hollow cylindrical fiber placed in a composite material is considered in this work and an analytical solution for this stress distribution has been constructed. Finally some parameters such as fiber-s thickness and fiber-s length are considered and their effects on the distribution of stress have been investigated. For finding the governing relations, continuity equations for the axisymmetric problem in cylindrical coordinate (r,o,z) are considered. Then by assuming some conditions and solving the governing equations and applying the boundary conditions, an equation relates the stress applied to the representative volume element with the stress distribution on the fiber has been found.Keywords: Axial Loading, Composite, Hollow CylindricalFiber, Stress Distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16119748 Influence of Outer Corner Radius in Equal Channel Angular Pressing
Authors: Basavaraj V. Patil, Uday Chakkingal, T. S. Prasanna Kumar
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Equal Channel Angular Pressing (ECAP) is currently being widely investigated because of its potential to produce ultrafine grained microstructures in metals and alloys. A sound knowledge of the plastic deformation and strain distribution is necessary for understanding the relationships between strain inhomogeneity and die geometry. Considerable research has been reported on finite element analysis of this process, assuming threedimensional plane strain condition. However, the two-dimensional models are not suitable due to the geometry of the dies, especially in cylindrical ones. In the present work, three-dimensional simulation of ECAP process was carried out for six outer corner radii (sharp to 10 mm in steps of 2 mm), with channel angle 105¶Çü▒, for strain hardening aluminium alloy (AA 6101) using ABAQUS/Standard software. Strain inhomogeneity is presented and discussed for all cases. Pattern of strain variation along selected radial lines in the body of the workpiece is presented. It is found from the results that the outer corner has a significant influence on the strain distribution in the body of work-piece. Based on inhomogeneity and average strain criteria, there is an optimum outer corner radius.Keywords: Equal Channel Angular Pressing, Finite Element Analysis, strain inhomogeneity, plastic equivalent strain, ultra fine grain size, aluminium alloy 6101.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22499747 A Hybrid Radial-Based Neuro-GA Multiobjective Design of Laminated Composite Plates under Moisture and Thermal Actions
Authors: Mohammad Reza Ghasemi, Ali Ehsani
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In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.Keywords: Composite Laminates, GA, Multi-objectiveOptimization, Neural Networks, RBFNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14669746 Comparative Study Using Weka for Red Blood Cells Classification
Authors: Jameela Ali Alkrimi, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy
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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithms tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital - Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.
Keywords: K-Nearest Neighbors, Neural Network, Radial Basis Function, Red blood cells, Support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29979745 Evaluation of Best-Fit Probability Distribution for Prediction of Extreme Hydrologic Phenomena
Authors: Karim Hamidi Machekposhti, Hossein Sedghi
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The probability distributions are the best method for forecasting of extreme hydrologic phenomena such as rainfall and flood flows. In this research, in order to determine suitable probability distribution for estimating of annual extreme rainfall and flood flows (discharge) series with different return periods, precipitation with 40 and discharge with 58 years time period had been collected from Karkheh River at Iran. After homogeneity and adequacy tests, data have been analyzed by Stormwater Management and Design Aid (SMADA) software and residual sum of squares (R.S.S). The best probability distribution was Log Pearson Type III with R.S.S value (145.91) and value (13.67) for peak discharge and Log Pearson Type III with R.S.S values (141.08) and (8.95) for maximum discharge in Jelogir Majin and Pole Zal stations, respectively. The best distribution for maximum precipitation in Jelogir Majin and Pole Zal stations was Log Pearson Type III distribution with R.S.S values (1.74&1.90) and then Pearson Type III distribution with R.S.S values (1.53&1.69). Overall, the Log Pearson Type III distributions are acceptable distribution types for representing statistics of extreme hydrologic phenomena in Karkheh River at Iran with the Pearson Type III distribution as a potential alternative.
