Numerical simulation of a stratigraphic model

A multi-lithology diffusive stratigraphic model is considered, which simulates at large scales in space and time the infill of sedimentary basins governed by the interaction between tectonics displacements, eustatic variations, sediment supply, and sediment transport laws. The model accounts for the mass conservation of each sediment lithology resulting in a mixed parabolic, hyperbolic system of partial differential equations (PDEs) for the lithology concentrations and the sediment thickness. It also takes into account a limit on the rock alteration velocity modeled as a unilaterality constraint. To obtain a robust, fast, and accurate simulation, fully and semi-implicit finite volume discre tization schemes are derived for which the existence of stable solutions is proved. Then, the set of nonlinear equations is solved using a Newton algorithm adapted to the unilaterality constraint, and preconditioning strategies are defined for the solution of the linear system at each Newton iteration. They are based on an algebraic approximate decoupling of the sediment thickness and the concentration variables as well as on a proper preconditioning of each variable. These algorithms are studied and compared in terms of robustness, scalability, and efficiency on two real basin test cases.     

A variable precision rough set approach to knowledge discovery in land cover classification

This paper presents a granular computing approach to spatial classification and prediction of land cover classes using rough set variable precision methods. In particular, it presents an approach to characterizing large spatially clustered data sets to discover knowledge in multi-source supervised classification. The evidential structure of spatial classification is founded on the notions of equivalence relations of rough set theory. It allows expressing spatial concepts in terms of approximation space wherein a decision class can be approximated through the partition of boundary regions. The paper also identifies how approximate reasoning can be introduced by using variable precision rough sets in the context of land cover characterization. The rough set theory is applied to demonstrate an empirical application and the predictive performance is compared with popular baseline machine learning algorithms. A comparison shows that the predictive performance of the rough set rule induction is slightly higher than the decision tree and significantly outperforms the baseline models such as neural network, naïve Bayesian and support vector machine methods.     

Singularly perturbed solution of coupled model in atmosphere-ocean for global climate

A box model of the interhemispheric thermohaline circulation （THC） in atmosphere-ocean for global climate is considered. By using the multi-scales method, the asymptotic solution of a simplified weakly nonlinear model is discussed. Firstly, by introducing first scale, the zeroth order approximate solution of the model is obtained. Secondly, by using the multi-scales, the first order approximate equation of the model is found. Finally, second order approximate equation is formed to eliminate the secular terms, and a uniformly valid asymptotic expansion of solution is decided. The multi-scales solving method is an analytic method which can be used to analyze operation sequentially. And then we can also study the diversified qualitative and quantitative behaviors for corresponding physical quantities. This paper aims at providing a valid method for solving a box model of the nonlinear equation.     

Uncertainty representation of ocean fronts based on fuzzy-rough set theory

Analysis of ocean fronts' uncertainties indicates that they result from indiseemibility of their spatial position and fuzzi-ness of their intensity. In view of this, a flow hierarchy for uncertainty representation of ocean fronts is proposed on the basis of fuzzy-rough set theory. Firstly, raster scanning and blurring are carried out on an ocean front, and the upper and lower approximate sets, the indiscernible relation in fuzzy-rough theories and related operators in fuzzy set theories are adopted to represent its uncer-tainties, then they are classified into three sets: with members one hundred pereent belonging to the ocean front, belonging to the ocean front's edge and definitely not belonging to the ocean front. Finally, the approximate precision and roughness degree are util-ized to evaluate the ocean front's degree of uncertainties and the precision of the representation. It has been proven that the method is not only capable of representing ocean fronts' uncertainties, but also provides a new theory and method for uncertainty representation of other oceanic phenomena.     

风机基础TLP平台在波浪中运动性能的CFD数值分析

随着海上风能的开发向深水发展,支撑风机的载体平台越来越受到关注。在经济性与安全性、稳定性的多重要求下,张力腿平台（TLP）在海洋风能资源的开发中体现出了重要地位。采用基于开源平台OpenFOAM开发的计算流体动力学（CFD）水动力学求解器naoe-FOAM-SJTU对一座处于中等水深下的风机基础水下TLP（STLP）的运动响应进行了数值模拟与研究。文中使用弹簧锚链模型模拟STLP的垂向系泊锁链系统,模拟该平台在不同波浪环境下的运动响应情况。首先将STLP单自由度自由衰减CFD模拟结果与已有全耦合时域分析结果进行对比,验证了naoe-FOAM-SJTU求解器及使用弹簧模型模拟STLP系泊系统的准确性与可靠性。随后在考虑非线性波浪载荷的情况下研究极端海况下与一般作业海况下STLP的运动响应情况,计算工况中的风机基础所受弯矩及锚链受力情况,并详细展示流场、速度场信息,分析高阶波浪成分、不同海况等条件对于STLP运动性能的影响。研究结果表明,TLP在中等水深中具有良好的运动性能,naoe-FOAM-SJTU求解器可以有效模拟水中生产平台在波浪环境下的水动力问题,并可以对整个流场进行可视化展示与分析。     

