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1.
Feed forward neural network and interpolation function models to predict the soil and subsurface sediments distribution in Bam,Iran 总被引：1，自引：1，他引：0
Khalil Rezaei Bernard Guest Anke Friedrich Farajollah Fayazi Muhammad Nakhaei Ali Beitollahi Seyed Mahmoud Fatemi Aghda 《Acta Geophysica》2009,57(2):271-293
An application of the artificial neural network (ANN) approach for predicting mean grain size using electric resistivity data
from Bam city is presented. A feed forward back propagation network was developed employing 45 sets of input data. The input
variables in the ANN model are the electrical resistivity, water table as a Boolean value and depth; the output is the mean
grain size. To demonstrate the authenticity of this approach, the network predictions are compared with those from interpolation
methods and the same data. This comparison shows that the ANN approach performs better results. The predicted and observed
mean grain size values were compared and show high correlation coefficients. The ANN approach maps show a high degree of correlation
with well data based grain size maps and can therefore be used conservatively to better understand the influence of input
parameters on sedimentological predictions. 相似文献
2.
Abstract We introduce a general expansion approach to obtain a fully consistent closed set of magnetohydrodynamic equations in two independent variables, which is particularly useful to describe axially symmetric, time-dependent problems with weak variation of all quantities in the radial direction. This is done by considering the hierarchy of expanded magnetofluid equations in cylindrical coordinates and equating terms with equal powers in the radial coordinate r. From geometrical considerations it is shown that the radial expansions of the pertaining physical quantities are either even series or odd series in r; this introduces a significant reduction in the number of variables and equations. The closure of the system is provided by appropriate boundary conditions. Among other possible applications, the method is relevant for the analysis of structure and dynamics of magnetic field concentrations in stellar atmospheres. 相似文献
3.
In this study,a new analytical approach is developed to analyze the free nonlinear vibration of conservative two-degree-of-freedom(TDOF) systems.The mathematical models of these systems are governed by second–order nonlinear partial differential equations.Nonlinear differential equations were transferred into a single equation by using some intermediate variables.The single nonlinear differential equations are solved by using the first order of the Hamiltonian approach(HA).Different parameters,which have a significant impact on the response of the systems,are considered and discussed.Some comparisons are presented to verify the results between the Hamiltonian approach and the exact solution.The maximum relative error is less than 2.2124 % for large amplitudes of vibration.It has been established that the first iteration of the Hamiltonian approach achieves very accurate results,does not require any small perturbations,and can be used for a wide range of nonlinear problems. 相似文献
4.
This paper deals with the lower order (first four) nonstationary statistical moments of the response of linear systems with random stiffness and random damping properties subject to random nonstationary excitation modeled as white noise multiplied by an envelope function. The method of analysis is based on a Markov approach using stochastic differential equations (SDE). The linear SDE with random coefficients subject to random excitation with deterministic initial conditions are transformed to an equivalent nonlinear SDE with deterministic coefficients and random initial conditions subject to random excitation. In this procedure, new SDE with random initial conditions, deterministic coefficients and zero forcing functions are introduced to represent the random variables. The joint statistical moments of the response are determined by considering an augmented dynamic system with state variables made up of the displacement and velocity vectors and the random variables of the structural system. The zero time-lag joint statistical moment equations for the augmented state vector are derived from the Itô differential formula. The statistical moment equations are ordinary nonlinear differential equations where hierarchy of moments appear. The hierarchy is closed by the cumulant neglect closure method applied at the fourth order statistical moment level. General formulation is given for multi-degree-of-freedom (MDOF) systems and the performance of the method in problems with nonstationary excitations and large variabilities is illustrated for a single-degree-of-freedom (SDOF) oscillator. 相似文献
5.
