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71.
Determining in-situ soil or rock geotechnical properties is a difficult task for a design engineer. Back analysis is a helpful technique for evaluating soil property by considering and measuring the convergence of an underground opening. Back analysis was performed by matching numerical modeling results with the measured tunnel convergence. The main purpose of this study was to determine optimum rock mass properties using back analysis in order to suggest the best and most economical support system. Accordingly, the difference between measured and calculated convergence values was minimized by using an error function (objective function). In this paper, through the parameters obtained from back analysis, a support system based on a set consisting of shotcrete, wire mesh, and lattice girder was suggested for the Babolak water conveyance tunnel in Mazandaran, Iran. Therefore, the suggested design was based on decreasing shotcrete thickness from 25 to 20?cm and eliminating of rock bolts.  相似文献   
72.
We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a principal component analysis (PCA) to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite tracking data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low- and high-degree potential coefficients reflected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily influenced by interannual variations.  相似文献   
73.
This study investigated the potential factors affecting arsenic concentration in the groundwater system of Lahore, Pakistan. The effects of several factors such as population density (PD), pumping rate (PR), impermeable land use (LU), surface elevation (SE), and water-table elevation (WL) on arsenic concentration were studied in 101 union councils of Lahore. Forty single and multi-factor models were established using geographic information system (GIS) techniques to develop an arsenic contamination map and to investigate the most effective combinations among factors. Additionally, statistical tests were used to evaluate arsenic concentration between classes of the same single factor. The arsenic concentration in the Lahore aquifer varied from 0.001 to 0.143 mg L?1. The highest arsenic concentrations were detected in the Walled City and the town of Shahdara. Among the 40 raster models, groundwater arsenic concentration showed the best matching frequency with single-factor models for PD (50.70 %) and SE (47 %). Thus, PD and SE were used to develop an arsenic distribution raster map, and they were also used to study the effect of aquifer depth on arsenic concentration. PD was found to have hidden latent variables such as PR and LU. The shallow aquifer depth was negatively correlated with arsenic concentration (r?=??0.23) and positively with PR (r?=?0.15). Therefore, when there was high PR in wells with smaller aquifer depth, the arsenic concentration was high. The existing water treatment and alternative water resources are good options, which should be developed to deal with Lahore wells contaminated with arsenic at high concentrations.  相似文献   
74.
Peng  Ruikun  Zhao  Yinyin  Elahi  Ehsan  Peng  Benhong 《Natural Hazards》2021,106(3):2883-2899
Natural Hazards - The study estimates the impact of disaster shocks and risk perception on farmers’ willingness for insurance. Based on data of 328 farmers from the Shandong province of East...  相似文献   
75.
Acta Geotechnica - Hydraulic conductivity is one of the most important characteristics of unsaturated soils. Its determination is essential for modeling various phenomena of interest such as...  相似文献   
76.
A tracer plume was created within a thin aquifer by injection for 299 d of two adjacent “sub‐plumes” to represent one type of plume heterogeneity encountered in practice. The plume was monitored by snapshot sampling of transects of fully screened wells. The mass injection rate and total mass injected were known. Using all wells in each transect (0.77 m well spacing, 1.4 points/m2 sampling density), the Theissen Polygon Method (TPM) yielded apparently accurate mass discharge (Md) estimates at three transects for 12 snapshots. When applied to hypothetical sparser transects using subsets of the wells with average spacing and sampling density from 1.55 to 5.39 m and 0.70 to 0.20 points/m2, respectively, the TPM accuracy depended on well spacing and location of the wells in the hypothesized transect with respect to the sub‐plumes. Potential error was relatively low when the well spacing was less than the widths of the sub‐plumes (>0.35 points/m2). Potential error increased for well spacing similar to or greater than the sub‐plume widths, or when less than 1% of the plume area was sampled. For low density sampling of laterally heterogeneous plumes, small changes in groundwater flow direction can lead to wide fluctuations in Md estimates by the TPM. However, sampling conducted when flow is known or likely to be in a preferred direction can potentially allow more useful comparisons of Md over multiyear time frames, such as required for performance evaluation of natural attenuation or engineered remediation systems.  相似文献   
77.
