Search results for: constriction factor based particle swarm optimization (CPSO)

Authors: Dávid Csercsik, Péter Kádár

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In the case of the proposed method, the problem is parallelized by considering multiple possible mode of operation profiles, which determine the range in which the generators operate in each period. For each of these profiles, the optimization is carried out independently, and the best resulting dispatch is chosen. For each such profile, the resulting problem is a quadratic programming (QP) problem with a potentially negative definite Q quadratic term, and constraints depending on the actual operation profile. In this paper we analyze the performance of available MATLAB optimization methods and solvers for the corresponding QP.

Keywords: optimization, MATLAB, quadratic programming, economic dispatch

Procedia PDF Downloads 531

Authors: Alexey V. Klyuev, Arkady V. Yakimov, Mikhail I. Ryzhkin, Andrey V. Klyuev

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Fluctuations of Schottky diode parameters in a structure of the mixer are investigated. These fluctuations are manifested in two ways. At the first, they lead to fluctuations in the transfer factor that is lead to the amplitude fluctuations in the signal of intermediate frequency. On the basis of the measurement data of 1/f noise of the diode at forward current, the estimation of a spectrum of relative fluctuations in transfer factor of the mixer is executed. Current dependence of the spectrum of relative fluctuations in transfer factor of the mixer and dependence of the spectrum of relative fluctuations in transfer factor of the mixer on the amplitude of the heterodyne signal are investigated. At the second, fluctuations in parameters of the diode lead to the occurrence of 1/f noise in the output signal of the mixer. This noise limits the sensitivity of the mixer to the value of received signal.

Keywords: current-voltage characteristic, fluctuations, mixer, Schottky diode, 1/f noise

Procedia PDF Downloads 565

Authors: R. S. Yadav, J. Havlica, I. Kuřitka, Z. Kozakova, J. Masilko, L. Kalina, M. Hajdúchová, V. Enev, J. Wasserbauer

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In this work, copper ferrite CuFe2O4 spinel ferrite nanoparticles with different particle size at different annealing temperature were synthesized using the starch-assisted sol-gel auto-combustion method. The synthesized nanoparticles were characterized by conventional powder X-ray diffraction (XRD) spectroscopy, Raman Spectroscopy, Fourier Transform Infrared Spectroscopy, Field-Emission Scanning Electron Microscopy, X-ray Photoelectron Spectroscopy, and Vibrating Sample Magnetometer. The XRD patterns confirmed the formation of CuFe2O4 spinel ferrite nanoparticles. Field-Emission Scanning Electron Microscopy revealed that particles are of spherical morphology with particle size 5-20 nm at lower annealing temperature. An infrared spectroscopy study showed the presence of two principal absorption bands in the frequency range around 530 cm-1 (ν1) and around 360 cm-1 (ν2); which indicate the presence of tetrahedral and octahedral group complexes, respectively, within the spinel ferrite nanoparticles. Raman spectroscopy study also indicated the change in octahedral and tetrahedral site related Raman modes in copper ferrite nanoparticles with change of particle size. This change in magnetic behavior with change of particle size of CuFe2O4 nanoparticles was also observed. The change in magnetic properties with change of particle size is due to cation redistribution, which was confirmed by X-Ray photoelectron study.

Keywords: copper ferrite, nanoparticles, magnetic property, CuFe2O4

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Authors: Vivek Upadhayay, Siddharth Deshmukh

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In recent years utilization of renewable energy sources has increased majorly because of the increase in global warming concerns. Organization these days are generally operated by Micro grid or smart grid on a small level. Power optimization and optimal load tripping is possible in a smart grid based industry. In any plant or industry loads can be divided into different categories based on their importance to the plant and power requirement pattern in the working days. Coming up with an idea to divide loads in different such categories and providing different power management algorithm to each category of load can reduce the power cost and can come handy in balancing stability and reliability of power. An objective function is defined which is subjected to a variable that we are supposed to minimize. Constraint equations are formed taking difference between the power usages pattern of present day and same day of previous week. By considering the objectives of minimal load tripping and optimal power distribution the proposed problem formulation is a multi-object optimization problem. Through normalization of each objective function, the multi-objective optimization is transformed to single-objective optimization. As a result we are getting the optimized values of power required to each load for present day by use of the past values of the required power for the same day of last week. It is quite a demand response scheduling of power. These minimized values then will be distributed to each load through an algorithm used to optimize the power distribution at a greater depth. In case of power storage exceeding the power requirement, profit can be made by selling exceeding power to the main grid.

