Search results for: linear equations

Authors: Hassnen M. Jafer, Khalid S. Hashim, W. Atherton, Ali W. Alattabi

Abstract:

This study investigates the effect of two important parameters (length of curing period and percentage of the added binder) on the strength of soil treated with OPC. An intermediate plasticity silty clayey soil with medium organic content was used in this study. This soft soil was treated with different percentages of a commercially available cement type 32.5-N. laboratory experiments were carried out on the soil treated with 0, 1.5, 3, 6, 9, and 12% OPC by the dry weight to determine the effect of OPC on the compaction parameters, consistency limits, and the compressive strength. Unconfined compressive strength (UCS) test was carried out on cement-treated specimens after exposing them to different curing periods (1, 3, 7, 14, 28, and 90 days). The results of UCS test were used to develop a non-linear multi-regression model to find the relationship between the predicted and the measured maximum compressive strength of the treated soil (qu). The results indicated that there was a significant improvement in the index of plasticity (IP) by treating with OPC; IP was decreased from 20.2 to 14.1 by using 12% of OPC; this percentage was enough to increase the UCS of the treated soil up to 1362 kPa after 90 days of curing. With respect to the statistical model of the predicted qu, the results showed that the regression coefficients (R2) was equal to 0.8534 which indicates a good reproducibility for the constructed model.

Keywords: Cement admixtures, soft soil stabilisation, geotechnical parameters, unconfined compressive strength, multi-regression model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1344

Authors: A. Selmi

Abstract:

Free vibration analysis of homogenous and axially functionally graded simply supported beams within the context of Euler-Bernoulli beam theory is presented in this paper. The material properties of the beams are assumed to obey the linear law distribution. The effective elastic modulus of the composite was predicted by using the rule of mixture. Here, the complexities which appear in solving differential equation of transverse vibration of composite beams which limit the analytical solution to some special cases are overcome using a relatively new approach called the Differential Transformation Method. This technique is applied for solving differential equation of transverse vibration of axially functionally graded beams. Natural frequencies and corresponding normalized mode shapes are calculated for different Young’s modulus ratios. MATLAB code is designed to solve the transformed differential equation of the beam. Comparison of the present results with the exact solutions proves the effectiveness, the accuracy, the simplicity, and computational stability of the differential transformation method. The effect of the Young’s modulus ratio on the normalized natural frequencies and mode shapes is found to be very important.

Keywords: Differential transformation method, functionally graded material, mode shape, natural frequency.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 749

Authors: G.Vinitha, A.Ramalingam

Abstract:

TiO2 nanoparticles were synthesized by hydrothermal method at 180°C from TiOSO4 aqueous solution with1m/l concentration. The obtained products were coated with silica by means of a seeded polymerization technique for a coating time of 1440 minutes to obtain well defined TiO2@SiO2 core-shell structure. The uncoated and coated nanoparticles were characterized by using X-Ray diffraction technique (XRD), Fourier Transform Infrared Spectroscopy (FT-IR) to study their physico-chemical properties. Evidence from XRD and FTIR results show that SiO2 is homogenously coated on the surface of titania particles. FTIR spectra show that there exists an interaction between TiO2 and SiO2 and results in the formation of Ti-O-Si chemical bonds at the interface of TiO2 particles and SiO2 coating layer. The non linear optical limiting properties of TiO2 and TiO2@SiO2 nanoparticles dispersed in ethylene glycol were studied at 532nm using 5ns Nd:YAG laser pulses. Three-photon absorption is responsible for optical limiting characteristics in these nanoparticles and it is seen that the optical nonlinearity is enhanced in core-shell structures when compared with single counterparts. This effective three-photon type absorption at this wavelength, is of potential application in fabricating optical limiting devices.