Keywords: Karkheh river, log pearson type III, probability distribution, residual sum of squares.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8839744 Study on the Addition of Solar Generating and Energy Storage Units to a Power Distribution System
Authors: T. Costa, D. Narvaez, K. Melo, M. Villalva
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Installation of micro-generators based on renewable energy in power distribution system has increased in recent years, with the main renewable sources being solar and wind. Due to the intermittent nature of renewable energy sources, such micro-generators produce time-varying energy which does not correspond at certain times of the day to the peak energy consumption of end users. For this reason, the use of energy storage units next to the grid contributes to the proper leveling of the buses’ voltage level according to Brazilian energy quality standards. In this work, the effect of the addition of a photovoltaic solar generator and a store of energy in the busbar voltages of an electric system is analyzed. The consumption profile is defined as the average hourly use of appliances in a common residence, and the generation profile is defined as a function of the solar irradiation available in a locality. The power summation method is validated with analytical calculation and is used to calculate the modules and angles of the voltages in the buses of an electrical system based on the IEEE standard, at each hour of the day and with defined load and generation profiles. The results show that bus 5 presents the worst voltage level at the power consumption peaks and stabilizes at the appropriate range with the inclusion of the energy storage during the night time period. Solar generator maintains improvement of the voltage level during the period when it receives solar irradiation, having peaks of production during the 12 pm (without exceeding the appropriate maximum levels of tension).
Keywords: Energy storage, power distribution system, solar generator, voltage level.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8299743 Confidence Intervals for Double Exponential Distribution: A Simulation Approach
Authors: M. Alrasheedi
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The double exponential model (DEM), or Laplace distribution, is used in various disciplines. However, there are issues related to the construction of confidence intervals (CI), when using the distribution.In this paper, the properties of DEM are considered with intention of constructing CI based on simulated data. The analysis of pivotal equations for the models here in comparisons with pivotal equations for normal distribution are performed, and the results obtained from simulation data are presented.Keywords: Confidence intervals, double exponential model, pivotal equations, simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35539742 Electrical Impedance Imaging Using Eddy Current
Authors: A. Ambia, T. Takemae, Y. Kosugi, M. Hongo
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Electric impedance imaging is a method of reconstructing spatial distribution of electrical conductivity inside a subject. In this paper, a new method of electrical impedance imaging using eddy current is proposed. The eddy current distribution in the body depends on the conductivity distribution and the magnetic field pattern. By changing the position of magnetic core, a set of voltage differences is measured with a pair of electrodes. This set of voltage differences is used in image reconstruction of conductivity distribution. The least square error minimization method is used as a reconstruction algorithm. The back projection algorithm is used to get two dimensional images. Based on this principle, a measurement system is developed and some model experiments were performed with a saline filled phantom. The shape of each model in the reconstructed image is similar to the corresponding model, respectively. From the results of these experiments, it is confirmed that the proposed method is applicable in the realization of electrical imaging.Keywords: Back projection algorithm, electrical impedancetomography, eddy current, magnetic inductance tomography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16969741 Recurrent Radial Basis Function Network for Failure Time Series Prediction
Authors: Ryad Zemouri, Paul Ciprian Patic
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An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18199740 Analysis of the Structural Fluctuation of the Permitted Building Areas and Housing Distribution Ratios - Focused on 5 Cities Including Bucheon
Authors: Cheon Sik Min, Hyeong Wook Song, Sook Yeon Shim, Hoon Chang
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The purpose of this study was to analyze the correlation between permitted building areas and housing distribution ratios and their fluctuation, and test a distribution model during 3 successive governments in 5 cities including Bucheon in reference to the time series administrative data, and thereby, interpret the results of the analysis in association with the policies pursued by the successive governments to examine the structural fluctuation of permitted building areas and housing distribution ratios. In order to analyze the fluctuation of permitted building areas and housing distribution ratios during 3 successive governments and examine the cycles of the time series data, the spectral analysis was performed, and in order to analyze the correlation between permitted building areas and housing distribution ratios, the tabulation was performed to describe the correlations statistically, and in order to explain about differences of fluctuation distribution of permitted building areas and housing distribution ratios among 3 governments, the goodness of fit test was conducted.Keywords: The Permitted Building Areas, Housing Distribution Ratios, the Structural Fluctuation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11959739 A Fitted Random Sampling Scheme for Load Distribution in Grid Networks
Authors: O. A. Rahmeh, P. Johnson, S. Lehmann
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Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.
Keywords: Complex networks, grid networks, load-balancing, random sampling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17859738 A Multi-Objective Evolutionary Algorithm of Neural Network for Medical Diseases Problems
Authors: Sultan Noman Qasem
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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.
Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22539737 An ACO Based Algorithm for Distribution Networks Including Dispersed Generations
Authors: B. Bahmani Firouzi, T. Niknam, M. Nayeripour
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With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.
