Search results for: Computational modelling

Authors: Junting Xiang, Jörg Uwe Schlüter, Fei Duan

Abstract:

The miniaturization of gas turbines promises many advantages. Miniature gas turbines can be used for local power generation or the propulsion of small aircraft, such as UAV and MAV. However, experience shows that the miniaturization of conventional gas turbines, which are optimized at their current large size, leads to a substantial loss of efficiency and performance at smaller scales. This may be due to a number of factors, such as the Reynolds-number effect, the increased heat transfer, and manufacturing tolerances. In the present work, we focus on computational investigations of the Reynolds number effect and the wall heat transfer on the performance of axial compressor during its size change. The NASA stage 35 compressor is selected as the configuration in this study and computational fluid dynamics (CFD) is used to carry out the miniaturization process and simulations. We perform parameter studies on the effect of Reynolds number and wall thermal conditions. Our results indicate a decrease of efficiency, if the compressor is miniaturized based on its original geometry due to the increase of viscous effects. The increased heat transfer through wall has only a small effect and will actually benefit compressor performance based on our study.

Keywords: Axial compressor, CFD, heat transfer, miniature gas turbines, Reynolds number.

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Authors: Nhon Do, Hien Nguyen

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Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: educational software, artificial intelligence, knowledge base system, knowledge representation.

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Authors: T. D. Kothalawala, A. Gatto, L. Wrobel

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An exploratory computational investigation using RANS & URANS was carried out to understand the aerodynamics around an isolatedsingle rotating wheel with decreasing ground proximity. The wheel was initially modeled in free air conditions, then with decreasing ground proximity and increased yaw angle with rotational speeds. Three speeds of rotation were applied to the wheel so that the effect of different angular velocities can be investigated. In addition to rotation, three different yaw angles were applied to the rotating wheel in order to understand how these two variables combined affect the aerodynamic flow field around the wheel.

Keywords: Aerodynamics, CFD, Ground Proximity, Landing Gear, Wheel, Rotation, Yaw.

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Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar

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Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.

To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.

It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.

Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.

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Authors: Pradya Pornnimitkul, Suwich Kunaruttanapruk, Bamrung Tau Sieskul, Somchai Jitapunkul

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In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.

Keywords: Channel estimation, MC-CDMA, SVD, URV.

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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.

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Authors: Reena Murali, David Peter S.

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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies show that upregulation of mRNA because serious diseases like cancer. So designing effective siRNA with good knockdown effects plays an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (%G), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: Artificial Neural Network, Double Stranded RNA, RNA Interference, Short Interfering RNA.

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Authors: A. Al-Rifaie, Z. W. Guan, S. W. Jones

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This paper presents a method for modelling and analysing end plate beam-to-column connections to obtain the quasi-static behaviour using non-linear dynamic explicit integration. In addition to its importance to study the static behaviour of a structural member, quasi-static behaviour is largely needed to be compared with the dynamic behaviour of such members in order to investigate the dynamic effect by proposing dynamic increase factors (DIFs). The beam-to-column bolted connections contain various contact surfaces at which the implicit procedure may have difficulties converging, resulting in a large number of iterations. Contrary, explicit procedure could deal effectively with complex contacts without converging problems. Hence, finite element modelling using ABAQUS/explicit is used in this study to address the dynamic effect may be produced using explicit procedure. Also, the effect of loading rate and mass scaling are discussed to investigate their effect on the time of analysis. The results show that the explicit procedure is valuable to model the end plate beam-to-column connections in terms of failure mode, load-displacement relationships. Also, it is concluded that loading rate and mass scaling should be carefully selected to avoid the dynamic effect in the solution.

Keywords: Quasi-static, end plate, finite element, connections.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

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A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

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Authors: Maisara Mohyeldin Gasim, A. K. Amirruddin, A. Shahrani

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This paper investigates the effect of replacing crankshaft with cam on the indicated torque during compression and power strokes in internal combustion engines. A Cycloidal cam profile was used in Revetec engine to calculate and compare the torque to a conventional engine, using a computational method. Firstly, the cylinder pressure was calculated using Ferguson equation, and then the torque calculated depending on cylinder pressure values in every crank angle. the results showed that by using Cycloidal cam profile in Revetec engine the torque can increased by 14% compared with conventional engines, which means an increase in engine efficiency.

Keywords: Revetec engine, indicated torque, cam profile.

