Search results for: particle swarmoptimization.

Authors: A. Zolfagharian, M.Z. Md. Zain, A. R. AbuBakar, M. Hussein

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Application of flexible structures has been significantly, increased in industry and aerospace missions due to their contributions and unique advantages over the rigid counterparts. In this paper, vibration analysis of a flexible structure i.e., automobile wiper blade is investigated and controlled. The wiper generates unwanted noise and vibration during the wiping the rain and other particles on windshield which may cause annoying noise in different ranges of frequency. A two dimensional analytical modeled wiper blade whose model accuracy is verified by numerical studies in literature is considered in this study. Particle swarm optimization (PSO) is employed in alliance with input shaping (IS) technique in order to control or to attenuate the amplitude level of unwanted noise/vibration of the wiper blade.

Keywords: Input shaping, noise reduction, particle swarmoptimization, wiper blade

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Authors: P. Acharjee, S. K. Goswami

Abstract:

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Keywords: critical conditions, ill-conditioned systems, localsearch technique, multiple power flow solutions, particle swarmoptimization.

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Authors: A. Borji, M. Hamidi

Abstract:

A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together in colonies. We use comprehensive learning particle swarm optimization (CLPSO) technique to find optimal fuzzy rules and membership functions because it discourages premature convergence. Here each particle of the swarm codes a set of fuzzy rules. During evolution, a population member tries to maximize a fitness criterion which is here high classification rate and small number of rules. Finally, particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Our results, using this method for soccer field image segmentation in Robocop contests shows 89% performance. Less computational load is needed when using this method compared with other methods like ANFIS, because it generates a smaller number of fuzzy rules. Large train dataset and its variety, makes the proposed method invariant to illumination noise

Keywords: Comprehensive learning Particle Swarmoptimization, fuzzy classification.

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Authors: Saeed Vaneshani, Hooshang Jazayeri-Rad

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Fuzzy logic control (FLC) systems have been tested in many technical and industrial applications as a useful modeling tool that can handle the uncertainties and nonlinearities of modern control systems. The main drawback of the FLC methodologies in the industrial environment is challenging for selecting the number of optimum tuning parameters. In this paper, a method has been proposed for finding the optimum membership functions of a fuzzy system using particle swarm optimization (PSO) algorithm. A synthetic algorithm combined from fuzzy logic control and PSO algorithm is used to design a controller for a continuous stirred tank reactor (CSTR) with the aim of achieving the accurate and acceptable desired results. To exhibit the effectiveness of proposed algorithm, it is used to optimize the Gaussian membership functions of the fuzzy model of a nonlinear CSTR system as a case study. It is clearly proved that the optimized membership functions (MFs) provided better performance than a fuzzy model for the same system, when the MFs were heuristically defined.

Keywords: continuous stirred tank reactor (CSTR), fuzzy logiccontrol (FLC), membership function(MF), particle swarmoptimization (PSO)

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Authors: N. Manavizadeh, M. Hosseini, M. Rabbani

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In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.

Keywords: Mixed-Model Assembly Line, particle swarmoptimization, Multi-objective sequencing problem, MTO system, kitto-assembly, rest time

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Authors: S. Park, J. Hwang, K. Rou, E. Kim

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In this paper, we consider a new particle filter inspired by biological evolution. In the standard particle filter, a resampling scheme is used to decrease the degeneracy phenomenon and improve estimation performance. Unfortunately, however, it could cause the undesired the particle deprivation problem, as well. In order to overcome this problem of the particle filter, we propose a novel filtering method called the genetic filter. In the proposed filter, we embed the genetic algorithm into the particle filter and overcome the problems of the standard particle filter. The validity of the proposed method is demonstrated by computer simulation.

Keywords: Particle filter, genetic algorithm, evolutionary algorithm.

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Authors: Yu Zhao, Shinsuke Kato, Jianing Zhao

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Particles exhausted from cars have adverse impacts on human health. The study developed a three-dimensional particle dispersion numerical model including particle coagulation to simulate the particle concentration distribution under idling conditions in a residential underground garage. The simulation results demonstrate that particle disperses much faster in the vertical direction than that in horizontal direction. The enhancement of particle dispersion in the vertical direction due to the increase of cars with engine running is much stronger than that in the car exhaust direction. Particle dispersion from each pair of adjacent cars has little influence on each other in the study. Average particle concentration after 120 seconds exhaust is 1.8-4.5 times higher than the initial total particles at ambient environment. Particle pollution in the residential underground garage is severe.

