231 resultados para Particle number distribution
Resumo:
Numerical investigation on mixed convection of a two-dimensional incompressible laminar flow over a horizontal flat plate with streamwise sinusoidal distribution of surface temperature has been performed for different values of Rayleigh number, Reynolds number and frequency of periodic temperature for constant Prandtl number and amplitude of periodic temperature. Finite element method adapted to rectangular non-uniform mesh elements by a non-linear parametric solution algorithm basis numerical scheme has been employed. The investigating parameters are the Rayleigh number, the Reynolds number and frequency of periodic temperature. The effect of variation of individual investigating parameters on mixed convection flow characteristics has been studied to observe the hydrodynamic and thermal behavior for while keeping the other parameters constant. The fluid considered in this study is air with Prandtl number 0.72. The results are obtained for the Rayleigh number range of 102 to 104, Reynolds number ranging from 1 to 100 and the frequency of periodic temperature from 1 to 5. Isotherms, streamlines, average and local Nusselt numbers are presented to show the effect of the different values of aforementioned investigating parameters on fluid flow and heat transfer.
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In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of dispatchable distributed generators (DDG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DDG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called modified discrete particle swarm optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DDGs are included in the optimization.
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The first representative chemical, structural, and morphological analysis of the solid particles from a single collection surface has been performed. This collection surface sampled the stratosphere between 17 and 19km in altitude in the summer of 1981, and therefore before the 1982 eruptions of El Chichón. A particle collection surface was washed free of all particles with rinses of Freon and hexane, and the resulting wash was directed through a series of vertically stacked Nucleopore filters. The size cutoff for the solid particle collection process in the stratosphere is found to be considerably less than 1 μm. The total stratospheric number density of solid particles larger than 1μm in diameter at the collection time is calculated to be about 2.7×10−1 particles per cubic meter, of which approximately 95% are smaller than 5μm in diameter. Previous classification schemes are expanded to explicitly recognize low atomic number material. With the single exception of the calcium-aluminum-silicate (CAS) spheres all solid particle types show a logarithmic increase in number concentration with decreasing diameter. The aluminum-rich particles are unique in showing bimodal size distributions. In addition, spheres constitute only a minor fraction of the aluminum-rich material. About 2/3 of the particles examined were found to be shards of rhyolitic glass. This abundant volcanic material could not be correlated with any eruption plume known to have vented directly to the stratosphere. The micrometeorite number density calculated from this data set is 5×10−2 micrometeorites per cubic meter of air, an order of magnitude greater than the best previous estimate. At the collection altitude, the maximum collision frequency of solid particles >5μm in average diameter is calculated to be 6.91×10−16 collisions per second, which indicates negligible contamination of extraterrestrial particles in the stratosphere by solid anthropogenic particles.
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Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key-chain), to each sensor node. If a pair of nodes does not have a common key after deployment then they must find a key-path with secured links. The objective is to minimize the keychain size while (i) maximizing pairwise key sharing probability and resilience, and (ii) minimizing average key-path length. This paper presents a deterministic key distribution scheme based on Expander Graphs. It shows how to map the parameters (e.g., degree, expansion, and diameter) of a Ramanujan Expander Graph to the desired properties of a key distribution scheme for a physical network topology.
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Greater than 750 individual particles have now been selected from collection flags housed in the JSC Cosmic Dust Curatorial Facility and most have been documented in the Cosmic Dust Catalogs [1]. As increasing numbers of particles are placed in Cosmic Dust Collections, and a greater diversity of particles are introduced to the stratosphere through natural and man-made processes (e.g. decaying orbits of space debris [2]), there is an even greater need for a classification scheme to encompass all stratospheric particles rather than only extraterrestrial particles. The fundamental requirements for a suitable classification scheme have been outlined in earlier communications [3,4]. A quantitative survey of particles on collection flag W7017 indicates that there is some bias in the number of samples selected within a given category for the Cosmic Dust Catalog [5]. However, the sample diversity within this selection is still appropriate for the development of a reliable classification scheme. In this paper, we extend the earlier works on stratospheric particle classification to include particles collected during the period May 1981 to November 1983.