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Authors: S. A. Che Osmi, W. M. F. Wan Ishak, H. Kim, M. A. Azman, M. A. Ramli

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River is one of important water sources for many activities including industrial and domestic usage such as daily usage, transportation, power supply and recreational activities. However, increasing activities in a river has grown the sources of pollutant enters the water bodies, and degraded the water quality of the river. It becomes a challenge to develop an effective river management to ensure the water sources of the river are well managed and regulated. In Malaysia, several approaches for river management have been implemented such as Integrated River Basin Management (IRBM) program for coordinating the management of resources in a natural environment based on river basin to ensure their sustainability lead by Department of Drainage and Irrigation (DID), Malaysia. Nowadays, Total Maximum Daily Load (TMDL) is one of the best approaches for river management in Malaysia. TMDL implementation is regulated and implemented in the United States. A study on the development of TMDL in Malacca River has been carried out by doing water quality monitoring, the development of water quality model by using Environmental Fluid Dynamic Codes (EFDC), and TMDL implementation plan. The implementation of TMDL will help the stakeholders and regulators to control and improve the water quality of the river. It is one of the good approaches for river management in Malaysia.

Keywords: EFDC, river management, TMDL, water quality modelling.

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Authors: Radhe Tado, Ashish B. Deoghare, K. M. Pandey

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The aim of this study is to estimate the effect of blood flow through the coronary artery in human heart so as to assess the coronary artery disease.Velocity, wall shear stress (WSS), strain rate and wall pressure distribution are some of the important hemodynamic parameters that are non-invasively assessed with computational fluid dynamics (CFD). These parameters are used to identify the mechanical factors responsible for the plaque progression and/or rupture in left coronary arteries (LCA) in coronary arteries.The initial step for CFD simulations was the construction of a geometrical model of the LCA. Patient specific artery model is constructed using computed tomography (CT) scan data with the help of MIMICS Research 19.0. For CFD analysis ANSYS FLUENT-14.5 is used.Hemodynamic parameters were quantified and flow patterns were visualized both in the absence and presence of coronary plaques. The wall pressure continuously decreased towards distal segments and showed pressure drops in stenotic segments. Areas of high WSS and high flow velocities were found adjacent to plaques deposition.

Keywords: Computational fluid dynamics, hemodynamics, velocity, strain rate, wall pressure, wall shear stress.

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Authors: Lukasz Peronski, Roy Bratley, Derek B. Ingham, Lin Ma, Mohamed Pourkashanian, StephenTaylor

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The aim of the study was to investigate the possible use of commercial Computational Fluid Dynamics (CFD) software in the design process of a domestic gas boiler. Because of the limited computational resources some simplifications had to be made in order to contribute to the design in a reasonable timescale. The porous media model was used in order to simulate the influence of the pressure drop characteristic of particular elements of a heat transfer system on the water-flow distribution in the system. Further, a combination of CFD analyses and spread sheet calculations was used in order to solve the flow distribution problem.

Keywords: CFD, domestic gas boilers, flow distribution, heatexchanger, porous media

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Authors: S. B. Liu, K. M. Ng, H. L. Ong

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This paper presents a new heuristic algorithm for the classical symmetric traveling salesman problem (TSP). The idea of the algorithm is to cut a TSP tour into overlapped blocks and then each block is improved separately. It is conjectured that the chance of improving a good solution by moving a node to a position far away from its original one is small. By doing intensive search in each block, it is possible to further improve a TSP tour that cannot be improved by other local search methods. To test the performance of the proposed algorithm, computational experiments are carried out based on benchmark problem instances. The computational results show that algorithm proposed in this paper is efficient for solving the TSPs.

Keywords: Local search, overlapped neighborhood, travelingsalesman problem.

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The modern Artificial Narrow Intelligence (ANI) models cannot: a) independently, situationally, and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, and cognize under uncertainty and changing of the environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU). This system uses a neural network as its computational memory, and activates functions of the perception, identification of real objects, fuzzy situational control, and forming images of these objects. These images and objects are used for modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision Making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, and Wisdom. In doing so are performed analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge of the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of situational control, fuzzy logic, psycholinguistics, informatics, and modern possibilities of data science were applied. The proposed self-controlled system of brain and mind is oriented on use as a plug-in in multilingual subject applications.

