Air pressure law of a reservoir constructed in karst sinkholes

Karst sinkholes with natural negative landform provide favorable conditions for the pumped storage reservoir construction for less excavation work.However,the construction of the reservoir would plug the natural karst channels for water and air,which would cause remarkable air pressure in karst channels when the groundwater level fluctuates.A large laboratory simulation test was carried out to study the air pressure variation of a reservoir built on the karst sinkhole.The air pressure in the karst channel and inside the model was monitored during the groundwater rising and falling process.Result showed that the variation of air pressure in the karst channel and the surrounding rock exhibited a high degree of similarity.The air pressure increased rapidly at the initial stage of water level rising,followed by a slight decrease,then the air pressure increased sharply when the water level approached the top of the karst cave.The initial peak of air pressure and the final peak of air pressure were defined,and both air pressure peaks were linearly increasing with the water level rising rate.The negative air pressure was also analyzed during the drainage process,which was linearly correlated with the water level falling rate.The causes of air pressure variation in karst channels of a pumped storage reservoir built on the karst sinkhole were discussed.The initial rapid increase,then slight decrease and final sudden increase of air pressure were controlled by the combined effects of air compression in karst channel and air seepage into the surrounding rock.For the drainage process,the instant negative air pressure and gradual recovering of air pressure were controlled by the combined effects of negative air pressure induced by water level falling and air supply from surrounding rock.This work could provide valuable reference for the reservoir construction in karst area.

Feasibility study on sinkhole monitoring with fiber optic strain sensing nerves

Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This paper presents an experimental study to evaluate the feasibility of fiber optic strain sensing nerves in sinkhole monitoring.Combining the artificial neural network(ANN)and particle image velocimetry(PIV)techniques,a series of model tests have been performed to explore the relationship between strain measurements and sinkhole development and to establish a conversion model from strain data to ground settlements.It is demonstrated that the failure mechanism of the soil above the sinkhole developed from a triangle failure plane to a vertical failure plane with increasing collapse volume.Meanwhile,the soil-embedded fiber optic strain sensing nerves allowed deformation monitoring of the ground soil in real time.Furthermore,the characteristics of the measured strain profiles indicate the locations of sinkholes and the associated shear bands.Based on the strain data,the ANN model predicts the ground settlement well.Additionally,micro-anchored fiber optic cables have been proven to increase the soil-to-fiber strain transfer efficiency for large deformation monitoring of ground collapse.

基于汇聚度的传感器网络Sinkhole攻击检测

传感器网络以数据为中心的特殊流量汇聚模式尤其易受Sinkhole攻击。通过分析Sinkhole攻击点邻近区域的路由特点,提出一种新颖的基于汇聚度检测Sinkhole攻击的策略。该策略无需运行密码算法,无需额外通信开销,适用于不同网络部署密度、信道质量及攻击强度下的攻击检测。

无线传感器网络中的sinkhole攻击检测

对sinkhole攻击进行了研究,提出了基于多点监测与回复信息的攻击检测方法。利用基站和节点间数据包的传输与确认,结合邻节点的监视机制对节点收发的数据包统计分析,检测sinkhole攻击。这种方法避免了复杂的加密算法与身份认证,与多路径安全机制相比有着更高的可靠性。对安全概率进行了理论分析,并进一步通过仿真实验对方法进行了验证。

无线传感器网络中的sinkhole攻击检测技术研究

在无线传感器系统中,Sinkhole是一种相对基础且常见的路由攻击类型,攻击者通过声称到目的节点或基站具有高质量的路径吸引周围节点的数据流,对网络的负载平衡造成了严重的影响.当前,sinkhole攻击检测技术在网络安全问题中占有重要的地位,其重要性越来越受到人们的重视.基于此,本文对无线传感器网络中的sinkhole攻击检测技术原理与设计进行了分析,以便于更好利用该技术对计算机网络进行保护.

基于模糊逻辑分类的WSN Sinkhole侦测

分析无线传感器网络Sinkhole攻击侦测的监测特征、方法和侦测流程,设计并实现基于模糊逻辑分类的攻击侦测方案。仿真实验表明,该方案能较好地解决多因素集合的模糊信息问题,克服以往方案侦测模型复杂、误报率较高的不足,具有运算量小,易于实现、适用性好的特点。