Keywords: hydrothermal method, optical limiting devicesseeded polymerization technique, three-photon type absorption

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1790

Authors: Samira Vafaye Eslahi

Abstract:

BCI (Brain Computer Interface) is a communication machine that translates brain massages to computer commands. These machines with the help of computer programs can recognize the tasks that are imagined. Feature extraction is an important stage of the process in EEG classification that can effect in accuracy and the computation time of processing the signals. In this study we process the signal in three steps of active segment selection, fractal feature extraction, and classification. One of the great challenges in BCI applications is to improve classification accuracy and computation time together. In this paper, we have used student’s 2D sample t-statistics on continuous wavelet transforms for active segment selection to reduce the computation time. In the next level, the features are extracted from some famous fractal dimension estimation of the signal. These fractal features are Katz and Higuchi. In the classification stage we used ANFIS (Adaptive Neuro-Fuzzy Inference System) classifier, FKNN (Fuzzy K-Nearest Neighbors), LDA (Linear Discriminate Analysis), and SVM (Support Vector Machines). We resulted that active segment selection method would reduce the computation time and Fractal dimension features with ANFIS analysis on selected active segments is the best among investigated methods in EEG classification.

Keywords: EEG, Student’s t- statistics, BCI, Fractal Features, ANFIS, FKNN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2089

Authors: R.V Pawar, P.P.Kajave, S.N.Mali

Abstract:

The speech signal conveys information about the identity of the speaker. The area of speaker identification is concerned with extracting the identity of the person speaking the utterance. As speech interaction with computers becomes more pervasive in activities such as the telephone, financial transactions and information retrieval from speech databases, the utility of automatically identifying a speaker is based solely on vocal characteristic. This paper emphasizes on text dependent speaker identification, which deals with detecting a particular speaker from a known population. The system prompts the user to provide speech utterance. System identifies the user by comparing the codebook of speech utterance with those of the stored in the database and lists, which contain the most likely speakers, could have given that speech utterance. The speech signal is recorded for N speakers further the features are extracted. Feature extraction is done by means of LPC coefficients, calculating AMDF, and DFT. The neural network is trained by applying these features as input parameters. The features are stored in templates for further comparison. The features for the speaker who has to be identified are extracted and compared with the stored templates using Back Propogation Algorithm. Here, the trained network corresponds to the output; the input is the extracted features of the speaker to be identified. The network does the weight adjustment and the best match is found to identify the speaker. The number of epochs required to get the target decides the network performance.

Keywords: Average Mean Distance function, Backpropogation, Linear Predictive Coding, MultilayeredPerceptron,

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1867

Authors: Wei-Hsin Sun, Jr-Ming Miao, Chang-Hsien Tai, Chien-Chun Hung

Abstract:

The development of biomimetic micro-aerial-vehicles (MAVs) with flapping wings is the future trend in military/domestic field. The successful flight of MAVs is strongly related to the understanding of unsteady aerodynamic performance of low Reynolds number airfoils under dynamic flapping motion. This study explored the effects of flapping frequency, stroke amplitude, and the inclined angle of stroke plane on lift force and thrust force of a bio-inspiration corrugated airfoil with 33 full factorial design of experiment and ANOVA analysis. Unsteady vorticity flows over a corrugated thin airfoil executing flapping motion are computed with time-dependent two-dimensional laminar incompressible Reynolds-averaged Navier-Stokes equations with the conformal hybrid mesh. The tested freestream Reynolds number based on the chord length of airfoil as characteristic length is fixed of 103. The dynamic mesh technique is applied to model the flapping motion of a corrugated airfoil. Instant vorticity contours over a complete flapping cycle clearly reveals the flow mechanisms for lift force generation are dynamic stall, rotational circulation, and wake capture. The thrust force is produced as the leading edge vortex shedding from the trailing edge of airfoil to form a reverse von Karman vortex. Results also indicated that the inclined angle is the most significant factor on both the lift force and thrust force. There are strong interactions between tested factors which mean an optimization study on parameters should be conducted in further runs.

Keywords: biomimetic, MAVs, aerodynamic, ANOVA analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2102

Authors: A. K. Al-Othman, Nabil A. Ahmed, A. M. Al-Kandari, H. K. Ebraheem

Abstract:

Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package.

