Search results for: Artificial joints

Authors: Artur Matuck, Guilherme F. Nobre

Abstract:

Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: Artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art.

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Authors: G. Shanmugasundar, R. Sivaramakrishnan, S. Venugopal

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Robots are booming as an essential substituent in the field of inspection. In hazardous environments like nuclear waste disposal, robots are really a necessitate one. In a view to meet such demands, this paper presents the seven degree of freedom articulated inspection robot. To design such a robot the kinematic analysis of seven Degree of freedom robot which can inspect the hazardous nuclear waste storage tanks is done. The effective utilization of universal joints for arms and screw jack mechanisms at the base gives the higher order of degree of freedom to the newly designed robot. The analytical method of deriving the manipulator forward as well as inverse kinematics is explained elaborately using the Denavit-Hartenberg Approach for the purpose of calculating the robot joints, links and end-effector parameters. The comparison of the geometric and the analytical approach is stated. The self-developed kinematic model gives the accurate positions of the end effector. The Graphical User Interface (GUI) is developed in Visual Basic language for the manipulation of kinematic results easily. This software gives the expected position of the end-effector accurately at short time compared to manual manipulations.

Keywords: Robot kinematics, screw jack mechanisms, Denavit-Hartenberg approach, universal joints.

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Authors: P. Zamani, S. Mohajerzadeh, R. Masoudinejad, Kh. Farhangdoost

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Riveting process is one of the important ways to keep fastening the lap joints in aircraft structures. Failure of aircraft lap joints directly depends on the stress field in the joint. An important application of riveting process is in the construction of aircraft fuselage structures. In this paper, a 3D finite element method is carried out in order to optimize residual stress field in a riveted lap joint and also to estimate its fatigue life. In continue, a number of experiments are designed and analyzed using design of experiments (DOE). Then, Taguchi method is used to select an optimized case between different levels of each factor. Besides that, the factor which affects the most on residual stress field is investigated. Such optimized case provides the maximum residual stress field. Fatigue life of the optimized joint is estimated by Paris-Erdogan law. Stress intensity factors (SIFs) are calculated using both finite element analysis and experimental formula. In addition, the effect of residual stress field, geometry and secondary bending are considered in SIF calculation. A good agreement is found between results of such methods. Comparison between optimized fatigue life and fatigue life of other joints has shown an improvement in the joint’s life.

Keywords: Fatigue life, Residual stress, Riveting process, Stress intensity factor, Taguchi method.

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: Khaled M. Alhawiti

Abstract:

This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: Speech recognition, acoustic phonetic, artificial intelligence, Hidden Markov Models (HMM), statistical models of speech recognition, human machine performance.

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Authors: Yu Zhang, Nao-Aki Noda, Kentaro Takaishi

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This paper discusses effects of adhesive thickness, overlap length and material combinations on the single-lap joints strength from the point of singular stress fields. A useful method calculating the ratio of intensity of singular stress is proposed using FEM for different adhesive thickness and overlap length. It is found that the intensity of singular stress increases with increasing adhesive thickness, and decreases with increasing overlap length. The increment and decrement are different depending on material combinations between adhesive and adherent.

Keywords: Adhesive thickness, Overlap length, Intensity ofsingular stress, Single-lap joint

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Authors: K. A. Laptinskiy, S. A. Burikov, A. M. Vervald, S. A. Dolenko, T. A. Dolenko

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The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Keywords: Artificial neural networks, fluorescence, data aggregation.

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Authors: Yuji Kageyama, Shin Nagata, Tatsuya Takino, Izuru Nomura, Hiroyuki Kamata

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In previous study, technique to estimate a self-location by using a lunar image is proposed.We consider the improvement of the conventional method in consideration of FPGA implementationin this paper. Specifically, we introduce Artificial Bee Colony algorithm for reduction of search time.In addition, we use fixed point arithmetic to enable high-speed operation on FPGA.

Keywords: SLIM, Artificial Bee Colony Algorithm, Location Estimate.

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Authors: Meng-Hui Chen, Pei-Chann Chang, Wei-Hsiu Huang

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Artificial Immune System is adopted as a Heuristic Algorithm to solve the combinatorial problems for decades. Nevertheless, many of these applications took advantage of the benefit for applications but seldom proposed approaches for enhancing the efficiency. In this paper, we continue the previous research to develop a Self-evolving Artificial Immune System II via coordinating the T and B cell in Immune System and built a block-based artificial chromosome for speeding up the computation time and better performance for different complexities of problems. Through the design of Plasma cell and clonal selection which are relative the function of the Immune Response. The Immune Response will help the AIS have the global and local searching ability and preventing trapped in local optima. From the experimental result, the significant performance validates the SEAIS II is effective when solving the permutation flows-hop problems.