Keywords: Computational psycholinguistic cognitive brain and mind system, situational fuzzy control, uncertainty, AI.

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Authors: Leong Lee, Cyriac Kandoth, Jennifer L. Leopold, Ronald L. Frank

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Protein 3D structure prediction has always been an important research area in bioinformatics. In particular, the prediction of secondary structure has been a well-studied research topic. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction algorithms rarely has exceeded 75%. In a previous paper [1], this research team presented a rule-based method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) to predict protein secondary structure. The average Q3 accuracy on the sample datasets using RT-RICO was 80.3%, an improvement over comparable computational methods. Although this demonstrated that RT-RICO might be a promising approach for predicting secondary structure, the algorithm-s computational complexity and program running time limited its use. Herein a parallelized implementation of a slightly modified RT-RICO approach is presented. This new version of the algorithm facilitated the testing of a much larger dataset of 396 protein domains [2]. Parallelized RTRICO achieved a Q3 score of 74.6%, which is higher than the consensus prediction accuracy of 72.9% that was achieved for the same test dataset by a combination of four secondary structure prediction methods [2].

Keywords: data mining, protein secondary structure prediction, parallelization.

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Authors: M. Satya Sai Ram, P. Siddaiah, M. Madhavi Latha

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Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization, This is a hybrid of two product code vector quantization techniques namely the Multi stage vector quantization technique, and Switched split vector quantization technique,. Multi Switched Split Vector Quantization technique quantizes the linear predictive coefficients in terms of line spectral frequencies. From results it is proved that Multi Switched Split Vector Quantization provides better trade off between bitrate and spectral distortion performance, computational complexity and memory requirements when compared to Switched Split Vector Quantization, Multi stage vector quantization, and Split Vector Quantization techniques. By employing the switching technique at each stage of the vector quantizer the spectral distortion, computational complexity and memory requirements were greatly reduced. Spectral distortion was measured in dB, Computational complexity was measured in floating point operations (flops), and memory requirements was measured in (floats).

Keywords: Unconstrained vector quantization, Linear predictiveCoding, Split vector quantization, Multi stage vector quantization, Switched Split vector quantization, Line Spectral Frequencies.

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Authors: Marco Hemmerling

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The paper outlines the relevance of computational geometry within the design and production process of architecture. Based on two case studies, the digital chain - from the initial formfinding to the final realization of spatial concepts - is discussed in relation to geometric principles. The association with the fascinating complexity that can be found in nature and its underlying geometry was the starting point for both projects presented in the paper. The translation of abstract geometric principles into a three-dimensional digital design model – realized in Rhinoceros – was followed by a process of transformation and optimization of the initial shape that integrated aesthetic, spatial and structural qualities as well as aspects of material properties and conditions of production.

Keywords: Architecture, Computer Aided Architectural Design, 3D-Modeling, Rapid Prototyping, CAD/CAM.

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Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mohamad Teshnelab, Ehsan Shahamatnia

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The anti-lock braking systems installed on vehicles for safe and effective braking, are high-order nonlinear and timevariant. Using fuzzy logic controllers increase efficiency of such systems, but impose a high computational complexity as well. The main concept introduced by this paper is reducing computational complexity of fuzzy controllers by deploying problem-solution data structure. Unlike conventional methods that are based on calculations, this approach is based on data oriented modeling.

Keywords: ABS, Fuzzy controller, PSDS, Time-Memory tradeoff, Data oriented modeling.

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Authors: Jun Sung Park, Hyo Jung Song

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H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standards such as MPEG-2, but computational complexity is increased significantly. In this paper, we propose selective mode decision schemes for fast intra prediction mode selection. The objective is to reduce the computational complexity of the H.264/AVC encoder without significant rate-distortion performance degradation. In our proposed schemes, the intra prediction complexity is reduced by limiting the luma and chroma prediction modes using the directional information of the 16×16 prediction mode. Experimental results are presented to show that the proposed schemes reduce the complexity by up to 78% maintaining the similar PSNR quality with about 1.46% bit rate increase in average.

Keywords: Video encoding, H.264, Intra prediction.

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Authors: Martín Agüero, Franco Madou, Gabriela Esperón, Daniela López De Luise

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This paper presents a software quality support tool, a Java source code evaluator and a code profiler based on computational intelligence techniques. It is Java prototype software developed by AI Group [1] from the Research Laboratories at Universidad de Palermo: an Intelligent Java Analyzer (in Spanish: Analizador Java Inteligente, AJI). It represents a new approach to evaluate and identify inaccurate source code usage and transitively, the software product itself. The aim of this project is to provide the software development industry with a new tool to increase software quality by extending the value of source code metrics through computational intelligence.

