Search results for: GCSC Parameters

Authors: Rajamani Doraiswami, Lahouari Cheded

Abstract:

Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: Keywords—Identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: Farhad Kolahan, A. Hamid Khajavi

Abstract:

Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.

Keywords: AWJ cutting, Mathematical modeling, Simulated Annealing, Optimization

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Authors: Mingaleva Zhanna, Gayfutdinova Oksana, Podgornova Evgenia

Abstract:

The regional innovative competitiveness is an integrating characteristic of the innovative sphere of the region. It depends on a big variety of different parameters connected with all kinds of economic entities- activities. But management parameters shouldn't be irregular, so in order to avoid it, an institutional system should be formed. This system should carry out strategic management of factors having the greatest influence on the region's innovative development. This article is devoted to different aspects of organization of the region's development institutional mechanism, which is based on management of regional innovative competitiveness parameters. The base of the analysis is innovatively-active Russian regions which were compared according to the level of the innovative competitiveness. After that the most important parameters of successful innovative development of the region were revealed with the help of the correlation-regression analysis. The results of the research could be used for investigation of the region's innovative policy.

Keywords: Regional innovative competitiveness, institutional mechanism, innovative region development, correlation-regression analysis.

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Authors: A. Hayati Soloot, A. Gholami, E. Agheb, A. Ghorbandaeipour, P. Mokhtari

Abstract:

The two significant overvoltages in power system, switching overvoltage and lightning overvoltage, are investigated in this paper. Firstly, the effect of various power system parameters on Line Energization overvoltages is evaluated by simulation in ATP. The dominant parameters include line parameters; short-circuit impedance and circuit breaker parameters. Solutions to reduce switching overvoltages are reviewed and controlled closing using switchsync controllers is proposed as proper method. This paper also investigates lightning overvoltages in the overhead-cable transition. Simulations are performed in PSCAD/EMTDC. Surge arresters are applied in both ends of cable to fulfill the insulation coordination. The maximum amplitude of overvoltages inside the cable is surveyed which should be of great concerns in insulation coordination studies.

Keywords: Switching Overvoltage, Lightning Overvoltage, Insulation Coordination, ATP, PSCAD/EMTDC.

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Authors: V. Ten

Abstract:

An approach of design of stable of control systems with ultimately wide ranges of uncertainly disturbed parameters is offered. The method relies on using of nonlinear structurally stable functions from catastrophe theory as controllers. Theoretical part presents an analysis of designed nonlinear second-order control systems. As more important the integrators in series, canonical controllable form and Jordan forms are considered. The analysis resumes that due to added controllers systems become stable and insensitive to any disturbance of parameters. Experimental part presents MATLAB simulation of design of control systems of epidemic spread, aircrafts angular motion and submarine depth. The results of simulation confirm the efficiency of offered method of design. KeywordsCatastrophes, robust control, simulation, uncertain parameters.

Keywords: Catastrophes, robust control, simulation, uncertain parameters.

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Authors: Keyvan Shahgholian, Hamid Hajihosseini

Abstract:

The significance of environmental protection is wellknown in today's world. The execution of any program depends on sufficient knowledge and required familiarity with environment and its pollutants. Taking advantage of a systematic method, as a new science, in environmental planning can solve many problems. In this article, air pollution in Tehran and its relationship with health and population growth have been analyzed using dynamic systems. Firstly, by using casual loops, the relationship between the parameters effective on air pollution in Tehran were taken into consideration, then these casual loops were turned into flow diagrams [6], and finally, they were simulated using the software Vensim [16]in order to conclude what the effect of each parameter will be on air pollution in Tehran in the next 10 years, how changing of one or more parameters influences other parameters, and which parameter among all other parameters requires to be controlled more.

Keywords: Air pollutions, Simulation, System Dynamics, Tehran, Vensim.