Keywords: Artificial Immune System, Clonal Selection, Immune Response, Permutation Flow-shop Scheduling Problems

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Authors: M. Mohagheghian, A. M. Ghaedi, A. Vafaei

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An artificial neural network (ANN) model is presented for the prediction of kinematic viscosity of binary mixtures of poly (ethylene glycol) (PEG) in water as a function of temperature, number-average molecular weight and mass fraction. Kinematic viscosities data of aqueous solutions for PEG (0.55419×10-6 – 9.875×10-6 m2/s) were obtained from the literature for a wide range of temperatures (277.15 - 338.15 K), number-average molecular weight (200 -10000), and mass fraction (0.0 – 1.0). A three layer feed-forward artificial neural network was employed. This model predicts the kinematic viscosity with a mean square error (MSE) of 0.281 and the coefficient of determination (R2) of 0.983. The results show that the kinematic viscosity of binary mixture of PEG in water could be successfully predicted using an artificial neural network model.

Keywords: Artificial neural network, kinematic viscosity, poly ethylene glycol (PEG)

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Authors: Valentina Di Maria, Anton Ianakiev

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The use OF adhesive anchors for wooden constructions is an efficient technology to connect and design timber members in new timber structures and to rehabilitate the damaged structural members of historical buildings. Due to the lack of standard regulation in this specific area of structural design, designers’ choices are still supported by test analysis that enables knowledge, and the prediction, of the structural behaviour of glued in rod joints. The paper outlines an experimental research activity aimed at identifying the tensile resistance capacity of several new adhesive joint prototypes made of epoxy resin, steel bar and timber, Oak and Douglas Fir species. The development of new adhesive connectors has been carried out by using epoxy to glue stainless steel bars into pre-drilled holes, characterised by smooth and rough internal surfaces, in timber samples. The realization of a threaded contact surface using a specific drill bit has led to an improved bond between wood and epoxy. The applied changes have also reduced the cost of the joints’ production. The paper presents the results of this parametric analysis and a Finite Element analysis that enables identification and study of the internal stress distribution in the proposed adhesive anchors.

Keywords: Glued in rod joints, adhesive anchors, timber, epoxy, rough contact surface, threaded hole shape.

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Authors: A. Naceri, M. Chikouche Hamina, P. Grosseau

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The effect of artificial pozzolan (waste brick) on the physico-chemical properties of cement manufactured was investigated. The waste brick is generated by the manufacture of bricks. It was used in the proportions of 0%, 5%, 10%, 15% and 20% by mass of cement to study its effect on the physico-chemical properties of cement incorporating artificial pozzolan. The physicochemical properties of cement at anhydrous state and the hydrated state (chemical composition, specific weight, fineness, consistency of the cement paste and setting times) were studied. The experimental results obtained show that the quantity of pozzolanic admixture (waste brick) of cement manufactured is the principal parameter who influences on the variation of the physico-chemical properties of the cement tested.

Keywords: Artificial pozzolan, waste brick, cement, physicochemicalcharacteristics.

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Authors: Thiang, Handry Khoswanto, Rendy Pangaldus

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Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.

Keywords: Artificial neural network, back propagation, inverse kinematics, manipulator, robot.

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Authors: Vishnu Pratap Singh Kirar

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The main aim of a communication system is to achieve maximum performance. In Cognitive Radio any user or transceiver has ability to sense best suitable channel, while channel is not in use. It means an unlicensed user can share the spectrum of a licensed user without any interference. Though, the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: Artificial Neural Network, Cognitive Radio, Cognitive Radio Networks, Back Propagation, Spectrum Sensing.

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Authors: Petar Halachev

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Forecasting the values of the indicators, which characterize the effectiveness of performance of organizations is of great importance for their successful development. Such forecasting is necessary in order to assess the current state and to foresee future developments, so that measures to improve the organization-s activity could be undertaken in time. The article presents an overview of the applied mathematical and statistical methods for developing forecasts. Special attention is paid to artificial neural networks as a forecasting tool. Their strengths and weaknesses are analyzed and a synopsis is made of the application of artificial neural networks in the field of forecasting of the values of different education efficiency indicators. A method of evaluation of the activity of universities using the Balanced Scorecard is proposed and Key Performance Indicators for assessment of e-learning are selected. Resulting indicators for the evaluation of efficiency of the activity are proposed. An artificial neural network is constructed and applied in the forecasting of the values of indicators for e-learning efficiency on the basis of the KPI values.