Regionalisation of the parameters of the log‐Pearson 3 distribution: a case study for New South Wales,Australia 
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下载免费PDF全文 The index flood method is widely used in regional flood frequency analysis (RFFA) but explicitly relies on the identification of ‘acceptable homogeneous regions’. This paper presents an alternative RFFA method, which is particularly useful when ‘acceptably homogeneous regions’ cannot be identified. The new RFFA method is based on the region of influence (ROI) approach where a ‘local region’ can be formed to estimate statistics at the site of interest. The new method is applied here to regionalize the parameters of the log‐Pearson 3 (LP3) flood probability model using Bayesian generalized least squares (GLS) regression. The ROI approach is used to reduce model error arising from the heterogeneity unaccounted for by the predictor variables in the traditional fixed‐region GLS analysis. A case study was undertaken for 55 catchments located in eastern New South Wales, Australia. The selection of predictor variables was guided by minimizing model error. Using an approach similar to stepwise regression, the best model for the LP3 mean was found to use catchment area and 50‐year, 12‐h rainfall intensity as explanatory variables, whereas the models for the LP3 standard deviation and skewness only had a constant term for the derived ROIs. Diagnostics based on leave‐one‐out cross validation show that the regression model assumptions were not inconsistent with the data and, importantly, no genuine outlier sites were identified. Significantly, the ROI GLS approach produced more accurate and consistent results than a fixed‐region GLS model, highlighting the superior ability of the ROI approach to deal with heterogeneity. This method is particularly applicable to regions that show a high degree of regional heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
6.
《水文科学杂志》2013,58(3):640-655
Abstract Water temperature is an important abiotic variable in aquatic habitat studies and may be one of the factors limiting the potential fish habitat (e.g. salmonids) in a stream. Stream water temperatures are modelled using statistical approaches with air temperature and streamflow as exogenous variables in the Nivelle River, southern France. Two different models are used to model mean weekly maximum temperature data: a non-parametric approach, the k-nearest neighbours method (k-NN) and a parametric approach, the periodic autoregressive model with exogenous variables (PARX). The k-NN is a data-driven method, which consists of finding, at each point of interest, a small number of neighbours nearest to this value, and the prediction is estimated based on these neighbours. The PARX model is an extension of commonly-used autoregressive models in which parameters are estimated for each period within the years. Different variants of air temperature and flow are used in the model development. In order to test the performance of these models, a jack-knife technique is used, whereby model goodness of fit is assessed separately for each year. The results indicate that both models give good performances, but the PARX model should be preferred, because of its good estimation of the individual weekly temperatures and its ability to explicitly predict water temperature using exogenous variables. 相似文献
7.
《Advances in water resources》2001,24(6):667-676
Gradient-based nonlinear programming (NLP) methods can solve problems with smooth nonlinear objectives and constraints. However, in large and highly nonlinear models, these algorithms can fail to find feasible solutions, or converge to local solutions which are not global. Evolutionary search procedures in general, and genetic algorithms (GAs) specifically, are less susceptible to the presence of local solutions. However, they often exhibit slow convergence, especially when there are many variables, and have problems finding feasible solutions in constrained problems with “narrow” feasible regions. In this paper, we describe strategies for solving large nonlinear water resources models management, which combine GAs with linear programming. The key idea is to identify a set of complicating variables in the model which, when fixed, render the problem linear in the remaining variables. The complicating variables are then varied by a GA. This GA&LP approach is applied to two nonlinear models: a reservoir operation model with nonlinear hydropower generation equations and nonlinear reservoir topologic equations, and a long-term dynamic river basin planning model with a large number of nonlinear relationships. For smaller instances of the reservoir model, the CONOPT2 nonlinear solver is more accurate and faster, but for larger instances, the GA&LP approach finds solutions with significantly better objective values. The multiperiod river basin model is much too large to be solved in its entirety. The complicating variables are chosen here so that, when they are fixed, each period's model is linear, and these models can be solved sequentially. This approach allows sufficient model detail to be retained so that long-term sustainability issues can be explored. 相似文献
8.
Shuang-Ye Wu 《水文科学杂志》2013,58(8):1251-1263
Abstract This study aims to assess the potential impact of climate change on flood risk for the city of Dayton, which lies at the outlet of the Upper Great Miami River Watershed, Ohio, USA. First the probability mapping method was used to downscale annual precipitation output from 14 global climate models (GCMs). We then built a statistical model based on regression and frequency analysis of random variables to simulate annual mean and peak streamflow from precipitation input. The model performed well in simulating quantile values for annual mean and peak streamflow for the 20th century. The correlation coefficients between simulated and observed quantile values for these variables exceed 0.99. Applying this model with the downscaled precipitation output from 14 GCMs, we project that the future 100-year flood for the study area is most likely to increase by 10–20%, with a mean increase of 13% from all 14 models. 79% of the models project increase in annual peak flow. Citation Wu, S.-Y. (2010) Potential impact of climate change on flooding in the Upper Great Miami River Watershed, Ohio, USA: a simulation-based approach. Hydrol. Sci. J. 55(8), 1251–1263. 相似文献
9.
