Search results for: dispersed particle swarm optimization

Authors: N. Mamode Khan, V. Jowaheer

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

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

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Authors: S. N. Deepa, G. Sugumaran

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This paper proposes a new algebraic scheme to design a PID controller for higher order linear time invariant continuous systems. Modified PSO (MPSO) based model order formulation techniques have applied to obtain the effective formulated second order system. A controller is tuned to meet the desired performance specification by using pole-zero cancellation method. Proposed PID controller is attached with both higher order system and formulated second order system. The closed loop response is observed for stabilization process and compared with general PSO based formulated second order system. The proposed method is illustrated through numerical example from literature.

Keywords: Higher order systems, model order formulation, modified particle swarm optimization, PID controller, pole-zero cancellation.

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Authors: S. Dehghan, B. Kiani, A. Kazemi, A. Parizad

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The utilization of renewable energy sources in electric power systems is increasing quickly because of public apprehensions for unpleasant environmental impacts and increase in the energy costs involved with the use of conventional energy sources. Despite the application of these energy sources can considerably diminish the system fuel costs, they can also have significant influence on the system reliability. Therefore an appropriate combination of the system reliability indices level and capital investment costs of system is vital. This paper presents a hybrid wind/photovoltaic plant, with the aim of supplying IEEE reliability test system load pattern while the plant capital investment costs is minimized by applying a hybrid particle swarm optimization (PSO) / harmony search (HS) approach, and the system fulfills the appropriate level of reliability.

Keywords: Distributed Generation, Fuel Cell, HS, Hybrid Power Plant, PSO, Photovoltaic, Reliability.

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: Automatic design, learning, fuzzy rules, hybrid, swarm optimization.

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Authors: Tarek Aboueldahab

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In this paper, we propose a new hybrid learning model for stock market indices prediction by adding a passive congregation term to the standard hybrid model comprising Particle Swarm Optimization (PSO) with Genetic Algorithm (GA) operators in training Neural Networks (NN). This new passive congregation term is based on the cooperation between different particles in determining new positions rather than depending on the particles selfish thinking without considering other particles positions, thus it enables PSO to perform both the local and global search instead of only doing the local search. Experiment study carried out on the most famous European stock market indices in both long term and short term prediction shows significantly the influence of the passive congregation term in improving the prediction accuracy compared to standard hybrid model.

Keywords: Global Search, Hybrid Model, Passive Congregation, Stock Market Prediction.

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Authors: Xiaoli Shen, Yuehui Chen

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Interactions among proteins are the basis of various life events. So, it is important to recognize and research protein interaction sites. A control set that contains 149 protein molecules were used here. Then 10 features were extracted and 4 sample sets that contained 9 sliding windows were made according to features. These 4 sample sets were calculated by Radial Basis Functional neutral networks which were optimized by Particle Swarm Optimization respectively. Then 4 groups of results were obtained. Finally, these 4 groups of results were integrated by decision fusion (DF) and Genetic Algorithm based Selected Ensemble (GASEN). A better accuracy was got by DF and GASEN. So, the integrated methods were proved to be effective.

Keywords: protein interaction sites, features, sliding windows, radial basis functional neutral networks, genetic algorithm basedselected ensemble.

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Authors: H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi

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In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.

Keywords: GEP Problem, IPPs, Reliability Criteria, GA, PSO.

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Authors: Yizhi Gai, Yukinori Kobayashi, Yohei Hoshino, Takanori Emaru

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Motion control of flexible arms is more difficult than that of rigid arms, however utilizing its dynamics enables improved performance such as a fast motion in short operation time. This paper investigates a ball throwing robot with one rigid link and one flexible link. This robot throws a ball at a set speed with a proper control torque. A mathematical model of this ball throwing robot is derived through Hamilton’s principle. Several patterns of torque input are designed and tested through the proposed simulation models. The parameters of each torque input pattern is optimized and determined by chaos embedded vector evaluated particle swarm optimization (CEVEPSO). Then, the residual vibration of the manipulator after throwing is suppressed with input shaping technique. Finally, a real experiment is set up for the model checking.

Keywords: Motion control, flexible robotic arm, CEVEPSO, ball throwing robot.

