Flume experiments to study fine-grain migration and its impact on slope stability

Fine grains migration is a primary cause of landslides and debris flows.This study investigates the effect of fine-grain migration on slope failure through flume experiments,focusing on the spatiotemporal characteristics and mechanisms of slope stability.A series of artificial rainfall flume experiments with varying rainfall intensities and slopes were conducted using soil samples collected from Wei Jia Gully.The experiments monitored pore-water pressure,grain migration,and failure sequences.Grain-size distribution parameters(μand Dc)were analyzed to understand the migration path and accumulation of fine grains.The experiments reveal that fine-grain migration significantly alters soil structure,leading to random blockage and interconnection of internal pore channels.These changes result in fluctuating pore-water pressure distributions and uneven fine-grain accumulation,critical factors in slope stability.Slope failures occur randomly and intermittently,influenced by fine-grain content in runoff and resulting pore-water pressure variations.This study highlights that fine-grain migration plays a vital role in slope stability,with significant implications for predicting and mitigating slope failures.The stochastic nature of fine-grain migration and its impact on soil properties should be incorporated into predictive models to enhance their accuracy and reliability.

基于Flume的分布式日志采集分析系统设计与实现

互联网的迅猛发展以及大数据相关技术的兴起,使得日志数据的规模日益剧增,给已有的日志采集及分析系统带来了挑战;同时针对互联网安全的攻击活动也层出不穷,如何在海量的日志中及时提取有效的信息以为企业安全提供信息支撑,也给现有的分析系统提出了新的需求。本文结合使用Flume、Elasticsearch以及Kibana等技术手段提出了一种分布式的日志采集分析系统,从系统设计和架构等方面提出了新的解决思路,并针对Nginx的访问日志进行了实时采集和分析及展示,完成了原型系统的实现,实验证明,基于Flume的分布式的日志采集分析系统方案具有可行性。

基于Flume的MySQL数据自动收集系统

针对分布式系统中、不同数据中心之间的数据收集,同时解决将数据由关系型数据库交换到非关系型数据库的问题,提出一种基于Flume的MySQL数据库数据自动收集系统。为了符合现实中的生产环境,该系统采用的是一种星型拓扑结构。系统可以自动查询给定的MySQL数据库表,自动检测表中的数据更新,实现自动增量传输,并对原始数据进行封装、解析,最终将数据存储到非关系型数据库HBase中。在测试中,系统中每台机器的平均传输速度可达到1 111 kb/s,系统总的平均传输速度可以达到3 333 kb/s,并且保证了数据的完整性,实现了可靠高效传输的目标。

基于Flume的网络安全可视化系统

随着互联网使用者的快速增长,网络安全问题也不断增多.传统的基于日志的入侵检测系统在处理海量信息时存在着实时性不足,认知负担过重等缺点.本文提出了一种基于Flume的网络安全日志可视化方法,利用Flume处理日志信息的高效性,实时收集网络安全日志,结合数据可视化方法,挖掘隐藏的网络异常信息.与传统的基于数据库存储的安全分析相比,提高了数据处理的实时性,能够更直观的展现网络网络异常.

基于Apache Flume的分布式日志收集系统设计与实现

基于Apache Flume的开源日志收集系统,设计并实现了一个适用于异构网站平台间的分布式日志收集系统。该系统将多个网站的日志集中存储,为进行下一步的日志分析提供了数据支持,也为云平台下的网站日志收集方案提供了参考依据。

基于Apache Flume的大数据日志收集系统

在信息化及大数据时代下,各种应用程序的分散及生成的日志信息成爆炸式增长,怎么有效的收集这些日志,并对它进行在线和离线分析,已经成为这领域的热点。我们在现有的Apache Flume、Hadoop等框架下,设计实现了一种大数据日志收集系统。

基于改进的Flume实时数据采集系统应用研究

通过对Apache Flume日志采集系统的实时数据采集方案进行比较,并针对Flume现有的实时数据采集方案进行分析,提出了一种基于Flume改进的实时数据采集方案。实验证明,改进后的实时数据采集方案具有可行性。

Flume系统的隐蔽信道搜索问题研究

Flume系统不仅可以为处于不同安全级别的进程传输信息提供安全保障,还可以通过显式标签机制解决在隐式标签系统中进程间通信连接超时导致的隐蔽信道问题.但是其系统中的部分不合理标签分配机制可能会导致信息在传递过程中同样存在泄露问题.针对这个问题提出一种隐蔽信道搜索模型(covert channel detection model,CCDM),将隐蔽信道的搜索问题抽象为有向图联通问题.最后结合回溯算法的思想提出IniaPathSearch算法和QuickPathSearch算法来对隐蔽信道进行自动搜索.实验结果表明,IniaPathSearch算法和QuickPathSearch算法可以正确有效地对Flume系统中隐蔽信道进行检测,并能为信息传递提供合法最短路径,其结果可以用于指导提高系统的安全性.

