25 resultados para reasonable accuracy
Resumo:
Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
The present paper reports some definite evidence for the significance of wavelength positioning accuracy in multicomponent analysis techniques for the correction of line interferences in inductively coupled plasma atomic emission spectrometry (ICP-AES). Using scanning spectrometers commercially available today, a large relative error, DELTA(A) may occur in the estimated analyte concentration, owing to wavelength positioning errors, unless a procedure for data processing can eliminate the problem of optical instability. The emphasis is on the effect of the positioning error (deltalambda) in a model scan, which is evaluated theoretically and determined experimentally. A quantitative relation between DELTA(A) and deltalambda, the peak distance, and the effective widths of the analysis and interfering lines is established under the assumption of Gaussian line profiles. The agreement between calculated and experimental DELTA(A) is also illustrated. The DELTA(A) originating from deltalambda is independent of the net analyte/interferent signal ratio; this contrasts with the situation for the positioning error (dlambda) in a sample scan, where DELTA(A) decreases with an increase in the ratio. Compared with dlambda, the effect of deltalambda is generally less significant.
Resumo:
Starting from nonhydrostatic Boussinesq approximation equations, a general method is introduced to deduce the dispersion relationships. A comparative investigation is performed on inertia-gravity wave with horizontal lengths of 100, 10 and 1 km. These are examined using the second-order central difference scheme and the fourth-order compact difference scheme on vertical grids that are currently available from the perspectives of frequency, horizontal and vertical component of group velocity. These findings are compared to analytical solutions. The obtained results suggest that whether for the second-order central difference scheme or for the fourth-order compact difference scheme, Charny-Phillips and Lorenz ( L) grids are suitable for studying waves at the above-mentioned horizontal scales; the Lorenz time-staggered and Charny-Phillips time staggered (CPTS) grids are applicable only to the horizontal scales of less than 10 km, and N grid ( unstaggered grid) is unsuitable for simulating waves at any horizontal scale. Furthermore, by using fourth-order compact difference scheme with higher difference precision, the errors of frequency and group velocity in horizontal and vertical directions produced on all vertical grids in describing the waves with horizontal lengths of 1, 10 and 100 km cannot inevitably be decreased. So in developing a numerical model, the higher-order finite difference scheme, like fourth-order compact difference scheme, should be avoided as much as possible, typically on L and CPTS grids, since it will not only take many efforts to design program but also make the calculated group velocity in horizontal and vertical directions even worse in accuracy.
Impact of spatial resolution and spatial difference accuracy on the performance of Arakawa A-D grids
Resumo:
This paper alms at illustrating the impact of spatial difference scheme and spatial resolution on the performance of Arakawa A-D grids in physical space. Linear shallow water equations are discretized and forecasted on Arakawa A-D grids for 120-minute using the ordinary second-order (M and fourth-order (C4) finite difference schemes with the grid spacing being 100 km, 10 km and I km, respectively. Then the forecasted results are compared with the exact solution, the result indicates that when the grid spacing is I kin, the inertial gravity wave can be simulated on any grid with the same results from C2 scheme or C4 scheme, namely the impact of variable configuration is neglectable; while the inertial gravity wave is simulated with lengthened grid spacing, the effects of different variable configurations are different. However, whether for C2 scheme or for C4 scheme, the RMS is minimal (maximal) on C (D) grid. At the same time it is also shown that when the difference accuracy increases from C2 scheme to C4 scheme, the resulted forecasts do not uniformly decrease, which is validated by the change of the group A velocity relative error from C2 scheme to C4 scheme. Therefore, the impact of the grid spacing is more important than that of the difference accuracy on the performance of Arakawa A-D grid.