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Authors: El H. Bouziani, H. A. Reguieg Yssaad

Abstract:

The phytotoxicity of heavy metals can be expressed on roots and visible part of plants and is characterized by molecular and metabolic answers at various levels of organization of the whole plant. The present study was undertaken on two varieties of broad bean Vicia faba (Sidi Aïch and Super Aguadulce). The device was mounted on a substrate prepared by mixing sand, soil and compost, the substrate was artificially contaminated with three doses of lead nitrate [Pb(NO3)2] 0, 500 and 1000 ppm. Our objective is to follow the behavior of plant opposite the stress by evaluating the physiological parameters. The results reveal a reduction in the parameters of the productivity (chlorophyll and proteins production) with an increase in the osmoregulators (soluble sugars and proline).These results show that the production of broad bean is strongly modified by the disturbance of its internal physiology under lead exposure.

Keywords: Broad bean, lead, stress, physiological parameters, phytotoxicity.

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: Hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters.

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Authors: H. A. Taner, V. Önen

Abstract:

A suitable choice of flotation parameters and reagents have a strong effect on the effectiveness of flotation process. The objective of this paper is to give an overview of the flotation of chalcopyrite with the different conditions and dispersants. Flotation parameters such as grinding time, pH, type, and dosage of dispersant were investigated. In order to understand the interaction of some dispersants, sodium silicate, sodium hexametaphosphate and sodium polyphosphate were used. The optimum results were obtained at a pH of 11.5 and a grinding time of 10 minutes. A copper concentrate was produced assaying 29.85% CuFeS₂ and 65.97% flotation recovery under optimum rougher flotation conditions with sodium silicate.

Keywords: Chalcopyrite, dispersant, flotation, copper.

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Authors: İbrahim Hakkı Erkan, Özcan Tan

Abstract:

The performance of jet grout columns was affected by many controlled and uncontrolled parameters. The leading parameters for the controlled ones can be listed as injection pressure, rod pulling speed, rod rotation speed, number of nozzles, nozzle diameter and Water/Cement ratio. And the uncontrolled parameters are soil type, soil structure, soil layering condition, underground water level, the changes in strength parameters and the rheologic properties of cement in time. In this study, the performance of jet grout columns and the effects of pulling speed and rotation speed were investigated experimentally. For this purpose, a laboratory type jet grouting system was designed for the experiments. Through this system, jet grout columns were produced in three different conditions. The results of the study showed that the grout pressure and the lifting speed significantly affect the performance of the jet grouting columns.

Keywords: Jet grout, sandy soils, soil improvement, soilcrete.

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Authors: Thejaswi H. Raya, Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

For over a decade, the Pulse Coupled Neural Network (PCNN) based algorithms have been successfully used in image interpretation applications including image segmentation. There are several versions of the PCNN based image segmentation methods, and the segmentation accuracy of all of them is very sensitive to the values of the network parameters. Most methods treat PCNN parameters like linking coefficient and primary firing threshold as global parameters, and determine them by trial-and-error. The automatic determination of appropriate values for linking coefficient, and primary firing threshold is a challenging problem and deserves further research. This paper presents a method for obtaining global as well as local values for the linking coefficient and the primary firing threshold for neurons directly from the image statistics. Extensive simulation results show that the proposed approach achieves excellent segmentation accuracy comparable to the best accuracy obtainable by trial-and-error for a variety of images.

Keywords: Automatic Selection of PCNN Parameters, Image Segmentation, Neural Networks, Pulse Coupled Neural Network

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Authors: R. Mahjoub, K. Maghsoudi Mehraban

Abstract:

Since the heart of the hybrid system is the fuel cell and it has vital impact on efficiency and performance of cycle, in this study, the major modeling of electrochemical reaction within the fuel cell is analyzed. Also, solid oxide fuel cell is integrated with the gas turbine and thermodynamic analysis on different elements of hybrid system is applied. Next, in predefined operational points of hybrid cycle, the simulation results are obtained. Then, different source of irreversibility in fuel cell is modeled and influence of different major parameters on different irreversibility is computed and applied. Then, the effect of important parameters such as thickness and surface of electrolyte fuel cell are simulated in fuel cell and its dependency to these parameters is explained. At the end of the paper, different impact of parameters on fuel cell with a gas turbine and current density and voltage of fuel cell are simulated.