基于改进的Flume的实时数据采集系统

任意一个分布式系统都必须满足CAP理论,在数据分析分析系统中,最为重要的是效率以及可靠性,而数据采集时整个分析系统的基石,构建基于改进的Flume的实时数据采集系统,通过Flume采集数据,采用复合型Channel与Flume相结合,在保证数据源的丰富性和可靠性的前提下,提高采集的效率。实验结果表明,该系统的各项功能符合预期结果,Flume使用复合型Channel可以提高采集效率。

基于Flume的XML数据自动收集系统

针对分布式系统中的数据收集,提出了一种基于Flume的XML数据自动收集系统。根据实际需求,系统设计了一种新型的多层星状拓扑结构,以满足数据收集实时性的要求。该系统能够自动检测指定存储位置的XML数据更新,解析XML文本后存储到HBase数据库中。在测试中,该系统中各机器的平均处理速度能够达到550 Kb/s,系统总处理平均速度能够达到1 650 Kb/s。

A two-dimensional numerical wave flume based on SA-MPLS method

A spatially adaptive (SA) two-dimensional (2-D) numerical wave flume is presented based on the quadtree mesh system,in which a new multiple particle level set (MPLS) method is proposed to solve the problem of interface tracking,in which common intersection may be traversed by multiple interfaces.By using the adaptive mesh technique and the MPLS method,mesh resolution is updated automatically with time according to flow characteristics in the modeling process with higher resolution around the free surface and the solid boundary and lower resolution in less important area.The model has good performance in saving computer memory and CPU time and is validated by computational examples of small amplitude wave,second-order Stokes wave and cnoidal wave.Computational results also indicate that standing wave and wave overtopping are also reasonably simulated by the model.

基于Apache Flume的MR数据采集实现方案

为用户提供高质量的网络覆盖是运营商不变的追求,随着4G业务的发展,作为网络质量分析重要依据的MR数据的数据体量也呈现出井喷式的增长势头。传统的以FTP技术为基础的MR数据采集方案面对越来越高的数据量显得力不从心。针对MR数据采集的业务场景,提出了基于Flume技术的数据采集实现方案,并针对海量数据的运行环境现行方案进行了对比。

Flume simulation of wave-induced release of internal dissolved nitrogen in Taihu Lake,China

A wave flume simulator was used to study internal nitrogen release from the surface sediment collected from Taihu Lake, China. Particulate nitrogen concentrations were positively correlated with the concentrations of suspended solids, primarily from surface erosion related to the shear stress and duration of wave action. In response to 4 cm- and 10 cm-high wave production representing waves generated in Taihu Lake by gentle and gusty winds, respectively, the mean dynamic release rate of ammonium （NH4＋） from the sediment to the overlying water was 1 × 10-3 mg/（m2.s） and the NH4＋ concentration in the overlying water increased by 0.016 mg/L, indicating that waves resulting from strong wind can induce the rapid release of dissolved nitrogen from Taihu Lake sediments. The decrease in interstitial NH4＋ concentrations at all sediment depths was associated with an increase in NH4＋ concentrations in the overlying water by 0.01 mg/L, showing that sediment below the eroded layer was the main source of internal nitrogen release. Changes in the interstitial dissolved oxygen and NH4＋ concentrations showed that wave-induced pore water movement can greatly increase the diffusion rate, and that these 15 cm. Diffusion induced by pore water movement sediment layer in Taihu Lake. effects can influence the sediment to a depth of at least may be very important for the formation of an active

Flume experimental study on evolution of a mouth bar under interaction of floods and waves

Based on the characteristics of hydrodynamics and sediment transport in the bar area in the Modaomen Estuary,a flume experiment was performed to study the evolution of the longitudinal profile of the mouth bar.The mouth bar evolution was investigated under the impacts of floods with different return periods as well as flood-wave interaction.The results showed that floods with different return periods had significant influences on the evolution of the river mouth bar.Particularly on the inner slope of the mouth bar,the sediment was substantially active and moveable.The inner slope and the bar crest tended to be remarkably scoured.The erosion was intensified with the increase of the magnitude of floods.Moreover,the bar crest moved seawards,while the elevation of the bar crest barely changed.Under the flood-wave interaction,a remarkable amount of erosion on the inner and outer slopes of the mouth bar was also found.The seaward displacement of the bar crest under the interaction of floods and waves was less than it was under only the impact of floods,while more deposition was found on the crest of the mouth bar in this case.

