995 resultados para Rainfall simulation


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It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

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Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.

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The aggregation property of multiheaded surfactants has been investigated by constant pressure molecular dynamics (MD) simulation in aqueous medium. The model multiheaded surfactants contain more than one headgroup (x = 2, 3, and 4) for a single tail group. This increases the hydrophilic charge progressively over the hydrophobic tail which has dramatic consequences in the aggregation behavior. In particular, we have looked at the change in the aggregation property such as critical micellar concentration (cmc), aggregation number, and size of the micelles for the multiheaded surfactants in water. We find with increasing number of headgroups of the Multiheaded surfactants that the cmc values increase and the aggregation numbers as well as the size of the micelles decrease. These trends are in agreement with the experimental findings as reported earlier with x = 1, 2, and 3. We also predict the aggregation properties of multiheaded surfactant With four headgroups (x = 4) for which no experimental studies exist yet.

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An interactive graphics package for modeling with Petri Nets has been implemented. It uses the VT-11 graphics terminal supported on the PDP-11/35 computer to draw, execute, analyze, edit and redraw a Petri Net. Each of the above mentioned tasks can be performed by selecting appropriate items from a menu displayed on the screen. Petri Nets with a reasonably large number of nodes can be created and analyzed using this package. The number of nodes supported may be increased by making simple changes in the program. Being interactive, the program seeks information from the user after displaying appropriate messages on the terminal. After completing the Petri Net, it may be executed step by step and the changes in the number of tokens may be observed on the screen, at each place. Some properties of Petri Nets like safety, boundedness, conservation and redundancy can be checked using this package. This package can be used very effectively for modeling asynchronous (concurrent) systems with Petri Nets and simulating the model by “graphical execution.”

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Population dynamics are generally viewed as the result of intrinsic (purely density dependent) and extrinsic (environmental) processes. Both components, and potential interactions between those two, have to be modelled in order to understand and predict dynamics of natural populations; a topic that is of great importance in population management and conservation. This thesis focuses on modelling environmental effects in population dynamics and how effects of potentially relevant environmental variables can be statistically identified and quantified from time series data. Chapter I presents some useful models of multiplicative environmental effects for unstructured density dependent populations. The presented models can be written as standard multiple regression models that are easy to fit to data. Chapters II IV constitute empirical studies that statistically model environmental effects on population dynamics of several migratory bird species with different life history characteristics and migration strategies. In Chapter II, spruce cone crops are found to have a strong positive effect on the population growth of the great spotted woodpecker (Dendrocopos major), while cone crops of pine another important food resource for the species do not effectively explain population growth. The study compares rate- and ratio-dependent effects of cone availability, using state-space models that distinguish between process and observation error in the time series data. Chapter III shows how drought, in combination with settling behaviour during migration, produces asymmetric spatially synchronous patterns of population dynamics in North American ducks (genus Anas). Chapter IV investigates the dynamics of a Finnish population of skylark (Alauda arvensis), and point out effects of rainfall and habitat quality on population growth. Because the skylark time series and some of the environmental variables included show strong positive autocorrelation, the statistical significances are calculated using a Monte Carlo method, where random autocorrelated time series are generated. Chapter V is a simulation-based study, showing that ignoring observation error in analyses of population time series data can bias the estimated effects and measures of uncertainty, if the environmental variables are autocorrelated. It is concluded that the use of state-space models is an effective way to reach more accurate results. In summary, there are several biological assumptions and methodological issues that can affect the inferential outcome when estimating environmental effects from time series data, and that therefore need special attention. The functional form of the environmental effects and potential interactions between environment and population density are important to deal with. Other issues that should be considered are assumptions about density dependent regulation, modelling potential observation error, and when needed, accounting for spatial and/or temporal autocorrelation.

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The monosaccharide 2-O-sulfo-α-l-iduronic acid (IdoA2S) is one of the major components of glycosaminoglycans. The ability of molecular mechanics force fields to reproduce ring-puckering conformational equilibrium is important for the successful prediction of the free energies of interaction of these carbohydrates with proteins. Here we report unconstrained molecular dynamics simulations of IdoA2S monosaccharide that were carried out to investigate the ability of commonly used force fields to reproduce its ring conformational flexibility in aqueous solution. In particular, the distribution of ring conformer populations of IdoA2S was determined. The GROMOS96 force field with the SPC/E water potential can predict successfully the dominant skew-boat to chair conformational transition of the IdoA2S monosaccharide in aqueous solution. On the other hand, the GLYCAM06 force field with the TIP3P water potential sampled transitional conformations between the boat and chair forms. Simulations using the GROMOS96 force field showed no pseudorotational equilibrium fluctuations and hence no inter-conversion between the boat and twist boat ring conformers. Calculations of theoretical proton NMR coupling constants showed that the GROMOS96 force field can predict the skew-boat to chair conformational ratio in good agreement with the experiment, whereas GLYCAM06 shows worse agreement. The omega rotamer distribution about the C5–C6 bond was predicted by both force fields to have torsions around 10°, 190°, and 360°.

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Aggregation of the microtubule associated protein tau (MAPT) within neurons of the brain is the leading cause of tauopathies such as Alzheimer's disease. MAPT is a phospho-protein that is selectively phosphorylated by a number of kinases in vivo to perform its biological function. However, it may become pathogenically hyperphosphorylated, causing aggregation into paired helical filaments and neurofibrillary tangles. The phosphorylation induced conformational change on a peptide of MAPT (htau225−250) was investigated by performing molecular dynamics simulations with different phosphorylation patterns of the peptide (pThr231 and/or pSer235) in different simulation conditions to determine the effect of ionic strength and phosphate charge. All phosphorylation patterns were found to disrupt a nascent terminal β-sheet pattern (226VAVVR230 and 244QTAPVP249), replacing it with a range of structures. The double pThr231/pSer235 phosphorylation pattern at experimental ionic strength resulted in the best agreement with NMR structural characterization, with the observation of a transient α-helix (239AKSRLQT245). PPII helical conformations were only found sporadically throughout the simulations. Proteins 2014; 82:1907–1923. © 2014 Wiley Periodicals, Inc.