无线传感器网络中基于Sinkhole攻击的入侵检测系统研究

随着无线传感器网络应用范围的扩大、传感数据重要性的提高,其安全性也日益受到关注。Sinkhole是一种比较基础且常见的路由攻击类型,在该攻击中,攻击者通过声称到目的节点或基站具有高质量的路径吸引周围节点的数据流,严重破坏了网络的负载平衡。根据AODV协议中Sinkhole攻击方式特点,设计一个基于规范的分布式入侵检测系统,并对入侵检测系统的各功能模块进行详细的设计和分析。该系统通过本地数据监控模块提供的信息对节点的行为进行状态转换,判断节点是否发生异常行为,同时结合其他节点提供的信息最终确定攻击者。仿真结果和分析表明所设计的基于AODV路由协议的入侵检测系统具有良好性能,即使在有攻击出现的情况下,网络仍可以保持较高的传输率。

无线传感器网络中sinkhole攻击研究

无线传感器网络在安全路由以及入侵检测研究等方面之所以没有显著的成绩,原因之一就是对于"入侵"的概念不是很清楚。对无线传感器网络中sinkhole这一类重要攻击进行了深入研究。首先介绍了sinkhole的产生及危害,然后分析了目前针对sinkhole攻击检测技术研究进展,其次重点描述了攻击者在具体的路由协议中如何成功发起攻击,最后提出针对sinkhole攻击研究的若干热点问题与展望。

无线传感器网络中的Sinkhole攻击检测

探讨了无限传感网络的构成及无线传感器网络协议栈各层所面临的安全问题,重点讨论了Sinkhole攻击的危害及检测,通过分析Sinkhole攻击点邻近区域的路由特点,提出了基于汇聚度检测Sinkhole攻击的策略和基于多点监测与回复信息的攻击检测方法。

ACO结合P2P信任模型的无线传感器网络Sinkhole攻击检测

针对无线传感器网络中的Sinkhole攻击问题,提出了一种基于蚁群优化(ACO)结合P2P信任模型的Sinkhole攻击检测(P-ACO)算法。首先,使用蚁群优化算法检测路由中是否存在Sinkhole攻击,并生成传感器节点的警报信息;然后,利用布尔表达式进化标记生成算法为群组警报节点分发密钥,并使用密钥标记可疑节点;最后,计算可疑节点列表中各节点的信任值,将信任值低于预设阈值的节点视为攻击节点。分析表明,相比二分查找算法与基于规则匹配的神经网络(RMNN)算法,该算法在匹配过程中需要更少的匹配搜索次数,提高了算法执行效率。实验结果显示,相比RMNN算法,该算法可以更加准确地检测Sinkhole攻击。

Analytical and numerical method assessing the risk of sinkholes formation in mining areas

Voids, which have not been liquidated and associated with shallow mining excavations, pose a serious threat of potential formation of sinkholes. This threat is connected with the loss of stability of voids that had been formed as a result of mining operations in the deeper strata. Taking into account the impact of lower coal seams mining on shallow excavations and based on the example of a region that had been intensely exploited, this paper proposes a methodology for analysing the stability of shallow mine voids in the rock mass. Deformations in the excavation region were calculated by using FLAC2D computer pro- gram and assigning the Coulomb-Mohr model to the rock mass. Based on the numerical analysis, this paper evaluated the stability of the void in the event of a roof support fall. The results indicate the like- lihood of void formation. Based on the Budryk-Knotbe theory, the deformations of rock mass and sand- stone strata in the roof of the void, which had been caused by mining exploitation in consecutive years, were calculated. The results of numerical calculations and analyses were compared with the limit defor- mations values of sandstone in tension. It is concluded that the exploitations cause the void to break down. The proposed method can forecast the discontinuous deformations threats in the areas that have undergone shallow undermining exploitation and the areas of underground urban.

GPSR地理路由协议中sinkhole攻击及其入侵检测方法的研究

随着微电子技术、计算技术和无线通信等技术的飞速发展和日益成熟,无线传感器网络被广泛应用于军事、环境监测等多个领域,但是网络的不安全性限制了它的应用,安全问题受到了越来越多研究者的关注。基于这一现状,提出了一种改进的GPSR地理路由协议。这种简易的能量改进策略,以减少由于GPSR协议中周围模式引起的过多的跳跃。无线传感器网络中存在着多种攻击威胁着网络的安全,其中Sinkhole攻击是一种常见的、基础型的攻击,很多攻击以它为基础或辅助手段对网络实施攻击。本文根据GPSR的Sinkhole攻击手段,对sinkhole的入侵检测方法进行分析。

