893 resultados para Moving kriging interpolation
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Kriging is a widely employed method for interpolating and estimating elevations from digital elevation data. Its place of prominence is due to its elegant theoretical foundation and its convenient practical implementation. From an interpolation point of view, kriging is equivalent to a thin-plate spline and is one species among the many in the genus of weighted inverse distance methods, albeit with attractive properties. However, from a statistical point of view, kriging is a best linear unbiased estimator and, consequently, has a place of distinction among all spatial estimators because any other linear estimator that performs as well as kriging (in the least squares sense) must be equivalent to kriging, assuming that the parameters of the semivariogram are known. Therefore, kriging is often held to be the gold standard of digital terrain model elevation estimation. However, I prove that, when used with local support, kriging creates discontinuous digital terrain models, which is to say, surfaces with “rips” and “tears” throughout them. This result is general; it is true for ordinary kriging, kriging with a trend, and other forms. A U.S. Geological Survey (USGS) digital elevation model was analyzed to characterize the distribution of the discontinuities. I show that the magnitude of the discontinuity does not depend on surface gradient but is strongly dependent on the size of the kriging neighborhood.
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The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this article, we propose to address this challenging problem by substituting the distillation columns by Kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate Kriging-based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush–Kuhn–Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.
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Superstructure approaches are the solution to the difficult problem which involves the rigorous economic design of a distillation column. These methods require complex initialization procedures and they are hard to solve. For this reason, these methods have not been extensively used. In this work, we present a methodology for the rigorous optimization of chemical processes implemented on a commercial simulator using surrogate models based on a kriging interpolation. Several examples were studied, but in this paper, we perform the optimization of a superstructure for a non-sharp separation to show the efficiency and effectiveness of the method. Noteworthy that it is possible to get surrogate models accurate enough with up to seven degrees of freedom.
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Condensation technique of degree of freedom is firstly proposed to improve the computational efficiency of meshfree method with Galerkin weak form. In present method, scattered nodes without connectivity are divided into several subsets by cells with arbitrary shape. The local discrete equations are established over each cell by using moving kriging interpolation, in which the nodes that located in the cell are used for approximation. Then, the condensation technique can be introduced into the local discrete equations by transferring equations of inner nodes to equations of boundary nodes based on cell. In the scheme of present method, the calculation of each cell is carried out by meshfree method with Galerkin weak form, and local search is implemented in interpolation. Numerical examples show that the present method has high computational efficiency and convergence, and good accuracy is also obtained.
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A sub‒domain smoothed Galerkin method is proposed to integrate the advantages of mesh‒free Galerkin method and FEM. Arbitrarily shaped sub‒domains are predefined in problems domain with mesh‒free nodes. In each sub‒domain, based on mesh‒free Galerkin weak formulation, the local discrete equation can be obtained by using the moving Kriging interpolation, which is similar to the discretization of the high‒order finite elements. Strain smoothing technique is subsequently applied to the nodal integration of sub‒domain by dividing the sub‒domain into several smoothing cells. Moreover, condensation of DOF can also be introduced into the local discrete equations to improve the computational efficiency. The global governing equations of present method are obtained on the basis of the scheme of FEM by assembling all local discrete equations of the sub‒domains. The mesh‒free properties of Galerkin method are retained in each sub‒domain. Several 2D elastic problems have been solved on the basis of this newly proposed method to validate its computational performance. These numerical examples proved that the newly proposed sub‒domain smoothed Galerkin method is a robust technique to solve solid mechanics problems based on its characteristics of high computational efficiency, good accuracy, and convergence.
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Condensation technique of degree of freedom is first proposed to improve the computational efficiency of meshfree method with Galerkin weak form for elastic dynamic analysis. In the present method, scattered nodes without connectivity are divided into several subsets by cells with arbitrary shape. Local discrete equation is established over each cell by using moving Kriging interpolation, in which the nodes that located in the cell are used for approximation. Then local discrete equations can be simplified by condensation of degree of freedom, which transfers equations of inner nodes to equations of boundary nodes based on cells. The global dynamic system equations are obtained by assembling all local discrete equations and are solved by using the standard implicit Newmark’s time integration scheme. In the scheme of present method, the calculation of each cell is carried out by meshfree method, and local search is implemented in interpolation. Numerical examples show that the present method has high computational efficiency and good accuracy in solving elastic dynamic problems.
