Search results for: wavelet particle decomposition

Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography (VOG)

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Authors: Nipa Debnath, Harinarayan Das, Takahiko Kawaguchi, Naonori Sakamoto, Kazuo Shinozaki, Hisao Suzuki, Naoki Wakiya

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Nowadays spinel ferrite magnetic thin films have drawn considerable attention due to their interesting magnetic and electrical properties with enhanced chemical and thermal stability. Spinel ferrite magnetic films can be implemented in magnetic data storage, sensors, and spin filters or microwave devices. It is well established that the structural, magnetic and transport properties of the magnetic thin films are dependent on microstructure. Spinodal decomposition (SD) is a phase separation process, whereby a material system is spontaneously separated into two phases with distinct compositions. The periodic microstructure is the characteristic feature of SD. Thus, SD can be exploited to control the microstructure at the nanoscale level. In bulk spinel ferrites having general formula, MₓFe₃₋ₓ O₄ (M= Co, Mn, Ni, Zn), phase separation via SD has been reported only for cobalt ferrite (CFO); however, long time post-annealing is required to occur the spinodal decomposition. We have found that SD occurs in CoF thin film without using any post-deposition annealing process if we apply magnetic field during thin film growth. Dynamic Aurora pulsed laser deposition (PLD) is a specially designed PLD system through which in-situ magnetic field (up to 2000 G) can be applied during thin film growth. The in-situ magnetic field suppresses the recombination of ions in the plume. In addition, the peak’s intensity of the ions in the spectra of the plume also increases when magnetic field is applied to the plume. As a result, ions with high kinetic energy strike into the substrate. Thus, ion-impingement occurred under magnetic field during thin film growth. The driving force of SD is the ion-impingement towards the substrates that is induced by in-situ magnetic field. In this study, we report about the occurrence of phase separation through SD and evolution of microstructure after phase separation in spinel ferrite thin films. The surface morphology of the phase separated films show checkerboard like domain structure. The cross-sectional microstructure of the phase separated films reveal columnar type phase separation. Herein, the decomposition wave propagates in lateral direction which has been confirmed from the lateral composition modulations in spinodally decomposed films. Large magnetic anisotropy has been found in spinodally decomposed nickel ferrite (NFO) thin films. This approach approves that magnetic field is also an important thermodynamic parameter to induce phase separation by the enhancement of up-hill diffusion in thin films. This thin film deposition technique could be a more efficient alternative for the fabrication of self-organized phase separated thin films and employed in controlling of the microstructure at nanoscale level.

Keywords: Dynamic Aurora PLD, magnetic anisotropy, spinodal decomposition, spinel ferrite thin film

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Authors: Eyuphan Manay

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In this study, it was aimed to determine the convective heat transfer characteristics of water-based silicon dioxide nanofluids (SiO₂) with particle volume fractions of 0.2 and 0.4% vol. Nanofluids were tested in a plate type heat exchanger with six plates. Plate type heat exchanger was manufactured from stainless steel. Water was driven in the hot flow side, and nanofluids were driven in the cold flow side. The thermal energy of the hot water was taken by nanofluids. Effect of the inlet temperature of the hot water was investigated on heat transfer performance of the nanofluids while the inlet temperature of the nanofluids was fixed. In addition, the effects of the particle volume fraction and the cold flow rate on the performance of the system were tested. Results showed that increasing inlet temperature of the hot flow caused heat transfer to enhance. The suspended solid particles into the carrier fluid also remarkably enhanced heat transfer, and, an increase in the particle volume fraction resulted in an increase in heat transfer.

Keywords: heat transfer enhancement, SiO₂-water, nanofluid, plate heat exchanger

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Authors: Sneha Thakur, Sanjeev Karmakar

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This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

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Authors: Shahriar Ghammamy, Maryam Gholipoor

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Metronidazole nano -powders with the average mean particle size around 90 nm were synthesized by high-energy milling using a planetary ball mill is provided. The Scattering factors, milling of time,the ball size and ball to powder ratio on the material properties powder by the Ray diffraction (XRD) study, scanning electron microscopy (SEM), IR. It has been observed that the density of nano-sized grinding balls as ball to powder ratio depends. Using the dispersion factor, the density Can be reduced below the initial particle size was achieved.