Resumo:
本文根据便携式移动机器人的特点,采用四元数法解算机器人导航系统的姿态,避免了在机器人运动角度较大时出现奇异点的问题。文中应用改进的四阶龙格-库塔算法解算四元数微分方程,经仿真实验,精度完全能够达到要求。给出了合理的变换公式,在机器人运动范围内,满足了四元数与欧拉角之间转换的一一对应。
Resumo:
结构光视觉传感器是视觉焊缝跟踪系统获得焊缝信息的重要组成部分,其测量误差与性能对焊缝跟踪系统的总体测量精度及可靠性有着直接影响。本文对应用于焊缝跟踪的结构光视觉传感器进行误差分析,包括传感器硬件系统结构误差、激光散斑噪声误差及镜头畸变误差等,并对不同结构方式下的视觉传感器建立了数学模型,具体分析了结构参数对其误差的影响,提出结构光视觉焊缝跟踪传感器优化设计方法,并依据仿真结果给出结构优化设计参数,最后通过实验验证了该优化设计方法的正确性。
Resumo:
With the continuously proceeding of petroleum exploratory development in China, exploratory development becomes more and more difficult. For increasing reserve volume and production, lithologic hydrocarbon reservoir has been the most workable, potential and universality exploration targets. In the past, Dagang Oil Field use the complicated fault reservoir theory as the guide, develop and form a suit of matching construction and instrument in prospecting complicated fault reservoir that reach top of exploration industry in China. But the research of lithologic hydrocarbon reservoir is not much, which affects the exploitation progress of lithologic hydrocarbon reservoir. In this thesis, is object, through the depth study of lithologic deposition in Shasan segment of Zhouqingzhuang Oil Field, a suit of holographic fine reservoir bed forecasting techniques is built up and finally gets following main results: 1. Applying geology, seism, drilling, logging and other information to sensitivity preferences, geological model, inversion and integrated stratum evaluation, realizing the method and flow of refined multi-information stratum forecast. 2. Built up a full three dimensional fine structural interpretation method: in view of r problem of accurately demarcating 90% inclined well, propose a inclined well air space demarcating method, make bed demarcating more exactly; in view of problem of faults demarcating and combination in seismic interpretation, propose a computational method of seismic interference based on wavelet translation, make identify the fault in different level more dependable and reasonable; for exactly identifying structural attitude, propose a velocity modeling method under multi-well restriction, make structural attitude closer to the facts. 3. Built up a high accuracy reservoir bed inversion method: in view of problem in exactly identifying reservoir and nonreservoir with conventional wave impedance inversion method in this place, propose a reservoir log response characteristic analysis and sensible log parameter inversion method. ①analysis log response of reservoir and nonreservoir in region of interest, make definite the most sensible log parameter in identifying reservoir and nonreservoir in this region; ②make sensible log parameter inversion based on wave impedance inversion, to improve inversion accuracy, the thickness of recognizable reservoir bed reach 4-5m. 4. Built up a 4-D reservoir forcasting circuit: in view of difficulty that in lithologic hydrocarbon reservoir making reservoir space characteristic clear by using structural map and reservoir forecasting techniques once only, propose a 4-D reservoir forcasting circuit. In other words, based on development conceptual design, forcast reservoir of different time, namely multiple 3D reservoir forcasting in time queue, each time the accuracy degree of reservoir forcasting is improved since apply the new well material, thereby achieve high quality and highly efficient in exploratory development. During exploratory development lithologic depositin in Shasan segment of Zhouqingzhuang Oil Field, there are thirteen wells get 100% success rate, which sufficiently proves that this suit of method is scientific and effective.
Resumo:
As a fast and effective method for approximate calculation of seismic numerical simulation, ray tracing method, which has important theory and practical application value, in terms of seismic theory and seismic simulation, inversion, migration, imaging, simplified from seismic theory according to geometric seismic, means that the main energy of seismic wave field propagates along ray paths in condition of high-frequency asymptotic approximation. Calculation of ray paths and traveltimes is one of key steps in seismic simulation, inversion, migration, and imaging. Integrated triangular grids layout on wavefront with wavefront reconstruction ray tracing method, the thesis puts forward wavefront reconstruction ray tracing method based on triangular grids layout on wavefront, achieves accurate and fast calculation of ray paths and traveltimes. This method has stable and reasonable ray distribution, and overcomes problems caused by shadows in conventional ray tracing methods. The application of triangular grids layout on wavefront, keeps all the triangular grids stable, and makes the division of grids and interpolation of a new ray convenient. This technology reduces grids and memory, and then improves calculation efficiency. It enhances calculation accuracy by accurate and effective description and division on wavefront. Ray tracing traveltime table, which shares the character of 2-D or 3-D scatter data, has great amount of data points in process of seismic simulation, inversion, migration, and imaging. Therefore the traveltime table file will be frequently read, and the calculation efficiency is very low. Due to these reasons, reasonable traveltime table compression will be very necessary. This thesis proposes surface fitting and scattered data compression with B-spline function method, applies to 2-D and 3-D traveltime table compression. In order to compress 2-D (3-D) traveltime table, first we need construct a smallest rectangular (cuboidal) region with regular grids to cover all the traveltime data points, through the coordinate range of them in 2-D surface (3-D space). Then the value of finite regular grids, which are stored in memory, can be calculated using least square method. The traveltime table can be decompressed when necessary, according to liner interpolation method of 2-D (3-D) B-spline function. In the above calculation, the coefficient matrix is stored using sparse method and the liner system equations are solved using LU decomposition based on the multi-frontal method according to the sparse character of the least square method matrix. This method is practiced successfully in several models, and the cubic B-spline function can be the best basal function for surface fitting. It make the construction surface smooth, has stable and effective compression with high approximate accuracy using regular grids. In this way, through constructing reasonable regular grids to insure the calculation efficiency and accuracy of compression and surface fitting, we achieved the aim of traveltime table compression. This greatly improves calculation efficiency in process of seismic simulation, inversion, migration, and imaging.