Keywords: PWM, AC/AC voltage converters, selectiveharmonic elimination, direct search method, pattern search method, Real-coded Genetic algorithms, evolutionary algorithms andoptimization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3293

Authors: Y. Deng, X. Li, C. Kwan, B. Raj, R. Stern

Abstract:

The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environmental noise such as tank noise, helicopter noise, etc. In this paper, we proposed a novel continuous acoustic feature adaptation algorithm for on-line accent and environmental adaptation. Implemented by incremental singular value decomposition (SVD), the algorithm captures local acoustic variation and runs in real-time. This feature-based adaptation method is then integrated with conventional model-based maximum likelihood linear regression (MLLR) algorithm. Extensive experiments have been performed on the NATO non-native speech corpus with baseline acoustic model trained on native American English. The proposed feature-based adaptation algorithm improved the average recognition accuracy by 15%, while the MLLR model based adaptation achieved 11% improvement. The corresponding word error rate (WER) reduction was 25.8% and 2.73%, as compared to that without adaptation. The combined adaptation achieved overall recognition accuracy improvement of 29.5%, and WER reduction of 31.8%, as compared to that without adaptation.

Keywords: speaker adaptation; environment adaptation; robust speech recognition; SVD; non-native speech recognition

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3191

Authors: Abdullah M. Alodhaiani, Yasir A. Alturki, Mohamed A. Elkady

Abstract:

Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF’s) or power transfer distribution factors (PTDF’s), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF’s), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method.

Keywords: Distribution Factors, Power System, Sensitivity Factors, Electricity Market.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2596

Authors: Hussin K. Ragb, Vijayan K. Asari

Abstract:

In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.

Keywords: Pedestrian detection, phase congruency, local phase, LBP features, CSLBP features, FST descriptor.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1458

Authors: Qian Liu, Steve Furber

Abstract:

To explore how the brain may recognise objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor (DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network (SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modelled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study’s largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognise the postures with an accuracy of around 86.4% - only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much improved cost to performance trade-off in its approach.

Keywords: Spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2020

Authors: A. M. Wahab, E. Rustighi

Abstract:

Elastomeric dielectric material has recently become a new alternative for actuator technology. The characteristics of dielectric elastomers placed between two electrodes to withstand large strain when electrodes are charged has attracted the attention of many researcher to study this material for actuator technology. Thus, in the past few years Danfoss Ventures A/S has established their own dielectric electro-active polymer (DEAP), which was called PolyPower. The main objective of this work was to investigate the dynamic characteristics for vibration control of a PolyPower actuator folded in ‘pull’ configuration. A range of experiments was carried out on the folded actuator including passive (without electrical load) and active (with electrical load) testing. For both categories static and dynamic testing have been done to determine the behavior of folded DEAP actuator. Voltage-Strain experiments show that the DEAP folded actuator is a non-linear system. It is also shown that the voltage supplied has no effect on the natural frequency. Finally, varying AC voltage with different amplitude and frequency shows the parameters that influence the performance of DEAP folded actuator. As a result, the actuator performance dominated by the frequency dependence of the elastic response and was less influenced by dielectric properties.

Keywords: Dielectric Electro-active Polymer, Pull Actuator, Static, Dynamic, Electromechanical.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2081

Authors: Sidhartha Panda, N. P. Padhy

Abstract:

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.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3129

Authors: Wei Yang, Xiaohui Cui, Weiping Zhu, Liqun Liu

Abstract:

The rapid development of the Confucius Institute is attracting more and more attention from mainstream media around the world. Mainstream media plays a large role in public information dissemination and public opinion. This study presents efforts to analyze the correlation and functional relationship between domestic and foreign mainstream media by analyzing the amount of reports on the Confucius Institute. Three kinds of correlation calculation methods, the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC), and the Kendall rank correlation coefficient (KCC), were applied to analyze the correlations among mainstream media from three regions: mainland of China; Hong Kong and Macao (the two special administration regions of China denoted as SARs); and overseas countries excluding China, such as the United States, England, and Canada. Further, the paper measures the functional relationships among the regions using a regression model. The experimental analyses found high correlations among mainstream media from the different regions. Additionally, we found that there is a linear relationship between the mainstream media of overseas countries and those of the SARs by analyzing the amount of reports on the Confucius Institute based on a data set obtained by crawling the websites of 106 mainstream media during the years 2004 to 2014.

Keywords: Confucius Institute, correlation analysis, mainstream media, regression model.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1323

Authors: Dakshina Ranjan Kisku, Hunny Mehrotra, Jamuna Kanta Sing, Phalguni Gupta

Abstract:

Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.