Keywords: Distributed Generation, Optimal Operation Management of distribution networks, Ant Colony Optimization(ACO).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17109736 Base Change for Fisher Metrics: Case of the q−Gaussian Inverse Distribution
Authors: Gabriel I. Loaiza O., Carlos A. Cadavid M., Juan C. Arango P.
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It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ = −1/2 , as does the family of usual Gaussian distributions. In the present paper, firstly we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ1, θ2; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the Inverse q−Gaussian distribution family (q < 3), as the family obtained by replacing the usual exponential function by the Tsallis q−exponential function in the expression for the Inverse Gaussian distribution, and observe that it supports two possible geometries, the Fisher and the q−Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q−Fisher geometry of the Inverse q−Gaussian distribution family, similar to the ones obtained in the case of the Inverse Gaussian distribution family.
Keywords: Base of Changes, Information Geometry, Inverse Gaussian distribution, Inverse q-Gaussian distribution, Statistical Manifolds.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3909735 Input Variable Selection for RBFN-based Electric Utility's CO2 Emissions Forecasting
Authors: I. Falconett, K. Nagasaka
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This study investigates the performance of radial basis function networks (RBFN) in forecasting the monthly CO2 emissions of an electric power utility. We also propose a method for input variable selection. This method is based on identifying the general relationships between groups of input candidates and the output. The effect that each input has on the forecasting error is examined by removing all inputs except the variable to be investigated from its group, calculating the networks parameter and performing the forecast. Finally, the new forecasting error is compared with the reference model. Eight input variables were identified as the most relevant, which is significantly less than our reference model with 30 input variables. The simulation results demonstrate that the model with the 8 inputs selected using the method introduced in this study performs as accurate as the reference model, while also being the most parsimonious.
Keywords: Correlation analysis, CO2 emissions forecasting, electric power utility, radial basis function networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15389734 eLearning for Electric Distribution Planning Engineers
Authors: Isaias Ramirez, Jose Luis Silva, Carlos Gonzalez, Gustavo Candelaria, Jose Pepe Rasgado, Carlos Carrillo
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This paper presents the experience in an eLearning training project that is being implemented for electrical planning engineers from the national Mexican utility Comision Federal de Electricidad (CFE) Distribution. This modality is implemented and will be used in the utility for training purposes to help personnel in their daily technical activities. One important advantage of this training project is that once it is implemented and applied, financial resources will be saved by CFE Distribution Company because online training will be used in all the country; the infrastructure for the eLearning training will be uploaded in computational servers installed in the National CFE Distribution Training Department, in Ciudad de Mexico, and can be used in workplaces of 16 Distribution Divisions and 150 Zones of CFE Distribution. In this way, workers will not need to travel to the National Training Department, saving enormous efforts, financial, and human resources.
Keywords: Moodle, eLearning, corporate training, electrical planning engineer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4659733 Solid Concentration in Circulating Fluidized Bed Reactor for the MTO Process
Authors: Biao Wang, Tao Li, Qi-wen Sun, Wei-yong Ying, Ding-ye Fang
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Methanol-to-olefins (MTO) coupled with transformation of coal or natural gas to methanol gives an interesting and promising way to produce ethylene and propylene. To investigate solid concentration in gas-solid fluidized bed for methanol-to-olefins process catalyzed by SAPO-34, a cold model experiment system is established in this paper. The system comprises a gas distributor in a 300mm internal diameter and 5000mm height acrylic column, the fiber optic probe system and series of cyclones. The experiments are carried out at ambient conditions and under different superficial gas velocity ranging from 0.3930m/s to 0.7860m/s and different initial bed height ranging from 600mm to 1200mm. The effects of radial distance, axial distance, superficial gas velocity, initial bed height on solid concentration in the bed are discussed. The effects of distributor shape and porosity on solid concentration are also discussed. The time-averaged solid concentration profiles under different conditions are obtained.Keywords: Branched pipe distributor, distributor porosity, gas-solid fluidized bed, solid concentration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22769732 Person Identification using Gait by Combined Features of Width and Shape of the Binary Silhouette
Authors: M.K. Bhuyan, Aragala Jagan.
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Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19119731 Estimating of the Renewal Function with Heavy-tailed Claims
Authors: Rassoul Abdelaziz
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We develop a new estimator of the renewal function for heavy-tailed claims amounts. Our approach is based on the peak over threshold method for estimating the tail of the distribution with a generalized Pareto distribution. The asymptotic normality of an appropriately centered and normalized estimator is established, and its performance illustrated in a simulation study.