Keywords: artificial neural network, balanced scorecard, e-learning

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Authors: U. Idachaba, F. Z. Wang, A. Qi, N. Helian

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Artificial Bee Colony (ABC) algorithm is a relatively new swarm intelligence technique for clustering. It produces higher quality clusters compared to other population-based algorithms but with poor energy efficiency, cluster quality consistency and typically slower in convergence speed. Inspired by energy saving foraging behavior of natural honey bees this paper presents a Quality and Quantity Aware Artificial Bee Colony (Q2ABC) algorithm to improve quality of cluster identification, energy efficiency and convergence speed of the original ABC. To evaluate the performance of Q2ABC algorithm, experiments were conducted on a suite of ten benchmark UCI datasets. The results demonstrate Q2ABC outperformed ABC and K-means algorithm in the quality of clusters delivered.

Keywords: Artificial bee colony algorithm, clustering.

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Authors: Ashok Kumar Goel, Suresh Chandra Saxena, Surekha Bhanot

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In this work, a Modified Functional Link Artificial Neural Network (M-FLANN) is proposed which is simpler than a Multilayer Perceptron (MLP) and improves upon the universal approximation capability of Functional Link Artificial Neural Network (FLANN). MLP and its variants: Direct Linear Feedthrough Artificial Neural Network (DLFANN), FLANN and M-FLANN have been implemented to model a simulated Water Bath System and a Continually Stirred Tank Heater (CSTH). Their convergence speed and generalization ability have been compared. The networks have been tested for their interpolation and extrapolation capability using noise-free and noisy data. The results show that M-FLANN which is computationally cheap, performs better and has greater generalization ability than other networks considered in the work.

Keywords: DLFANN, FLANN, M-FLANN, MLP

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Authors: T. Teruzzi, S. Antonietti, C. Mosca, C. Paglia

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This paper discusses the causes of the structural failure in a tower crane. The structural collapse occurred at the upper joints of the extension element used to increase the height of the crane. The extension element consists of a steel lattice structure made with angular profiles and plates joined to the tower element by arc welding. Macroscopic inspection of the sections showed that the break was always observed on the angular profiles at the weld bead edge. The case study shows how, using mechanical characterization, chemical analysis of the steel and macroscopic and microscopic metallographic examinations, it was possible to obtain significant evidence that identified the mechanism causing the breakage. The analyses identified the causes of the structural failure as the use of materials that were not suitable for welding and poor performance in the welding joints.

Keywords: Failure, weld, microstructure, microcracks.

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Authors: Mircea I. Pastrav, Cornelia Baera, Florea Dinu

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A different concept for designing and detailing of reinforced concrete precast frame structures is analyzed in this paper. The new detailing of the joints derives from the special hybrid moment frame joints. The special reinforcements of this alternative detailing, named modified special hybrid joint, are bondless with respect to both column and beams. Full scale tests were performed on a plan model, which represents a part of 5 story structure, cropped in the middle of the beams and columns spans. Theoretical approach was developed, based on testing results on twice repaired model, subjected to lateral seismic type loading. Discussion regarding the modified special hybrid joint behavior and further on widening research needed concludes the presentation.

Keywords: Acceptance criteria, modified hybrid joint, repair, seismic loading type.

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Authors: Youngsuck Ji, Youngjoon Han, Hernsoo Hahn

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In this paper, we proposed the robust mobile object detection method for light effect in the night street image block based updating reference background model using block state analysis. Experiment image is acquired sequence color video from steady camera. When suddenly appeared artificial illumination, reference background model update this information such as street light, sign light. Generally natural illumination is change by temporal, but artificial illumination is suddenly appearance. So in this paper for exactly detect artificial illumination have 2 state process. First process is compare difference between current image and reference background by block based, it can know changed blocks. Second process is difference between current image-s edge map and reference background image-s edge map, it possible to estimate illumination at any block. This information is possible to exactly detect object, artificial illumination and it was generating reference background more clearly. Block is classified by block-state analysis. Block-state has a 4 state (i.e. transient, stationary, background, artificial illumination). Fig. 1 is show characteristic of block-state respectively [1]. Experimental results show that the presented approach works well in the presence of illumination variance.