基于Ansible和Flume的海量数据自动化采集系统

随着国产数据库技术的发展,电网企业对相应数据库及中间件的应用逐步增多,业务中产生的大量的运维信息对国产数据库的自动化运维技术要求也随之提高。针对国产数据库和中间件产生的海量运维数据和日志,文中提出一种基于Ansible和Flume的高效数据采集系统。该系统通过调用Python脚本的方式定期从Ansible Inventory中拉取各主机的运行状态信息,同时由Flume配置采集agent到各数据库和中间件服务器中,进行日志数据的采集、预处理和下放,并将数据输出到数据库中,实现对数据库和中间件运行数据的自动化采集与管理。经系统测试,该系统可以高效完成多线程Web访问,并在数据采集方面表现出良好的性能。

基于Flume的分布式日志聚合系统的研究

互联网的迅猛发展以及大数据相关技术的兴起,使得日志数据的规模日益剧增,给已有的日志采集及分析系统带来了挑战;本文结合使用Flume、Elasticsearch以及Kibana等技术手段提出了一种分布式的日志采集分析系统,从系统设计和架构等方面提出了新的解决思路,并针对Flume的访问日志进行了实时采集和分析及展示。

一种基于Flume的海量数据分流方案

随着各类业务系统接入数据量的爆炸式增长,传统的基于负载均衡器的数据分流方案已无法满足海量数据业务场景的要求。介绍了一种适用于大数据场景下的负载均衡方案,并讨论了和传统方式相比所具备的主要优势。

Sedimentary characteristics and internal architecture of a river-dominated delta controlled by autogenic process:implications from a flume tank experiment

Autogenic processes are widely found in various sedimentary systems and they play an important role in the depositional evolution and corresponding sedimentary architecture.However,autogenic processes are often affected by changing allogenic factors and are difficult to be identified and analyzed from modern and ancient records.Through the flume tank experiment under constant boundary conditions,the depositional process,evolution principles,and the sedimentary architecture of a river-dominated delta was presented,and a corresponding sedimentary architecture model was constructed.The evolution of river-dominated delta controlled only by autogenic process is obviously periodic,and each autogenic cycle can be divided into an initial progradational stage,a middle retrogratational stage,and a late aggradational–progradational stage.In the initial progradational stage,one feeder channel incised into the delta plain,mouth bar(s)was formed in front of the channel mouth,and small-scale crevasse splays were formed on the delta plain.In the middle retrogradational stage,the feeder channel was blocked by the mouth bar(s)which grew out of water at the end of the initial stage,and a set of large-scale distributary splay complexes were formed on the delta plain.These distributary splay complexes were retrogradationally overlapped due to the continuous migration of the bifurcation point of the feeder channel.In the late aggradational–progradational stage,the feeder channel branched into several radial distributary channels,overlapped distributary channels were formed on the delta plain,and terminal lobe complexes were formed at the end of distributary channels.The three sedimentary layers formed in the three stages constituted an autogenic succession.The experimental delta consisted of six autogenic depositional successions.Dynamic allocation of accommodation space and the following adaptive sediments filling were the two main driving factors of the autogenic evolution of deltas.

基于Flume、Kafka的日志采集系统分析研究

本文对数据采集工具flume、Kafka进行简单介绍、分析研究和应用,对flume+Kafka的组合优势和原理进行阐述分析。本文通过多种flume和Kafka组件种类的组合,在日志采集系统上的应用进行了分析,并对channel组件吞吐速率和容错率之间的矛盾进行讨论研究。数据采集已成为大数据产业的重要组成部分,而日志文件逐渐成为数据分析的主要来源之一。日志文件生成速度快、来源广,使得实时日志采集系统的开发与更新变得至关重要。分布式日志采集系统正在朝着负载均衡、高容错、高可靠的方向发展。

Numerical Model of Cnoidal Wave Flume

The volume of fluid (VOF) method is used to set up a wave flume with an absorbing wave maker of cnoidal waves. Based on the transfer function between wave surface and paddle velocity obtained by the shallow water wave theory, the velocity boundary condition of an absorbing wave maker is introduced to absorb reflected waves that reach the numerical wave maker. For Hid ranging from 0.1 to 0.59 and T root g/d from 7.9 to 18.3, the parametric studies have been carried out and compared with experiments.