Search results for: Regularization Parameter Search.

Authors: David Boyajian, Tadeh Zirakian

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Stability and performance of steel plates are characterized by geometrical buckling and material yielding. In this paper, the geometrical buckling and material yielding behaviors of low yield point (LYP) steel plates are studied from the point of view of their application in steel plate shear wall (SPSW) systems. Use of LYP steel facilitates the design and application of web plates with improved buckling and energy absorption capacities in SPSW systems. LYP steel infill plates may yield first and then undergo inelastic buckling. Hence, accurate determination of the limiting plate thickness corresponding to simultaneous buckling and yielding can be effective in seismic design of such lateral force-resisting and energy dissipating systems. The limiting thicknesses of plates with different loading and support conditions are determined theoretically and verified through detailed numerical simulations. Effects of use of LYP steel and plate aspect ratio parameter on the limiting plate thickness are investigated as well. In addition, detailed studies are performed on determination of the limiting web-plate thickness in code-designed SPSWs. Some practical recommendations are accordingly provided for efficient seismic design of SPSW systems with LYP steel infill plates.

Keywords: Plates, buckling, yielding, low yield point steel, steel plate shear walls.

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Authors: R. Resmi, M. R. Baiju

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The thermal damping of a dynamic vibrating micromirror is an important factor affecting the design of MEMS based actuator systems. In the development process of new micromirror systems, assessing the extent of energy loss due to thermal damping accurately and predicting the performance of the system is very essential. In this paper, the depth of the thermal penetration layer at different eigenfrequencies and the temperature variation distributions surrounding a vibrating micromirror is analyzed. The thermal penetration depth corresponds to the thermal boundary layer in which energy is lost which is a measure of the thermal damping is found out. The energy is mainly dissipated in the thermal boundary layer and thickness of the layer is an important parameter. The detailed thermoacoustics is used to model the air domain surrounding the micromirror. The thickness of the boundary layer, temperature variations and thermal power dissipation are analyzed for a Si based torsional mode micromirror. It is found that thermal penetration depth decreases with eigenfrequency and hence operating the micromirror at higher frequencies is essential for reducing thermal damping. The temperature variations and thermal power dissipations at different eigenfrequencies are also analyzed. Both frequency-response and eigenfrequency analyses are done using COMSOL Multiphysics software.

Keywords: Eigen frequency analysis, micromirrors, thermal damping, thermoacoustic interactions.

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Authors: M.A.Behrang, M. Ghalambaz, E. Assareh, A.R. Noghrehabadi

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Fluid flow and heat transfer of vertical full cone embedded in porous media is studied in this paper. Nonlinear differential equation arising from similarity solution of inverted cone (subjected to wall temperature boundary conditions) embedded in porous medium is solved using a hybrid neural network- particle swarm optimization method. To aim this purpose, a trial solution of the differential equation is defined as sum of two parts. The first part satisfies the initial/ boundary conditions and does contain an adjustable parameter and the second part which is constructed so as not to affect the initial/boundary conditions and involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. Particle swarm optimization (PSO) is applied to find adjustable parameters of trial solution (in first and second part). The obtained solution in comparison with the numerical ones represents a remarkable accuracy.

Keywords: Porous Media, Ordinary Differential Equations (ODE), Particle Swarm Optimization (PSO), Neural Network (NN).

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Authors: Hajar Sadeghi, Payman Moallem, S. Amirhassn Monadjemi

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This paper presents a new feature based dense stereo matching algorithm to obtain the dense disparity map via dynamic programming. After extraction of some proper features, we use some matching constraints such as epipolar line, disparity limit, ordering and limit of directional derivative of disparity as well. Also, a coarseto- fine multiresolution strategy is used to decrease the search space and therefore increase the accuracy and processing speed. The proposed method links the detected feature points into the chains and compares some of the feature points from different chains, to increase the matching speed. We also employ color stereo matching to increase the accuracy of the algorithm. Then after feature matching, we use the dynamic programming to obtain the dense disparity map. It differs from the classical DP methods in the stereo vision, since it employs sparse disparity map obtained from the feature based matching stage. The DP is also performed further on a scan line, between any matched two feature points on that scan line. Thus our algorithm is truly an optimization method. Our algorithm offers a good trade off in terms of accuracy and computational efficiency. Regarding the results of our experiments, the proposed algorithm increases the accuracy from 20 to 70%, and reduces the running time of the algorithm almost 70%.