Geospatial Modeling for Sinkholes Hazard Map Based on GIS &RS Data

The Kinta Valley is an area of karst in the north-western part of Peninsular Malaysia. Over 30 years of uncontrolled land use and development has led to significant changes in topography and geomorphology, such as the appearance of sinkholes. In this paper, geospatial techniques were utilized to the task of evaluating sinkholes susceptibility map using a spatial multi criteria evaluation approach (SMCE). Sinkhole location and a spatial database were applied to calculate eight inherent causative factors for limestone instability namely: lithology, structure (lineament), soil cover, slope, land use mining, urban area features, ponds and rivers. The preparation of the sinkhole geohazard map involved summing the weighted values for each hazard element, which permits the construction of geohazard model;the results of the analysis were validated using the previous actual sinkholes locations in the study area. The spatial distribution of sinkholes occurrence, urban development, faults distribution and ex-mining ponds are factors that are directly responsible for all sinkholes subsidence hazards. Further, the resulting geo-hazard map shows that 93% of recent sinkholes occur in areas where the model flags as “high” and “very high” potential hazard, located in the urbanized part of the valley, while less-developed areas to the west and southwest suffered less sinkhole development. The results can be used for hazard prevention and land-use planning.

Tectonic Analysis of the Al Hamadah Al Hamra Plateau of the Ghadamis Basin (NW Libya): Hydrological Network, Sinkholes, Folds and Fractures. Style of Reactivation and Setting of Cenozoic Volcanism

Remote sensing analysis is an efficient tool for updating geological maps. The regional scale map obtained in this project from compilation of the pre-existing maps and of a number of space images is somewhat more complete. It takes into account the usual field and laboratory parameters of the rock units, through the previous geologic maps, together with remote sensing parameters such as spectral signatures, textures, roughness, morphology that are observed from optical, microwave and DEM imagery. With more rock characteristics, the old maps are obligatory improved. The Cenozoic faulting in the Al Hamra al Hamadah plateau is largely influenced by the tectonics affecting the Paleozoic oil bearing structures that are hidden by the late Cretaceous-Paleocene layers. The tectonic style is that of reactivation of the Paleozoic faults under effects of the NNE-trending regional tension. Then the faults on the surface of the plateau would indicate location of the hidden Paleozoic faults in depth. A flat plateau, in the arid environment, appears to be a very favorable environment for mapping of gentle folds, faults and tectonic sinkholes. Remote sensing is a fruitful approach in this case study. The gentle anticlines for instance are undetectable in the field, but computer assisted shadowing with a low elevation angle of illumination is the key processing for evidencing these features. Problems of drillings in the area are well known for example to Waha, AGOCO and PB Companies during their exploration activities in the concessions in Ghadames Basin. According to them several incidents of losing drilling Pits have occurred and drilling came into a hole. Because this paper is aimed to know the exact location of sinkholes in the Ghadames basin, I would recommend all the oil companies to review this work and try to trace the sinkholes indicated to minimize the risk of drilling problems.

Geological and Morphological Features of the Karap?nar Sinkholes(Konya,Central Anatolia,Türkiye)

Karapınar region(Konya,Türkiye)is one of the important regions of the world in terms of sinkhole formations.The research aimed to map the sinkholes in detail,to determine their spatial distribution and geometrical parameters.For this purpose,the long axes,short axes,depths and the proximity to settlements of the sinkholes were measured and their circumferences and areas were calculated.During the studies,the relationship of the sinkholes with lithology,their cross sections,shapes and the related structures were determined and the sinkholes were divided into five main groups as following:Basement rock sinkholes,Obruk Plateau sinkholes,Seyithacı sinkholes,Siyeklik sinkholes and Basin sinkholes.The d/l ratios of each sinkhole group were separately determined and interpreted.Accordingly,most of the d/l ratios are smaller than 0.2.Namely,the long axes are higher than the depth and it indicates that the shallow and wide sinkholes are common in the region.It has been determined that the fracture systems in the region,as well as the lithology and groundwater factors,are quite effective in the formation and distribution of the sinkholes in the Karapınar region.Considering the distance of the sinkholes to the settlements,Seyithac?sinkholes are the most risky group in the region because they are deep and close to the settlements.

Vertical Displacement Measurement in a Slow-Moving Sinkhole Using BOTDA

The effectiveness of monitoring and early-warning systems for ground deformation phenomena,such as sinkholes,depends on their ability to accurately resolve the ongoing ground displacement and detect the subtle deformation preceding catastrophic failures.Sagging sinkholes with a slow subsidence rate and diffuse edges pose a significant challenge for subsidence monitoring due to the low deformation rates and limited lateral strain gradients.In this work,we satisfactorily illustrate the practicality of the Brillouin optical time domain analysis(BOTDA)to measure the spatial-temporal patterns of the vertical displacement in such challenging slow-moving sagging sinkholes.To assess the performance of the approach,we compare the strain recorded by the distributed optical fiber sensor with the vertical displacement measured by high-precision leveling.The results show a good spatial correlation with the ability to identify the maximum subsidence point.There is also a good temporal correlation with the detection of an acceleration phase in the subsidence associated with a flood event.