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Authors: P. Shunmugapriya, S. Kanmani, P. Jude Fredieric, U. Vignesh, J. Reman Justin, K. Vivek

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Vehicle Routing Problem (VRP) is a complex combinatorial optimization problem and it is quite difficult to find an optimal solution consisting of a set of routes for vehicles whose total cost is minimum. Evolutionary and swarm intelligent (SI) algorithms play a vital role in solving optimization problems. While the SI algorithms perform search, the diversity between the solutions they exploit is very important. This is because of the need to avoid early convergence and to get an appropriate balance between the exploration and exploitation. Therefore, it is important to check how far the solutions are diverse. In this paper, we measure the similarity between solutions, which ABC exploits while optimizing VRP. The similar solutions found are discarded at the end of the iteration and only unique solutions are passed on to the next iteration. The bees of discarded solutions become scouts and they start searching for new solutions. This process is continued and results show that the solution is optimized at lesser number of iterations but with the overhead of computing similarity in all the iterations. The problem instance from Solomon benchmarked dataset has been used for evaluating the presented methodology.

Keywords: ABC algorithm, vehicle routing problem, optimization, Jaccard’s similarity measure.

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Authors: Rathapon Asasutjarit, Chayanid Sorrachaitawatwong, Nardauma Tipchuwong, Sirijit Pouthai

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This study was conducted to formulate diclofenac sodium-loaded chitosan nanoparticles and to study the effect of formulation compositions on particle size and zeta potential of chitosan nanoparticles (CSN) containing diclofenac sodium (DC) prepared by ionotropic gelation method. It was found that the formulations containing chitosan, DC and tripolyphosphate (TPP) at a weight ratio of 4:1:1, respectively, with various pH provided various systems. At pH 5.0 and 6.0, the obtained systems were turbid because of precipitation of DC and chitosan, respectively. However, the dispersed system of CSN possessing diameter of 108±1 nm and zeta potential of 19±1 mV could be obtained at pH 5.5. These CSN also showed spherical morphology observed via a transmission scanning electron microscope. Change in weight ratio of chitosan:DC:TPP i.e. 1:1:1, 2:1:1, 3:1:1 and 4:1:1 showed that these ratios led to precipitation of particles except for the ratio of 4:1:1 providing CSN properly. The effect of Tween 80 as a stabilizer was also determined. It suggested that increment of Tween 80 concentration to 0.02% w/v could stabilize CSN at least 48 hours. However, increment of Tween 80 to 0.03% w/v led to quick precipitation of particles. The study of effect of TPP suggested that increment of TPP concentration increased particle size but decreased zeta potential. The excess TPP caused precipitation of CSN. Therefore, the optimized CSN was the CSN containing chitosan, DC and TPP at the ratio of 4:1:1and 0.02% w/v Tween 80 prepared at pH 5.5. Their particle size, zeta potential and entrapment efficiency were 128±1 nm, 15±1 mV and 45.8±2.6%, respectively.

Keywords: Chitosan nanoparticles, diclofenac sodium, size, zeta potential.

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Authors: Sufian Ashraf Mazhari, Surendra Kumar

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This paper compares the heuristic Global Search Techniques; Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Generalized Pattern Search, genetic algorithm hybridized with Nelder–Mead and Generalized pattern search technique for tuning of fuzzy PID controller for Puma 560. Since the actual control is in joint space ,inverse kinematics is used to generate various joint angles correspoding to desired cartesian space trajectory. Efficient dynamics and kinematics are modeled on Matlab which takes very less simulation time. Performances of all the tuning methods with and without disturbance are compared in terms of ITSE in joint space and ISE in cartesian space for spiral trajectory tracking. Genetic Algorithm hybridized with Generalized Pattern Search is showing best performance.

Keywords: Controller tuning, Fuzzy Control, Genetic Algorithm, Heuristic search, Robot control.

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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: Wenlong Liu, Yucheng Liu

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This paper introduces the application of seismic wave method in earthquake prediction and early estimation. The advantages of the seismic wave method over the traditional earthquake prediction method are demonstrated. An example is presented in this study to show the accuracy and efficiency of using the seismic wave method in predicting a medium-sized earthquake swarm occurred in Wencheng, Zhejiang, China. By applying this method, correct predictions were made on the day after this earthquake swarm started and the day the maximum earthquake occurred, which provided scientific bases for governmental decision-making.

Keywords: earthquake prediction, earthquake swarm, seismicactivity method, seismic wave method, Wencheng earthquake

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Authors: T. Vigneswari, M. A. Maluk Mohamed

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Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Heterogeneous Earliest First Min- Min Artificial Bee Colony (CHMM-ABC), to optimally schedule jobs for the available resources. The proposed model utilizes a novel Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm along with Min-Min algorithm to identify the initial food source. Simulation results show the performance improvement of the proposed algorithm over other swarm intelligence techniques.

Keywords: Grid Computing, Grid Scheduling, Heterogeneous Earliest Finish Time (HEFT), Artificial Bee colony (ABC) Algorithm, Resource Management.

