Exact linearization of non-planar intermediary orbits in the satellite theory

In this paper we consider the reduction of the equations of motion for non-planar perturbed two body problems into linear form. It is seen that this can be easily accomplished for any element of the class of radial intermediaries to the satellite problem proposed by Deprit in 1981, since they have a functional dependence suitable for linearization. The transformation is worked out by using an adequate set of redundant variables. Four harmonic oscillators are obtained, of which two are coupled through gyroscopic terms. Their constant frequencies contain the secular contribution of the main problem of artificial satellite theory up to the order of the considered intermediary. Therefore, this result may well be interesting in relation to the study and prediction of accurate long-term solutions to satellite problems.     

A direct inversion scheme for deep resistivity sounding data using artificial neural networks

Initialization of model parameters is crucial in the conventional 1D inversion of DC electrical data, since a poor guess may result in undesired parameter estimations. In the present work, we investigate the performance of neural networks in the direct inversion of DC sounding data, without the need ofa priori information. We introduce a two-step network approach where the first network identifies the curve type, followed by the model parameter estimation using the second network. This approach provides the flexibility to accommodate all the characteristic sounding curve types with a wide range of resistivity and thickness. Here we realize a three layer feed-forward neural network with fast back propagation learning algorithms performing well. The basic data sets for training and testing were simulated on the basis of available deep resistivity sounding (DRS) data from the crystalline terrains of south India. The optimum network parameters and performance were decided as a function of the testing error convergence with respect to the network training error. On adequate training, the final weights simulate faithfully to recover resistivity and thickness on new data. The small discrepancies noticed, however, are well within the resolvability of resistivity sounding curve interpretations.     

A new method for computing the spectrum of the gravitational perturbations on satellite orbits

Some aspects for efficient computation of the tidal perturbation due to the ellipticity effects of the Earth, the luni-solar potential on an Earth-orbiting satellite and the perturbations of the satellite's radial, transverse and normal position components due to the effects of the Earth's gravitational and ocean tide fields are presented. A straightforward method for computing the spectrum of the geopotential and the tidal-induced perturbations of the orbit elements and the radial, transverse and normal components is described.     

地下水人工回灌淤积的室内试验研究

在进行地下水人工回灌过程中常常产生淤积问题,而淤积与回灌水源的浊度、回灌水层厚度、回灌地点的颗粒级配有关。为了研究淤积的影响因素,本文利用室内试验对其影响因素进行的分析表明,影响淤积的主要因素是浊度,其次是水层厚度。在此基础上,建立了淤积高度与影响因素的多元统计方程。     

Redemarcation of recharge area of stressed confined aquifers of Neyveli groundwater basin, India, through tritium tracer studies

Natural recharge due to rainfall (annual average 1,200 mm) over an area of 1,500 km² of the Neyveli groundwater basin was carried out for two consecutive hydrological years, using the tritium injection technique. The lignite seams, occurring within the Upper Miocene formation in the basin have been mined for the last 40 years. The confined aquifer underlying the lignite seams has been pumped continuously since 1961, for depressurization and safety around the mine. The recharge zone is identified as an elongated zone, oriented in a NE–SW direction within the basin. Natural recharge measurements were made at several sites (single and duplicate injections), covering the entire basin. They indicate a recharge rate of 333–556 mm/year (24–40% of rainfall) in the north and northeastern parts, covering the previously defined recharge areas as well as some adjoining areas. Soil moisture movement at several duplicate sites in these areas showed significant downward migration of tracer during the non-monsoon period, probably caused by pumping in the mine area. Isotopic data of ground water samples in the northern and northeastern part of the basin indicates modern ages. Concurrent field observations like deep water table with high annual fluctuations and exposure of pebble beds, enabled the redemarcation of the aggregate recharge area as 650 km². The redefined recharge area includes the areas identified by earlier workers as well as the new area on the northeastern side of the lignite mine.     

A method to estimate the artificial recharge capacity of the Crestatx aquifer (Majorca, Spain).