Keywords: Biometrics, Multiview face Recognition, Gaborwavelets, LDA, SVM.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1474

Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

Abstract:

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3151

Authors: Gozel Judakova, Markus Bause

Abstract:

We present and analyze reliable numerical techniques for simulating complex flow and transport phenomena related to natural gas transportation in pipelines. Such kind of problems are of high interest in the field of petroleum and environmental engineering. Modeling and understanding natural gas flow and transformation processes during transportation is important for the sake of physical realism and the design and operation of pipeline systems. In our approach a two fluid flow model based on a system of coupled hyperbolic conservation laws is considered for describing natural gas flow undergoing hydratization. The accurate numerical approximation of two-phase gas flow remains subject of strong interest in the scientific community. Such hyperbolic problems are characterized by solutions with steep gradients or discontinuities, and their approximation by standard finite element techniques typically gives rise to spurious oscillations and numerical artefacts. Recently, stabilized and discontinuous Galerkin finite element techniques have attracted researchers’ interest. They are highly adapted to the hyperbolic nature of our two-phase flow model. In the presentation a streamline upwind Petrov-Galerkin approach and a discontinuous Galerkin finite element method for the numerical approximation of our flow model of two coupled systems of Euler equations are presented. Then the efficiency and reliability of stabilized continuous and discontinous finite element methods for the approximation is carefully analyzed and the potential of the either classes of numerical schemes is investigated. In particular, standard benchmark problems of two-phase flow like the shock tube problem are used for the comparative numerical study.

Keywords: Discontinuous Galerkin method, Euler system, inviscid two-fluid model, streamline upwind Petrov-Galerkin method, two-phase flow.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 763

Authors: Mohamed Elghorab, Vendra C. Madhav Rao, Jennifer X. Wen

Abstract:

Turbulence modelling is still evolving, and efforts are on to improve and develop numerical methods to simulate the real turbulence structures by using the empirical and experimental information. The monotonically integrated large eddy simulation (MILES) is an attractive approach for modelling turbulence in high Re flows, which is based on the solving of the unfiltered flow equations with no explicit sub-grid scale (SGS) model. In the current work, this approach has been used, and the action of the SGS model has been included implicitly by intrinsic nonlinear high-frequency filters built into the convection discretization schemes. The MILES solver is developed using the opensource CFD OpenFOAM libraries. The role of flux limiters schemes namely, Gamma, superBee, van-Albada and van-Leer, is studied in predicting turbulent statistical quantities for a fully developed channel flow with a friction Reynolds number, Re_T = 180, and compared the numerical predictions with the well-established Direct Numerical Simulation (DNS) results for studying the wall generated turbulence. It is inferred from the numerical predictions that Gamma, van-Leer and van-Albada limiters produced more diffusion and overpredicted the velocity profiles, while superBee scheme reproduced velocity profiles and turbulence statistical quantities in good agreement with the reference DNS data in the streamwise direction although it deviated slightly in the spanwise and normal to the wall directions. The simulation results are further discussed in terms of the turbulence intensities and Reynolds stresses averaged in time and space to draw conclusion on the flux limiter schemes performance in OpenFOAM context.

Keywords: Flux limiters, MILES, OpenFOAM, turbulence structures, TVD schemes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1089

Authors: Chinnaiah Madduri, Raghu V. Prakash

Abstract:

This paper presents the results of corrosion fatigue crack growth behaviour of a Ni-Cr-Mn steel commonly used in marine applications. The effect of mechanical variables such as frequency and load ratio on fatigue crack growth rate at various stages has been studied using compact tension (C(T)) specimens along the rolling direction of steel plate under 3.5% saturated NaCl aqueous environment. The significance of crack closure on corrosion fatigue, and the validity of Elber-s empirical linear crack closure model with the ASTM compliance offset method have been examined. Fatigue crack growth rate is higher and threshold stress intensities are lower in aqueous environment compared to the lab air conditions. It is also observed that the crack growth rate increases at lower frequencies. The higher stress ratio promotes the crack growth. The effect of oxidization and corrosion pit formation is very less as the stress ratio is increased. It is observed that as stress ratios are increased, the Elber-s crack closure model agrees well with the crack closure estimated by the ASTM compliance offset method for tests conducted at 5Hz frequency compared to tests conducted at 1Hz in corrosive environment.

