The Parameters Analysis for the Intersection Collision Avoidance Systems Based on Radar Sensors

This paper mainly studies the analyses of parameters in the intersection collision avoidance (ICA) system based on the radar sensors. The parameters include the positioning errors, the repeat period of the radar sensor, the conditions of potential collisions of two cross-path vehicles, etc. The analyses of the parameters can provide the requirements, limitations, or specifications of this ICA system. In these analyses, the positioning errors will be increased as the measured vehicle approach the intersection. In addition, it is not necessary to implement the radar sensor in higher position since the positioning sensitivities become serious as the height of the radar sensor increases. A concept of the safety buffer distances for front and rear of the measured vehicle is also proposed. The conditions for potential collisions of two cross-path vehicles are also presented to facilitate the computation algorithm.

Artificial Neural Network based Modeling of Evaporation Losses in Reservoirs

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.

Identification of Optimum Parameters of Deep Drawing of a Cylindrical Workpiece using Neural Network and Genetic Algorithm

Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.

CFD Simulation of SO2 Removal from Gas Mixtures using Ceramic Membranes

This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.

MAP-Based Image Super-resolution Reconstruction

From a set of shifted, blurred, and decimated image , super-resolution image reconstruction can get a high-resolution image. So it has become an active research branch in the field of image restoration. In general, super-resolution image restoration is an ill-posed problem. Prior knowledge about the image can be combined to make the problem well-posed, which contributes to some regularization methods. In the regularization methods at present, however, regularization parameter was selected by experience in some cases and other techniques have too heavy computation cost for computing the parameter. In this paper, we construct a new super-resolution algorithm by transforming the solving of the System stem Є=An into the solving of the equations X+A*X-1A=I , and propose an inverse iterative method.

Methanol Concentration Sensitive SWCNT/Nafion Composites

An aqueous methanol sensor for use in direct methanol fuel cells (DMFCs) applications is demonstrated; the methanol sensor is built using dispersed single-walled carbon nanotubes (SWCNTs) with Nafion117 solution to detect the methanol concentration in water. The study is aimed at the potential use of the carbon nanotubes array as a methanol sensor for direct methanol fuel cells (DMFCs). The concentration of methanol in the fuel circulation loop of a DMFC system is an important operating parameter, because it determines the electrical performance and efficiency of the fuel cell system. The sensor is also operative even at ambient temperatures and responds quickly to changes in the concentration levels of the methanol. Such a sensor can be easily incorporated into the methanol fuel solution flow loop in the DMFC system.

Radiation Damage as Nonlinear Evolution of Complex System

Irradiated material is a typical example of a complex system with nonlinear coupling between its elements. During irradiation the radiation damage is developed and this development has bifurcations and qualitatively different kinds of behavior. The accumulation of primary defects in irradiated crystals is considered in frame work of nonlinear evolution of complex system. The thermo-concentration nonlinear feedback is carried out as a mechanism of self-oscillation development. It is shown that there are two ways of the defect density evolution under stationary irradiation. The first is the accumulation of defects; defect density monotonically grows and tends to its stationary state for some system parameters. Another way that takes place for opportune parameters is the development of self-oscillations of the defect density. The stationary state, its stability and type are found. The bifurcation values of parameters (environment temperature, defect generation rate, etc.) are obtained. The frequency of the selfoscillation and the conditions of their development is found and rated. It is shown that defect density, heat fluxes and temperature during self-oscillations can reach much higher values than the expected steady-state values. It can lead to a change of typical operation and an accident, e.g. for nuclear equipment.

Performance Evaluation of an Amperometric Biosensor using a Simple Microcontroller based Data Acquisition System

In this paper we have proposed a methodology to develop an amperometric biosensor for the analysis of glucose concentration using a simple microcontroller based data acquisition system. The work involves the development of Detachable Membrane Unit (enzyme based biomembrane) with immobilized glucose oxidase on the membrane and interfacing the same to the signal conditioning system. The current generated by the biosensor for different glucose concentrations was signal conditioned, then acquired and computed by a simple AT89C51-microcontroller. The optimum operating parameters for the better performance were found and reported. The detailed performance evaluation of the biosensor has been carried out. The proposed microcontroller based biosensor system has the sensitivity of 0.04V/g/dl, with a resolution of 50mg/dl. It has exhibited very good inter day stability observed up to 30 days. Comparing to the reference method such as HPLC, the accuracy of the proposed biosensor system is well within ± 1.5%. The system can be used for real time analysis of glucose concentration in the field such as, food and fermentation and clinical (In-Vitro) applications.