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As the world’s population is growing, so is the demand for agricultural products. However, natural nitrogen (N) fixation and phosphorus (P) availability cannot sustain the rising agricultural production, thus, the application of N and P fertilisers as additional nutrient sources is common. It is those anthropogenic activities that can contribute high amounts of organic and inorganic nutrients to both surface and groundwaters resulting in degradation of water quality and a possible reduction of aquatic life. In addition, runoff and sewage from urban and residential areas can contain high amounts of inorganic and organic nutrients which may also affect water quality. For example, blooms of the cyanobacterium Lyngbya majuscula along the coastline of southeast Queensland are an indicator of at least short term decreases of water quality. Although Australian catchments, including those with intensive forms of land use, show in general a low export of nutrients compared to North American and European catchments, certain land use practices may still have a detrimental effect on the coastal environment. Numerous studies are reported on nutrient cycling and associated processes on a catchment scale in the Northern Hemisphere. Comparable studies in Australia, in particular in subtropical regions are, however, limited and there is a paucity in the data, in particular for inorganic and organic forms of nitrogen and phosphorus; these nutrients are important limiting factors in surface waters to promote algal blooms. Therefore, the monitoring of N and P and understanding the sources and pathways of these nutrients within a catchment is important in coastal zone management. Although Australia is the driest continent, in subtropical regions such as southeast Queensland, rainfall patterns have a significant effect on runoff and thus the nutrient cycle at a catchment scale. Increasingly, these rainfall patterns are becoming variable. The monitoring of these climatic conditions and the hydrological response of agricultural catchments is therefore also important to reduce the anthropogenic effects on surface and groundwater quality. This study consists of an integrated hydrological–hydrochemical approach that assesses N and P in an environment with multiple land uses. The main aim is to determine the nutrient cycle within a representative coastal catchment in southeast Queensland, the Elimbah Creek catchment. In particular, the investigation confirms the influence associated with forestry and agriculture on N and P forms, sources, distribution and fate in the surface and groundwaters of this subtropical setting. In addition, the study determines whether N and P are subject to transport into the adjacent estuary and thus into the marine environment; also considered is the effect of local topography, soils and geology on N and P sources and distribution. The thesis is structured on four components individually reported. The first paper determines the controls of catchment settings and processes on stream water, riverbank sediment, and shallow groundwater N and P concentrations, in particular during the extended dry conditions that were encountered during the study. Temporal and spatial factors such as seasonal changes, soil character, land use and catchment morphology are considered as well as their effect on controls over distributions of N and P in surface waters and associated groundwater. A total number of 30 surface and 13 shallow groundwater sampling sites were established throughout the catchment to represent dominant soil types and the land use upstream of each sampling location. Sampling comprises five rounds and was conducted over one year between October 2008 and November 2009. Surface water and groundwater samples were analysed for all major dissolved inorganic forms of N and for total N. Phosphorus was determined in the form of dissolved reactive P (predominantly orthophosphate) and total P. In addition, extracts of stream bank sediments and soil grab samples were analysed for these N and P species. Findings show that major storm events, in particular after long periods of drought conditions, are the driving force of N cycling. This is expressed by higher inorganic N concentrations in the agricultural subcatchment compared to the forested subcatchment. Nitrate N is the dominant inorganic form of N in both the surface and groundwaters and values are significantly higher in the groundwaters. Concentrations in the surface water range from 0.03 to 0.34 mg N L..1; organic N concentrations are considerably higher (average range: 0.33 to 0.85 mg N L..1), in particular in the forested subcatchment. Average NO3-N in the groundwater has a range of 0.39 to 2.08 mg N L..1, and organic N averages between 0.07 and 0.3 mg N L..1. The stream bank sediments are dominated by organic N (range: 0.53 to 0.65 mg N L..1), and the dominant inorganic form of N is NH4-N with values ranging between 0.38 and 0.41 mg N L..1. Topography and soils, however, were not to have a significant effect on N and P concentrations in waters. Detectable phosphorus in the surface and groundwaters of the catchment is limited to several locations typically in the proximity of areas with intensive animal use; in soil and sediments, P is negligible. In the second paper, the stable isotopes of N (14N/15N) and H2O (16O/18O and 2H/H) in surface and groundwaters are used to identify sources of dissolved inorganic and organic N in these waters, and to determine their pathways within the catchment; specific emphasis is placed on