Formation process of cover collapse sinkholes related to groundwater level decline in karst areas

The decline in groundwater level is a key factor contributing to cover collapse in karst areas.In this study,the model tests and numerical simulations are conducted to reveal the breeding process and formation mechanism of cover collapse sinkholes caused by the decline of groundwater level in karst area.Firstly,the model tests confirm that the decline of groundwater level generates negative pressure at the lower edge of overlying soil.The negative pressure experiences four distinct phases during the groundwater drawdown process:rapid rise,slow decline,rapid decline,and gradual dissipation.The maximum negative pressure is influenced by the particle size distribution of the overlying soil.Then,the numerical simulations are carried out to investigate the change process of negative pressure caused by the loss of fillers in karst pipe.The simulated results indicate that the rate of groundwater decline and the thickness and initial void ratio of the overlying soil can affect the maximum negative pressure.As groundwater level drops,a negative pressure zone forms underground,causing tensile failure in the surrounding soil and creating an arched soil hole,which weakens the support for the overlying soil.This phenomenon can also lead to the collapse of the overlying soil under its self-weight.Groundwater table decline in karst areas can result in both internal and surface collapses.When the overlying soil is thin,internal and surface collapses occur simultaneously.In contrast,for thick overlying soil,internal collapse happens first,followed by a layer-by-layer collapse,ultimately forming sinkholes.Finally,the breeding process and formation mechanism of the Yujiawan Reservoir sinkholes are discussed.Geological conditions and groundwater level decline significantly affect internal collapse in karst areas,requiring careful consideration from on-site engineers.

Machine Learning and Statistical Analysis in Groundwater Monitoring for Total Dissolved Solids Assessment in Winkler County, Texas

This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved Solids (TDS) in wells of the Permian basin, Winkler County, Texas. The data for this contribution was obtained from the Texas Water Development Board website (TWDB). Five hundred and ninety-three samples were obtained from two hundred and ninety-eight wells in the study area. The wells were drilled at different county locations into five aquifers, including Pecos Valley, Dockum, Capitan Reef, Edward Trinity, and Rustler aquifers. A total of fourteen different water quality parameters were used, and they include Potential hydrogen (pH), Sodium, Chloride, Magnesium, Fluoride, TDS, Specific Conductance, Nitrate, Total Hardness, Calcium, Temperature, Well Depth, Sulphate, and Bicarbonates. Four machine learning regression algorithms were developed to get a good model to help predict TDS in this area: Decision Tree regression, Linear regression, Support Vector Regression, and K-nearest neighbor. The study showed that the Decision Tree produced the best model with attributes like the coefficient of determination R2 = 1.00 and 0.96 for the training and testing, respectively. It also produced the lowest score of mean absolute error MAE = 0.00 and 0.04 for training and testing, respectively. This study will reduce the cost of obtaining different water quality parameters in TDS determination by leveraging machine learning to use only the parameters contributing to TDS, thereby helping researchers obtain only the parameters necessary for TDS prediction. It will also help the authorities enact policies that will improve the water quality in areas where drinking water availability is a challenge by providing important information for monitoring and assessing groundwater quality.

Efficiency of local minima and GLM techniques in sinkhole extraction from a LiDAR-based terrain model

The aim of this paper was to study reliable automated delineationpossibilities of karst sinkholes using a LiDAR-based digital terrain model(DTM) with pixel-based classifications. We applied two approaches toextract sinkholes: (1) general linear modeling (GLM) with morphometricindices derived from DTM;(2) and a local minima-based delineationusing only LiDAR DTM as the input layer. The outcome of the localminima was significantly different from the reference ones but found allthe sinkholes without previous knowledge of the area. The GLM-basedoutcome did not differ statistically from the reference. Results showedthat these approaches were efficient in detecting sinkholes based onLIDAR derivatives, and can be used for risk assessment and hazardpreparedness in karst areas: GLM had an overall accuracy of 89.5% andlocal minima had an accuracy of 92.3%;both methods identifiedsinkholes but also had commission errors, identifying depressions assinkholes.

一种蚁群优化的WSN分布式入侵检测模型

针对无线传感器网络中入侵者能在多个节点上移动并隐藏攻击源头的特点,提出了一种基于蚁群优化的无线传感器网络分布式入侵检测模型。分析了现有入侵检测对未知攻击检测率和误报率方面的不足,在此基础上提出了分布式入侵检测的体系结构,设计了基于蚁群优化的入侵检测算法。仿真实验表明提出的方案能够提高无线传感器网络对未知攻击的检测率和降低对正常网络流量的误报率,较好地解决了路由攻击、Sinkhole攻击问题,能够降低入侵检测的能耗。