Keywords: Software metrics, artificial intelligence, neuralnetworks, clustering algorithms, expert systems

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Authors: M.St. Węglowski, D. Miara, S. Błacha, J. Dworak, J. Rykała, K. Kwieciński, J. Pikuła, G. Ziobro, A. Szafron, P. Zimierska-Nowak, M. Richert, P. Noga

Abstract:

In the paper the results of welding of car’s air-conditioning elements are presented. These systems based on, mainly, the environmental unfriendly refrigerants. Thus, the producers of cars will have to stop using traditional refrigerant and to change it to carbon dioxide (R744). This refrigerant is environmental friendly. However, it should be noted that the air condition system working with R744 refrigerant operates at high temperature (up to 150 °C) and high pressure (up to 130 bar). These two parameters are much higher than for other refrigerants. Thus new materials, design as well as joining technologies are strongly needed for these systems. AISI 304 and 316L steels as well as aluminium alloys 5xxx are ranked among the prospective materials. As a joining process laser welding, plasma welding, electron beam welding as well as high rotary friction welding can be applied. In the study, the metallographic examination based on light microscopy as well as SEM was applied to estimate the quality of welded joints. The analysis of welding was supported by numerical modelling based on Sysweld software. The results indicated that using laser, plasma and electron beam welding, it is possible to obtain proper quality of welds in stainless steel. Moreover, high rotary friction welding allows to guarantee the metallic continuity in the aluminium welded area. The metallographic examination revealed that the grain growth in the heat affected zone (HAZ) in laser and electron beam welded joints were not observed. It is due to low heat input and short welding time. The grain growth and subgrains can be observed at room temperature when the solidification mode is austenitic. This caused low microstructural changes during solidification. The columnar grain structure was found in the weld metal. Meanwhile, the equiaxed grains were detected in the interface. The numerical modelling of laser welding process allowed to estimate the temperature profile in the welded joint as well as predicts the dimensions of welds. The agreement between FEM analysis and experimental data was achieved.  

Keywords: Car’s air–conditioning, microstructure, numerical modelling, welding.

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Authors: S.C. Swain, S. Panda, A.K. Mohanty, C. Ardil

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This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.

Keywords: Economic Load Dispatch, Continuous Fuel Cost, Quadratic Programming, Real-Coded Genetic Algorithm, Discontinuous Fuel Cost, Particle Swarm Optimization.

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Authors: Sudipta Majumdar, Jayant Bharadwaj

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This paper presents feature level image fusion using Haar lifting wavelet transform. Feature fused is edge and boundary information, which is obtained using wavelet transform modulus maxima criteria. Simulation results show the superiority of the result as entropy, gradient, standard deviation are increased for fused image as compared to input images. The proposed methods have the advantages of simplicity of implementation, fast algorithm, perfect reconstruction, and reduced computational complexity. (Computational cost of Haar wavelet is very small as compared to other lifting wavelets.)

Keywords: Lifting wavelet transform, wavelet transform modulus maxima.

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Authors: Nazar Zaki, Safaai Deris, Hany Alashwal

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Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.

Keywords: Protein-Protein Interaction, support vector machine, feature extraction, pairwise alignment, Smith-Waterman score.

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Authors: Ahmad R. Zamani, Luigi Sanguigno, Angelo R. Maligno

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A 3D woven composite, designed for automotive applications, is studied using Abaqus Finite Element (FE) software suite. Python scripts were developed to build FE models of the woven composite in Complete Abaqus Environment (CAE). They can read TexGen or WiseTex files and automatically generate consistent meshes of the fabric and the matrix. A user menu is provided to help define parameters for the FE models, such as type and size of the elements in fabric and matrix as well as the type of matrix-fabric interaction. Node-to-node constraints were imposed to guarantee periodicity of the deformed shapes at the boundaries of the representative volume element of the composite. Tensile loads in three axes and biaxial loads in x-y directions have been applied at different Fibre Volume Fractions (FVFs). A simple damage model was implemented via an Abaqus user material (UMAT) subroutine. Existing tools for homogenization were also used, including voxel mesh generation from TexGen as well as Abaqus Micromechanics plugin. Linear relations between homogenised elastic properties and the FVFs are given. The FE models of composite exhibited balanced behaviour with respect to warp and weft directions in terms of both stiffness and strength.