An Advanced Time-Frequency Domain Method for PD Extraction with Non-Intrusive Measurement

Partial discharge (PD) detection is an important method to evaluate the insulation condition of metal-clad apparatus. Non-intrusive sensors which are easy to install and have no interruptions on operation are preferred in onsite PD detection. However, it often lacks of accuracy due to the interferences in PD signals. In this paper a novel PD extraction method that uses frequency analysis and entropy based time-frequency (TF) analysis is introduced. The repetitive pulses from convertor are first removed via frequency analysis. Then, the relative entropy and relative peak-frequency of each pulse (i.e. time-indexed vector TF spectrum) are calculated and all pulses with similar parameters are grouped. According to the characteristics of non-intrusive sensor and the frequency distribution of PDs, the pulses of PD and interferences are separated. Finally the PD signal and interferences are recovered via inverse TF transform. The de-noised result of noisy PD data demonstrates that the combination of frequency and time-frequency techniques can discriminate PDs from interferences with various frequency distributions.

Transient Combined Conduction and Radiation in a Two-Dimensional Participating Cylinder in Presence of Heat Generation

Simultaneous transient conduction and radiation heat transfer with heat generation is investigated. Analysis is carried out for both steady and unsteady situations. two-dimensional gray cylindrical enclosure with an absorbing, emitting, and isotropically scattering medium is considered. Enclosure boundaries are assumed at specified temperatures. The heat generation rate is considered uniform and constant throughout the medium. The lattice Boltzmann method (LBM) was used to solve the energy equation of a transient conduction-radiation heat transfer problem. The control volume finite element method (CVFEM) was used to compute the radiative information. To study the compatibility of the LBM for the energy equation and the CVFEM for the radiative transfer equation, transient conduction and radiation heat transfer problems in 2-D cylindrical geometries were considered. In order to establish the suitability of the LBM, the energy equation of the present problem was also solved using the the finite difference method (FDM) of the computational fluid dynamics. The CVFEM used in the radiative heat transfer was employed to compute the radiative information required for the solution of the energy equation using the LBM or the FDM (of the CFD). To study the compatibility and suitability of the LBM for the solution of energy equation and the CVFEM for the radiative information, results were analyzed for the effects of various parameters such as the boundary emissivity. The results of the LBMCVFEM combination were found to be in excellent agreement with the FDM-CVFEM combination. The number of iterations and the steady state temperature in both of the combinations were found comparable. Results are found for situations with and without heat generation. Heat generation is found to have significant bearing on temperature distribution.

Investigations on the Influence of Process Parameters on the Sliding Wear Behavior of Components Produced by Direct Metal Laser Sintering (DMLS)

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.

Investigation of SSR Characteristics of SSSC With GA Based Voltage Controller

In this paper, investigation of subsynchronous resonance (SSR) characteristics of a hybrid series compensated system and the design of voltage controller for three level 24-pulse Voltage Source Converter based Static Synchronous Series Compensator (SSSC) is presented. Hybrid compensation consists of series fixed capacitor and SSSC which is a active series FACTS controller. The design of voltage controller for SSSC is based on damping torque analysis, and Genetic Algorithm (GA) is adopted for tuning the controller parameters. The SSR Characteristics of SSSC with constant reactive voltage control modes has been investigated. The results show that the constant reactive voltage control of SSSC has the effect of reducing the electrical resonance frequency, which detunes the SSR.The analysis of SSR with SSSC is carried out based on frequency domain method, eigenvalue analysis and transient simulation. While the eigenvalue and damping torque analysis are based on D-Q model of SSSC, the transient simulation considers both D-Q and detailed three phase nonlinear system model using switching functions.

Response Surface Based Optimization of Toughness of Hybrid Polyamide 6 Nanocomposites

Toughening of polyamide 6 (PA6)/ Nanoclay (NC) nanocomposites with styrene-ethylene/butadiene-styrene copolymer (SEBS) using maleated styrene-ethylene/butadiene-styrene copolymer (mSEBS)/ as a compatibilizer were investigated by blending them in a co-rotating twin-screw extruder. Response surface method of experimental design was used for optimizing the material and processing parameters. Effect of four factors, including SEBS, mSEBS and NC contents as material variables and order of mixing as a processing factor, on toughness of hybrid nanocomposites were studied. All the prepared samples showed ductile behavior and low temperature Izod impact toughness of some of the hybrid nanocomposites demonstrated 900% improvement compared to the PA6 matrix while the modulus showed maximum enhancement of 20% compared to the pristine PA6 resin.