Keywords: Dispersion, Idling conditions, Particle concentration, Residential underground garage.

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Authors: Wen-Ken Li, Pei-Yuan Tzeng, Chyi-Yeou Soong, Chung-Ho Liu

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The present study is concerned with the absorption center of photophoresis within a micro-sized and spheroidal particle in a gaseous medium. A particle subjected to an intense light beam can absorb electromagnetic energy within the particle unevenly, which results in photophoretic force to drive the particle in motion. By evaluating the energy distribution systematically at various conditions, the study focuses on the effects of governing parameters, such as particle aspect ratio, size parameter, refractivity, and absorptivity, on the heat source function within the particle and their potential influences to the photophoresis.

Keywords: photophoresis, spheroidal particle, aspect ratio, refractivity, absorptivity, heat source function

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Authors: Yongzheng Li, Hongfang Ma, Qiwen Sun, Haitao Zhang, Weiyong Ying

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Radial profiles of particle velocities were investigated in a 6.1m high methanol-to-olefins cold model experimental device using a TSI laser Doppler velocimeter. The effect of axial height on flow development was not obvious in fully developed region under the same operating condition. Superficial gas velocity and solid circulating rate had significant influence on particle velocity in the center region of the riser. Besides, comparisons among rising, descending and average particle velocity were conducted. The particle average velocity was similar to the rising particle velocity and higher than the descending particle velocity in radial locations except the wall region of riser.

Keywords: Circulating fluidized bed, laser doppler velocimeter, particle velocity, radial profile.

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Authors: Michiharu Maeda, Shinya Tsuda

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This paper presents an algorithm of particle swarm optimization with reduction for global optimization problems. Particle swarm optimization is an algorithm which refers to the collective motion such as birds or fishes, and a multi-point search algorithm which finds a best solution using multiple particles. Particle swarm optimization is so flexible that it can adapt to a number of optimization problems. When an objective function has a lot of local minimums complicatedly, the particle may fall into a local minimum. For avoiding the local minimum, a number of particles are initially prepared and their positions are updated by particle swarm optimization. Particles sequentially reduce to reach a predetermined number of them grounded in evaluation value and particle swarm optimization continues until the termination condition is met. In order to show the effectiveness of the proposed algorithm, we examine the minimum by using test functions compared to existing algorithms. Furthermore the influence of best value on the initial number of particles for our algorithm is discussed.

Keywords: Particle swarm optimization, Global optimization, Metaheuristics, Reduction.

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Authors: Qurban A. Memon, Mohammad S. Laghari

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Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear particle analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self organizing maps. This is achieved using relationship measurements among corresponding attributes of various measurements for wear particle. Finally, visualization technique is proposed that helps the viewer in understanding and utilizing these relationships that enable accurate diagnostics.

Keywords: Neural Network, Relationship Measurement, Selforganizing Clusters, Wear Particle Analysis.

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Authors: Riaz A. Bhatti, Wang Yanrong

Abstract:

Particle damping is a technique to reduce the structural vibrations by means of placing small metallic particles inside a cavity that is attached to the structure at location of high vibration amplitudes. In this paper, we have presented an analytical model to simulate the particle damping of two dimensional transient vibrations in structure operating under high centrifugal loads. The simulation results show that this technique remains effective as long as the ratio of the dynamic acceleration of the structure to the applied centrifugal load is more than 0.1. Particle damping increases with the increase of particle to structure mass ratio. However, unlike to the case of particle damping in the absence of centrifugal loads where the damping efficiency strongly depends upon the size of the cavity, here this dependence becomes very weak. Despite the simplicity of the model, the simulation results are considerably in good agreement with the very scarce experimental data available in the literature for particle damping under centrifugal loads.

Keywords: Impact damping, particle damping, vibration control, vibration suppression.

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Authors: F. N. Budiman, Y. Khan, A. A. Khan, A. Beroual, N. H. Malik, A. A. Al-Arainy

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It is well known that metallic particles reduce the reliability of Gas-Insulated Substation (GIS) equipments by initiating partial discharge (PDs) that can lead to breakdown and complete failure of GIS. This paper investigates the characteristics of PDs caused by metallic particle adhering to the solid spacer. The PD detection and measurement were carried out by using IEC 60270 method with particles of different sizes and at different positions on the spacer surface. The results show that a particle of certain size at certain position possesses a unique PD characteristic as compared to those caused by particles of different sizes and/or at different positions. Therefore PD characteristics may be useful for the particle size and position identification.