Keywords: metronidazole, ball-milling, nanoparticles, characterization, XRD diffraction

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Authors: Sang Beom Kim, Kyung Ju Kim, Myung Hoon Cho, Ji Hoon Kim, Soo Hyung Kim

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In this study, we systematically investigated the effect of nanoscale energetic materials in formulations of aluminum nanoparticles (Al NPs; heat source)/copper oxide nanoparticles (CuO NPs; oxidizer) on the combustion and gas-generating properties of sodium azide microparticles (NaN3 MPs; gas-generating agent) for potential applications in gas generators. The burn rate of the NaN3 MP/CuO NP composite powder was only ~0.3 m/s. However, the addition of Al NPs to the NaN3 MP/CuO NP matrix caused the rates to reach ~5.3 m/s, respectively. In addition, the N2 gas volume flow rate generated by the ignition of the NaN3 MP/CuO NP composite powder was only ~0.6 L/s, which was significantly increased to ~3.9 L/s by adding Al NPs to the NaN3 MP/CuO NP composite powder. This suggested that the highly reactive NPs, with the assistance of CuO NPs, were effective heat-generating sources enabling the complete thermal decomposition of NaN3 MPs upon ignition. Al NPs were highly effective in the gas generators because of the increased reactivity induced by the reduced particle size. Finally, we successfully demonstrated that a homemade airbag with a specific volume of ~140 mL could be rapidly and fully inflated by the thermal activation of nanoscale energetic material-added gas-generating agents (i.e., NaN3 MP/Al NP/CuO NP composites) within the standard time of ~50 ms for airbag inflation.

Keywords: nanoenergetic materials, aluminum nanoparticles, copper oxide nanoparticles, gas generators

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Authors: Abdulhakeem Yusuf, Yomi Monday Aiyesimi, Mohammed Jiya

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The failure in an ordinary heat transfer fluid to meet up with today’s industrial cooling rate has resulted in the development of high thermal conductivity fluid which nanofluids belongs. In this work, the problem of unsteady one dimensional laminar flow of an incompressible fluid within a parallel wall is considered with one wall assumed to be wavy. The model is presented in its rectangular coordinate system and incorporates the effects of thermophoresis and Brownian motion. The local similarity solutions were also obtained which depends on Soret number, Dufour number, Biot number, Lewis number, and heat generation parameter. The analytical solution is obtained in a closed form via the Adomian decomposition method. It was found that the method has a good agreement with the numerical method, and it is also established that the heat generation parameter has to be kept low so that heat energy are easily evacuated from the system.

Keywords: Adomian decomposition method, Biot number, Dufour number, nanofluid

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

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Authors: Mohamed Ali Abdennadher

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Digital rock physics, an emerging field leveraging advanced imaging and numerical techniques, offers a promising approach to investigating the mechanical properties of granular materials without extensive physical experiments. This study focuses on using X-Ray Computed Tomography (CT) to capture the three-dimensional (3D) structure of coarse-grained soil at the particle level, combined with finite element analysis (FEA) to simulate the soil's behavior under compression. The primary goal is to establish a reliable virtual testing framework that can replicate laboratory results and offer deeper insights into soil mechanics. The methodology involves acquiring high-resolution CT scans of coarse-grained soil samples to visualize internal particle morphology. These CT images undergo processing through noise reduction, thresholding, and watershed segmentation techniques to isolate individual particles, preparing the data for subsequent analysis. A custom Python script is employed to extract particle shapes and conduct a statistical analysis of particle size distribution. The processed particle data then serves as the basis for creating a finite element model comprising approximately 500 particles subjected to one-dimensional compression. The FEA simulations explore the effects of mesh refinement and friction coefficient on stress distribution at grain contacts. A multi-layer meshing strategy is applied, featuring finer meshes at inter-particle contacts to accurately capture mechanical interactions and coarser meshes within particle interiors to optimize computational efficiency. Despite the known challenges in parallelizing FEA to high core counts, this study demonstrates that an appropriate domain-level parallelization strategy can achieve significant scalability, allowing simulations to extend to very high core counts. The results show a strong correlation between the finite element simulations and laboratory compression test data, validating the effectiveness of the virtual experiment approach. Detailed stress distribution patterns reveal that soil compression behavior is significantly influenced by frictional interactions, with frictional sliding, rotation, and rolling at inter-particle contacts being the primary deformation modes under low to intermediate confining pressures. These findings highlight that CT data analysis combined with numerical simulations offers a robust method for approximating soil behavior, potentially reducing the need for physical laboratory experiments.