Resumo:
The processes of seismic wave propagation in phase space and one way wave extrapolation in frequency-space domain, if without dissipation, are essentially transformation under the action of one parameter Lie groups. Consequently, the numerical calculation methods of the propagation ought to be Lie group transformation too, which is known as Lie group method. After a fruitful study on the fast methods in matrix inversion, some of the Lie group methods in seismic numerical modeling and depth migration are presented here. Firstly the Lie group description and method of seismic wave propagation in phase space is proposed, which is, in other words, symplectic group description and method for seismic wave propagation, since symplectic group is a Lie subgroup and symplectic method is a special Lie group method. Under the frame of Hamiltonian, the propagation of seismic wave is a symplectic group transformation with one parameter and consequently, the numerical calculation methods of the propagation ought to be symplectic method. After discrete the wave field in time and phase space, many explicit, implicit and leap-frog symplectic schemes are deduced for numerical modeling. Compared to symplectic schemes, Finite difference (FD) method is an approximate of symplectic method. Consequently, explicit, implicit and leap-frog symplectic schemes and FD method are applied in the same conditions to get a wave field in constant velocity model, a synthetic model and Marmousi model. The result illustrates the potential power of the symplectic methods. As an application, symplectic method is employed to give synthetic seismic record of Qinghai foothills model. Another application is the development of Ray+symplectic reverse-time migration method. To make a reasonable balance between the computational efficiency and accuracy, we combine the multi-valued wave field & Green function algorithm with symplectic reverse time migration and thus develop a new ray+wave equation prestack depth migration method. Marmousi model data and Qinghai foothills model data are processed here. The result shows that our method is a better alternative to ray migration for complex structure imaging. Similarly, the extrapolation of one way wave in frequency-space domain is a Lie group transformation with one parameter Z and consequently, the numerical calculation methods of the extrapolation ought to be Lie group methods. After discrete the wave field in depth and space, the Lie group transformation has the form of matrix exponential and each approximation of it gives a Lie group algorithm. Though Pade symmetrical series approximation of matrix exponential gives a extrapolation method which is traditionally regarded as implicit FD migration, it benefits the theoretic and applying study of seismic imaging for it represent the depth extrapolation and migration method in a entirely different way. While, the technique of coordinates of second kind for the approximation of the matrix exponential begins a new way to develop migration operator. The inversion of matrix plays a vital role in the numerical migration method given by Pade symmetrical series approximation. The matrix has a Toepelitz structure with a helical boundary condition and is easy to inverse with LU decomposition. A efficient LU decomposition method is spectral factorization. That is, after the minimum phase correlative function of each array of matrix had be given by a spectral factorization method, all of the functions are arranged in a position according to its former location to get a lower triangular matrix. The major merit of LU decomposition with spectral factorization (SF Decomposition) is its efficiency in dealing with a large number of matrixes. After the setup of a table of the spectral factorization results of each array of matrix, the SF decomposition can give the lower triangular matrix by reading the table. However, the relationship among arrays is ignored in this method, which brings errors in decomposition method. Especially for numerical calculation in complex model, the errors is fatal. Direct elimination method can give the exact LU decomposition But even it is simplified in our case, the large number of decomposition cost unendurable computer time. A hybrid method is proposed here, which combines spectral factorization with direct elimination. Its decomposition errors is 10 times little than that of spectral factorization, and its decomposition speed is quite faster than that of direct elimination, especially in dealing with a large number of matrix. With the hybrid method, the 3D implicit migration can be expected to apply on real seismic data. Finally, the impulse response of 3D implicit migration operator is presented.
Resumo:
As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.