Keywords: power flow optimization, power trading enhancement, smart grid, multi-object optimization

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Authors: Maryam Sayadi, Rana Sedighpour, Hossein Rezaie

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In this study, in order to evaluate water quality of Gamasiab and Gharehsoo rivers located in Kermanshah province, the information of a 5-year statistical period during the years 2014-2018 was used. To evaluate the hydrochemistry of water, first the type and hydrogeochemical facies of river water were determined using Stiff and Piper diagrams. Then, based on Gibbs diagram and combination diagrams, the factors controlling the chemical parameters of the two rivers were identified. Saturation indices were used to predict the possibility of dissolution and deposition of some minerals. Then, in order to classify water in different sections, fourteen water quality indicators for different uses along with WHO standard were used. Finally, factor analysis was used to determine the processes affecting the hydrochemistry of the two rivers. The results of this study showed that in both rivers, the predominant type and facies are bicarbonate of calcite. Also, the main factor in changing the chemical quality of water in both Gamasiab and Gharehsoo rivers is the water-rock reaction. According to the results of factor analysis in both rivers, two factors have the greatest impact on water quality in the region. Among the parameters of Gamasiab river in the first factor, HCO3-, Na+ and Cl-, respectively, had the highest factor loads, and in the second factor, SO42- and Mg2+ were selected as the main parameters. The parameters Ca2+, Cl- and Na have the highest factor loads in the first factor and in the second factor Mg2+ and SO42- have the highest factor loads in Gharehsoo river. The dissolution of carbonate formations due to their abundance and expansion in the two basins has a more significant effect on changing water chemistry. It has saturated the water of rivers with aragonite, calcite and dolomite. Due to the low contribution of the second factor in changing the chemical parameters, the water of both rivers is saturated with respect to evaporative minerals such as gypsum, halite and anhydrite in all stations. Based on Schoeller diagrams, Wilcox and other quality indicators in these two sections, the amount of main physicochemical parameters are in the desired range for drinking and agriculture. The results of Langelier, Ryznar, Larson-Skold and Puckorius indices showed that water is corrosive in industry.

Keywords: factor analysis, hydrochemical, saturation index, surface water quality

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Authors: Zair Firdaous, Fourka Mohamed, Elfelsoufi Zoubir

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The arrival of e-commerce has changed the supply chain management on the operational level as well as on the organization and strategic and even tactical decisions of the companies. The optimization of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. Every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource in customized online shopping service mode. Then, we realized an optimization model and algorithm for the development based on the analysis of the of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: supply chain resource, e-commerce, pure-players, optimization

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Authors: Mandeep Kaur, Fatehgarh Sahib

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The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

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Authors: Mayada Attia Ibrahim

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Evaluating and developing the electroplating production process is a key challenge in this type of process. The process is influenced by several factors such as process parameters, process costs, and production environments. Analyzing and optimizing all these factors together requires extensive analytical techniques that are not available in real-case industrial entities. This paper presents a practice-based framework for the evaluation and optimization of some of the crucial factors that affect the costs and production times associated with this type of process, energy costs, material costs, and product flow times. The proposed approach uses Design of Experiments, Discrete-Event Simulation, and Theory of Constraints were respectively used to identify the most significant factors affecting the production process and simulate a real production line to recognize the effect of these factors and assign possible bottlenecks. Several scenarios are generated as corrective strategies for improving the production line. Following that, data envelopment analysis CCR input-oriented DEA model is used to evaluate and optimize the suggested scenarios.

Keywords: electroplating process, simulation, design of experiment, performance optimization, theory of constraints, data envelopment analysis

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Authors: Yue Huang, Yiheng Feng

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Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

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Authors: Younghyun Jeon, Seungjoo Maeng

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In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.

Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power

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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: Theodore Grosch, Felipe Koji Godinho Hoshino

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In wireless communications, 3GPP LTE is one of the solutions to meet the greater transmission data rate demand. One issue inherent to this technology is the PAPR (Peak-to-Average Power Ratio) of OFDM (Orthogonal Frequency Division Multiplexing) modulation. This high PAPR affects the efficiency of power amplifiers. One approach to mitigate this effect is the Crest Factor Reduction (CFR) technique. In this work, we simulate the impact of Hard Limited Clipping Crest Factor Reduction technique on BER (Bit Error Rate) in OFDM based Systems. In general, the results showed that CFR has more effects on higher digital modulation schemes, as expected. More importantly, we show the worst-case degradation due to CFR on QPSK, 16QAM, and 64QAM signals in a linear system. For example, hard clipping of 9 dB results in a 2 dB increase in signal to noise energy at a 1% BER for 64-QAM modulation.