the relation of forestry and agriculture. Forestry is predominantly concentrated in the northern subcatchment (Beerburrum Creek) while agriculture is mainly found in the southern subcatchment (Six Mile Creek). Results show that agriculture (horticulture, crops, grazing) is the main source of inorganic N in the surface waters of the agricultural subcatchment, and their isotopic signature shows a close link to evaporation processes that may occur during water storage in farm dams that are used for irrigation. Groundwaters are subject to denitrification processes that may result in reduced dissolved inorganic N concentrations. Soil organic matter delivers most of the inorganic N to the surface water in the forested subcatchment. Here, precipitation and subsequently runoff is the main source of the surface waters. Groundwater in this area is affected by agricultural processes. The findings also show that the catchment can attenuate the effects of anthropogenic land use on surface water quality. Riparian strips of natural remnant vegetation, commonly 50 to 100 m in width, act as buffer zones along the drainage lines in the catchment and remove inorganic N from the soil water before it enters the creek. These riparian buffer zones are common in most agricultural catchments of southeast Queensland and are indicated to reduce the impact of agriculture on stream water quality and subsequently on the estuary and marine environments. This reduction is expressed by a significant decrease in DIN concentrations from 1.6 mg N L..1 to 0.09 mg N L..1, and a decrease in the �15N signatures from upstream surface water locations downstream to the outlet of the agricultural subcatchment. Further testing is, however, necessary to confirm these processes. Most importantly, the amount of N that is transported to the adjacent estuary is shown to be negligible. The third and fourth components of the thesis use a hydrological catchment model approach to determine the water balance of the Elimbah Creek catchment. The model is then used to simulate the effects of land use on the water balance and nutrient loads of the study area. The tool that is used is the internationally widely applied Soil and Water Assessment Tool (SWAT). Knowledge about the water cycle of a catchment is imperative in nutrient studies as processes such as rainfall, surface runoff, soil infiltration and routing of water through the drainage system are the driving forces of the catchment nutrient cycle. Long-term information about discharge volumes of the creeks and rivers do, however, not exist for a number of agricultural catchments in southeast Queensland, and such information is necessary to calibrate and validate numerical models. Therefore, a two-step modelling approach was used to calibrate and validate parameters values from a near-by gauged reference catchment as starting values for the ungauged Elimbah Creek catchment. Transposing monthly calibrated and validated parameter values from the reference catchment to the ungauged catchment significantly improved model performance showing that the hydrological model of the catchment of interest is a strong predictor of the water water balance. The model efficiency coefficient EF shows that 94% of the simulated discharge matches the observed flow whereas only 54% of the observed streamflow was simulated by the SWAT model prior to using the validated values from the reference catchment. In addition, the hydrological model confirmed that total surface runoff contributes the majority of flow to the surface water in the catchment (65%). Only a small proportion of the water in the creek is contributed by total base-flow (35%). This finding supports the results of the stable isotopes 16O/18O and 2H/H, which show the main source of water in the creeks is either from local precipitation or irrigation waters delivered by surface runoff; a contribution from the groundwater (baseflow) to the creeks could not be identified using 16O/18O and 2H/H. In addition, the SWAT model calculated that around 68% of the rainfall occurring in the catchment is lost through evapotranspiration reflecting the prevailing long-term drought conditions that were observed prior and during the study. Stream discharge from the forested subcatchment was an order of magnitude lower than discharge from the agricultural Six Mile Creek subcatchment. A change in land use from forestry to agriculture did not significantly change the catchment water balance, however, nutrient loads increased considerably. Conversely, a simulated change from agriculture to forestry resulted in a significant decrease of nitrogen loads. The findings of the thesis and the approach used are shown to be of value to catchment water quality monitoring on a wider scale, in particular the implications of mixed land use on nutrient forms, distributions and concentrations. The study confirms that in the tropics and subtropics the water balance is affected by extended dry periods and seasonal rainfall with intensive storm events. In particular, the comprehensive data set of inorganic and organic N and P forms in the surface and groundwaters of this subtropical setting acquired during the one year sampling program may be used in similar catchment hydrological studies where these detailed information is missing. Also, the study concludes that riparian buffer zones along the catchment drainage system attenuate the transport of nitrogen from agricultural sources in the surface water. Concentrations of N decreased from upstream to downstream locations and were negligible at the outlet of the catchment.