Keywords: Particle, partial discharge, GIS, spacer.

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Authors: A. Abou El-Azm Aly, F. Nicolleau, T. M. Michelitsch, A. F. Nowakowski

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In this study, the dispersion of heavy particles line in an isotropic and incompressible three-dimensional turbulent flow has been studied using the Kinematic Simulation techniques to find out the evolution of the line fractal dimension. The fractal dimension of the line is found in the case of different particle gravity (in practice, different values of particle drift velocity) in the presence of small particle inertia with a comparison with that obtained in the diffusion case of material line at the same Reynolds number. It can be concluded for the dispersion of heavy particles line in turbulent flow that the particle gravity affect the fractal dimension of the line for different particle gravity velocities in the range 0.2 < W < 2. With the increase of the particle drift velocity, the fractal dimension of the line decreases which may be explained as the particles pass many scales in their journey in the direction of the gravity and the particles trajectories do not affect by these scales at high particle drift velocities.

Keywords: Heavy particles, two-phase flow, Kinematic Simulation, Fractal dimension.

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Authors: Rehab F. Abdel-Kader, Rabab M. Ramadan, Rawya Y. Rizk

Abstract:

The recognition of human faces, especially those with different orientations is a challenging and important problem in image analysis and classification. This paper proposes an effective scheme for rotation invariant face recognition using Log-Polar Transform and Discrete Cosine Transform combined features. The rotation invariant feature extraction for a given face image involves applying the logpolar transform to eliminate the rotation effect and to produce a row shifted log-polar image. The discrete cosine transform is then applied to eliminate the row shift effect and to generate the low-dimensional feature vector. A PSO-based feature selection algorithm is utilized to search the feature vector space for the optimal feature subset. Evolution is driven by a fitness function defined in terms of maximizing the between-class separation (scatter index). Experimental results, based on the ORL face database using testing data sets for images with different orientations; show that the proposed system outperforms other face recognition methods. The overall recognition rate for the rotated test images being 97%, demonstrating that the extracted feature vector is an effective rotation invariant feature set with minimal set of selected features.

Keywords: Discrete Cosine Transform, Face Recognition, Feature Extraction, Log Polar Transform, Particle SwarmOptimization.

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Authors: Zhao Wang, Hong Yan

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In this paper, a unified-gas kinetic scheme (UGKS) for the gas-particle flow is constructed. UGKS is a direct modeling method for both continuum and rarefied flow computations. The dynamics of particle and gas are described as rarefied and continuum flow, respectively. Therefore, we use the Bhatnagar-Gross-Krook (BGK) equation for the particle distribution function. For the gas phase, the gas kinetic scheme for Navier-Stokes equation is solved. The momentum transfer between gas and particle is achieved by the acceleration term added to the BGK equation. The new scheme is tested by a 2cm-in-thickness dense bed comprised of glass particles with 1.5mm in diameter, and reasonable agreement is achieved.

Keywords: Gas-particle flow, unified gas-kinetic scheme, momentum transfer, shock-induced fluidization.

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Authors: E. Pikushchak, J. Dueck, L. Minkov

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In hydrocyclones, the particle separation efficiency is limited by the suspended fine particles, which are discharged with the coarse product in the underflow. It is well known that injecting water in the conical part of the cyclone reduces the fine particle fraction in the underflow. This paper presents a mathematical model that simulates the water injection in the conical component. The model accounts for the fluid flow and the particle motion. Particle interaction, due to hindered settling caused by increased density and viscosity of the suspension, and fine particle entrainment by settling coarse particles are included in the model. Water injection in the conical part of the hydrocyclone is performed to reduce fine particle discharge in the underflow. The model demonstrates the impact of the injection rate, injection velocity, and injection location on the shape of the partition curve. The simulations are compared with experimental data of a 50-mm cyclone.

Keywords: Classification, fine particle processing, hydrocyclone, water injection.