This paper presents a method for the feasibility of an artificial recharge scheme in a limestone aquifer. A 3D digital groundwater flow model was developed and calibrated to gain a better understanding of the aquifer dynamics and to estimate its capacity for artificial recharge. Several scenarios, based on different pumping alternatives, were tested over a 30 year period. The results were then analysed by yearly input-output balances. Worst case scenario model output suggests that implementing the scheme might ensure a sustainable use of the aquifer in the future.     

Opportunities to enhance management of karstic aquifers

Methods exist to obtain “new sources of water.” Examples include: (1) capturing and enhancing stormwater recharge and retention within diffuse-flow portions of karst and other aquifers; (2) recycling and reuse of waste water; (3) reducing evapotranspiration and rejected recharge; and (4) ameliorating atmospheric acid deposition through use of alkaline groundwater. These little used management methods have immense potential to sustain future water demands. Full utilization of “new” and traditional water resources requires an understanding of the hydrogeologic framework of karstic aquifers. Reliable conceptual, numerical flow and transport models are needed to help evaluate, select, and design viable water management options. Three such simulation examples are provided together with a discussion of Penn State’s Wastewater reuse project where recharge approaches 3.785 × 10⁹l/year     

Prediction of agriculture derived groundwater nitrate distribution in North China Plain with GIS-based BPNN

In recent years, nitrate contamination of groundwater has become a growing concern for people in rural areas in North China Plain (NCP) where groundwater is used as drinking water. The objective of this study was to simulate agriculture derived groundwater nitrate pollution patterns with artificial neural network (ANN), which has been proved to be an effective tool for prediction in many branches of hydrology when data are not sufficient to understand the physical process of the systems but relative accurate predictions is needed. In our study, a back propagation neural network (BPNN) was developed to simulate spatial distribution of NO₃-N concentrations in groundwater with land use information and site-specific hydrogeological properties in Huantai County, a typical agriculture dominated region of NCP. Geographic information system (GIS) tools were used in preparing and processing input–output vectors data for the BPNN. The circular buffer zones centered on the sampling wells were designated so as to consider the nitrate contamination of groundwater due to neighboring field. The result showed that the GIS-based BPNN simulated groundwater NO₃-N concentration efficiently and captured the general trend of groundwater nitrate pollution patterns. The optimal result was obtained with a learning rate of 0.02, a 4-7-1 architecture and a buffer zone radius of 400 m. Nitrogen budget combined with GIS-based BPNN can serve as a cost-effective tool for prediction and management of groundwater nitrate pollution in an agriculture dominated regions in North China Plain.     

人工冻土温度场影响因素灵敏度分析

在冻结法凿井施工中,全面掌握诸因素对人工冻土温度场发展的影响程度,对于优化冻结方案、处理紧急情况有重要的意义.文章通过对两淮地区大量的冻结法施工井筒冻结时段的温度场实测数据样本分析,较全面地考虑影响人工冻土温度场发展的诸因素,利用人工智能方法构建一个大型的能预测温度场的动态网络结构,通过对网络结构隐含信息的分析,得出系统中各因素对冻土温度场影响的灵敏度.     

Artificial neural network application to estimate kinematic soil pile interaction response parameters

Six artificial neural network (ANN) models are developed to predict various response parameters of kinematic soil pile interaction. These responses include (1) kinematic response factors for free and fixed head piles in homogenous soil layer to derive foundation input motion (2) normalized bending moment at fixed head of pile in homogenous soil layer (3) normalized kinematic pile moment at the interface of two soil layers of sharply different soil stiffnesses. These ANN models represent simple solutions that can be implemented in a simple calculator capable of matrix operation and bypass the site response analysis and the complex wave diffraction analysis. The data required for ANN training is generated using beam on dynamic Winkler formulation (BDWF). Fifty percent of the data is used to train the ANN models while remaining 50% is used to test the ANN models. The trained ANN models show good agreement with BDWF results.