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This paper asks a new question: how we can use RFID technology in marketing products in supermarkets and how we can measure its performance or ROI (Return-on-Investment). We try to answer the question by proposing a simulation model whereby customers become aware of other customers' real-time shopping behavior and may hence be influenced by their purchases and the levels of purchases. The proposed model is orthogonal to sales model and can have the similar effects: increase in the overall shopping volume. Managers often struggle with the prediction of ROI on purchasing such a technology, this simulation sets to provide them the answers of questions like the percentage of increase in sales given real-time purchase information to other customers. The simulation is also flexible to incorporate any given model of customers' behavior tailored to particular supermarket, settings, events or promotions. The results, although preliminary, are promising to use RFID technology for marketing products in supermarkets and provide several dimensions to look for influencing customers via feedback, real-time marketing, target advertisement and on-demand promotions. Several other parameters have been discussed including the herd behavior, fake customers, privacy, and optimality of sales-price margin and the ROI of investing in RFID technology for marketing purposes. © 2010 Springer Science+Business Media B.V.

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This work proposes a supermarket optimization simulation model called Swarm-Moves is based on self organized complex system studies to identify parameters and their values that can influence customers to buy more on impulse in a given period of time. In the proposed model, customers are assumed to have trolleys equipped with technology like RFID that can aid the passing of products' information directly from the store to them in real-time and vice-versa. Therefore, they can get the information about other customers purchase patterns and constantly informing the store of their own shopping behavior. This can be easily achieved because the trolleys "know" what products they contain at any point. The Swarm-Moves simulation is the virtual supermarket providing the visual display to run and test the proposed model. The simulation is also flexible to incorporate any given model of customers' behavior tailored to particular supermarket, settings, events or promotions. The results, although preliminary, are promising to use RFID technology for marketing products in supermarkets and provide several dimensions to look for influencing customers via feedback, real-time marketing, target advertisement and on-demand promotions. ©2009 IEEE.

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Purpose - The purpose of this paper is to apply lattice Boltzmann equation method (LBM) with multiple relaxation time (MRT) model, to investigate lid-driven flow in a three-dimensional (3D), rectangular cavity, and compare the results with flow in an equivalent two-dimensional (2D) cavity. Design/methodology/approach - The second-order MRT model is implemented in a 3D LBM code. The flow structure in cavities of different aspect ratios (0.25-4) and Reynolds numbers (0.01-1000) is investigated. The LBM simulation results are compared with those from numerical solution of Navier-Stokes (NS) equations and with available experimental data. Findings - The 3D simulations demonstrate that 2D models may predict the flow structure reasonably well at low Reynolds numbers, but significant differences with experimental data appear at high Reynolds numbers. Such discrepancy between 2D and 3D results are attributed to the effect of boundary layers near the side-walls in transverse direction (in 3D), due to which the vorticity in the core-region is weakened in general. Secondly, owing to the vortex stretching effect present in 3D flow, the vorticity in the transverse plane intensifies whereas that in the lateral plane decays, with increase in Reynolds number. However, on the symmetry-plane, the flow structure variation with respect to cavity aspect ratio is found to be qualitatively consistent with results of 2D simulations. Secondary flow vortices whose axis is in the direction of the lid-motion are observed; these are weak at low. Reynolds numbers, but become quite strong at high Reynolds numbers. Originality/value - The findings will be useful in the study of variety of enclosed fluid flows.

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Flexible objects such as a rope or snake move in a way such that their axial length remains almost constant. To simulate the motion of such an object, one strategy is to discretize the object into large number of small rigid links connected by joints. However, the resulting discretised system is highly redundant and the joint rotations for a desired Cartesian motion of any point on the object cannot be solved uniquely. In this paper, we revisit an algorithm, based on the classical tractrix curve, to resolve the redundancy in such hyper-redundant systems. For a desired motion of the `head' of a link, the `tail' is moved along a tractrix, and recursively all links of the discretised objects are moved along different tractrix curves. The algorithm is illustrated by simulations of a moving snake, tying of knots with a rope and a solution of the inverse kinematics of a planar hyper-redundant manipulator. The simulations show that the tractrix based algorithm leads to a more `natural' motion since the motion is distributed uniformly along the entire object with the displacements diminishing from the `head' to the `tail'.

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In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.

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The southern Western Ghats tropical montane cloud forest sites (Gavi, Periyar, High wavys and Venniyar), which are characterized by frequent or seasonal cloud cover at the vegetation level, are considered one of the most threatened ecosystems in India and the world. Three out of four montane cloud forest sites studied in the southern Western Ghats had experienced diminishing trends of seasonal average and total rainfall, especially during summer monsoon season. The highest level of reduction for summer monsoon season was observed at Gavi rainforest station (>20 mm/14 years) in Kerala followed by Venniyar (>20 mm/20 years) site in Tamil Nadu. Average annual and total precipitation increased during the study period irrespective of the seasons over Periyar area, and the greatest values were recorded for season 2 (>25 mm/28 years). Positive trends for winter monsoon rainfall has been observed for three stations (Periyar, High wavys and Venniyar) except Gavi, and the trend was positive and significant (90%) for Periyar and High wavys. Increase in summer monsoon rainfall was observed for Periyar site and the trend was found to be significant (95%).

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This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.