Keywords: bit error rate, crest factor reduction, OFDM, physical layer simulation

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Authors: Jiaxu Huang

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The melt carbonized blast furnace slag containing TiC was produced by carbothermal reduction of high titanium blast furnace slag. The treatment technology of melt carbonized blast furnace slag with TiC as raw material was studied, including the influence of different cooling methods, crushing atmosphere and sieving particle size on the target product TiC in the slag. The results show that air-cooling and water-cooling have little effect on TiC content of molten carbide blast furnace slag, and have great effect on crystal structure and grain size. TiC content in slag is different when carbide blast furnace slag is crushed in argon atmosphere and air atmosphere. After screening, the difference of TiC content of carbide blast furnace slag with different particle size distribution is obvious. The average TiC content of 100-400 mesh carbide blast furnace slag is 14%. And the average TiC content of carbide blast furnace slag with particle size less than 400 mesh is 10.5%.

Keywords: crushing atmosphere, cooling methods, sieving particle size, TiC

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Authors: Eun Ju Park, Wendy Rusli, He Tao, Alexander M. Van Herk, Sanggu Kim

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Hollow micro-/nano- structured materials have proven to be promising in wide range of applications, such as catalysis, drug delivery and controlled release, biotechnology, and personal and consumer care. Hollow sphere structures can be obtained through various templating approaches; colloid templates, emulsion templates, multi-surfactant templates, and single crystal templates. Vesicles are generally the self-directed assemblies of amphiphilic molecules including cationic, anionic, and cationic surfactants in aqueous solutions. The directed silica capsule formations were performed at the surface of dioctadecyldimethylammoniumbromide(DODAB) bilayer vesicles as soft template. The size of DODAB bilayer vesicles could be tuned by extrusion of a preheated dispersion of DODAB. The synthesized hollow silica particles were characterized by conventional TEM, cryo-TEM and SEM to determine the morphology and structure of particles and dynamic light scattering (DLS) method to measure the particle size and particle size distribution.

Keywords: characterization, DODAB, hollow silica particle, synthesis, vesicle

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet

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This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.

Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application

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Authors: Mohammad Javad Afroughi, Farjad Falahati, Larry W. Kostiuk, Jason S. Olfert

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This study investigates the physical characteristics of nanoparticles generated during pyrolysis of methane in hot products of a premixed propane-air flame. An inverted burner is designed to provide a laminar premixed propane-air flame (35 SLPM) then introduce methane co-flow to be pyrolyzed within a closed cylindrical chamber (20 cm in diameter and 68 cm in length). The formed products are discharged through an exhaust with a sampling branch to measure emission characteristics. Carbon particles are sampled with a preheated nitrogen dilution system, and the size distribution of particles formed by pyrolysis is measured by a scanning mobility particle sizer (SMPS). Dilution ratio is calculated using simultaneously measured CO2 concentrations in the exhaust products and diluted samples. Results show that particle size distribution (PSD) is strongly affected by dilution ratio and preheating temperature. PSD becomes unstable at high dilution ratios (typically above 700 times) and/or low preheating temperatures (below 40° C). At a suitable dilution ratio of 55 and preheating temperature up to 70° C, the median diameter of PSD increases from 20 to 220 nm following the introduction of 0.5 SLPM of methane to the propane-air premixed flame. Furthermore, with pyrolysis of methane, total particle number concentration and estimated total mass concentration of particles in the size range of 14 to 700 nm, increase from 1.12 to 3.90 *107 cm-3 and from 0.11 to 154 µg L-1, respectively.

Keywords: laminar premixed flame, methane pyrolysis, nanoparticle physical characteristics, particle mass concentration, particle number concentration, particle size distribution (PSD)

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Authors: Joshua Paul Steimel, Michael Pappas, Ethan Hall

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Particle-particle interactions are critical in determining the state of an active matter system. Unique and ubiquitous non-equilibrium behavior like swarming, vortexing, spiraling, and much more is governed by interactions between active units or particles. In hybrid active-passive matter systems, the attraction between spinning active units in a 2D monolayer of passive particles is controlled by the mechanical behavior of the passive monolayer. We demonstrate here that the range and dynamics of this attraction can be controlled by changing the composition of the passive monolayer by adding dopant passive particles. These dopant passive particles effectively pin the movement of dislocation motion in the passive media and reduce the probability of defect motion required to erode the bridge of passive particles between active spinners, thus reducing the range of attraction. Additionally, by adding an out of plane component to the magnetic moment and creating a top-like motion a short range repulsion emerges between the top-like particle. At inter-top distances less than four particle diameters apart, the tops repel but beyond that, distance attract up to 13 particle diameters apart. The tops were also able to locally and transiently anneal the passive monolayer. Thus we demonstrate that by tuning several parameters of the hybrid active matter system, one can observe very different emergent behavior.