Keywords: X-Ray computed tomography, finite element analysis, soil compression behavior, particle morphology

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Authors: Iddy Iddy, Qin Jiang, Changkuan Zhang

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This paper addresses the hydraulic performance of curtain wall breakwaters as a coastal structure protection based on the particles method modelling. The hydraulic functions of curtain wall as wave barriers by reflecting large parts of incident waves through the vertical wall, a part transmitted and a particular part was dissipating the wave energies through the eddy flows formed beneath the lower end of the plate. As a Lagrangian particle, the Moving Particle Semi-implicit (MPS) method which has a robust capability for numerical representation has proven useful for design of structures application that concern free-surface hydrodynamic flow, such as wave breaking and overtopping. In this study, a vertical two-dimensional numerical model for the simulation of violent flow associated with the interaction between the curtain-wall breakwaters and progressive water waves is developed by MPS method in which a higher precision pressure gradient model and free surface particle recognition model were proposed. The wave transmission, reflection, and energy dissipation of the vertical wall were experimentally and theoretically examined. With the numerical wave flume by particle method, very detailed velocity and pressure fields around the curtain-walls under the action of waves can be computed in each calculation steps, and the effect of different wave and structural parameters on the hydrodynamic characteristics was investigated. Also, the simulated results of temporal profiles and distributions of velocity and pressure in the vicinity of curtain-wall breakwaters are compared with the experimental data. Herein, the numerical investigation of hydraulic performance of curtain wall breakwaters indicated that the incident wave is largely reflected from the structure, while the large eddies or turbulent flows occur beneath the curtain-wall resulting in big energy losses. The improved MPS method shows a good agreement between numerical results and analytical/experimental data which are compared to related researches. It is thus verified that the improved pressure gradient model and free surface particle recognition methods are useful for enhancement of stability and accuracy of MPS model for water waves and marine structures. Therefore, it is possible for particle method (MPS method) to achieve an appropriate level of correctness to be applied in engineering fields through further study.

Keywords: curtain wall breakwaters, free surface flow, hydraulic performance, improved MPS method

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Authors: Mohammedi Ferhate

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This paper deals with the generalized the notion of the function of wave a micro particle moving free, the concept of the linear operator in the representation function delta of Dirac which is a generalization of the symbol of Kronecker to the case of a continuous variation of the sizes concerned with the condition of orthonormation of the Eigen functions the use of linear operators and their Eigen functions in connection with the solution of given differential equations, it is of interest to study the properties of the operators themselves and determine which of them follow purely from the nature of the operators, without reference to specific forms of Eigen functions. The models simulation examples are also presented.

Keywords: function, operator, simulation, wave

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Authors: Wei Wang, Martin Chen