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The urban heat island phenomenon is the most well-known all-year-round urban climate phenomenon. It occurs in summer during the daytime due to the short-wave radiation from the sun and in wintertime, through anthropogenic heat production. In summertime, the properties of the fabric of city buildings determine how much energy is stored, conducted and transmitted through the material. During night-time, when there is no incoming short-wave radiation, all fabrics of the city release the energy in form of heat back to the urban atmosphere. In wintertime anthropogenic heating of buildings and traffic deliver energy into the urban atmosphere. The initial focus of Helsinki urban heat island was on the description of the intensity of the urban heat island (Fogelberg 1973, Alestalo 1975). In this project our goal was to carry out as many measurements as possible over a large area of Helsinki to give a long term estimate of the Helsinki urban heat island. Helsinki is a city with 550 000 inhabitants and located on the north shore of Finnish Bay of the Baltic Sea. Initially, comparison studies against long-term weather station records showed that our regular, but weekly, sampling of observations adequately describe the Helsinki urban heat island. The project covered an entire seasonal cycle over the 12 months from July 2009 to June 2010. The measurements were conducted using a moving platform following microclimatological traditions. Tuesday was selected as the measuring day because it was the only weekday during the one year time span without any public holidays. Once a week, two set of measurements, in total 104, were conducted in the heterogeneous temperature conditions of Helsinki city centre. In the more homogeneous suburban areas, one set of measurements was taken every second week, to give a total of 52.The first set of measurements took place before noon, and the second 12 hours, just prior to midnight. Helsinki Kaisaniemi weather station was chosen as the reference station. This weather station is located in a large park in the city centre of Helsinki. Along the measurement route, 336 fixed points were established, and the monthly air temperature differences to Kaisaniemi were calculated to produce monthly and annual maps. The monthly air temperature differences were interpolated 21.1 km by 18.1 km horizontal grid with 100 metre resolution residual kriging method. The following independent variables for the kriging interpolation method were used: topographical height, portion of sea area, portion of trees, fraction of built-up and not built-up area, volumes of buildings, and population density. The annual mean air temperature difference gives the best representation of the Helsinki urban heat island effect- Due to natural variability of weather conditions during the measurement campaign care must be taken when interpretation the results for the monthly values. The main results of this urban heat island research project are: a) The city centre of Helsinki is warmer than its surroundings, both on a monthly main basis, and for the annual mean, however, there are only a few grid points, 46 out of 38 191, which display a temperature difference of more than 1K. b) If the monthly spatial variation is air temperature differences is small, then usually the temperature difference between the city and the surroundings is also small. c) Isolated large buildings and suburban centres create their own individual heat island. d) The topographical influence on air temperature can generally be neglected for the monthly mean, but can be strong under certain weather conditions.
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A method is described to allow searches for transonic aeroelastic instability of realistically sized aircraft models in multidimensional parameter spaces when computational fluid dynamics are used to model the aerodynamics. Aeroelastic instability is predicted from a small nonlinear eigenvalue problem. The approximation of the computationally expensive interaction term modeling the fluid response is formulated to allow the automated and blind search for aeroelastic instability. The approximation uses a kriging interpolation of exact numerical samples covering the parameter space. The approach, demonstrated for the Goland wing and the multidisciplinary optimization transport wing, results in stability analyses over whole flight envelopes at an equivalent cost of several steady-state simulations.