Keywords: 3D woven composite, meso-scale finite element modelling, homogenisation of elastic material properties, Abaqus Python scripting.

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Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free overfall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, Support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, Support vector machine (Polynomial and rbf) models and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free overfall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: Air entrainment rate, dissolved oxygen, regression, SVM, weir.

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Authors: N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, L. Gverdtsiteli

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Tbilisi, a large city of the South Caucasus, is a junction point connecting Asia and Europe, Russia and republics of the Asia Minor. Over the last years, its atmosphere has been experienced an increasing anthropogenic load. Numerical modeling method is used for study of Tbilisi atmospheric air pollution. By means of 3D non-linear non-steady numerical model a peculiarity of city atmosphere pollution is investigated during background western light air. Dust concentration spatial and time changes are determined. There are identified the zones of high, average and less pollution, dust accumulation areas, transfer directions etc. By numerical modeling, there is shown that the process of air pollution by the dust proceeds in four stages, and they depend on the intensity of motor traffic, the micro-relief of the city, and the location of city mains. In the interval of time 06:00-09:00 the intensive growth, 09:00-15:00 a constancy or weak decrease, 18:00-21:00 an increase, and from 21:00 to 06:00 a reduction of the dust concentrations take place. The highly polluted areas are located in the vicinity of the city center and at some peripherical territories of the city, where the maximum dust concentration at 9PM is equal to 2 maximum allowable concentrations. The similar investigations conducted in case of various meteorological situations will enable us to compile the map of background urban pollution and to elaborate practical measures for ambient air protection.

Keywords: Numerical modelling, source of pollution, dust propagation, western light air.

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Authors: Aïssa Rezzoug

Abstract:

This paper is aimed to bring new elements that demonstrate the tide caused the groundwater to rise in the shoreline band, on which the urban areas occurs, especially in the western coastal cities of the Kingdom of Saudi Arabia like Jeddah. The reason for the last events of Jeddah inundation was the groundwater rise in the city coupled at the same time to a strong precipitation event. This paper will illustrate the tide participation in increasing the groundwater level significantly. It shows that the reason for internal groundwater recharge within the urban area is not only the excess of the water supply coming from surrounding areas, due to the human activity, with lack of sufficient and efficient sewage system, but also due to tide effect. The research study follows a quantitative method to assess groundwater level rise risks through many in-situ measurements and mathematical modelling. The proposed approach highlights groundwater level, in the urban areas of the city on the shoreline band, reaching the high tide level without considering any input from precipitation. Despite the small tide in the Red Sea compared to other oceanic coasts, the groundwater level is considerably enhanced by the tide from the seaside and by the freshwater table from the landside of the city. In these conditions, the groundwater level becomes high in the city and prevents the soil to evacuate quickly enough the surface flow caused by the storm event, as it was observed in the last historical flood catastrophe of Jeddah in 2009.

Keywords: Flood, groundwater rise, Jeddah, tide.

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Authors: Wu Di, Yeo Khoon Seng, Lim Tee Tai

Abstract:

The typical insects employ a flapping-wing mode of flight. The numerical simulations on free flight of a model fruit fly (Re=143) including hovering and are presented in this paper. Unsteady aerodynamics around a flapping insect is studied by solving the three-dimensional Newtonian dynamics of the flyer coupled with Navier-Stokes equations. A hybrid-grid scheme (Generalized Finite Difference Method) that combines great geometry flexibility and accuracy of moving boundary definition is employed for obtaining flow dynamics. The results show good points of agreement and consistency with the outcomes and analyses of other researchers, which validate the computational model and demonstrate the feasibility of this computational approach on analyzing fluid phenomena in insect flight. The present modeling approach also offers a promising route of investigation that could complement as well as overcome some of the limitations of physical experiments in the study of free flight aerodynamics of insects. The results are potentially useful for the design of biomimetic flapping-wing flyers.

Keywords: Free hovering flight, flapping wings, fruit fly, insect aerodynamics, leading edge vortex (LEV), computational fluid dynamics (CFD), Navier-Stokes equations (N-S), fluid structure interaction (FSI), generalized finite-difference method (GFD).

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