Bifurcations of a Delayed Prototype Model

In this paper, a delayed prototype model is studied. Regarding the delay as a bifurcation parameter, we prove that a sequence of Hopf bifurcations will occur at the positive equilibrium when the delay increases. Using the normal form method and center manifold theory, some explicit formulae are worked out for determining the stability and the direction of the bifurcated periodic solutions. Finally, Computer simulations are carried out to explain some mathematical conclusions.

Unsupervised Segmentation by Hidden Markov Chain with Bi-dimensional Observed Process

In unsupervised segmentation context, we propose a bi-dimensional hidden Markov chain model (X,Y) that we adapt to the image segmentation problem. The bi-dimensional observed process Y = (Y 1, Y 2) is such that Y 1 represents the noisy image and Y 2 represents a noisy supplementary information on the image, for example a noisy proportion of pixels of the same type in a neighborhood of the current pixel. The proposed model can be seen as a competitive alternative to the Hilbert-Peano scan. We propose a bayesian algorithm to estimate parameters of the considered model. The performance of this algorithm is globally favorable, compared to the bi-dimensional EM algorithm through numerical and visual data.

Dispersion of a Solute in Peristaltic Motion of a Couple Stress Fluid in the Presence of Magnetic Field

An analytical solution for dispersion of a solute in the peristaltic motion of a couple stress fluid in the presence of magnetic field with both homogeneous and heterogeneous chemical reactions is presented. The average effective dispersion coefficient has been found using Taylor-s limiting condition and long wavelength approximation. The effects of various relevant parameters on the average effective coefficient of dispersion have been studied. The average effective dispersion coefficient tends to decrease with magnetic field parameter, homogeneous chemical reaction rate parameter and amplitude ratio but tends to increase with heterogeneous chemical reaction rate parameter.

Determination of the Proper Quality Costs Parameters via Variable Step Size Steepest Descent Algorithm

This paper presents the determination of the proper quality costs parameters which provide the optimum return. The system dynamics simulation was applied. The simulation model was constructed by the real data from a case of the electronic devices manufacturer in Thailand. The Steepest Descent algorithm was employed to optimise. The experimental results show that the company should spend on prevention and appraisal activities for 850 and 10 Baht/day respectively. It provides minimum cumulative total quality cost, which is 258,000 Baht in twelve months. The effect of the step size in the stage of improving the variables to the optimum was also investigated. It can be stated that the smaller step size provided a better result with more experimental runs. However, the different yield in this case is not significant in practice. Therefore, the greater step size is recommended because the region of optima could be reached more easily and rapidly.

A New Correlation for Overall Sherwood Number in Packed Liquid-Liquid Extraction Column

Using plug flow model in conjunction with experimental solute concentration profiles, overall volumetric mass transfer coefficient based on continuous phase (Koca), in a packed liquid-liquid extraction column has been optimized. Number of 12 experiments has been done using standard system of water/acid acetic/toluene in a 6 cm diameter, 120 cm height column. Thorough consideration of influencing parameters we intended to correlate dimensionless parameters in term of overall Sherwood number which has an acceptable average error of about 15.8%.

Design and Control Strategy of Diffused Air Aeration System

During the past decade, pond aeration systems have been developed which will sustain large quantities of fish and invertebrate biomass. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fishponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. This paper presents a new design of diffused aeration system using fuel cell as a power source. Also fuzzy logic control Technique (FLC) is used for controlling the speed of air flow rate from the blower to air piping connected to the pond by adjusting blower speed. MATLAB SIMULINK results show high performance of fuzzy logic control (FLC).

Quantitative Analysis of Weld Defect Images in Industrial Radiography Based Invariant Attributes

For the characterization of the weld defect region in the radiographic image, looking for features which are invariant regarding the geometrical transformations (rotation, translation and scaling) proves to be necessary because the same defect can be seen from several angles according to the orientation and the distance from the welded framework to the radiation source. Thus, panoply of geometrical attributes satisfying the above conditions is proposed and which result from the calculation of the geometrical parameters (surface, perimeter, etc.) on the one hand and the calculation of the different order moments, on the other hand. Because the large range in values of the raw features and taking into account other considerations imposed by some classifiers, the scaling of these values to lie between 0 and 1 is indispensable. The principal component analysis technique is used in order to reduce the number of the attribute variables in the aim to give better performance to the further defect classification.