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Authors: A. Bagheri Garmarudi, M. Khanmohammadi, N. Khoddami, K. Shabani

Abstract:

Determination of nano particle size is substantial since the nano particle size exerts a significant effect on various properties of nano materials. Accordingly, proposing non-destructive, accurate and rapid techniques for this aim is of high interest. There are some conventional techniques to investigate the morphology and grain size of nano particles such as scanning electron microscopy (SEM), atomic force microscopy (AFM) and X-ray diffractometry (XRD). Vibrational spectroscopy is utilized to characterize different compounds and applied for evaluation of the average particle size based on relationship between particle size and near infrared spectra [1,4] , but it has never been applied in quantitative morphological analysis of nano materials. So far, the potential application of nearinfrared (NIR) spectroscopy with its ability in rapid analysis of powdered materials with minimal sample preparation, has been suggested for particle size determination of powdered pharmaceuticals. The relationship between particle size and diffuse reflectance (DR) spectra in near infrared region has been applied to introduce a method for estimation of particle size. Back propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near infrared diffuse reflectance spectra. Thirty five different nano TiO2 samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP- ANN.

Keywords: near infrared, particle size, chemometrics, neuralnetwork, nano structure.

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Authors: Hrabe Thomas, Beck Florian, Nickell Stephan

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Cryo-electron microscopy (CEM) in combination with single particle analysis (SPA) is a widely used technique for elucidating structural details of macromolecular assemblies at closeto- atomic resolutions. However, development of automated software for SPA processing is still vital since thousands to millions of individual particle images need to be processed. Here, we present our workflow for automated particle picking. Our approach integrates peak shape analysis to the classical correlation and an iterative approach to separate macromolecules and background by classification. This particle selection workflow furthermore provides a robust means for SPA with little user interaction. Processing simulated and experimental data assesses performance of the presented tools.

Keywords: Cryo-electron Microscopy, Single Particle Analysis, Image Processing.

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Authors: A.F. Salarashayeri, M. Siosemarde

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Hydraulic conductivity is one parameter important for predicting the movement of water and contaminants dissolved in the water through the soil. The hydraulic conductivity is measured on soil samples in the lab and sometimes tests carried out in the field. The hydraulic conductivity has been related to soil particle diameter by a number of investigators. In this study, 25 set of soil samples with sand texture. The results show approximately success in predicting hydraulic conductivity from particle diameters data. The following relationship obtained from multiple linear regressions on data (R2 = 0.52): Where d10, d50 and d60, are the soil particle diameter (mm) that 10%, 50% and 60% of all soil particles are finer (smaller) by weight and Ks, saturated hydraulic conductivity is expressed in m/day. The results of regression analysis showed that d10 play a more significant role with respect to Ks, saturated hydraulic conductivity (m/day), and has been named as the effective parameter in Ks calculation.

Keywords: hydraulic conductivity, particle diameter, particle-size distribution and soil

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Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su, Junjie Wang

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The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of the targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms.

Keywords: Bernoulli filter, particle filter, particle flow filter, random finite sets, target tracking.

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Authors: Sang Won Han, Won Joo Lee, Sang Jun Lee

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A new multi inner stage (MIS) cyclone was designed to remove the acidic gas and fine particles produced from electronic industry. To characterize gas flow in MIS cyclone, pressure and velocity distribution were calculated by means of CFD program. Also, the flow locus of fine particles and particle removal efficiency were analyzed by Lagrangian method. When outlet pressure condition was –100mmAq, the efficiency was the best in this study.

Keywords: Cyclone, SiO2 particle, Particle removal efficiency, CFD simulation

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Authors: N. Khelil. L. Djerou , A. Zerarka, M. Batouche

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Consider the Gregory integration (G) formula with end corrections where h Δ is the forward difference operator with step size h. In this study we prove that can be optimized by minimizing some of the coefficient k a in the remainder term by particle swarm optimization. Experimental tests prove that can be rendered a powerful formula for library use.

Keywords: Numerical integration, Gregory Formula, Particle Swarm optimization.

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Authors: Sajith Sajeev, Brenton McLaury, Siamack Shirazi

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In the petroleum industry, solid particles are often present along with the produced fluids. It is imperative to keep particles from accumulating in flow lines. In this study, various experiments are conducted to study sand particle transport, where critical velocity is defined as the average fluid velocity to keep particles continuously moving. Many parameters related to the fluid, particles and pipe affect the transport process. Experimental results are presented varying the particle concentration. Additionally, CFD simulations using a discrete element modeling (DEM) approach are presented to compare with experimental result.