Keywords: Block-state, Edge component, Reference backgroundi, Artificial illumination.

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Authors: İ. Kıyak, G. Gökmen

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Using of natural lighting has come into prominence in constructed buildings, especially in last ten years, under scope of energy efficiency. Natural lighting methods are one of the methods that aim to take advantage of day light in maximum level and decrease using of artificial lighting. Increasing of day light amount in buildings by using suitable methods will give optimum result in terms of comfort and energy saving when the daylight-artificial light integration is ensured with a suitable control system. Using of natural light in places that require lighting will ensure energy saving in great extent. With this study, it is aimed to save energy used for purpose of lighting. Under this scope, lighting of a scanning laboratory of a hospital was realized by using a lighting automation containing natural and artificial lighting. In natural lighting, light pipes were used and in artificial lighting, dimmable power LED modules were used. Necessity of lighting was followed with motion sensors. The lighting automation containing natural and artificial light was ensured with fuzzy logic control. At the scanning laboratory where this application was realized, energy saving in lighting was obtained.

Keywords: Daylight transfer, fuzzy logic controller, light pipe, Power LED.

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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The gases generated in oil filled transformers can be used for qualitative determination of incipient faults. The Dissolved Gas Analysis has been widely used by utilities throughout the world as the primarily diagnostic tool for transformer maintenance. In this paper, various Artificial Intelligence Techniques that have been used by the researchers in the past have been reviewed, some conclusions have been drawn and a sequential hybrid system has been proposed. The synergy of ANN and FIS can be a good solution for reliable results for predicting faults because one should not rely on a single technology when dealing with real–life applications.

Keywords: Dissolved Gas Analysis, Artificial IntelligenceTechniques, Incipient Faults, Transformer Fault Diagnosis, andHybrid Systems.

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Authors: K. Kalaiselvan, A. Elango, N. M. Nagarajan

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Today automobile and aerospace industries realise Laser Beam Welding for a clean and non contact source of heating and fusion for joining of sheets. The welding performance is mainly based on by the laser welding parameters. Some concepts related to Artificial Neural Networks and how can be applied to model weld bead geometry and mechanical properties in terms of equipment parameters are reported in order to evaluate the accuracy and compare it with traditional modeling schemes. This review reveals the output features of Titanium and Aluminium weld bead geometry and mechanical properties such as ultimate tensile strength, yield strength, elongation and reduction of the area of the weld using Artificial Neural Network.

Keywords: Laser Beam Welding (LBW), Artificial Neural Networks (ANN), Optimization, Titanium and Aluminium sheets.

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Authors: Birol Yildiz, Abdullah Yalama, Metin Coskun

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Many studies have shown that Artificial Neural Networks (ANN) have been widely used for forecasting financial markets, because of many financial and economic variables are nonlinear, and an ANN can model flexible linear or non-linear relationship among variables. The purpose of the study was to employ an ANN models to predict the direction of the Istanbul Stock Exchange National 100 Indices (ISE National-100). As a result of this study, the model forecast the direction of the ISE National-100 to an accuracy of 74, 51%.

Keywords: Artificial Neural Networks, Istanbul StockExchange, Non-linear Modeling.

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Authors: T.S.Balasubramanian, V.Balasubramanian, M.A.Muthumanikkam

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This paper reports the fatigue crack growth behaviour of gas tungsten arc, electron beam and laser beam welded Ti-6Al-4V titanium alloy. Centre cracked tensile specimens were prepared to evaluate the fatigue crack growth behaviour. A 100kN servo hydraulic controlled fatigue testing machine was used under constant amplitude uniaxial tensile load (stress ratio of 0.1 and frequency of 10 Hz). Crack growth curves were plotted and crack growth parameters (exponent and intercept) were evaluated. Critical and threshold stress intensity factor ranges were also evaluated. Fatigue crack growth behaviour of welds was correlated with mechanical properties and microstructural characteristics of welds. Of the three joints, the joint fabricated by laser beam welding exhibited higher fatigue crack growth resistance due to the presence of fine lamellar microstructure in the weld metal.