Keywords: Chain Correspondence, Color Stereo Matching, Dynamic Programming, Epipolar Line, Stereo Vision.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: Time series modelling, stochastic processes, ARIMA model, Karkheh River.

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Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst

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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.

Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.

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Authors: Elena Ezhova, Vadim Mottl, Olga Krasotkina

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The problem of estimating time-varying regression is inevitably concerned with the necessity to choose the appropriate level of model volatility - ranging from the full stationarity of instant regression models to their absolute independence of each other. In the stationary case the number of regression coefficients to be estimated equals that of regressors, whereas the absence of any smoothness assumptions augments the dimension of the unknown vector by the factor of the time-series length. The Akaike Information Criterion is a commonly adopted means of adjusting a model to the given data set within a succession of nested parametric model classes, but its crucial restriction is that the classes are rigidly defined by the growing integer-valued dimension of the unknown vector. To make the Kullback information maximization principle underlying the classical AIC applicable to the problem of time-varying regression estimation, we extend it onto a wider class of data models in which the dimension of the parameter is fixed, but the freedom of its values is softly constrained by a family of continuously nested a priori probability distributions.

Keywords: Time varying regression, time-volatility of regression coefficients, Akaike Information Criterion (AIC), Kullback information maximization principle.

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Authors: S. Panda, J. S. Yadav, N. P. Patidar, C. Ardil

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Order Reduction, Stability, Transfer Function, Integral Squared Error.

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Authors: Sidhartha Panda, N. P. Padhy

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: Marley Rosa Luciano, Rodney Rezende Saldanha

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The race for electrification and the need for innovation to attract customers has led the automotive industry to do something different with vehicles. New emissions control challenges and efficient technological availability are the pillars of creation. The growing demand to upgrade industrial manufacturing systems creates actions that directly impact vehicle production. With this comes the search for new prototyping methods and virtual tools for component testing and validation, and vehicle systems have established themselves. The demand for Electronic Control Units (ECU) is increasing due to the availability of intelligence and safety in today's vehicles, directly affecting their development, performance, and functional testing. In order to keep up with global changes, the automotive industry uses different virtual environments to produce, verify and validate their vehicles and test prototypes used during development. Therefore, in this paper, integration and validation were performed using the Hardware in the Loop (HIL) test platform, focusing on the ECU Body Control Module (BCM). Then, a brief commentary reviews other test medium platforms, such as the Plywood Buck (PWB), and examines the reliability, flexibility, installation time, and cost of the three test platforms, software in the loop (SIL), Model in the loop (MIL), and HIL, to review their benefits, challenges, and issues in use and information to optimize the use of each platform and test medium.

Keywords: Automotive, Electronic Central Unit, xIL, Hardware in the loop.

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Authors: R. Bhargava, Sonam Singh

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In the present study, a numerical analysis is carried out to investigate unsteady MHD (magneto-hydrodynamic) flow and heat transfer of a non-Newtonian second grade viscoelastic fluid over an oscillatory stretching sheet. The flow is induced due to an infinite elastic sheet which is stretched oscillatory (back and forth) in its own plane. Effect of viscous dissipation and joule heating are taken into account. The non-linear differential equations governing the problem are transformed into system of non-dimensional differential equations using similarity transformations. A newly developed meshfree numerical technique Element free Galerkin method (EFGM) is employed to solve the coupled non linear differential equations. The results illustrating the effect of various parameters like viscoelastic parameter, Hartman number, relative frequency amplitude of the oscillatory sheet to the stretching rate and Eckert number on velocity and temperature field are reported in terms of graphs and tables. The present model finds its application in polymer extrusion, drawing of plastic films and wires, glass, fiber and paper production etc.