微扰Kepler系统轨道微分方程的近似Lie对称性与近似不变量

把极角θ视为独立变量,得到Kepler系统的轨道微分方程. 首先讨论Kepler系统轨道微分方程的Lie对称性和不变量,微扰Kepler系统轨道微分方程的精确Lie对称性和精确不变量,其次讨论微扰Kepler系统轨道微分方程的近似Lie对称性和近似不变量,并得到了微扰Kepler系统的9个一阶近似Lie对称性和6个一阶近似不变量,其中1个实为精确不变量,而其余5个分别等于微扰系数ε乘以Kepler系统相应的5个不变量.     

Investigation of highly efficient algorithms for solving linear equations in the discontinuous deformation analysis method

Large‐scale engineering computing using the discontinuous deformation analysis (DDA) method is time‐consuming, which hinders the application of the DDA method. The simulation result of a typical numerical example indicates that the linear equation solver is a key factor that affects the efficiency of the DDA method. In this paper, highly efficient algorithms for solving linear equations are investigated, and two modifications of the DDA programme are presented. The first modification is a linear equation solver with high efficiency. The block Jacobi (BJ) iterative method and the block conjugate gradient with Jacobi pre‐processing (Jacobi‐PCG) iterative method are introduced, and the key operations are detailed, including the matrix‐vector product and the diagonal matrix inversion. Another modification consists of a parallel linear equation solver, which is separately constructed based on the multi‐thread and CPU‐GPU heterogeneous platforms with OpenMP and CUDA, respectively. The simulation results from several numerical examples using the modified DDA programme demonstrate that the Jacobi‐PCG is a better iterative method for large‐scale engineering computing and that adoptive parallel strategies can greatly enhance computational efficiency. Copyright © 2015 John Wiley & Sons, Ltd.     

Three dimensional velocity structure beneath the Kunming Telemetered Seismic Network

Ｔｈｒｅｅ　ｄｉｍｅｎｓｉｏｎａｌ　ｖｅｌｏｃｉｔｙ　ｓｔｒｕｃｔｕｒｅ　ｂｅｎｅａｔｈ　ｔｈｅ　Ｋｕｎｍｉｎｇ　Ｔｅｌｅｍｅｔｅｒｅｄ　Ｓｅｉｓｍｉｃ　Ｎｅｔｗｏｒｋ（王椿镛）（王溪莉）（颜其中）Ｔｈｒｅｅｄｉｍｅｎｓｉｏｎａｌｖｅｌｏｃｉｔｙｓｔ...     

p—范分布的近似表示

p-范分布是一个包含拉普拉斯分布、正态分析、均匀分布等常见分布的分布族。用p-范分布描述观测误差的统计特性，只需假定误差的分布为单峰、对称，因此、p-范分布似然平差可以避免事先假定误差的具体分布模式，而在平差过程中确定未知参数及误差的分布具有自适应的特点。但是p-范分布的密度函数比较复杂，不利于理论分析和实际应用。 的研究表明，p-范分布可以近似地表示为拉普拉斯分布与正态分析或正态分布均均匀分布的线性组全。p-范分布与本文给出的近似分布具有相的前四阶矩。由于拉普拉斯分布。正态分布。均匀分布的密度函数都比较简单，用近似分布代替p-范分布会使相关的问题得到简化。     

双线偏振雷达的降水估测Ⅰ. 排序配对逼近法

提出使用新的途径──排序配对逼近法得出的双线偏振雷达降水估测ＺＲ关系参数因子比线性拟合法具有更好的代表性,且能体现提高区域降水估测精度,也能根据实际情形采用其它的误差类型作为获取及衡量参数的标准。对指数函数形式的ＺＲ关系来说,其参数因子Ａ０,ＡＨ及ＡＤＲ分别为０．０１６８４,０．０９６和－０．４１６５。该方法可以推广应用到多个变元及参数因子的复杂函数中。