Keywords: Electrochemical analysis, Gas turbine, Hybrid system, Irreversibility analysis.

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Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

Abstract:

Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: Epoxy molding compounds, optimization, regression analysis, transfer molding process, voids, wire sweep.

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Authors: J. Dzugan, M. Spaniel, P. Konopík, J. Ruzicka, J. Kuzelka

Abstract:

The modeling of inelastic behavior of plastic materials requires measurements providing information on material response to different multiaxial loading conditions. Different triaxiality conditions and values of Lode parameters have to be covered for complex description of the material plastic behavior. Samples geometries providing material plastic behavoiur over the range of interest are proposed with the use of FEM analysis. Round samples with 3 different notches and smooth surface are used together with butterfly type of samples tested at angle ranging for 0 to 90°. Identification of ductile damage parameters is carried out on the basis of obtained experimental data for austenitic stainless steel. The obtained material plastic damage parameters are subsequently applied to FEM simulation of notched CT normally samples used for fracture mechanics testing and results from the simulation are compared with real tests.

Keywords: baqus, austenitic steel, computer simulation, ductile damage, triaxiality

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Authors: Tatjana Rakcejeva, Jelena Zagorska, Elina Zvezdina

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The aim of the current research was to investigate the gassy ozone effect on quality parameters of flaxes made form whole biologically activated wheat grains. The research was accomplished on wheat grains variety

Keywords: Gassy ozone, flaxes, biologically activated grains, quality parameters, treatment.

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Authors: Fadi Eleiwi, Taous Meriem Laleg-Kirati, Sofiane Khelladi, Farid Bakir

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This paper presents the use of a semi-classical signal analysis method that has been developed recently for the analysis of turbomachinery flow unsteadiness. We will focus on the correlation between theSemi-Classical Signal Analysis parameters and some physical parameters in relation with turbomachinery features. To demonstrate the potential of the proposed approach, a static pressure signal issued from a rotor/stator interaction of a centrifugal pump is studied. Several configurations of the pump are compared.

Keywords: Semi-classical signal analysis, turbomachines, newindices, physical parameters

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Authors: J. Kundrák, I. Sztankovics, K. Gyáni

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In addition to the increase of the material removal rate or surface rate, or the improvement of the surface quality, which are the main aims of the development of manufacturing technology, a growing number of other manufacturing requirements have appeared in the machining of workpiece surfaces. Among these it is becoming increasingly dominant to generate a surface topography in finishing operations which meets more closely the needs of operational requirements.

These include the examination of the surface periodicity and/or ensuring that the twist-structure values are within the limits (or even preventing its occurrence) in specified cases such as on the sealing surfaces of rotating shafts or on the inside working surfaces of needle roller bearings. In the view of the measurement the twist has different parameters from surface roughness, which must be determined for the machining procedures. Therefore in this paper the alteration of the theoretical values of the parameters determining twist structure are studied as a function of the kinematic properties.

Keywords: Kinematic parameters, rotational turning, surface topography, twist structure

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Authors: Wei-Chih Tang, Shih-Wei Lu, Chih-Mong Tsai, Cheng-Yan Kao, Hsiu-Hui Lee

Abstract:

Previously, harmonic parameters (HPs) have been selected as features extracted from EEG signals for automatic sleep scoring. However, in previous studies, only one HP parameter was used, which were directly extracted from the whole epoch of EEG signal. In this study, two different transformations were applied to extract HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet transform (WT). EEG signals are decomposed by the two transformations; and features were extracted from different components. Twelve parameters (four sets of HPs) were extracted. Some of the parameters are highly diverse among different stages. Afterward, HPs from two transformations were used to building a rough sleep stages scoring model using the classifier SVM. The performance of this model is about 78% using the features obtained by our proposed extractions. Our results suggest that these features may be useful for automatic sleep stages scoring.

