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1.
地下水补给对河流水质模型的影响 总被引：1，自引：0，他引：1
以经典的一维水质模型及其解为基础,将地下水对河流的补给作用作为河流水质模型的一项影响因子,利用迭加原理,给出受到沿途地下水补给影响下的河流水质模型的解析解.利用这一新解析解,定量研究地下水补给作用对河流水质模型参数的影响规律.地下水渗出(相当于一点污染源)进入河流后,在随河水向下游运移的过程中,其水质浓度也将发生衰减."连续线源"对河流水体中溶质衰减过程的影响,不简单等同于几个"点源"的迭加.含水层与河流间水量交换作用,更宜用"连续线源"去刻画.以颖河为例,河流两岸潜水补给对河流水质模拟计算的影响程度研究表明,地下水补给对河流溶质沿河变化规律的影响,理论上不能用"综合衰减系数k值"简单反映,而且它对k值计算影响相当大. 相似文献
2.
针对随机游走水质模型仅考虑污染物对流输移、扩散效应而忽略污染物降解作用的缺陷,基于可降解污染物的一级反应动力学假设,对现有的随机游走水质模式进行了改进,建立了考虑自净作用的二维随机游走水质模型.作为模型检验,构造典型案例,将改进的随机游走模型计算结果与二维对流分散方程的解析解进行了对比分析,模拟结果表明改进的随机游走水质模式与解析解具有一致性.改进的随机游走模型具有既可考虑水污染物的降解特性,又能够形象直观地描述污染物迁移特征的优点. 相似文献
3.
本文介绍了一种求一维水质弥散参数的新方法——半对数配线法。该方法计算简便、适用性强且具有较高的精度。 相似文献
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依据干旱地区河流水文、水力特性,合理简化对流扩散方程,给出瞬时突然排污条件下的动态解析解.建立了有干旱地区特点的、含有碳化BOD5、氨氮和溶解氧三水质要素的河流水质模型,推导出水质模拟矩阵,并应用于新疆乌鲁木齐地区水磨河动态水质模拟计算. 相似文献
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在有限体积法框架下应用通量向量分裂(FVS)格式进行平面二维水流 水质模拟。通过对偏微分方程进行有限体积的积分离散、利用通量的旋转不变性,把二维问题转化为一系列局部的一维问题进行求解,采用FVS格式计算各跨单元边界的水量、动量及污染物输运等通量。应用该格式计算了理想条件下的浓度输移,其结果与精确解拟合很好;模拟了长江江苏靖江段的水质及污染带,计算结果与水质监测值相当吻合,为长江江苏干流段水质评价提供了科学依据。 相似文献
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根据研究工程、工业废水及生活污水的水环境影响的需要,提出一个平面二维水流-水质有限体积法及黎曼近似解模型。在无结构网格上对偏微分方程进行有限体积的积分离散,把二维问题转化为一系列局部的一维问题进行求解,模型具备有限单元法及有限差分法两者的优点。由于模型采用黎曼近似解计算水量、动量及污染物输运等通量,不仅提高了数值模拟的精度,而且能模拟包括恒定、非恒定或急流、缓流等水流-水质状态。应用若干理想条件下的精确解对模型精度进行了检验,并结合汉江中下游的水质问题验证了模型的实际应用能力。模型计算结果与精确解拟合极好,与汉江中下游实测的污染分布带也相当吻合,为中线南水北调对汉江中下游水质的影响评价提供了依据。 相似文献
9.