Keywords: Particle transport, critical velocity, CFD, DEM.

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Authors: M. Jalali Azizpour, D. Sajedipour, H. Mohammadi Majd, M.R. Tahmasbi Birgani, M.Rabiae

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An explicit axisymmetrical FE methodology is developed here to study the particle temperature arising in WC-Co particle on an AISI 1045 steel substrate. Parameters of constitutive Johnson-cook model were used for simulation. The results show that particle velocity and kinetic energy have important role in temperature arising of particles.

Keywords: FEM, HVOF, Interfacial Temperature, Splat

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Authors: S. Y. Ahmadi-Brooghani, H. Hassanzadeh, P. Kahhal

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This work presents a study on the abrasive water jet (AWJ) machining. An explicit finite element analysis (FEA) of single abrasive particle impact on stainless steel 1.4304 (AISI 304) is conducted. The abrasive water jet machining is modeled by FEA software ABAQUS/CAE. Shapes of craters in FEM simulation results were used and compared with the previous experimental and FEM works by means of crater sphericity. The influence of impact angle and particle velocity was observed. Adaptive mesh domain is used to model the impact zone. Results are in good agreement with those obtained from the experimental and FEM simulation. The crater-s depth is also obtained for different impact angle and abrasive particle velocities.

Keywords: Abrasive water jet machining, Adaptive meshcontrol, Explicit finite elements analysis, Single-particle impact.

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Authors: Felix Platzer, Eric Fimbinger

Abstract:

In Discrete Element Method (DEM) simulations, the breakage behavior of particles can be simulated based on different principles. In the case of large, complex-shaped particles that show various breakage patterns depending on the scenario leading to the failure and often only break locally instead of fracturing completely, some of these principles do not lead to realistic results. The reason for this is that in said cases, the methods in question, such as the Particle Replacement Method (PRM) or Voronoi Fracture, replace the initial particle (that is intended to break) into several sub-particles when certain breakage criteria are reached, such as exceeding the fracture energy. That is why those methods are commonly used for the simulation of materials that fracture completely instead of breaking locally. That being the case, when simulating local failure, it is advisable to pre-build the initial particle from sub-particles that are bonded together. The dimensions of these sub-particles  consequently define the minimum size of the fracture results. This structure of bonded sub-particles enables the initial particle to break at the location of the highest local loads – due to the failure of the bonds in those areas – with several sub-particle clusters being the result of the fracture, which can again also break locally. In this project, different methods for the generation and calibration of complex-shaped particle conglomerates using bonded particle modeling (BPM) to enable the ability to depict more realistic fracture behavior were evaluated based on the example of filter cake. The method that proved suitable for this purpose and which furthermore  allows efficient and realistic simulation of breakage behavior of complex-shaped particles applicable to industrial-sized simulations is presented in this paper.

Keywords: Bonded particle model (BPM), DEM, filter cake, particle breakage, particle fracture.

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Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

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In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS, microfluidics.

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Authors: Diogo Silva, Fadul Rodor, Carlos Moraes

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This work compares the results of multidimensional function approximation using two algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum Particle Swarm Optimization (QPSO). These algorithms were both tested on three functions - The Rosenbrock, the Rastrigin, and the sphere functions - with different characteristics by increasing their number of dimensions. As a result, this study shows that the higher the function space, i.e. the larger the function dimension, the more evident the advantages of using the QPSO method compared to the PSO method in terms of performance and number of necessary iterations to reach the stop criterion.

Keywords: PSO, QPSO, function approximation, AI, optimization, multidimensional functions.

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Authors: Sijie Fu, Pascal-Henry Biwolé, Christian Mathis

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Among modern airflow measurement methods, Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV), as visualized and non-instructive measurement techniques, are playing more important role. This paper conducts a comparative experimental study for airflow measurement employing both techniques with the same condition. Velocity vector fields, velocity contour fields, voticity profiles and turbulence profiles are selected as the comparison indexes. The results show that the performance of both PIV and PTV techniques for airflow measurement is satisfied, but some differences between the both techniques are existed, it suggests that selecting the measurement technique should be based on a comprehensive consideration.

Keywords: PIV, PTV, airflow measurement.

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