Keywords: EEG, harmonic parameter, Hilbert-Huang transform, sleep stages, wavelet transform.

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Authors: Nassereldeen A. Kabashi, Suleyman A. Muyibi. Mohammed E. Saeed., Farhana I. Yahya

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It is important to remove manganese from water because of its effects on human and the environment. Human activities are one of the biggest contributors for excessive manganese concentration in the environment. The proposed method to remove manganese in aqueous solution by using adsorption as in carbon nanotubes (CNT) at different parameters: The parameters are CNT dosage, pH, agitation speed and contact time. Different pHs are pH 6.0, pH 6.5, pH 7.0, pH 7.5 and pH 8.0, CNT dosages are 5mg, 6.25mg, 7.5mg, 8.75mg or 10mg, contact time are 10 min, 32.5 min, 55 min, 87.5 min and 120 min while the agitation speeds are 100rpm, 150rpm, 200rpm, 250rpm and 300rpm. The parameters chosen for experiments are based on experimental design done by using Central Composite Design, Design Expert 6.0 with 4 parameters, 5 levels and 2 replications. Based on the results, condition set at pH 7.0, agitation speed of 300 rpm, 7.5mg and contact time 55 minutes gives the highest removal with 75.5%. From ANOVA analysis in Design Expert 6.0, the residual concentration will be very much affected by pH and CNT dosage. Initial manganese concentration is 1.2mg/L while the lowest residual concentration achieved is 0.294mg/L, which almost satisfy DOE Malaysia Standard B requirement. Therefore, further experiments must be done to remove manganese from model water to the required standard (0.2 mg/L) with the initial concentration set to 0.294 mg/L.

Keywords: Adsorption, CNT, DOE, Manganese, Parameters.

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Authors: Md Asif Imrul, Maria Rafique, M. Habibur Rahman

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The study deals with an investigation into the impact of the relocation of tannery industry on water quality parameters of Buriganga. For this purpose, previous records have been collected from authentic data resources and for the attainment of present values, several samples were collected from three major locations of the Buriganga River during summer and winter seasons in 2018 to determine the distribution and variation of water quality parameters. Samples were collected six ft below the river water surface. Analysis indicates slightly acidic to slightly alkaline (6.8-7.49) in nature. Bio-Chemical Oxygen Demand, Total Dissolved Solids, Total Solids (TS) & Total Suspended Solids (TSS) have been found greater in summer. On the other hand, Dissolved Oxygen is found greater in rainy seasons. Relocation shows improvement in water quality parameters. Though the improvement related to relocation of tannery industry is not adequate to turn the water body to be an inhabitable place for aquatic lives.

Keywords: Buriganga river, river pollution, tannery industry, water quality parameters.

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Authors: Kooshina Koosha, Sima Habibi, Azam Talebian

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Electrospinning is a simple, versatile and widely accepted technique to produce ultra-fine fibers ranging from nanometer to micron. Recently there has been great interest in developing this technique to produce nanofibers with novel properties and functionalities. The electrospinning field is extremely broad, and consequently there have been many useful reviews discussing various aspects from detailed fiber formation mechanism to the formation of nanofibers and to discussion on a wide range of applications. On the other hand, the focus of this study is quite narrow, highlighting electrospinning parameters. This work will briefly cover the solution and processing parameters (for instance; concentration, solvent type, voltage, flow rate, distance between the collector and the tip of the needle) impacting the morphological characteristics of nanofibers, such as diameter. In this paper, a comprehensive work would be presented on the research of producing nanofibers from natural polymer entitled Gelatin.

Keywords: Electro spinning, solution parameters, process parameters, natural fiber.

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Authors: Surinder Deswal, Mahesh Pal

Abstract:

An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Keywords: Artificial neural network, evaporation losses, multiple linear regression, modeling.