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The surface area of inhaled particles deposited in the alveolar region, as reported by the TSI nanoparticle surface area monitor (NSAM), was compared with the corresponding value estimated by a TSI scanning mobility particle sizer (SMPS) for a range of environmentally relevant aerosols, including petrol emissions, ETS, laser printer emissions, cooking emissions and ambient aerosols. The SMPS values were based on a mobility size distribution assuming spherical particles using the appropriate size-dependent alveolar-deposition factors provided by the ICRP. In most cases, the two instruments showed good linear agreement. With petrol emissions and ETS, the linearity extended to over 103 μm2 cm-3. With printer emissions, there was good linearity up to about 300 μm2 cm-3 while the NSAM increasingly overestimated the surface area at higher concentrations. The presence of a nucleation event in ambient air caused the NSAM to over-estimate the surface area by a factor of 2. We summarize these results and conclude that the maximum number concentration up to which the NSAM is accurate clearly depends on the type of aerosol being sampled and provide guidance for the use of the instrument.
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A nanoparticles size is one of their key physical characteristics that can affect their fate in a human’s respiratory tract (in case of inhalation) and also in the environment. Hence, measuring the size distribution of nanoparticles is absolutely essential and contributes greatly to their characterization. For years, Scanning Mobility Particle Sizers (SMPS), which rely on measuring the electrical mobility diameter of particles, have been used as one of the most reliable real-time instruments for the size distribution measurement of nanoparticles. Despite its benefits, this instrument has some drawbacks, including equivalency problems for non-spherical particles (i.e. assuming a non-spherical particle is equal to a spherical particle of diameter d due to the same electrical mobility), as well as limitations in terms of its use in workplaces, because of its large size and the complexity of its operation...
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Sugarcane bagasse is an abundant and sustainable resource, generated as a by-product of sugarcane milling. The cellulosic material within bagasse can be broken down into glucose molecules and fermented to produce ethanol, making it a promising feedstock for biofuel production. Mild acid pretreatment hydrolyses the hemicellulosic component of biomass, thus allowing enzymes greater access to the cellulosic substrate during saccharification. A particle-scale mathematical model describing the mild acid pretreatment of sugarcane bagasse has been developed, using a volume averaged framework. Discrete population-balance equations are used to characterise the polymer degradation kinetics, and diffusive effects account for mass transport within the cell wall of the bagasse. As the fibrous material hydrolyses over time, variations in the porosity of the cell wall and the downstream effects on the reaction kinetics are accounted for using conservation of volume arguments. Non-dimensionalization of the model equations reduces the number of parameters in the system to a set of four dimensionless ratios that compare the timescales of different reaction and diffusion events. Theoretical yield curves are compared to macroscopic experimental observations from the literature and inferences are made as to constraints on these “unknown” parameters. These results enable connections to be made between experimental data and the underlying thermodynamics of acid pretreatment. Consequently, the results suggest that data-fitting techniques used to obtain kinetic parameters should be carefully applied, with prudent consideration given to the chemical and physiological processes being modeled.
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The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.
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This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.
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This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).
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This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.
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This paper deals with an efficient hybrid evolutionary optimization algorithm in accordance with combining the ant colony optimization (ACO) and the simulated annealing (SA), so called ACO-SA. The distribution feeder reconfiguration (DFR) is known as one of the most important control schemes in the distribution networks, which can be affected by distributed generations (DGs) for the multi-objective DFR. In such a case, DGs is used to minimize the real power loss, the deviation of nodes voltage and the number of switching operations. The approach is carried out on a real distribution feeder, where the simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving the DFR problem.
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This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.