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The reconstitution behaviours of nutritional products could impact user experience. Reconstitution issues such as lump formation and white flecks sticking to bottles surfaces could be very unappealing for the consumers in milk preparation. The controlling steps in dissolving instant milk powders include wetting, swelling, sinking, dispersing, and dissolution as in the literature. Each stage happens simultaneously with the others during milk preparation, and it is challenging to isolate and measure each step individually. This study characterized three adult nutritional products for different properties including particle size, density, dispersibility, stickiness, and capillary wetting to understand the relationship between powder physical properties and their reconstitution behaviours. From the results, the formation of clumps can be caused by different factors limiting the critical steps of powder reconstitution. It can be caused by small particle size distribution, light particle density limiting powder wetting, or the rapid swelling and dissolving of particle surface materials to impede water penetration in the capillary channels formed by powder agglomerates. For the grain or white flecks formation in milk preparation, it was believed to be controlled by dissolution speed of the particles after dispersion into water. By understanding those relationship between fundamental powder structure and their user experience in reconstitution, this information provides us new and multiple perspectives on how to improve the powder characteristics in the commercial manufacturing.

Keywords: characterization, dairy nutritional powder, physical property, reconstitution

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Authors: Sung Uk Park, Young Su Kang, Sangmo Kang, Young Kweon Suh

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Mineral product, waste concrete (fine aggregates), waste in the optical field, industry, and construction employ separators to separate solids and classify them according to their size. Various sorting machines are used in the industrial field such as those operating under electrical properties, centrifugal force, wind power, vibration, and magnetic force. Study on separators has been carried out to contribute to the environmental industry. In this study, we perform CFD analysis for understanding the basic mechanism of the separation of waste concrete (fine aggregate) particles from air with a machine built with a rotor with blades. In CFD, we first performed two-dimensional particle tracking for various particle sizes for the model with 1 degree, 1.5 degree, and 2 degree angle between each blade to verify the boundary conditions and the method of rotating domain method to be used in 3D. Then we developed 3D numerical model with ANSYS CFX to calculate the air flow and track the particles. We judged the capability of particle separation for given size by counting the number of particles escaping from the domain toward the exit among 10 particles issued at the inlet. We confirm that particles experience stagnant behavior near the exit of the rotating blades where the centrifugal force acting on the particles is in balance with the air drag force. It was also found that the minimum particle size that can be separated by the machine with the rotor is determined by its capability to stay at the outlet of the rotor channels.

Keywords: environmental industry, separator, CFD, fine aggregate

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Ramya Rachel S.

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For women in a developing country like India, poverty is an ever-clinging problem which has rooted itself without any trace of absolute abolition. Poverty is a deprivation of many imminent needs and must be measured accordingly. Therefore, it is important to study the dimensions of education, health, and standard of living to understand the true nature of the impoverished. The study focused on studying the deprivation on these aspects using the Alkire-Foster methodology to estimate the Multidimensional Poverty Index. The study has utilized the individual data of women aged 15 to 49 of the National Family Health Survey (NFHS) for the year 2015-16. Findings reveal that women in India still face extreme levels of deprivation in various dimensions. More than one-third of the total women aged 15 to 24 in India were multidimensionally poor. Dimensional breakdown of the levels of multidimensional poverty indicates that the dimension of Education is the highest contributor to poverty. Decomposition of the multidimensional poverty among various demographic sub-groups, reveals that the multidimensional poverty level increases with age. Results point out that deprivations were higher among widowed and married women, and among women who lived alone. There was also a huge rural-urban divide with respect to poverty. The basic needs of these women must be targeted and met so that they are withdrawn from all forms of poverty.

Keywords: deprivations, multidimensional poverty, sub-group decomposition, women

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Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

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Authors: Yingjie Zhang, Ming Li, Ying Zhang, Jing Zhang, Zuolei Hu

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In the actual start-up process of DC motors, the DC drive system often faces a conflict between energy consumption and acceleration performance. To resolve the conflict, this paper proposes a comprehensive performance index that energy consumption index is added on the basis of classical control performance index in the DC motor starting process. Taking the comprehensive performance index as the cost function, particle swarm optimization algorithm is designed to optimize the comprehensive performance. Then it conducts simulations on the optimization of the comprehensive performance of the DC motor on condition that the weight coefficient of the energy consumption index should be properly designed. The simulation results show that as the weight of energy consumption increased, the energy efficiency was significantly improved at the expense of a slight sacrifice of fastness indicators with the comprehensive performance index method. The energy efficiency was increased from 63.18% to 68.48% and the response time reduced from 0.2875s to 0.1736s simultaneously compared with traditional proportion integrals differential controller in energy saving.

