Response of the interaction between groundwater and other components of the environment in Mexico

This article reviews and discusses environmental aspects related to vertical upward and downward groundwater flow. Flow systems are an important tool to understand groundwater functioning as related to the environment, in terms of obtaining indicators of human impact and solving specific questions about a groundwater-environment system that has been influenced by anthropogenic means. This involves two broad processes. First, groundwater changes due to activities of man in the surrounding environment as a result of: (1) alteration of recharge by modification of native vegetation and original soil cover; (2) reduction of groundwater discharge to coastal areas and to inland water bodies producing desiccation of wetlands, lakes and springs; (3) groundwater contamination from sewage looses and uncontrolled waste disposal locations, and (4) up-welling of undesirable water quality induced by extraction. Second, environmental alterations due to changes in the groundwater regime produce: (1) increase in soil erosion through the disappearance of vegetation due to water-table decline, (2) water-table rise due to unplanned artificial recharge resulting from water imports to a catchment, (3) decline in water levels for improper extraction regime, (4) soil subsidence due to extraction mismanagement, and (5) disappearance of phreatofites caused by excessive extraction. Unless further understanding between groundwater and the other components of the environment is sought, the relationship between people and its environment will be subject to some of these effects, potentially endangering adequate human development and sustainable water management.     

Suspended sediment yield modeling in Mahanadi River,India by multi-objective optimization hybridizing artificial intelligence algorithms

River sediment produced through weathering is one of the principal landscape modification processes on earth.Rivers are an integral part of the hydrologic cycle and are the major geologic agents that erode the continents and transport water and sediments to the oceans.Estimation of suspended sediment yield is always a key parameter for planning and management of any river system.It is always challenging to model sediment yield using traditional mathematical models because they are incapable of handling the complex non-linearity and non-stationarity.The suspended sediment modeling of the river depends on the number of factors such as rock type,relief,rainfall,temperature,water discharge and catchment area.In this study,we proposed a hybrid genetic algorithm-based multi-objective optimization with artificial neural network(GA-MOO-ANN)with automated parameter tuning model using these factors to estimate the suspended sediment yield in the entire Mahanadi River basin.The model was validated by comparing statistically with other models,and it appeared that the GA-MOO-ANN model has the lowest root mean squared error(0.009)and highest coefficient of correlation(0.885)values among all comparative models(traditional neural network,multiple linear regression,and sediment rating curve)for all stations.It was also observed that the proposed model is the least biased(0.001)model.Thus,the proposed GA-MOOANN is the most capable model,compared to other studied models,for estimating the suspended sediment yield in the entire Mahanadi river basin,India.The results also suggested that the proposed GA-MOO-ANN model is unable to estimate suspended sediment yield satisfactorily at gauge stations having very small catchment areas whereas performing satisfactorily on locations having moderate to the large catchment area.The models provide the best result at Tikarapara,the gauge station location in the extreme downstream,having the largest catchment area.     

广西凭祥大型市政隧道施工技术

广西凭祥弄怀隧道属岩溶地区大型市政深埋越岭短隧道,跨度大、岩溶发育,根据实际工程地质情况,采用钻爆开挖法——新奥法施工,洞口及围岩较破碎地段遵循短开挖、弱爆破、超前强支护、早衬砌的原则,通过采取综合措施圆满完成了隧道的掘进开挖。     

地震相分析技术在滨里海盆地AS油田沉积相分析中的应用

针对滨里海AS地区的勘探开发目标层系,运用人工神经网络和主组分分析等技术和方法,对研究区的地震反射波形变化特征及其反映的地质特征进行识别和分类,得到地震相图,应用主要地震相单元中单井相分析成果建立地震相与沉积相的对应关系,将地震相转化为沉积相.该方法弥补了单纯用钻井资料进行沉积相划分的缺陷,提高了沉积相划分精度.     

Image and non-image parameters of atmospheric Cherenkov events: a comparative study of their γ-ray/hadron classification potential in ultrahigh energy regime

In this exploratory simulation study, we compare the event-progenitor classification potential of a variety of measurable parameters of atmospheric Cherenkov pulses which are produced by ultrahigh energy γ-ray and hadron progenitors and are likely to be recorded by the TACTIC (TeV atmospheric Cherenkov telescope with imaging camera) array of atmospheric Cherenkov telescopes. The parameters derived from Cherenkov images include Hillas, fractal and wavelet moments, while those obtained from non-image Cherenkov data consist of pulse profile rise time and base width and the relative ultraviolet to visible light content of the Cherenkov event. It is shown by a neural-net approach that these parameters, when used in suitable combinations, can bring about a proper segregation of the two event types, even with modest sized data samples of progenitor particles.     