Keywords: Corrosion fatigue, oxide induced crack closure, Elber's crack closure, ASTM compliance offset method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2124

Authors: M. T. Sichani, B. J. Pedersen, S. R. K. Nielsen

Abstract:

Turbulence of the incoming wind field is of paramount importance to the dynamic response of civil engineering structures. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and structural safety analysis. In the paper an empirical cross spectral density function for the along-wind turbulence component over the wind field area is taken as the starting point. The spectrum is spatially discretized in terms of a Hermitian cross-spectral density matrix for the turbulence state vector which turns out not to be positive definite. Since the succeeding state space and ARMA modelling of the turbulence rely on the positive definiteness of the cross-spectral density matrix, the problem with the non-positive definiteness of such matrices is at first addressed and suitable treatments regarding it are proposed. From the adjusted positive definite cross-spectral density matrix a frequency response matrix is constructed which determines the turbulence vector as a linear filtration of Gaussian white noise. Finally, an accurate state space modelling method is proposed which allows selection of an appropriate model order, and estimation of a state space model for the vector turbulence process incorporating its phase spectrum in one stage, and its results are compared with a conventional ARMA modelling method.

Keywords: Turbulence, wind turbine, complex coherence, state space modelling, ARMA modelling.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1617

Authors: Marcus Banda

Abstract:

In this article the influence of higher frequency effects in addition to a special damper design on the electrical behavior of a synchronous generator main exciter machine is investigated. On the one hand these machines are often highly stressed by harmonics from the bridge rectifier thus facing additional eddy current losses. On the other hand the switching may cause the excitation of dangerous voltage peaks in resonant circuits formed by the diodes of the rectifier and the commutation reactance of the machine. Therefore modern rotating exciters are treated like synchronous generators usually modeled with a second order equivalent circuit. Hence the well known Standstill Frequency Response Test (SSFR) method is applied to a test machine in order to determine parameters for the simulation. With these results it is clearly shown that higher frequencies have a strong impact on the conventional equivalent circuit model. Because of increasing field displacement effects in the stranded armature winding the sub-transient reactance is even smaller than the armature leakage at high frequencies. As a matter of fact this prevents the algorithm to find an equivalent scheme. This issue is finally solved using Laplace transfer functions fully describing the transient behavior at the model ports.

Keywords: Synchronous exciter machine, Linear transfer function, SSFR, Equivalent Circuit

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2011

Authors: T.C. Manjunath, B. Bandyopadhyay

Abstract:

Active Vibration Control (AVC) is an important problem in structures. One of the ways to tackle this problem is to make the structure smart, adaptive and self-controlling. The objective of active vibration control is to reduce the vibration of a system by automatic modification of the system-s structural response. This paper features the modeling and design of a Periodic Output Feedback (POF) control technique for the active vibration control of a flexible Timoshenko cantilever beam for a multivariable case with 2 inputs and 2 outputs by retaining the first 2 dominant vibratory modes using the smart structure concept. The entire structure is modeled in state space form using the concept of piezoelectric theory, Timoshenko beam theory, Finite Element Method (FEM) and the state space techniques. Simulations are performed in MATLAB. The effect of placing the sensor / actuator at 2 finite element locations along the length of the beam is observed. The open loop responses, closed loop responses and the tip displacements with and without the controller are obtained and the performance of the smart system is evaluated for active vibration control.

Keywords: Smart structure, Timoshenko theory, Euler-Bernoulli theory, Periodic output feedback control, Finite Element Method, State space model, Vibration control, Multivariable system, Linear Matrix Inequality

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2286

Authors: Jahan Zeb, Muhammad Younus Javed, Usman Qayyum

Abstract:

This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

Keywords: Average filtering, Bicubic Interpolation, Neurons, vectorization.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1724

Authors: Kang-Gyu Park, Sun-Jong Park, Hong Jae Yim, Hyo-Gyung Kwak

Abstract:

This paper attempts to evaluate the effect of fire damage on concrete by using nonlinear resonance vibration method, one of the nonlinear nondestructive method. Concrete exhibits not only nonlinear stress-strain relation but also hysteresis and discrete memory effect which are contained in consolidated materials. Hysteretic materials typically show the linear resonance frequency shift. Also, the shift of resonance frequency is changed according to the degree of micro damage. The degree of the shift can be obtained through nonlinear resonance vibration method. Five exposure scenarios were considered in order to make different internal micro damage. Also, the effect of post-fire-curing on fire-damaged concrete was taken into account to conform the change in internal damage. Hysteretic nonlinearity parameter was obtained by amplitudedependent resonance frequency shift after specific curing periods. In addition, splitting tensile strength was measured on each sample to characterize the variation of residual strength. Then, a correlation between the hysteretic nonlinearity parameter and residual strength was proposed from each test result.