Keywords: EFGM, MHD, Oscillatory stretching sheet, Unsteady, Viscoelastic

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Authors: Ali Keshavarzi, Fereydoon Sarmadian

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Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Keywords: Easily measurable characteristics, Feed-forwardback propagation, Pedotransfer functions, CEC.

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: Model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs.

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Authors: M. S. Reza, M. Hamdi, S. H. Tomadi, A. R. Ismail

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The operating control parameters of injection flushing type of electrical discharge machining process on stainless steel 304 workpiece using copper tools are being optimized according to its individual machining characteristic i.e. Electrode Wear Ratio (EWR). Higher EWR would give bad dimensional precision for the EDM machined workpiece because of high electrode wear. Hence, the quality characteristic for EWR is set to lower-the-better to achieve the optimum dimensional precision for the machined workpiece. Taguchi method has been used for the construction, layout and analysis of the experiment for EWR machining characteristic. The use of Taguchi method in the experiment saves a lot of time and cost of preparing and machining the experiment samples. Therefore, an L18 Orthogonal array which was the fundamental component in the statistical design of experiments has been used to plan the experiments and Analysis of Variance (ANOVA) is used to determine the optimum machining parameters for this machining characteristic. The control parameters selected for this optimization experiments are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. The result had shown that negative polarity machining parameter setting will decreases EWR.

Keywords: ANOVA, EDM, Injection Flushing, L18Orthogonal Array, EWR, Stainless Steel 304

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Authors: Satish Kumar, Arun Kumar Gupta, Pankaj Chandna

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The present work analyses different parameters of pressure die casting to minimize the casting defects. Pressure diecasting is usually applied for casting of aluminium alloys. Good surface finish with required tolerances and dimensional accuracy can be achieved by optimization of controllable process parameters such as solidification time, molten temperature, filling time, injection pressure and plunger velocity. Moreover, by selection of optimum process parameters the pressure die casting defects such as porosity, insufficient spread of molten material, flash etc. are also minimized. Therefore, a pressure die casting component, carburetor housing of aluminium alloy (Al2Si2O5) has been considered. The effects of selected process parameters on casting defects and subsequent setting of parameters with the levels have been accomplished by Taguchi-s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L18 orthogonal array. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the percent contribution of different process parameters. Confidence interval has also been estimated for 95% consistency level and three conformational experiments have been performed to validate the optimum level of different parameters. Overall 2.352% reduction in defects has been observed with the help of suggested optimum process parameters.

Keywords: Aluminium Casting, Pressure Die Casting, Taguchi Methodology, Design of Experiments

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Authors: H. Shayeghi, H.A. Shayanfar, A. Jalili

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In the LFC problem, the interconnections among some areas are the input of disturbances, and therefore, it is important to suppress the disturbances by the coordination of governor systems. In contrast, tie-line power flow control by TCPS located between two areas makes it possible to stabilize the system frequency oscillations positively through interconnection, which is also expected to provide a new ancillary service for the further power systems. Thus, a control strategy using controlling the phase angle of TCPS is proposed for provide active control facility of system frequency in this paper. Also, the optimum adjustment of PID controller's parameters in a robust way under bilateral contracted scenario following the large step load demands and disturbances with and without TCPS are investigated by Particle Swarm Optimization (PSO), that has a strong ability to find the most optimistic results. This newly developed control strategy combines the advantage of PSO and TCPS and has simple stricture that is easy to implement and tune. To demonstrate the effectiveness of the proposed control strategy a three-area restructured power system is considered as a test system under different operating conditions and system nonlinearities. Analysis reveals that the TCPS is quite capable of suppressing the frequency and tie-line power oscillations effectively as compared to that obtained without TCPS for a wide range of plant parameter changes, area load demands and disturbances even in the presence of system nonlinearities.