Keywords: active matter, colloids, ferromagnetic, annealing

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

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Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

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Authors: Tory Erickson

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The "Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model introduces a framework aimed at unifying general relativity (GR) and quantum mechanics (QM). By proposing a concept of bidirectional spacetime, this model suggests that time can flow in more than one direction, thus offering a perspective on temporal dynamics. Integrated with spatial covariance and wave-particle duality in spacetime flow, the BST-SCWPDF Model resolves long-standing discrepancies between GR and QM. This unified theory has profound implications for quantum gravity, potentially offering insights into quantum entanglement, the collapse of the wave function, and the fabric of spacetime itself. The Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model offers researchers a framework for a better understanding of theoretical physics.

Keywords: astrophysics, quantum mechanics, general relativity, unification theory, theoretical physics

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Authors: V. Ziegler, F. Schneider, M. Pesch

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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.

Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection

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Authors: Manuel Alejandro Taborda Ceballos, Martin Sommerfeld

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Transport phenomena and dispersion of non-spherical particle in turbulent flows are found everywhere in industrial application and processes. Powder handling, pollution control, pneumatic transport, particle separation are just some examples where the particle encountered are not only spherical. These types of multiphase flows are wall bounded and mostly highly turbulent. The particles found in these processes are rarely spherical but may have various shapes (e.g., fibers, and rods). Although research related to the behavior of regular non-spherical particles in turbulent flows has been carried out for many years, it is still necessary to refine models, especially near walls where the interaction fiber-wall changes completely its behavior. Imaging-based experimental studies on dispersed particle-laden flows have been applied for many decades for a detailed experimental analysis. These techniques have the advantages that they provide field information in two or three dimensions, but have a lower temporal resolution compared to point-wise techniques such as PDA (phase-Doppler anemometry) and derivations therefrom. The applied imaging techniques in dispersed two-phase flows are extensions from classical PIV (particle image velocimetry) and PTV (particle tracking velocimetry) and the main emphasis was simultaneous measurement of the velocity fields of both phases. In a similar way, such data should also provide adequate information for validating the proposed models. Available experimental studies on the behavior of non-spherical particles are uncommon and mostly based on planar light-sheet measurements. Especially for elongated non-spherical particles, however, three-dimensional measurements are needed to fully describe their motion and to provide sufficient information for validation of numerical computations. For further providing detailed experimental results allowing a validation of numerical calculations of non-spherical particle dispersion in turbulent flows, a water channel test facility was built around a horizontal closed water channel. Into this horizontal main flow, a small cross-jet laden with fiber-like particles was injected, which was also solely driven by gravity. The dispersion of the fibers was measured by applying imaging techniques based on a LED array for backlighting and high-speed cameras. For obtaining the fluid velocity fields, almost neutrally buoyant tracer was used. The discrimination between tracer and fibers was done based on image size which was also the basis to determine fiber orientation with respect to the inertial coordinate system. The synchronous measurement of fluid velocity and fiber properties also allow the collection of statistics of fiber orientation, velocity fields of tracer and fibers, the angular velocity of the fibers and the orientation between fiber and instantaneous relative velocity. Consequently, an experimental study the behavior of elongated non-spherical particles in wall bounded turbulent flows was achieved. The development of a comprehensive analysis was succeeded, especially near the wall region, where exists hydrodynamic wall interaction effects (e.g., collision or lubrication) and abrupt changes of particle rotational velocity. This allowed us to predict numerically afterwards the behavior of non-spherical particles within the frame of the Euler/Lagrange approach, where the particles are therein treated as “point-particles”.