改进模拟退火法在估计河流水质参数中的应用 总被引：3，自引：0，他引：3
将模拟退火法应用于求解分析河流水团示踪试验数据，确定河流水质参数的函数优化问题。针对标准SA算法收敛速度缓慢的弱点，采取了增加附加约束条件、设置内阈值提前降温和增加记忆功能等综合措施对算法进行了改进。算例表明，综合改进措施能够明显地提高算法收敛速度，并可以得到满意的参数计算结果。计算结果也表明，内循环次数不会对外循环次数产生明显的影响。由于算法对目标函数没有附加要求，而且算法的收敛性与待估参数的初值无关，因此，改进SA算法在分析河流水质试验数据、确定水质参数方面．将会具有非常广的应用范围。 相似文献
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Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system 总被引：3，自引：0，他引：3
The aim of this study is to predict the peak particle velocity (PPV) values from both presently constructed simple regression
model and fuzzy-based model. For this purpose, vibrations induced by bench blasting operations were measured in an open-pit
mine operated by the most important magnesite producing company (MAS) in Turkey. After gathering the ordered pairs of distance
and PPV values, the site-specific parameters were determined using traditional regression method. Also, an attempt has been
made to investigate the applicability of a relatively new soft computing method called as the adaptive neuro-fuzzy inference
system (ANFIS) to predict PPV. To achieve this objective, data obtained from the blasting measurements were evaluated by constructing
an ANFIS-based prediction model. The distance from the blasting site to the monitoring stations and the charge weight per
delay were selected as the input parameters of the constructed model, the output parameter being the PPV. Valid for the site,
the PPV prediction capability of the constructed ANFIS-based model has proved to be successful in terms of statistical performance
indices such as variance account for (VAF), root mean square error (RMSE), standard error of estimation, and correlation between
predicted and measured PPV values. Also, using these statistical performance indices, a prediction performance comparison
has been made between the presently constructed ANFIS-based model and the classical regression-based prediction method, which
has been widely used in the literature. Although the prediction performance of the regression-based model was high, the comparison
has indicated that the proposed ANFIS-based model exhibited better prediction performance than the classical regression-based
model. 相似文献
12.
Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region. 相似文献
13.
An integrated analysis about computational time complexity of the Local Ensemble Transform Kalman Filter (LETKF) was performed. It is found that the calculation step of inverse matrix of the error covariance in ensemble space is the most computationally intensive and time consuming. In a parallel computing environment, the uneven distribution of CPU calculations in this step directly leads to low computational efficiency. To solve this problem, a new load balancing strategy was designed based on the "greedy algorithm". A high-performance parallel ocean data assimilation system based on the LETKF was developed and tested using this strategy. This system was based on the Parallel Ocean Program 2 (POP2) of the Community Earth System Model (CESM). The optimal interpolated sea surface temperature data (OISST) and Argo temperature profile data from January to February, 2004 were assimilated into the POP2. The results show that data assimilation effectively reduces the root mean square error of temperature and salinity. Using the new strategy, the exact same results are obtained but the computation time is reduced by half. At higher resolution (0.1°×0.1°),the computing performance is still doubled, indicating that this load balancing scheme is stable and reliable. In addition, the new method has high scalability and portability with great potential to be applied in operational forecasting. 相似文献
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通过对局地集合变换卡尔曼滤波(LETKF)算法的计算时间复杂度的完整分析,发现计算集合空间分析场误差协方差的逆矩阵这一过程计算量最大,耗时最长。且在并行计算环境下,该步骤CPU计算量分配不均是影响计算效率的直接原因。为解决这一问题,采用“贪心算法”设计了一套新的负载均衡策略,并使用该策略开发了一个基于LETKF和并行海洋模块2(POP2)的高性能并行海洋资料同化系统。将2004年1~2月日平均的最优插值海表温度资料(OISST)和同时期的Argo温盐剖面资料同化进入POP2。结果表明,同化有效降低了温度和盐度的均方根误差。同时,在不改变计算结果的前提下,相比原始同化系统,新系统计算性能提升1倍。在更高分辨率(0.1°×0.1°)下,该系统的计算性能仍然可以提升1倍,说明新设计的负载均衡方案稳定可靠。该方案具有很强的可扩展性和移植性,在业务预报中有广泛的应用前景。 相似文献
15.
中国地质调查局用了近10年时间,在基础地质调查和矿产调查领域基本完成了地质调查全流程数字化过程。在"云"计算与大数据技术等新一代信息技术的兴起大环境下,未来5至10年,地质调查主流程信息化的方向和目标是什么呢?本文基于新一代信息智能技术和智能设备在地质调查数据采集、数据分析处理、数据交换传输、三维建模、信息泛在服务、业务管理全面深度融合的基础上,结合智能空间与普适计算概念给出了智能地质调查定义,提出了基于云计算和Hadoop生态体系为基础的天地空一体化的智能地质调查体系、架构和应用模式,并对其关键技术进行了讨论。 相似文献
16.
Lin Jun 《吉林大学学报(地球科学版)》1989,(4)
本文根据最新发展的个人仪器理论,讨论了在微机地学仪器设计中如何利用软件算法消除测量误差,实现传感器的非线性校正、数据平滑、信号分析与信息变换等方法技术,某些方法技术引用了笔者的微机地学仪器设计实例加以说明。 相似文献
17.