Keywords: LFC, TCPS, Dregulated Power System, PowerSystem Control, PSO.

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Authors: J. Tospornsampan, I. Kita, M. Ishii, Y. Kitamura

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In this paper a procedure for the split-pipe design of looped water distribution network based on the use of simulated annealing is proposed. Simulated annealing is a heuristic-based search algorithm, motivated by an analogy of physical annealing in solids. It is capable for solving the combinatorial optimization problem. In contrast to the split-pipe design that is derived from a continuous diameter design that has been implemented in conventional optimization techniques, the split-pipe design proposed in this paper is derived from a discrete diameter design where a set of pipe diameters is chosen directly from a specified set of commercial pipes. The optimality and feasibility of the solutions are found to be guaranteed by using the proposed method. The performance of the proposed procedure is demonstrated through solving the three well-known problems of water distribution network taken from the literature. Simulated annealing provides very promising solutions and the lowest-cost solutions are found for all of these test problems. The results obtained from these applications show that simulated annealing is able to handle a combinatorial optimization problem of the least cost design of water distribution network. The technique can be considered as an alternative tool for similar areas of research. Further applications and improvements of the technique are expected as well.

Keywords: Combinatorial problem, Heuristics, Least-cost design, Looped network, Pipe network, Optimization

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: Black box modeling, fixed wing aircraft, least square error, longitudinal dynamics, system identification.

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Authors: N. Mamode Khan, V. Jowaheer

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In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Keywords: Breakdowns, under-dispersion, com-poisson, generalized linear model, marginal quasi-likelihood estimation, joint quasi-likelihood estimation.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: Automatic detection, wavelets, defects, fracture lines.

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Authors: Muhammed Ertuğrul Çeloğlu, Mehmet Yılmaz

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In this study, apricot seed shell, walnut shell, and sawdust were chosen as biomass sources. The materials were sorted by using a sieve No. 50 and the sieved materials were subjected to pyrolysis process at 400 °C, resulting in three different biochar products. The resulting biochar products were added to the bitumen at three different rates (5%, 10% and 15%), producing modified bitumen. Penetration, softening point, rotation viscometer and dynamic shear rheometer (DSR) tests were conducted on modified binders. Thus the modified bitumen, which was obtained by using additives at 3 different rates obtained from biochar produced at 400 °C temperatures of 3 different biomass sources were compared and the effects of pyrolysis temperature and additive rates were evaluated. As a result of the conducted tests, it was determined that the rheology of the pure bitumen improved significantly as a result of the modification of the bitumen with the biochar. Additionally, with biochar additive, it was determined that the rutting parameter values obtained from softening point, viscometer and DSR tests were increased while the values in terms of penetration and phase angle decreased. It was also observed that the most effective biomass is sawdust while the least effective was ground apricot seed shell.

Keywords: Rheology, biomass, pyrolysis, biochar.

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Authors: Seyed Abolhasan Naeini, Mohammad Hossein Zade, E. Izadi, M. Hossein Zade

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The different seismic behavior of liquid storage tanks rather than conventional structures makes their responses more complicated. Uplifting and excessive settlement due to liquid sloshing are the most frequent damages in cylindrical liquid tanks after shell bucking failure modes. As a matter of fact, uses of liquid storage tanks because of the simple construction on compact layer of soil as a foundation are very conventional, but in some cases need to retrofit are essential. The tank seismic behavior can be improved by modifying dynamic characteristic of tank with verifying seismic loads as well as retrofitting and improving base ground. This paper focuses on a typical steel tank on loose, medium and stiff sandy soil and describes an evaluation of displacement of the tank before and after retrofitting. The Abaqus program was selected for its ability to include shell and structural steel elements, soil-structure interaction, and geometrical nonlinearities and contact type elements. The result shows considerable decreasing in settlement and uplifting in the case of retrofitted tank. Also, by increasing shear strength parameter of soil, the performance of the liquid storage tank under the case of seismic load increased.