In this paper, a comprehensive study is carried out to examine the possibility of dynamic instability produced in soil‐structure systems using an ensemble of 50 pulse‐like records. A number of structural models with various vibration periods varying from 0.1 to 2 s are used in this study. The superstructure is simulated as a non‐linear SDOF oscillator with a two‐segment backbone curve having negative post‐yield stiffness. The soil is idealized based on the cone model concept widely used for practical purposes. The results of this investigation demonstrate that as the pulse period increases, the collapse relative lateral strength ratio decreases and probability of dynamic instability enhances. Moreover, soil flexibility makes the system dynamically more unstable, and as the non‐dimensional frequency increases, the collapse relative lateral strength ratio highly reduces. Additionally, the aspect ratio has insignificant effects on the collapse relative lateral strength ratio. Furthermore, comparison of the collapse relative lateral strength ratios resulting from pulse‐like motions with those obtained from studies under non‐pulse‐like motions (Miranda and Akkar; FEMA 440) for fixed‐base conditions shows that high‐velocity pulses exacerbate the dynamic instability problem and decrease the collapse relative lateral strength ratio. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
78.
A ballast water short-time high temperature heat treatment technique was applied on board a car-carrier during a voyage from Egypt to Belgium. Ballast water from three tanks was subjected for a few seconds to temperatures ranging from 55 degrees C to 80 degrees C. The water was heated using the vessel's heat exchanger steam and a second heat exchanger was used to pre-heat and cool down the water. The treatment was effective at causing mortality of bacteria, phytoplankton and zooplankton. The International Maritime Organization (IMO) standard was not agreed before this study was carried out, but comparing our results gives a broad indication that the IMO standard would have been met in some of the tests for the zooplankton, in all the tests for the phytoplankton; and probably on most occasions for the bacteria. Passing the water through the pump increased the kill rate but increasing the temperature above 55 degrees C did not improve the heat treatment's efficacy.  相似文献   
79.
We study a holographic dark energy model in the framework of Brans-Dicke (BD) theory with taking into account the interaction between dark matter and holographic dark energy. We use the recent observational data sets, namely SN Ia compressed Joint Light-Analysis (cJLA) compilation, Baryon Acoustic Oscillations (BAO) from BOSS DR12 and the Cosmic Microwave Background (CMB) of Planck 2015. After calculating the evolution of the equation of state as well as the deceleration parameters, we find that with a logarithmic form for the BD scalar field the phantom crossing can be achieved in the late time of cosmic evolution. Unlike the conventional theory of holographic dark energy in standard cosmology (\(\omega_{D}=0\)), our model results in a late time accelerated expansion. It is also shown that the cosmic coincidence problem may be resolved in the proposed model. We execute the statefinder and Om diagnostic tools and demonstrate that interaction term does not play a significant role. Based on the observational data sets used in this paper it seems that the best value with \(1\sigma \) and \(2\sigma \) confidence interval are \(\varOmega_{m}=0.268^{+0.008~+0.010}_{-0.007~-0.009}\), \(\alpha =3.361^{+0.332~+0.483} _{-0.401~-0.522}\), \(\beta =5.560^{+0.541~+0.780}_{-0.510~-0.729}\), \(c=0.777^{+0.023~+0.029}_{-0.017~-0.023}\) and \(b^{2} =0.045\), according to which we find that the proposed model in the presence of interaction is compatible with the recent observational data.  相似文献   
80.
Wave parameters prediction is an important issue in coastal and offshore engineering. In this literature, several models and methods are introduced. In the recent years, the well-known soft computing approaches, such as artificial neural networks, fuzzy and adaptive neuro-fuzzy inference systems and etc., have been known as novel methods to form intelligent systems, these approaches has also been used to predict wave parameters, as well. It is not a long time that support vector machine (SVM) is introduced as a strong machine learning and data mining tool. In this paper, it is used to predict significant wave height (Hs). The data set used in this study comprises wave wind data gathered from deep water locations in Lake Michigan. Current wind speed (u) and those belonging up to six previous hours are given as input variables, while the significant wave height is the output parameter. The SVM results are compared with those of artificial neural networks, multi-layer perceptron (MLP) and radial basis function (RBF) models. The results show that SVM can be successfully used for prediction of Hs. Furthermore, comparisons indicate that the error statistics of SVM model marginally outperforms ANN even with much less computational time required.  相似文献   
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