Non‐point source (NPS) pollution from agricultural land is increasing exponentially in many countries of the world, including India. A modified approach based on the conservation of mass and reaction kinetics has been derived to estimate the inflow of non‐point source pollutants from a river reach. Two water quality variables, namely, nitrate (NO3) and ortho‐phosphate (o‐PO4), which are main contributors as non‐point source pollution, were monitored at four locations of River Kali, western Uttar Pradesh, India, and used for calibration and validation of the model. Extensive water quality sampling was done with a total of 576 field data sets collected during the period from March 1999 to February 2000. Remote sensing and geographical information system (GIS) techniques were used to obtain land use/land cover of the region, digital elevation model (DEM), delineation of basin area contributing to non‐point source pollution at each sampling location and drainage map. The results obtained from a modified approach were compared with the existing mass‐balance equations and distributed modelling, and the performances of different equations were evaluated using error estimation viz. standard error, normal mean error, mean multiplicative error and correlation statistics. The developed model for the River Kali minimizes error estimates and improves correlation between observed and computed NPS loads. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
10.
Modeling large multicomponent reactive transport systems in porous media is particularly challenging when the governing partial differential algebraic equations (PDAEs) are highly nonlinear and tightly coupled due to complex nonlinear reactions and strong solution-media interactions. Here we present a preconditioned Jacobian-Free Newton-Krylov (JFNK) solution approach to solve the governing PDAEs in a fully coupled and fully implicit manner. A well-known advantage of the JFNK method is that it does not require explicitly computing and storing the Jacobian matrix during Newton nonlinear iterations. Our approach further enhances the JFNK method by utilizing physics-based, block preconditioning and a multigrid algorithm for efficient inversion of the preconditioner. This preconditioning strategy accounts for self- and optionally, cross-coupling between primary variables using diagonal and off-diagonal blocks of an approximate Jacobian, respectively. Numerical results are presented demonstrating the efficiency and massive scalability of the solution strategy for reactive transport problems involving strong solution-mineral interactions and fast kinetics. We found that the physics-based, block preconditioner significantly decreases the number of linear iterations, directly reducing computational cost; and the strongly scalable algebraic multigrid algorithm for approximate inversion of the preconditioner leads to excellent parallel scaling performance. 相似文献
11.
A Bayesian approach to characterize the predictive uncertainty in the delineation of time-related well capture zones in heterogeneous formations is presented and compared with the classical or non-Bayesian approach. The transmissivity field is modelled as a random space function and conditioned on distributed measurements of the transmissivity. In conventional geostatistical methods the mean value of the log transmissivity and the functional form of the covariance and its parameters are estimated from the available measurements, and then entered into the prediction equations as if they are the true values. However, this classical approach accounts only for the uncertainty that stems from the lack of ability to exactly predict the transmissivity at unmeasured locations. In reality, the number of measurements used to infer the statistical properties of the transmissvity field is often limited, which introduces error in the estimation of the structural parameters. The method presented accounts for the uncertainty that originates from the imperfect knowledge of the parameters by treating them as random variables. In particular, we use Bayesian methods of inference so as to make proper allowance for the uncertainty associated with estimating the unknown values of the parameters. The classical and Bayesian approach to stochastic capture zone delineation are detailed and applied to a hypothetical flow field. Two different sampling densities on a regular grid are considered to evaluate the effect of data density in both methods. Results indicate that the predictions of the Bayesian approach are more conservative. 相似文献
12.