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Authors: S. Sabzchi Asl, N. Tahouni, M. H. Panjeshahi

Abstract:

Benchmarking of a process with respect to energy consumption, without accomplishing a full retrofit study, can save both engineering time and money. In order to achieve this goal, the first step is to develop a conceptual-mathematical model that can easily be applied to a group of similar processes. In this research, we have aimed to identify a set of key parameters for the model which is supposed to be used for benchmarking of combined cycle power plants. For this purpose, three similar combined cycle power plants were studied. The results showed that ambient temperature, pressure and relative humidity, number of HRSG evaporator pressure levels and relative power in part load operation are the main key parameters. Also, the relationships between these parameters and produced power (by gas/ steam turbine), gas turbine and plant efficiency, temperature and mass flow rate of the stack flue gas were investigated.

Keywords: Combined cycle power plant, energy benchmarking, modelling, Retrofit.

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Authors: Mahmoud Zarrini, R. N. Pralhad

Abstract:

In this paper, mathematical modeling of detonation in the ground is studied. Estimation of flow parameters such as velocity, maximum velocity, acceleration, maximum acceleration, shock pressure as a result of an explosion in the ground have been computed in an appropriate dynamic model approach. The variation of these parameters with the diameter of detonation place (L), density of earth or stone (¤ü), time decay of detonation (T), peak pressure (Pm), and time (t) have been analyzed. The model has been developed from the concept of underwater explosions [Refs. [1]-[3]] with appropriate changes to the present model requirements.

Keywords: Shock velocity, detonation, shock acceleration, shock pressure.

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Authors: T. Hacib, M. R. Mekideche, N. Ferkha

Abstract:

This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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Authors: P.Saravanan, Narayanan .C.K., P.V.S.S Prakash, Prabhakara Rao .G.V

Abstract:

Video Mosaicing is the stitching of selected frames of a video by estimating the camera motion between the frames and thereby registering successive frames of the video to arrive at the mosaic. Different techniques have been proposed in the literature for video mosaicing. Despite of the large number of papers dealing with techniques to generate mosaic, only a few authors have investigated conditions under which these techniques generate good estimate of motion parameters. In this paper, these techniques are studied under different videos, and the reasons for failures are found. We propose algorithms with incorporation of outlier removal algorithms for better estimation of motion parameters.

Keywords: Motion parameters, Outlier removal algorithms, Registering , and Video Mosaicing.

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Authors: Shivakumar, G. S. Vijay, P. Srinivas Pai, B. R. Shrinivasa Rao

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In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: Radial Basis Function networks, emissions, Performance parameters, Fuzzy c means.

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Authors: Farhad Kolahan, Mehdi Heidari

Abstract:

Gas Metal Arc Welding (GMAW) processes is an important joining process widely used in metal fabrication industries. This paper addresses modeling and optimization of this technique using a set of experimental data and regression analysis. The set of experimental data has been used to assess the influence of GMAW process parameters in weld bead geometry. The process variables considered here include voltage (V); wire feed rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate distance (D). The process output characteristics include weld bead height, width and penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the GMAW process parameters. The objective is to determine a suitable set of process parameters that can produce desired bead geometry, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.

Keywords: Weld Bead Geometry, GMAW welding, Processparameters Optimization, Modeling, SA algorithm

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Authors: C. D. Naiju, K. Annamalai, Siva Prasad Darla, Y. Murali Krishna

Abstract:

This work presents the results of a study carried out to determine the sliding wear behavior and its effect on the process parameters of components manufactured by direct metal laser sintering (DMLS). A standard procedure and specimen had been used in the present study to find the wear behavior. Using Taguchi-s experimental technique, an orthogonal array of modified L8 had been developed. Sliding wear testing using pin-on-disk machine was carried out and analysis of variance (ANOVA) technique was used to investigate the effect of process parameters and to identify the main process parameter that influences the properties of wear behavior on the DMLS components. It has been found that part orientation, one of the selected process parameter had more influence on wear as compared to other selected process parameters.

Keywords: ANOVA, DMLS, Taguchi, Wear.

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model.

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