Keywords: Steel tank, soil-structure, sandy soil, seismic load.

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Authors: V. C. Sathish Gandhi, R. Kumaravelan, S. Ramesh, M. Venkatesan, M. Ponraj

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Each year nearly nine hundred persons die in head injuries and over fifty thousand persons are severely injured due to non wearing of helmets. In motor cycle accidents, the human head is exposed to heavy impact loading against natural protection. In this work, an attempt has been made for analyzing the helmet with all the standard data. The simulation software ‘ANSYS’ is used to analyze the helmet with different conditions such as bottom fixed-load on top surface, bottom fixed -load on top line, side fixed –load on opposite surface, side fixed-load on opposite line and dynamic analysis. The maximum force of 19.5 kN is applied on the helmet to study the model in static and dynamic conditions. The simulation has been carried out for the static condition for the parameters like total deformation, strain energy, von-Mises stress for different cases. The dynamic analysis has been performed for the parameter like total deformation and equivalent elastic strain. The result shows that these values are concentrated in the retention portion of the helmet. These results have been compared with the standard experimental data proposed by the BIS and well within the acceptable limit.

Keywords: Helmet, Deformation, Strain energy, Equivalent elastic strain.

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Authors: Petra Wächter

Abstract:

A comprehensive discussion of feasible strategies for sustainable energy supply is urgently needed to achieve a turnaround of the current energy situation. The necessary fundamentals required for the development of a long term energy vision are lacking to a great extent due to the absence of reasonable long term scenarios that fulfill the requirements of climate protection and sustainable energy use. The contribution of the study is based on a search for sustainable energy paths in the long run for Austria. The analysis makes use of secondary data predominantly. The measures developed to avoid CO2 emissions and other ecological risk factors vary to a great extent among all economic sectors. This is shown by the calculation of CO2 cost of abatement curves. In this study it is demonstrated that the most effective technical measures with the lowest CO2 abatement costs yield solutions to the current energy problems. Various scenarios are presented concerning the question how the technological and environmental options for a sustainable energy system for Austria could look like in the long run. It is shown how sustainable energy can be supplied even with today-s technological knowledge and options available. The scenarios developed include an evaluation of the economic costs and ecological impacts. The results are not only applicable to Austria but demonstrate feasible and cost efficient ways towards a sustainable future.

Keywords: Cost of CO2 Abatement, Energy Economics, Energy Efficiency, Renewable Energy Technologies, Sustainable Energy and Development.

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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The idea of adding metallic energy dissipaters to a structure to absorb a large part of the seismic energy began four decades ago. There are several types of metal-based devices conceived as dampers for the seismic energy absorber whereby damages to the major structural components could be minimized for both new and existing structures. This paper aimed to develop and evaluate structural performance of both stiffened and non stiffened circular shear panel damper for passive seismic energy protection by inelastic deformation. Structural evaluation was done using commercially available nonlinear FE simulation program. Diameter-to-thickness ratio is employed as main parameter to investigate the hysteresis performance of stiffened and unstiffened circular shear panel. Depending on these parameters three different buckling mode and hysteretic behavior was found: yielding prior to buckling without strength degradation, yielding prior to buckling with strength degradation and yielding with buckling and strength degradation which forms pinching at initial displacement. Hence, the hysteresis behavior is identified, specimens which deform without strength degradation so it will be used as passive energy dissipating device in civil engineering structures.

Keywords: Circular shear panel damper, FE analysis, Hysteretic behavior, Large deformation.