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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: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

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Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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Authors: Riaz A. Bhatti, Wang Yanrong

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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: 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: P. Vazan, P. Tanuska

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The paper provides the basic overview of simulation optimization. The procedure of its practical using is demonstrated on the real example in simulator Witness. The simulation optimization is presented as a good tool for solving many problems in real praxis especially in production systems. The authors also characterize their own experiences and they mention the strengths and weakness of simulation optimization.

Keywords: discrete event simulation, simulation optimization, Witness

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

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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: Rami N. Khushaba, Ahmed Al-Ani, Adel Al-Jumaily

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One of the approaches enabling people with amputated limbs to establish some sort of interface with the real world includes the utilization of the myoelectric signal (MES) from the remaining muscles of those limbs. The MES can be used as a control input to a multifunction prosthetic device. In this control scheme, known as the myoelectric control, a pattern recognition approach is usually utilized to discriminate between the MES signals that belong to different classes of the forearm movements. Since the MES is recorded using multiple channels, the feature vector size can become very large. In order to reduce the computational cost and enhance the generalization capability of the classifier, a dimensionality reduction method is needed to identify an informative yet moderate size feature set. This paper proposes a new fuzzy version of the well known Fisher-s Linear Discriminant Analysis (LDA) feature projection technique. Furthermore, based on the fact that certain muscles might contribute more to the discrimination process, a novel feature weighting scheme is also presented by employing Particle Swarm Optimization (PSO) for estimating the weight of each feature. The new method, called PSOFLDA, is tested on real MES datasets and compared with other techniques to prove its superiority.

Keywords: Discriminant Analysis, Pattern Recognition, SignalProcessing.

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Authors: Jana P. Vejpravova, Daniel Niznansky, Vaclav Vales, Barbara Bittova, Vaclav Tyrpekl, Stanislav Danis, Vaclav Holy, Stephen Doyle

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The aim of our work is to study phase composition, particle size and magnetic response of Fe2O3/TiO2 nanocomposites with respect to the final annealing temperature. Those nanomaterials are considered as smart catalysts, separable from a liquid/gaseous phase by applied magnetic field. The starting product was obtained by an ecologically acceptable route, based on heterogeneous precipitation of the TiO2 on modified g-Fe2O3 nanocrystals dispersed in water. The precursor was subsequently annealed on air at temperatures ranging from 200 oC to 900 oC. The samples were investigated by synchrotron X-ray powder diffraction (S-PXRD), magnetic measurements and Mössbauer spectroscopy. As evidenced by S-PXRD and Mössbauer spectroscopy, increasing the annealing temperature causes evolution of the phase composition from anatase/maghemite to rutile/hematite, finally above 700 oC the pseudobrookite (Fe2TiO5) also forms. The apparent particle size of the various Fe2O3/TiO2 phases has been determined from the highquality S-PXRD data by using two different approaches: the Rietveld refinement and the Debye method. Magnetic response of the samples is discussed in considering the phase composition and the particle size.

Keywords: X-ray diffraction, profile analysis, Mössbauer spectroscopy, magnetic properties, TiO2, Fe2O3, Fe2TiO5

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: Parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems.

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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: Zhiguo Yang, Xiangan Yue, Minglu Shao, Yang Yue, Tianqi Yue

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In low permeability reservoirs, the reservoir pore throat is small and the micro heterogeneity is prominent. Conventional microsphere profile control agents generally have good injectability but poor plugging effect; however, profile control agents with good plugging effect generally have poor injectability, which makes it difficult for agent to realize deep profile control of reservoir. To solve this problem, styrene and acrylamide were used as monomers in the laboratory. Emulsion polymerization was used to prepare the Controllable Self-Aggregating Colloidal Particle (CSA), which was rich in amide group. The CSA microsphere dispersion solution with a particle diameter smaller than the pore throat diameter was injected into the reservoir to ensure that the profile control agent had good inject ability. After dispersing the CSA microsphere to the deep part of the reservoir, the CSA microspheres dispersed in static for a certain period of time will self-aggregate into large-sized particle clusters to achieve plugging of hypertonic channels. The CSA microsphere has the characteristics of low expansion and avoids shear fracture in the process of migration. It can be observed by transmission electron microscope that CSA microspheres still maintain regular and uniform spherical and core-shell heterogeneous structure after aging at 100 ºC for 35 days, and CSA microspheres have good thermal stability. The results of bottle test showed that with the increase of cation concentration, the aggregation time of CSA microspheres gradually shortened, and the influence of divalent cations was greater than that of monovalent ions. Physical simulation experiments show that CSA microspheres have good injectability, and the aggregated CSA particle clusters can produce effective plugging and migrate to the deep part of the reservoir for profile control.

Keywords: Heterogeneous reservoir, deep profile control, emulsion polymerization, colloidal particles, plugging characteristic.

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