Keywords: Renewal function, peak-over-threshold, POT method, extremes value, generalized pareto distribution, heavy-tailed distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14739730 On the Analysis of IP Traffic Distribution in the Network of Suranaree University of Technology
Authors: Paramet Nualmuenwai, Chutima Prommak
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This paper presents the IP traffic analysis. The traffic was collected from the network of Suranaree University of Technology using the software based on the Simple Network Management Protocol (SNMP). In particular, we analyze the distribution of the aggregated traffic during the hours of peak load and light load. The traffic profiles including the parameters described the traffic distributions were derived. From the statistical analysis applying three different methods, including the Kolmogorov Smirnov test, Anderson Darling test, and Chi-Squared test, we found that the IP traffic distribution is a non-normal distribution and the distributions during the peak load and the light load are different. The experimental study and analysis show high uncertainty of the IP traffic.Keywords: IP traffic analysis, IP traffic distribution, Traffic uncertainty
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15179729 The Effect of Correlated Service and Inter-arrival Times on System Performance
Authors: Gang Uk Hwang
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In communication networks where communication nodes are connected with finite capacity transmission links, the packet inter-arrival times are strongly correlated with the packet length and the link capacity (or the packet service time). Such correlation affects the system performance significantly, but little attention has been paid to this issue. In this paper, we propose a mathematical framework to study the impact of the correlation between the packet service times and the packet inter-arrival times on system performance. With our mathematical model, we analyze the system performance, e.g., the unfinished work of the system, and show that the correlation affects the system performance significantly. Some numerical examples are also provided.
Keywords: Performance analysis, Correlated queueing system, Unfinished work, PH-type distribution, Communicationsystem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13829728 An Approach for Reducing the Computational Complexity of LAMSTAR Intrusion Detection System using Principal Component Analysis
Authors: V. Venkatachalam, S. Selvan
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The security of computer networks plays a strategic role in modern computer systems. Intrusion Detection Systems (IDS) act as the 'second line of defense' placed inside a protected network, looking for known or potential threats in network traffic and/or audit data recorded by hosts. We developed an Intrusion Detection System using LAMSTAR neural network to learn patterns of normal and intrusive activities, to classify observed system activities and compared the performance of LAMSTAR IDS with other classification techniques using 5 classes of KDDCup99 data. LAMSAR IDS gives better performance at the cost of high Computational complexity, Training time and Testing time, when compared to other classification techniques (Binary Tree classifier, RBF classifier, Gaussian Mixture classifier). we further reduced the Computational Complexity of LAMSTAR IDS by reducing the dimension of the data using principal component analysis which in turn reduces the training and testing time with almost the same performance.Keywords: Binary Tree Classifier, Gaussian Mixture, IntrusionDetection System, LAMSTAR, Radial Basis Function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17529727 Real-time Laser Monitoring based on Pipe Detective Operation
Authors: Mongkorn Klingajay, Tawatchai Jitson
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The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18209726 Biological Control of Tomato Wilt Fungi Using Leaf Extracts of Bitter Leaf (Vernonia amygdalina)
Authors: Terna T. Paul, Agbara D. Onwoke
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The antifungal potential of ethanolic leaf extracts of Vernonia amygdalina in the biological control of some common tomato wilt fungi was investigated. The experiment was set up in Completely Randomized Design (CRD) with eight treatments and three replicates. 5 mm diameter agar discs of 7 days old cultures of Fusarium oxysporum and Sclerotium rolfsii were obtained using a sterile 5 mm diameter cork borer and cultured on Potato Dextrose Agar (PDA) inoculated with 5 ml of various concentrations of V. amygdalina ethanolic leaf extracts in petri dishes, and incubated for 10 days at 28 0C. The highest radial growth inhibitions of F. oxysporum (34.98%) and S. rolfsii (31.05%) were recorded 48 hours post-inoculation, both at 75% extract concentration. The leaf extracts of V. amygdalina used in the study exhibited significant inhibition of radial growth of the test organisms (P ≤ 0.05) and could be applied in the biological control of fungal wilt pathogens of tomato as a means of enhancing tomato yield and productivity.
Keywords: Biological control, fungi, leaf extracts, tomato wilt, V. amygdalina.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12249725 Nonlinear Adaptive PID Control for a Semi-Batch Reactor Based On an RBF Network
Authors: Magdi M. Nabi, Ding-Li Yu
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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.
Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward and feedback control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26769724 Flow of a Second Order Fluid through Constricted Tube with Slip Velocity at Wall Using Integral Method
Authors: Nosheen Zareen Khan, Abdul Majeed Siddiqui, Muhammad Afzal Rana
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The steady flow of a second order fluid through constricted tube with slip velocity at wall is modeled and analyzed theoretically. The governing equations are simplified by implying no slip in radial direction. Based on Karman Pohlhausen procedure polynomial solution for axial velocity profile is presented. Expressions for pressure gradient, shear stress, separation and reattachment points, and radial velocity are also calculated. The effect of slip and no slip velocity on magnitude velocity, shear stress, and pressure gradient are discussed and depicted graphically. It is noted that when Reynolds number increases magnitude velocity of the fluid decreases in both slip and no slip conditions. It is also found that the wall shear stress, separation, and reattachment points are strongly affected by Reynolds number.Keywords: Approximate solution, constricted tube, non-Newtonian fluids, Reynolds number.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17269723 Reliability Analysis of Computer Centre at Yobe State University Using LRU Algorithm
Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad
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In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.Keywords: Reliability, availability Gumbel-Hougaard family copula, MTTF, internet data center.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8709722 Experimental Investigation on Solid Concentration in Gas-Solid Circulating Fluidized Bed for Methanol-to-Olefins Process
Authors: Biao Wang, Tao Li, Qi-Wen Sun, Wei-Yong Ying, Ding-Ye Fang
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Methanol-to-olefins coupled with transformation of coal or natural gas to methanol gives an interesting and promising way to produce ethylene and propylene. To investigate solid concentration in gas-solid fluidized bed for methanol-to-olefins process catalyzed by SAPO-34, a cold model experiment system is established in this paper. The system comprises a gas distributor in a 300mm internal diameter and 5000mm height acrylic column, the fiber optic probe system and series of cyclones. The experiments are carried out at ambient conditions and under different superficial gas velocity ranging from 0.3930m/s to 0.7860m/s and different initial bed height ranging from 600mm to 1200mm. The effects of radial distance, axial distance, superficial gas velocity, initial bed height on solid concentration in the bed are discussed. The effects of distributor shape and porosity on solid concentration are also discussed. The time-averaged solid concentration profiles under different conditions are obtained.Keywords: Branched pipe distributor, distributor porosity, gas-solid fluidized bed, solid concentration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14629721 Estimating the Life-Distribution Parameters of Weibull-Life PV Systems Utilizing Non-Parametric Analysis
Authors: Saleem Z. Ramadan
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In this paper, a model is proposed to determine the life distribution parameters of the useful life region for the PV system utilizing a combination of non-parametric and linear regression analysis for the failure data of these systems. Results showed that this method is dependable for analyzing failure time data for such reliable systems when the data is scarce.Keywords: Masking, Bathtub model, reliability, non-parametric analysis, useful life.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18479720 Optimization of Energy Conservation Potential for VAV Air Conditioning System using Fuzzy based Genetic Algorithm
Authors: R. Parameshwaran, R. Karunakaran, S. Iniyan, Anand A. Samuel
Abstract:
The objective of this study is to present the test results of variable air volume (VAV) air conditioning system optimized by two objective genetic algorithm (GA). The objective functions are energy savings and thermal comfort. The optimal set points for fuzzy logic controller (FLC) are the supply air temperature (Ts), the supply duct static pressure (Ps), the chilled water temperature (Tw), and zone temperature (Tz) that is taken as the problem variables. Supply airflow rate and chilled water flow rate are considered to be the constraints. The optimal set point values are obtained from GA process and assigned into fuzzy logic controller (FLC) in order to conserve energy and maintain thermal comfort in real time VAV air conditioning system. A VAV air conditioning system with FLC installed in a software laboratory has been taken for the purpose of energy analysis. The total energy saving obtained in VAV GA optimization system with FLC compared with constant air volume (CAV) system is expected to achieve 31.5%. The optimal duct static pressure obtained through Genetic fuzzy methodology attributes to better air distribution by delivering the optimal quantity of supply air to the conditioned space. This combination enhanced the advantages of uniform air distribution, thermal comfort and improved energy savings potential.Keywords: Energy savings, fuzzy logic, Genetic algorithm, Thermal Comfort
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