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The structure and function of northern ecosystems are strongly influenced by climate change and variability and by human-induced disturbances. The projected global change is likely to have a pronounced effect on the distribution and productivity of different species, generating large changes in the equilibrium at the tree-line. In turn, movement of the tree-line and the redistribution of species produce feedback to both the local and the regional climate. This research was initiated with the objective of examining the influence of natural conditions on the small-scale spatial variation of climate in Finnish Lapland, and to study the interaction and feedback mechanisms in the climate-disturbances-vegetation system near the climatological border of boreal forest. The high (1 km) resolution spatial variation of climate parameters over northern Finland was determined by applying the Kriging interpolation method that takes into account the effect of external forcing variables, i.e., geographical coordinates, elevation, sea and lake coverage. Of all the natural factors shaping the climate, the geographical position, local topography and altitude proved to be the determining ones. Spatial analyses of temperature- and precipitation-derived parameters based on a 30-year dataset (1971-2000) provide a detailed description of the local climate. Maps of the mean, maximum and minimum temperatures, the frost-free period and the growing season indicate that the most favourable thermal conditions exist in the south-western part of Lapland, around large water bodies and in the Kemijoki basin, while the coldest regions are in highland and fell Lapland. The distribution of precipitation is predominantly longitudinally dependent but with the definite influence of local features. The impact of human-induced disturbances, i.e., forest fires, on local climate and its implication for forest recovery near the northern timberline was evaluated in the Tuntsa area of eastern Lapland, damaged by a widespread forest fire in 1960 and suffering repeatedly-failed vegetation recovery since that. Direct measurements of the local climate and simulated heat and water fluxes indicated the development of a more severe climate and physical conditions on the fire-disturbed site. Removal of the original, predominantly Norway spruce and downy birch vegetation and its substitution by tundra vegetation has generated increased wind velocity and reduced snow accumulation, associated with a large variation in soil temperature and moisture and deep soil frost. The changed structural parameters of the canopy have determined changes in energy fluxes by reducing the latter over the tundra vegetation. The altered surface and soil conditions, as well as the evolved severe local climate, have negatively affected seedling growth and survival, leading to more unfavourable conditions for the reproduction of boreal vegetation and thereby causing deviations in the regional position of the timberline. However it should be noted that other factors, such as an inadequate seed source or seedbed, the poor quality of the soil and the intensive logging of damaged trees could also exacerbate the poor tree regeneration. In spite of the failed forest recovery at Tunsta, the position and composition of the timberline and tree-line in Finnish Lapland may also benefit from present and future changes in climate. The already-observed and the projected increase in temperature, the prolonged growing season, as well as changes in the precipitation regime foster tree growth and new regeneration, resulting in an advance of the timberline and tree-line northward and upward. This shift in the distribution of vegetation might be decelerated or even halted by local topoclimatic conditions and by the expected increase in the frequency of disturbances.
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The ionospheric parameter M(3000)F2 (the so-called transmission factor or the propagation factor) is important not only in practical applications such as frequency planning for radio-communication but also in ionospheric modeling. This parameter is strongly anti-correlated with the ionospheric F2-layer peak height hmF2,a parameter often used as a key anchor point in some widely used empirical models of the ionospheric electron density profile (e.g., in IRI and NeQuick models). Since hmF2 is not easy to obtain from measurements and M(3000)F2 can be routinely scaled from ionograms recorded by ionosonde/digisonde stations distributed globally and its data has been accumulated for a long history, usually the value of hmF2 is calculated from M(3000)F2 using the empirical formula connecting them. In practice, CCIR M(3000)F2 model is widely used to obtain M(3000)F2 value. However, recently some authors found that the CCIR M(3000)F2 model has remarkable discrepancies with the measured M(3000)F2, especially in low-latitude and equatorial regions. For this reason, the International Reference Ionosphere (IRI) research community proposes to improve or update the currently used CCIR M(3000)F2 model. Any efforts toward the improvement and updating of the current M(3000)F2 model or newly development of a global hmF2 model are encouraged. In this dissertation, an effort is made to construct the empirical models of M(3000)F2 and hmF2 based on the empirical orthogonal function (EOF) analysis combined with regression analysis method. The main results are as follows: 1. A single station model is constructed using monthly median hourly values of M(3000)F2 data observed at Wuhan Ionospheric Observatory during the years of 1957–1991 and compared with the IRI model. The result shows that EOF method is possible to use only a few orders of EOF components to represent most of the variance of the original data set. It is a powerful method for ionospheric modeling. 2. Using the values of M(3000)F2 observed by ionosondes distributed globally, data at grids uniformly distributed globally were obtained by using the Kriging interpolation method. Then the gridded data were decomposed into EOF components using two different coordinates: (1) geographical longitude and latitude; (2) modified dip (Modip) and local time. Based on the EOF decompositions of the gridded data under these two coordinates systems, two types of the global M(3000)F2 model are constructed. Statistical analysis showed that the two types of the constructed M(3000)F2 model have better agreement with the observational M(3000)F2 than the M(3000)F2 model currently used by IRI. The constructed models can represent the global variations of M(3000)F2 better. 3. The hmF2 data used to construct the hmF2 model were converted from the observed M(3000)F2 based on the empirical formula connecting them. We also constructed two types of the global hmF2 model using the similar method of modeling M(3000)F2. Statistical analysis showed that the prediction of our models is more accurate than the model of IRI. This demonstrated that using EOF analysis method to construct global model of hmF2 directly is feasible. The results in this thesis indicate that the modeling technique based on EOF expansion combined with regression analysis is very promising when used to construct the global models of M(3000)F2 and hmF2. It is worthwhile to investigate further and has the potential to be used to the global modeling of other ionospheric parameters.