R. Willis B. A. Finney M. McKee A. Militello 《Stochastic Environmental Research and Risk Assessment (SERRA)》1989,3(2):71-84
A new methodology is presented for the solution of the stochastic hydraulic equations characterizing steady, one-dimensional estuarine flow. The methodology is predicated on quasi-linearization, perturbation methods, and the finite difference approximation of the stochastic differential operators. Assuming Manning's roughness coefficient is the principal source of uncertainty in the model, stochastic equations are presented for the water depths and flow rates in the estuarine system. Moment equations are developed for the mean and variance of the water depths. The moment equations are compared with the results of Monte Carlo simulation experiments. The results confirm that for any spatial location in the estuary that (1) as the uncertainty in the channel roughness increases, the uncertainty in mean depth increases, and (2) the predicted mean depth will decrease with increasing uncertainty in Manning'sn. The quasi-analytical approach requires significantly less computer time than Monte Carlo simulations and provides explicit 相似文献
13.
The main subject of the paper is to resolve the Ekman layer analytically and to formulate an appropriate set of 3D-geodynamo equations. The equations are formulated in the mean field approximation where the mean values of magnetic field and velocity over azimuthal direction vanish. This approach should allow the numerical calculation to be performed for small Ekman numbers, down to 10–12
, which are usually considered to be realistic in the geodynamo. The solution of the Ekman layer is also newly interpreted and consequently a new term appears in the usual expression for the geostrophic shear. The viscous terms are neglected in the main volume of the core and their leading role is assumed just in the thin Ekman layer. The inner core is not included in these considerations and no concrete calculations of a model are presented. 相似文献
14.
Estimating sediment transport in a braided gravel channel — The Kawerong River, Bougainville, Papua New Guinea 总被引：1，自引：0，他引：1
It is difficult to estimate sediment transport in braided rivers because of the complex hydraulics of rapidly changing multi-channel systems. This paper describes an algorithm for generating sets of braided-river hydraulic parameters for use with sediment transport equations. The algorithm uses random number-based simulation techniques and empirically determined probability distributions of individual hydraulic variables from the White River (U.S.A.) and the Kawerong River. A test of the suitability of the algorithm for the estimation of sediment transport was carried out over a period of two years using the Meyer-Peter and Muller equation on eight reaches of the Kawerong River in which sediment transport is known. The test produced a mean absolute error of 16.3% suggesting that the algorithm may have some potential in braided-river modelling. 相似文献
15.
Liu和Sen（2010和2012）在地震波场数值模拟中提出一种混合吸收边界条件. 该方法具有计算量小、容易实现及吸收效果好等优点. 但现有的混合吸收边界条件是针对二阶位移-应力方程设计的,存在稳定性问题. 本文首先推导了两种速度-应力单程波方程：二阶Higdon单程波方程和一阶Higdon单程波方程. 进而提出基于一阶弹性波方程的混合吸收边界条件方法. 在内部区域和边界之间引入一个过渡区域,通过单程波与双程波方程平滑过渡来消除人工边界反射. 为了改善混合吸收边界条件的吸收效果和稳定性,我们采用了能同时吸收纵、横波反射的一阶单程波方程和与变量位置有关的加权系数. 为了验证混合吸收边界条件的有效性,将其与常规分裂完全匹配层（PML）方法进行了比较. 数值模拟结果表明,与PML边界条件相比,混合吸收边界条件在耗用更小计算时间和存储量的前提下,可以获得更好的吸收效果. 另外,本文提出的两种混合吸收边界条件中,混合一阶Higdon吸收边界条件具有更好的稳定性. 相似文献
16.
In this article we present the modelling of uncertainty in strong-motion studies for engineering applications, particularly
for the assessment of earthquake hazard. We examine and quantify the sources of uncertainty in the basic variables involved
in ground motion estimation equations, including those associated with the seismological parameters, which we derive from
a considerable number of strong-motion records. Models derived from regression analysis result in ground motion equations
with uncertain parameters, which are directly related to the selected basic variables thus providing an uncertainty measure
for the derivative variable. These uncertainties are exemplified and quantified. An alternative approach is presented which
is based on theoretical modelling defining a functional relationship on a set of independent basic variables. Uncertainty
in the derivative variable is then readily obtained when the uncertainties of the basic variables have been defined. In order
to simplify the presentation, only the case of shallow strike-slip earthquakes is presented. We conclude that the uncertainty
is approximately the same as given by the residuals typical for regression modelling. This implies that uncertainty in ground
motion modelling cannot be reduced below certain limits, which is in accordance with findings reported in the literature.