Keywords: comprehensive performance index, energy consumption, acceleration performance, particle swarm optimal control

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Adrian Kong, William Chang, Rolando Valdes, Alec Rodriguez, Roberto Miki

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The Pneumask consists of a custom snorkel-specific adapter that attaches a snorkel-port of the mask to a 3D-printed filter. This full-face snorkel mask was designed for use as personal protective equipment (PPE) during the COVID-19 pandemic when there was a widespread shortage of PPE for medical personnel. Various clinical validation tests have been conducted, including the sealing capability of the mask, filter performance, CO2 buildup, and clinical usability. However, data regarding the filter efficiencies of Pneumask and multiple filter types have not been determined. Using an experimental system, we evaluated the filtration efficiency across various masks and filters during inhalation. Eighteen combinations of respirator models (5 P100 FFRs, 4 Dolfino Masks) and filters (2091, 7093, 7093CN, BB50T) were evaluated for their exposure to airborne particles sized 0.3 - 10.0 microns using an electronic airborne particle counter. All respirator model combinations provided similar performance levels for 1.0-micron, 3.0-micron, 5.0-micron, 10.0-microns, with the greatest differences in the 0.3-micron and 0.5-micron range. All models provided expected performances against all particle sizes, with Class P100 respirators providing the highest performance levels across all particle size ranges. In conclusion, the modified snorkel mask has the potential to protect providers who care for patients with COVID-19 from increased airborne particle exposure.

Keywords: COVID-19, PPE, mask, filtration, efficiency

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Authors: Cheng Sheng, Yuemin Zhao, Chenlong Duan

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Air dense medium fluidized bed is a typical application of fluidization techniques for coal particle separation in arid areas, where it is costly to implement wet coal preparation technologies. In the last three decades, air dense medium fluidized bed, as an efficient dry coal separation technique, has been studied in many aspects, including energy and mass transfer, hydrodynamics, bubbling behaviors, etc. Despite numerous researches have been published, the fluidization features, especially dual dense medium fluidization features have been rarely reported. In dual dense medium fluidized beds, different combinations of different dense mediums play a significant role in fluidization quality variation, thus influencing coal separation efficiency. Moreover, to what extent different dense mediums mix and to what extent the two-component particulate mixture affects the fluidization performance and quality have been in suspense. The proposed work attempts to reveal underlying mechanisms of generation and evolution of two-component particulate mixture in the fluidization process. Based on computational fluid dynamics methods and discrete particle modelling, movement and evolution of dual dense mediums in air dense medium fluidized bed have been simulated. Dual dense medium fluidization experiments have been conducted. Electrical capacitance tomography was employed to investigate the distribution of two-component mixture in experiments. Underlying mechanisms involving two-component particulate fluidization are projected to be demonstrated with the analysis and comparison of simulation and experimental results.

Keywords: air dense medium fluidized bed, particle separation, computational fluid dynamics, discrete particle modelling

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Authors: M. Tabatabaee, N. Binavayan, M. R. Nateghi

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In this research nano-size of yttrium aluminum garnet (YAG) containing lanthanide metals was synthesized by the sol-gel method in presente citric acid as a complexing agent. Samarium (III) was used to synthesis of YAG:M3+. The prepared powders were characterized by powder X-ray diffraction (PXRD). The size distribution and morphology of the samples were analyzed by scanning electron microscopy (SEM). XRD results show that Sm, La, and ce doped YAG crystallizes in the cubic system and additional peaks compared to pure YAG can be assigned to the presence of Sm in the synthesize YAG. The SEM images show possess spherical nano-sized particle with average 50 nm in diameter.