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A Kriging interpolation method is combined with an object-based evaluation measure to assess the ability of the UK Met Office's dispersion and weather prediction models to predict the evolution of a plume of tracer as it was transported across Europe. The object-based evaluation method, SAL, considers aspects of the Structure, Amplitude and Location of the pollutant field. The SAL method is able to quantify errors in the predicted size and shape of the pollutant plume, through the structure component, the over- or under-prediction of the pollutant concentrations, through the amplitude component, and the position of the pollutant plume, through the location component. The quantitative results of the SAL evaluation are similar for both models and close to a subjective visual inspection of the predictions. A negative structure component for both models, throughout the entire 60 hour plume dispersion simulation, indicates that the modelled plumes are too small and/or too peaked compared to the observed plume at all times. The amplitude component for both models is strongly positive at the start of the simulation, indicating that surface concentrations are over-predicted by both models for the first 24 hours, but modelled concentrations are within a factor of 2 of the observations at later times. Finally, for both models, the location component is small for the first 48 hours after the start of the tracer release, indicating that the modelled plumes are situated close to the observed plume early on in the simulation, but this plume location error grows at later times. The SAL methodology has also been used to identify differences in the transport of pollution in the dispersion and weather prediction models. The convection scheme in the weather prediction model is found to transport more pollution vertically out of the boundary layer into the free troposphere than the dispersion model convection scheme resulting in lower pollutant concentrations near the surface and hence a better forecast for this case study.
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Com o objetivo de avaliar as relações entre formas de paisagem e erosão em um Latossolo Vermelho eutroférrico (LVef) por meio de técnicas geoestatísticas na Fazenda Santa Isabel, município de Jaboticabal (SP), identificaram-se modelos de paisagem côncavo e linear. Coletaram-se amostras de solo em ambas as formas de paisagem em uma malha regular espaçada de 50 x 50 m em sete transeções na profundidade de 0,00-0,20 m, totalizando 412 pontos em 93 ha. Determinou-se a erodibilidade dos solos pelo método indireto, granulometria, bem como o carbono orgânico para cada ponto da malha, sendo esses valores usados na estimativa do potencial natural de erosão (pne). Os dados obtidos das propriedades de solo, erodibilidade e potencial natural de erosão foram analisados por meio de estatística descritiva e geoestatística com a modelagem de semivariogramas, sendo este utilizado para a confecção de mapas de krigagem. Segundo os resultados, as propriedades do solo e do pne apresentaram maior variabilidade espacial na pedoforma côncava, apesar de esta forma de paisagem apresentar menores perdas de solo por erosão e menor variabilidade espacial da erodibilidade. Deste modo, conclui-se que a erosão não adicionou variabilidade espacial para as propriedades do solo na mesma magnitude do relevo.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Studies show the importance of knowing the variability of soil attributes for a more efficient management. This work was carried out to evaluate the spatial variability of the chemical attributes of an Ultisol, cultivated with Brachiaria decumbens pasture in Alegre - ES. Soil samples were collected at a depth of 00-0.2 m, at the crossing points of a regular grid with 10 m-intervals, comprising a total of 64 points. Data were submitted to descriptive statistics, geostatistics and kriging interpolation analysis. The coefficient of variation was low for pH, high for Al and m%, and medium the other attributes. The attributes pH, P, H+Al and m% presented strong dependence, and the other moderate dependence. The attributes presented a spatial dependence structure, allowing their mapping by geostatistics techniques.