Finally we discuss the implications of the presented methodology in hazard analyses, which is sensitive to the truncation
of the internal error term, commonly given as an integral part of ground motion estimation equations. The presented methodology
does not suffer from this shortcoming; it does not require truncation of the error term and yields realistic hazard estimates.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
17.
Abstract A two-stage formal approach to hydrological model conceptualization is described. The approach requires the definition of hydrological variables in terms of states and rates, the construction of state-rate diagrams and the definition of equations for the rates based on an indepth understanding of the related hydrological processes. It is inferred that the approach can help modellers arrive at models which are conceptually more feasible for operational use and for theoretical studies. STELLA, a programme specifically designed to facilitate model conceptualization using this approach, is also briefly described. The use of the two stage formal approach with STELLA will be an excellent teaching tool for hydrological modelling. 相似文献
18.
A stochastic approach to nonlinear unconfined flow subject to multiple random fields 总被引：3，自引：3，他引：0
Liangsheng Shi Jinzhong Yang Dongxiao Zhang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(6):823-835
In this study, the KLME approach, a moment-equation approach based on the Karhunen–Loeve decomposition developed by Zhang
and Lu (Comput Phys 194(2):773–794, 2004), is applied to unconfined flow with multiple random inputs. The log-transformed hydraulic conductivity F, the recharge R, the Dirichlet boundary condition H, and the Neumann boundary condition Q are assumed to be Gaussian random fields with known means and covariance functions. The F, R, H and Q are first decomposed into finite series in terms of Gaussian standard random variables by the Karhunen–Loeve expansion. The
hydraulic head h is then represented by a perturbation expansion, and each term in the perturbation expansion is written as the products of
unknown coefficients and Gaussian standard random variables obtained from the Karhunen–Loeve expansions. A series of deterministic
partial differential equations are derived from the stochastic partial differential equations. The resulting equations for
uncorrelated and perfectly correlated cases are developed. The equations can be solved sequentially from low to high order
by the finite element method. We examine the accuracy of the KLME approach for the groundwater flow subject to uncorrelated
or perfectly correlated random inputs and study the capability of the KLME method for predicting the head variance in the
presence of various spatially variable parameters. It is shown that the proposed numerical model gives accurate results at
a much smaller computational cost than the Monte Carlo simulation. 相似文献
19.
While the chemical structure of the earth's mantle is probably rather complex, multi-box models have been used as a first approximation to evaluate this structure. Most commonly, a three-box model is used, involving the continental crust, the upper mantle and the lower mantle. The depleted upper mantle and the continental crust are assumed to represe1nt complementary reservoirs, related by crust formation processes occurring during geologic history.Here we investigate the Rb/Sr and Sm/Nd isotopic systematics of several three-box models, using mass balance equations and the definition of the mean age of the reservoirs. The geochemical uniqueness of the models, chosen from a large family of possible models, is evaluated from elementary graph theory, and these models are then solved using a total inversion approach. This paper (Part I) describes the methodology of the procedure; the companion paper (Part II) discusses the application of this approach to multi-box mantle models. 相似文献
20.
Modeling of flow and transport in environmental systems often involves formulation of conservation equations at spatial scales involving tens to hundreds of pore diameters in porous media or the depth of flow in a channel. Quantities such as density, temperature, internal energy, and velocity may not be uniform over these macroscopic length scales. The external gravitational potential causes gradients in density, pressure, and chemical potential even at equilibrium. Despite these complications, it is important to formulate the thermodynamic analysis of environmental systems at the macroscopic scale. Heretofore, this has been accomplished primarily using the approach of rational thermodynamics whereby the thermodynamic dependence of macroscale internal energy on macroscale variables is hypothesized directly without development of any systematic method for transforming microscale energy dependence from the microscale to the macroscale. However when thermodynamic variables are inhomogeneous at the microscale, the functional dependence of macroscale internal energy on macroscale variables is not a simple extension of the microscale case. In the present work, the relation between the definitions of microscale and macroscale intensive thermodynamic variables is established. Expressions for the material derivatives of macroscale internal energy of phases, interfaces, and common lines are derived from and consistent with their microscopic counterparts by integrating to the macroscale. The forms obtained and the consistency required will be important for use in analyses of systems at scales where microscopic heterogeneities cannot be neglected. 相似文献