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Authors: Chana Raksiri, Pornchai Chatchaikulsiri

Abstract:

The objective of this research is parameters optimized of the stair shape workpiece which is cut by CNC Wire-Cut EDM (WEDW). The experiment material is SKD-11 steel of stair-shaped with variable height workpiece 10, 20, 30 and 40 mm. with the same 10 mm. thickness are cut by Sodick's CNC Wire-Cut EDM model AD325L. The experiments are designed by 3k full factorial experimental design at 3 level 2 factors and 9 experiments with 2 replicate. The selected two factor are servo voltage (SV) and servo feed rate (SF) and the response is cutting thickness error. The experiment is divided in two experiments. The first experiment determines the significant effective factor at confidential interval 95%. The SV factor is the significant effective factor from first result. In order to result smallest cutting thickness error of workpieces is 17 micron with the SV value is 46 volt. Also show that the lower SV value, the smaller different thickness error of workpiece. Then the second experiment is done to reduce different cutting thickness error of workpiece as small as possible by lower SV. The second experiment result show the significant effective factor at confidential interval 95% is the SV factor and the smallest cutting thickness error of workpieces reduce to 11 micron with the experiment SV value is 36 volt.

Keywords: CNC Wire-Cut, Variable Thickness Workpiece, Design of Experiments, Full Factorial Design

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Authors: Gang Li, Ghulam Mubashar Hassan, Arcady Dyskin, Cara MacNish

Abstract:

Digital image correlation (DIC) is a contactless fullfield displacement and strain reconstruction technique commonly used in the field of experimental mechanics. Comparing with physical measuring devices, such as strain gauges, which only provide very restricted coverage and are expensive to deploy widely, the DIC technique provides the result with full-field coverage and relative high accuracy using an inexpensive and simple experimental setup. It is very important to study the natural patterns effect on the DIC technique because the preparation of the artificial patterns is time consuming and hectic process. The objective of this research is to study the effect of using images having natural pattern on the performance of DIC. A systematical simulation method is used to build simulated deformed images used in DIC. A parameter (subset size) used in DIC can have an effect on the processing and accuracy of DIC and even cause DIC to failure. Regarding to the picture parameters (correlation coefficient), the higher similarity of two subset can lead the DIC process to fail and make the result more inaccurate. The pictures with good and bad quality for DIC methods have been presented and more importantly, it is a systematic way to evaluate the quality of the picture with natural patterns before they install the measurement devices.

Keywords: Digital image correlation (DIC), Deformation simulation, Natural pattern, Subset size.

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

This paper presents modeling and optimization of two NP-hard problems in flexible manufacturing system (FMS), part type selection problem and loading problem. Due to the complexity and extent of the problems, the paper was split into two parts. The first part of the papers has discussed the modeling of the problems and showed how the real coded genetic algorithms (RCGA) can be applied to solve the problems. This second part discusses the effectiveness of the RCGA which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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Authors: F. Farzin

Abstract:

Research has shown that techno-entrepreneurship is economically significant. Therefore, it is suggested that teaching techno-entrepreneurship may be important because such programmes would prepare current and future generations of learners to recognise and act on high-technology opportunities. Education in technoentrepreneurship may increase the knowledge of how to start one’s own enterprise and recognise the technological opportunities for commercialisation to improve decision-making about starting a new venture; also it influence decisions about capturing the business opportunities and turning them into successful ventures. Universities can play a main role in connecting and networking technoentrepreneurship students towards a cooperative attitude with real business practice and industry knowledge. To investigate and answer whether education for techno-entrepreneurs really helps, this paper choses a comparison of literature reviews as its method of research. After reviewing literature related to the impact of technoentrepreneurship education on self-employment 6 studies which had similar aim and objective to this paper were. These particular papers were selected based on a keywords search and as their aim, objectives, and gaps were close to the current research. In addition, they were all based on the influence of techno-entrepreneurship education in self-employment and intention of students to start new ventures. The findings showed that teaching techno-entrepreneurship education may have an influence on students’ intention and their future self-employment, but which courses should be covered and the duration of programmes, needs further investigation.

Keywords: Techno-entrepreneurship education, training, higher education, intention, self-employment.

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