Keywords: Fire damaged concrete, nonlinear resonance vibration method, nonlinearity parameter, post-fire-curing, splitting tensile strength.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2095

Authors: Merve Ermis, Murat Yılmaz, Nihal Eratlı, Mehmet H. Omurtag

Abstract:

The static and dynamic analyses of hyperboloidal helix having the closed and the open square box sections are investigated via the mixed finite element formulation based on Timoshenko beam theory. Frenet triad is considered as local coordinate systems for helix geometry. Helix domain is discretized with a two-noded curved element and linear shape functions are used. Each node of the curved element has 12 degrees of freedom, namely, three translations, three rotations, two shear forces, one axial force, two bending moments and one torque. Finite element matrices are derived by using exact nodal values of curvatures and arc length and it is interpolated linearly throughout the element axial length. The torsional moments of inertia for close and open square box sections are obtained by finite element solution of St. Venant torsion formulation. With the proposed method, the torsional rigidity of simply and multiply connected cross-sections can be also calculated in same manner. The influence of the close and the open square box cross-sections on the static and dynamic analyses of hyperboloidal helix is investigated. The benchmark problems are represented for the literature.

Keywords: Hyperboloidal helix, squared cross section, thin walled cross section, torsional rigidity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1633

Authors: Rajneesh Sharma, M. Gopal

Abstract:

Markov games are a generalization of Markov decision process to a multi-agent setting. Two-player zero-sum Markov game framework offers an effective platform for designing robust controllers. This paper presents two novel controller design algorithms that use ideas from game-theory literature to produce reliable controllers that are able to maintain performance in presence of noise and parameter variations. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. Our approach generates an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment, and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed controller architectures attempt to improve controller reliability by a gradual mixing of algorithmic approaches drawn from the game theory literature and the Minimax-Q Markov game solution approach, in a reinforcement-learning framework. We test the proposed algorithms on a simulated Inverted Pendulum Swing-up task and compare its performance against standard Q learning.

Keywords: Reinforcement learning, Markov Decision Process, Matrix Games, Markov Games, Smooth Fictitious play, Controller, Inverted Pendulum.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1498

Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

Abstract:

In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2695

Authors: Natalia Koltovaya, Nadezhda Zhuchkina, Ksenia Lyubimova

Abstract:

We study the biological effects induced by ionizing radiation in view of therapeutic exposure and the idea of space flights beyond Earth's magnetosphere. In particular, we examine the differences between base pair substitution induction by ionizing radiation in model haploid and diploid yeast Saccharomyces cerevisiae cells. Such mutations are difficult to study in higher eukaryotic systems. In our research, we have used a collection of six isogenic trp5-strains and 14 isogenic haploid and diploid cyc1-strains that are specific markers of all possible base-pair substitutions. These strains differ from each other only in single base substitutions within codon-50 of the trp5 gene or codon-22 of the cyc1 gene. Different mutation spectra for two different haploid genetic trp5- and cyc1-assays and different mutation spectra for the same genetic cyc1-system in cells with different ploidy — haploid and diploid — have been obtained. It was linear function for dose-dependence in haploid and exponential in diploid cells. We suggest that the differences between haploid yeast strains reflect the dependence on the sequence context, while the differences between haploid and diploid strains reflect the different molecular mechanisms of mutations.

Keywords: Base pair substitutions, γ-rays, haploid and diploid cells, yeast Saccharomyces cerevisiae.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 805

Authors: V.S.Kale, S.R.Bhide, P.P.Bedekar, G.V.K.Mohan

Abstract:

The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.

Keywords: Artificial neural network, fault detection and classification, parallel transmission lines, wavelet transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2975

Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

Abstract:

Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: Cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1099