Keywords: crossflow, non-spherical particles, particle tracking velocimetry, PIV

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Authors: Fahad Y. Al-dawish

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The current trend by a large number of organizations and individuals to use cloud computing. Many consider it a significant shift in the field of computing. Cloud computing are distributed and parallel systems consisting of a collection of interconnected physical and virtual machines. With increasing request and profit of cloud computing infrastructure, diverse computing processes can be executed on cloud environment. Many organizations and individuals around the world depend on the cloud computing environments infrastructure to carry their applications, platform, and infrastructure. One of the major and essential issues in this environment related to allocating incoming tasks to suitable virtual machine (cloud task scheduling). Cloud task scheduling is classified as optimization problem, and there are several meta-heuristic algorithms have been anticipated to solve and optimize this problem. Good task scheduler should execute its scheduling technique on altering environment and the types of incoming task set. In this research project a cloud task scheduling methodology based on ant colony optimization ACO algorithm, we call it ACO-TS Ant Colony Optimization for Task Scheduling has been proposed and compared with different scheduling algorithms (Random, First Come First Serve FCFS, and Fastest Processor to the Largest Task First FPLTF). Ant Colony Optimization (ACO) is random optimization search method that will be used for assigning incoming tasks to available virtual machines VMs. The main role of proposed algorithm is to minimizing the makespan of certain tasks set and maximizing resource utilization by balance the load among virtual machines. The proposed scheduling algorithm was evaluated by using Cloudsim toolkit framework. Finally after analyzing and evaluating the performance of experimental results we find that the proposed algorithm ACO-TS perform better than Random, FCFS, and FPLTF algorithms in each of the makespaan and resource utilization.

Keywords: cloud Task scheduling, ant colony optimization (ACO), cloudsim, cloud computing

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Authors: Emad Askar, Eldesoky Elsoaly, Mohamed Kamel, Hisham Kamel

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The objective of this article is to improve the passive vibration damping of solar array (SA) used in space structures, by the effective application of numerical optimization. A case study of a SA is used for demonstration. A finite element (FE) model was created and verified by experimental testing. Optimization was then conducted by implementing the FE model with the genetic algorithm, to find the optimal placement of aluminum circular patches, to suppress the first two bending mode shapes. The results were verified using experimental testing. Finally, a parametric study was conducted using the FE model where patch locations, material type, and shape were varied one at a time, and the results were compared with the optimal ones. The results clearly show that through the proper application of FE modeling and numerical optimization, passive vibration damping of space structures has been successfully achieved.

Keywords: damping optimization, genetic algorithm optimization, passive vibration damping, solar array vibration damping

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Authors: Rimmy Yadav, Avtar Singh

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—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

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Authors: Farahnaz Karami

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Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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Authors: Anika Zafiah M. Rus, S. Shafizah

Abstract:

This study was developed to compare the behavior and the ability of polymer foam composites towards sound absorption test of Shorea leprosula wood (SL) of acid hydrolysis treatment with particle size < 355µm. Three different weight ratio of polyol to wood particle has been selected which are 10wt%, 15wt%, and 20wt%. The acid hydrolysis treatment is to optimize the surface interaction of a wood particle with polymer foam matrix. In addition, the acoustic characteristic of sound absorption coefficient (Į) was determined. Further treatment is to expose the polymer composite in UV irradiation by using UV-Weatherometer. Polymer foam composite of untreated shorea leprosula particle (SL-B) with respective percentage loading shows uniform pore structure as compared with treated wood particle (SL-A). As the filler percentage loading in polymer foam increases, the Į value approaching 1 for both samples. Furthermore, SL-A shows better Į value at 3500-4500 frequency absorption level(Hz), meanwhile Į value for SL-B is maximum at 4000-5000 Hz. The frequencies absorption level for both SL-B and SL-A after UV exposure was increased with the increasing of exposure time from 0-1000 hours. It is, therefore, concluded that the Į for each sound absorbing material, with or without acid hydrolysis treatment of wood particles and it’s percentages loading in polymer matrix effect the sound absorption behavior.

Keywords: polymer foam composite, sound absorption coefficient, UV-irradiation, wood

Procedia PDF Downloads 445

Authors: Esam I. Jassim

Abstract:

The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.

Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography

Procedia PDF Downloads 471

Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

Abstract:

Lunar exploration is a necessary foundation for deep-space exploration. For the functional limitations of the fixed landers which are widely used currently and are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability, a movable lunar soft-landing device based on cantilever type buffer mechanism and leg-foot type walking mechanism is presented. Firstly, a 20 DoFs quadruped configuration based on pushrod is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and can make the kinematics of the whole mechanism unchanged before and after buffering. Secondly, the multi-function main/auxiliary buffers based on crumple-energy absorption and screw-nut mechanism, as well as the telescopic device which could be used to protect the plantar force sensors during the buffer process are designed. Finally, the kinematic model of the whole mechanism is established, and the configuration optimization of the whole mechanism is completed based on the performance requirements of slope adaptation and obstacle crossing. This research can provide a technical solution integrating soft-landing, large-scale inspection and material-transfer for future lunar exploration and even mars exploration, and can also serve as the technical basis for developing the reusable landers.

Keywords: configuration design, lunar soft-landing device, movable, optimization

Procedia PDF Downloads 136

Authors: Abir Derouiche, Abdesslem Layeb

Abstract:

Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics.

Keywords: Optimization, Metaheuristics, Data Mining, Association rules Mining

Procedia PDF Downloads 144