In this paper, analytical methods, artificial neural network (ANN) and multivariate adaptive regression splines (MARS) techniques were utilised to estimate the discharge capacity of compound open channels (COC). To this end, related datasets were collected from literature. The results showed that the divided channel method with a coefficient of determination (R 2) value of 0.76 and root mean square error (RMSE) value of 0.162 has the best performance, among the various analytical methods tested. The performance of applied soft computing models with R 2=0.97 and RMSE = 0.03 was found to be more accurate than analytical approaches. Comparison of MARS with the ANN model, in terms of developed discrepancy ratio (DDR) index, showed that the accuracy of MARS model was better than that of MLP model. Reviewing the structure of the derived MARS model showed that the longitudinal slope of the channel (S), relative flow depth (H r ) and relative area (A r ) have a high impact on modelling and forecasting the discharge capacity of COCs. 相似文献
18.
Hector A. Duran-Limon Jesus Flores-Contreras Nikos Parlavantzas Ming Zhao Angel Meulenert-Peña 《Earth Science Informatics》2016,9(3):365-382
There are many scientific applications that have high performance computing (HPC) demands. Such demands are traditionally supported by cluster- or Grid-based systems. Cloud computing, which has experienced a tremendous growth, emerged as an approach to provide on-demand access to computing resources. The cloud computing paradigm offers a number of advantages over other distributed platforms. For example, the access to resources is flexible and cost-effective since it is not necessary to invest a large amount of money on a computing infrastructure nor pay salaries for maintenance functions. Therefore, the possibility of using cloud computing for running high performance computing applications is attractive. However, it has been shown elsewhere that current cloud computing platforms are not suitable for running some of these kinds of applications since the performance offered is very poor. The reason is mainly the overhead from virtualisation which is extensively used by most cloud computing platforms as a means to optimise resource usage. Furthermore, running HPC applications in current cloud platforms is a complex task that in many cases requires configuring a cluster of virtual machines (VMs). In this paper, we present a lightweight virtualisation approach for efficiently running the Weather Research and Forecasting (WRF) model (a computing- and communication-intensive application) in a cloud computing environment. Our approach also provides a higher-level programming model that automates the process of configuring a cluster of VMs. We assume such a cloud environment can be shared with other types of HPC applications such as mpiBLAST (an embarrassingly parallel application), and MiniFE (a memory-intensive application). Our experimental results show that lightweight virtualisation imposes about 5 % overhead and it substantially outperforms traditional heavyweight virtualisation such as KVM. 相似文献
19.
波动方程叠前深度偏移在地震勘探成像处理方面起着不可替代的作用。随着高性能大规模并行计算机技术的发展,波动方程叠前深度偏移计算在地震勘探中的应用有了很大进步。在波动方程叠前深度偏移处理中,庞大的数据规模与海量计算对计算性能提出了很高的要求。曙光4000A超级计算机系统是我国目前峰值速度最快的商用超级计算机系统,无论是硬件平台建设还是应用软件的配置方面,都具有良好的应用性能。基于该系统设计的三维波动方程叠前深度偏移(炮域)PSDM软件,采用动态负载平衡并行计算模式,具有较高的计算效率,高度的可扩展性和可靠性。 相似文献
20.
A systematic analysis ofmethods for computing the trajectories of solid-phase particles applied in modern astrophysics codes designed for modeling gas–dust circumstellar disks has been carried out for the first time. Themotion of grains whose velocities are determinedmainly by the gas drag, that is, for which the stopping time or relaxation time for the velocity of the dust to the velocity of the gas tstop is less than or comparable to the rotation period, are considered. The methods are analyzed from the point of view of their suitability for computing the motions of small bodies, including dust grains less than 1 μm in size, which are strongly coupled to the gas. Two test problems are with analytical solutions. Fast first order accurate methods that make it possible to avoid additional restrictions on the time step size τ due to gas drag in computations of the motion of grains of any size are presented. For the conditions of a circumstellar disk, the error in the velocity computations obtained when using some stable methods becomes unacceptably large when the time step size is τ > tstop. For the radial migration of bodies that exhibit drifts along nearly Keplerian orbits, an asymptotic approximation, sometimes called the short friction time approximation or drift flux model, gives a relative error for the radial-velocity computations equals to St2, where St is the Stokes number, the ratio of the stopping time of the body to some fraction of the rotation period (dynamical time scale) in the disk. 相似文献