Keywords: Fatigue, Non ferrous metals and alloys, welding

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Authors: Ali Khaleel Kareem, Shian Gao, Ahmed Qasim Ahmed

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A numerical investigation of unsteady mixed convection heat transfer in a 3D moving top wall enclosure, which has a central rotating cylinder and uses either artificial roughness on the bottom hot plate or smooth bottom hot plate to study the heat transfer enhancement, is completed for fixed circular cylinder, and anticlockwise and clockwise rotational speeds, -1 ≤ Ω ≤ 1, at Reynolds number of 5000. The top lid-driven wall was cooled, while the other remaining walls that completed obstructed cubic were kept insulated and motionless. A standard k-ε model of Unsteady Reynolds-Averaged Navier-Stokes (URANS) method is involved to deal with turbulent flow. It has been clearly noted that artificial roughness can strongly control the thermal fields and fluid flow patterns. Ultimately, the heat transfer rate has been dramatically increased by involving artificial roughness on the heated bottom wall in the presence of rotating cylinder.

Keywords: Artificial roughness, Lid-driven cavity, Mixed convection heat transfer, Rotating cylinder, URANS method.

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Authors: T. Vigneswari, M. A. Maluk Mohamed

Abstract:

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques.

Keywords: Grid Computing, Grid Scheduling, Heterogeneous Earliest Finish Time (HEFT), Artificial Bee colony (ABC) Algorithm, Resource Management.

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Authors: Vahid Zeighami, Mohsen Ghasemi, Reza Akbari

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In this work, a Multi-Level Artificial Bee Colony (called MLABC) for optimizing numerical test functions is presented. In MLABC, two species are used. The first species employs n colonies where each of them optimizes the complete solution vector. The cooperation between these colonies is carried out by exchanging information through a leader colony, which contains a set of elite bees. The second species uses a cooperative approach in which the complete solution vector is divided to k sub-vectors, and each of these sub-vectors is optimized by a colony. The cooperation between these colonies is carried out by compiling sub-vectors into the complete solution vector. Finally, the cooperation between two species is obtained by exchanging information. The proposed algorithm is tested on a set of well-known test functions. The results show that MLABC algorithm provides efficiency and robustness to solve numerical functions.

Keywords: Artificial bee colony, cooperative artificial bee colony, multilevel cooperation.

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Authors: Ju-Na Hwang, Yong-Jun Park, Min-Hae Park, Kee-Joe Lim

Abstract:

Many studies have been conducted on DC transmission. Of power apparatus for DC transmission, high voltage direct current (HVDC) cable systems are being evaluated because of the increase in power demand and transmission distance. Therefore, dc insulation characteristics of liquid silicone rubber (LSR), which has various advantages such as short curing time and the ease of maintenance, were investigated to assess its performance as a HVDC insulation material for cable joints. The electrical performance of LSR added to nano-aluminum trihydrate (ATH) were confirmed by measurements of the breakdown strength and electrical conductivity. In addition, field emission scanning electron microscope (FE-SEM) was used as a means of confirmation of nanofiller dispersion state. The LSR nanocomposite was prepared by compounding LSR filled nano-sized ATH filler. The dc insulation properties of LSR added to nano-sized ATH fillers were found to be superior to those of the LSR without a filler. 

Keywords: Liquid silicone rubber, Nanocomposite, Nano-ATH, HVDC insulation, Cable joints.

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Authors: S. D. El Wakil

Abstract:

The research work reported here was aimed at investigating the feasibility of joining high-porosity stainless steel discs and wrought iron bars by friction welding. The sound friction-welded joints were then subjected to a metallurgical investigation and an analysis of failure resulting from tensile loading. Discs having 50 mm diameter and 10 mm thickness were produced by loose sintering of stainless steel powder at a temperature of 1350 ^oC in an argon atmosphere for one hour. Minor machining was then carried out to control the dimensions of the discs, and the density of each disc could then be determined. The level of porosity was calculated and was found to be about 40% in all of those discs. Solid wrought iron bars were also machined to facilitate tensile testing of the joints produced by friction welding. Using our previously gained experience, the porous stainless steel disc and the wrought iron tube were successfully friction welded. SEM was employed to examine the fracture surface after a tensile test of the joint in order to determine the type of failure. It revealed that the failure did not occur in the joint, but rather in the in the porous metal in the area adjacent to the joint. The load carrying capacity was actually determined by the strength of the porous metal and not by that of the welded joint. Macroscopic and microscopic metallographic examinations were also performed and showed that the welded joint involved a dense heat-affected zone where the porous metal underwent densification at elevated temperature, explaining and supporting the findings of the SEM study.

Keywords: Fracture of friction-welded joints, metallurgy of friction welding, solid-porous structures, strength of joint.

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