Keywords: citric acid, nano particle, samarium, yttrium aluminum garnet

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Authors: Mohamed Ahmed AbdelKawy, A. H. El-Shazly

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In this study, Nano iron-copper core-shell was synthesized by using Kinetic energy micro reactor ( K-M reactor). The reaction between nano-pure iron with copper sulphate pentahydrate (CuSO4.5H2O) beside NaCMC as a stabilizer at K-M reactor gives many advantages in comparison with the traditional chemical method for production of nano iron-Copper core-shell in batch reactor. Many factors were investigated for its effect on the process performance such as initial concentrations of nano iron and copper sulphate pentahydrate solution. Different techniques were used for investigation and characterization of the produced nano iron particles such as SEM, XRD, UV-Vis, XPS, TEM and PSD. The produced Nano iron-copper core-shell particle using micro mixer showed better characteristics than those produced using batch reactor in different aspects such as homogeneity of the produced particles, particle size distribution and size, as core diameter 10nm particle size were obtained. The results showed that 10 nm core diameter were obtained using Micro mixer as compared to 80 nm core diameter in one-fourth the time required by using traditional batch reactor and high thickness of copper shell and good stability.

Keywords: nano iron, core-shell, reduction reaction, K-M reactor

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Authors: hassan gheisari

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Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder, as prepared, is annealed at three different temperatures (900 ºC, 1000 ºC, and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks, and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic, which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic; magnetic materials; sol– gel, silicate calcium

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Authors: Hassan Gheisari

Abstract:

Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder as prepared is annealed at three different temperatures (900 ºC, 1000 ºC and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic, magnetic materials, sol– gel, silicate calcium

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Authors: Qianhua He, Weili Zhou, Aiwu Chen

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A sparse representation speech denoising method based on adapted stopping residue error was presented in this paper. Firstly, the cross-correlation between the clean speech spectrum and the noise spectrum was analyzed, and an estimation method was proposed. In the denoising method, an over-complete dictionary of the clean speech power spectrum was learned with the K-singular value decomposition (K-SVD) algorithm. In the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the adjusted noise spectrum, and the orthogonal matching pursuit (OMP) approach was applied to reconstruct the clean speech spectrum from the noisy speech. Finally, the clean speech was re-synthesised via the inverse Fourier transform with the reconstructed speech spectrum and the noisy speech phase. The experiment results show that the proposed method outperforms the conventional methods in terms of subjective and objective measure.

Keywords: speech denoising, sparse representation, k-singular value decomposition, orthogonal matching pursuit

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Authors: Ankur Dixit, Hiroaki Wagatsuma

Abstract:

The crack detection on a concrete bridge is an important and constant task in civil engineering. Chronically, humans are checking the bridge for inspection of cracks to maintain the quality and reliability of bridge. But this process is very long and costly. To overcome such limitations, we have used a drone with a digital camera, which took some images of bridge deck and these images are processed by morphological component analysis (MCA). MCA technique is a very strong application of sparse coding and it explores the possibility of separation of images. In this paper, MCA has been used to decompose the image into coarse and fine components with the effectiveness of two dictionaries namely anisotropic diffusion and wavelet transform. An anisotropic diffusion is an adaptive smoothing process used to adjust diffusion coefficient by finding gray level and gradient as features. These cracks in image are enhanced by subtracting the diffused coarse image into the original image and the results are treated by Sobel edge detector and binary filtering to exhibit the cracks in a fine way. Our results demonstrated that proposed MCA framework using anisotropic diffusion followed by Sobel operator and binary filtering may contribute to an automation of crack detection even in open field sever conditions such as bridge decks.

Keywords: anisotropic diffusion, coarse component, fine component, MCA, Sobel edge detector and wavelet transform

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Authors: Mont Kumpugdee-Vollrath, Khaled Abdallah

Abstract:

Liposomes and pegylated liposomes were widely used as drug delivery system in pharmaceutical field since a long time. However, in the former time, polyethylene glycol (PEG) was connected into phospholipid after the liposomes were already prepared. In this paper, we intend to study the possibility of applying phospholipids which already connected with PEG and then they were used to prepare liposomes. The model drug resveratrol was used because it can be applied against different diseases. Cholesterol was applied to stabilize the membrane of liposomes. The thin film technique in a laboratory scale was a preparation method. The liposomes were then characterized by nanoparticle tracking analysis (NTA), photon correlation spectroscopy (PCS) and light microscopic techniques. The stable liposomes can be produced and the particle sizes after filtration were in nanometers. The 2- and 3-chains-PEG-phospholipid (PL) caused in smaller particle size than the 4-chains-PEG-PL. Liposomes from PL 90G and cholesterol were stable during storage at 8 °C of 56 days because the particle sizes measured by PCS were almost not changed. There was almost no leakage of resveratrol from liposomes PL 90G with cholesterol after diffusion test in dialysis tube for 28 days. All liposomes showed the sustained release during measuring time of 270 min. The maximum release amount of 16-20% was detected with liposomes from 2- and 3-chains-PEG-PL. The other liposomes gave max. release amount of resveratrol only of 10%. The release kinetic can be explained by Korsmeyer-Peppas equation. 

Keywords: liposome, NTA, resveratrol, pegylation, cholesterol

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Authors: Michael Leo L. Dela Cruz, Khryslyn G. Arano, Eden May B. Dela Pena, Leslie Joy Diaz

Abstract:

Arsenic adsorbents were continuously being researched to ease the detrimental impact of arsenic to human health. A comparative study on the adsorption mechanism of arsenic on iron modified nanoclays was undertaken. Iron intercalated montmorillonite (Fe-MMT) and montmorillonite supported zero-valent iron (ZVI-MMT) were the adsorbents investigated in this study. Fe-MMT was produced through ion-exchange by replacing the sodium intercalated ions in montmorillonite with iron (III) ions. The iron (III) in Fe-MMT was later reduced to zero valent iron producing ZVI-MMT. Adsorption study was performed by batch technique. Obtained data were fitted to intra-particle diffusion, pseudo-first order, and pseudo-second-order models and the Elovich equation to determine the kinetics of adsorption. The adsorption of arsenic on Fe-MMT followed the intra-particle diffusion model with intra-particle rate constant of 0.27 mg/g-min0.5. Arsenic was found to be chemically bound on ZVI-MMT as suggested by the pseudo-second order and Elovich equation. The derived pseudo-second order rate constant was 0.0027 g/mg-min with initial adsorption rate computed from the Elovich equation was 113 mg/g-min.

Keywords: adsorption mechanism, arsenic, montmorillonite, zero valent iron

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

Abstract:

The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

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Authors: Teng lin, Li Yuxing, Han Hui, Zhao Pengfei, Zhang Datong

Abstract:

With the development of carbon capture and storage (CCS), the flow assurance of CO2 transportation becomes more important, particularly for supercritical CO2 pipelines. The relieving system using the choke valve is applied to control the pressure in CO2 pipeline. However, the temperature of fluid would drop rapidly because of Joule-Thomson cooling (JTC), which may cause solid CO2 form and block the pipe. In this paper, a Computational Fluid Dynamic (CFD) model, using the modified Lagrangian method, Reynold's Stress Transport model (RSM) for turbulence and stochastic tracking model (STM) for particle trajectory, was developed to predict the deposition characteristic of solid carbon dioxide. The model predictions were in good agreement with the experiment data published in the literature. It can be observed that the particle distribution affected the deposition behavior. In the region of the sudden expansion, the smaller particles accumulated tightly on the wall were dominant for pipe blockage. On the contrary, the size of solid CO2 particles deposited near the outlet usually was bigger and the stacked structure was looser. According to the calculation results, the movement of the particles can be regarded as the main four types: turbulent motion close to the sudden expansion structure, balanced motion at sudden expansion-middle region, inertial motion near the outlet and the escape. Furthermore the particle deposits accumulated primarily in the sudden expansion region, reattachment region and outlet region because of the four type of motion. Also the Stokes number had an effect on the deposition ratio and it is recommended for Stokes number to avoid 3-8St.

Keywords: carbon capture and storage, carbon dioxide pipeline, gas-particle flow, deposition

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