基于OGRE引擎的三维矿山爆破设计与实现

在三维矿山、爆破原理和爆破设计原则的基础上,采用Visual Studio 2010中的Visual C++环境,使用OGRE三维引擎、QT、三维GIS等技术手段,自主研发了三维可视化系统软件。对矿山巷道、岩层、炮孔进行三维建模,实现了爆破设计可视化、爆破二三维联动显示、炮孔布局与绘图、爆破效果预测,从而简化了爆破设计人员的设计工作,减轻了劳动强度,提高了爆破设计的准确性和矿山开采的数字化程度。     

Optimization of artificial ground freezing in tunneling in the presence of seepage flow

Artificial ground freezing is an environmentally friendly technique to provide temporary excavation support and groundwater control during tunnel construction under difficult geological and hydrological ground conditions. Evidently, groundwater flow has a considerable influence on the freezing process. Large seepage flow may lead to large freezing times or even may prevent the formation of a closed frozen soil body. For safe and economic design of freezing operations, this paper presents a coupled thermo-hydraulic finite element model for freezing soils integrated within an optimization algorithm using the Ant Colony Optimization (ACO) technique to optimize ground freezing in tunneling by finding the optimal positions of the freeze pipe, considering seepage flow. The simulation model considers solid particles, liquid water and crystal ice as separate phases, and the mixture temperature and liquid pressure as primary field variables. Through two fundamental physical laws and corresponding state equations, the model captures the most relevant couplings between the phase transition associated with latent heat effect, and the liquid transport within the pores. The numerical model is validated by means of laboratory results considering different scenarios for seepage flow. As demonstrated in numerical simulations of ground freezing in tunneling in the presence of seepage flow connected with the ACO optimization algorithm, the optimized arrangement of the freeze pipes may lead to a substantial reduction of the freezing time and of energy costs.     

Hybrid meta-heuristic machine learning methods applied to landslide susceptibility mapping in the Sahel-Algiers

Landslides are considered as one among many phenomena jeopardizing human beings as well as their constructions. To prevent this disastrous problem, researchers have used several approaches for landslide susceptibility modeling, for the purpose of preparing accurate maps marking landslide prone areas. Among the most frequently used approaches for landslide susceptibility mapping is the Artificial Neural Network (ANN) method. However, the effectiveness of ANN methods could be enhanced by using hybrid metaheuristic algorithms, which are scarcely applied in landslide mapping. In the current study, nine hybrid metaheuristic algorithms, genetic algorithm (GA)-ANN, evolutionary strategy (ES)-ANN, ant colony optimization (ACO)-ANN, particle swarm optimization (PSO)-ANN, biogeography based optimization (BBO)-ANN, gravitational search algorithm (GHA)-ANN, particle swarm optimization and gravitational search algorithm (PSOGSA)-ANN, grey wolves optimization (GWO)-ANN, and probability based incremental learning (PBIL)-ANN have been used to spatially predict landslide susceptibility in Algiers’ Sahel, Algeria. The modeling phase was done using a database of 78 landslides collected utilizing Google Earth images, field surveys, and six conditioning factors (lithology, elevation, slope, land cover, distance to stream, and distance to road). Initially, a gamma test was used to decrease the input variable numbers. Furthermore, the optimal inputs have been modeled by the mean of hybrid metaheuristic ANN techniques and their performance was assessed through seven statistical indicators. The comparative study proves the effectiveness of the co-evolutionary PSOGSA-ANN model, which yielded higher performance in predicting landslide susceptibility compared to the other models. Sensitivity analysis using the step-by-step technique was done afterward, which revealed that the distance to the stream is the most influential factor on landslide susceptibility, followed by the slope factor which ranked second. Lithology and the distance to road have demonstrated a moderate effect on landslide susceptibility. Based on these findings, an accurate map has been designed to help land-use managers and decision-makers to mitigate landslide hazards.     

A comparative analysis of seismic response of shallow buried underground structure under incident P,SV and Rayleigh waves

In this study, A time-domain seismic response analysis method and a calculation model of the underground structure that can realize the input of seismic P, SV and Rayleigh waves are established, based on the viscoelastic artificial boundary elements and the boundary substructure method for seismic wave input. After verifying the calculation accuracy, a comparative study on seismic response of a shallow-buried, double-deck, double-span subway station structure under incident P, SV and Rayleigh waves is conducted. The research results show that there are certain differences in the cross-sectional internal force distribution characteristics of underground structures under different types of seismic waves. The research results show that there are certain differences in the internal force distribution characteristics of underground structures under different types of seismic waves. At the bottom of the side wall, the top and bottom of the center pillar of the underground structure, the section bending moments of the underground structure under the incidences of SV wave and Rayleigh wave are relatively close, and are significantly larger than the calculation result under the incidence of P wave. At the center of the side wall and the top floor of the structure, the peak value of the cross-sectional internal force under the incident Rayleigh wave is larger than the calculation result under SV wave. In addition, the floor of the underground structure under Rayleigh waves vibrates in both the horizontal and vertical directions, and the magnification effect in the vertical direction is more significant. Considering that the current seismic research of underground structures mainly considers the effect of body waves such as the shear waves, sufficient attention should be paid to the incidence of Rayleigh waves in the future seismic design of shallow underground structures.