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This study presents single‐objective and multi‐objective particle swarm optimization (PSO) algorithms for automatic calibration of Hydrologic Engineering Center‐ Hydrologic Modeling Systems rainfall‐runoff model of Tamar Sub‐basin of Gorganroud River Basin in north of Iran. Three flood events were used for calibration and one for verification. Four performance criteria (objective functions) were considered in multi‐objective calibration where different combinations of objective functions were examined. For comparison purposes, a fuzzy set‐based approach was used to determine the best compromise solutions from the Pareto fronts obtained by multi‐objective PSO. The candidate parameter sets determined from different single‐objective and multi‐objective calibration scenarios were tested against the fourth event in the verification stage, where the initial abstraction parameters were recalibrated. A step‐by‐step screening procedure was used in this stage while evaluating and comparing the candidate parameter sets, which resulted in a few promising sets that performed well with respect to at least three of four performance criteria. The promising sets were all from the multi‐objective calibration scenarios which revealed the outperformance of the multi‐objective calibration on the single‐objective one. However, the results indicated that an increase of the number of objective functions did not necessarily lead to a better performance as the results of bi‐objective function calibration with a proper combination of objective functions performed as satisfactorily as those of triple‐objective function calibration. This is important because handling multi‐objective optimization with an increased number of objective functions is challenging especially from a computational point of view. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
23.
Microgranular enclaves are common in the Jurassic Aligoodarz granitoids of western Iran. Enclaves Enclosed in Granodiorite (EEG) and Enclaves Enclosed in Tonalite (EET) are different but they overlap their hosts on variation diagrams. The EEG is compositionally intermediate between tonalite and granodiorite. Mixing between tonalitic and granodioritic magmas and fractional crystallization are two models examined as the origin of the EEG. Field, textural, mineralogical and chemical observations suggest that chemical equilibration, common in magma mixing, was not attained between the EEG and its host. This, together with other observations does not support magma mixing as a mechanism for forming the EEG. Alternatively, excessive nucleation of biotite ± Fe-Ti-oxides ± amphibole by rapid cooling at borders of a shallow magma chamber and later fragmentation and dispersal by dynamic arc plutonism best explains the EEG. However, channeling of a new magma into the nearly solid tonalitic host explains formation of the EET.  相似文献   
24.
A systematic study of the linear thermal instability of a self-gravitating magnetic molecular cloud is carried out for the case when the unperturbed background is subject to local expansion or contraction. We consider the ambipolar diffusion, or ion-neutral friction on the perturbed states. In this way, we obtain a non-dimensional characteristic equation that reduces to the prior characteristic equation in the non-gravitating stationary background. By parametric manipulation of this characteristic equation, we conclude that there are, not only oblate condensation forming solutions, but also prolate solutions according to local expansion or contraction of the background. We obtain the conditions for existence of the Field lengths that thermal instability in the molecular clouds can occur. If these conditions establish, small-scale condensations in the form of spherical, oblate, or prolate shape may be produced via thermal instability.  相似文献   
25.
Significant potential exists for CO2 sequestration in coalbed methane reservoirs of the Black Warrior basin. Reservoir simulation is an appropriate approach to estimate both the storage capacity and methane recovery enhancement. However, prior to a reliable reservoir modeling and simulation, conducting an accurate and comprehensive reservoir characterization study is necessary. The purpose of the present study is twofold: (a) to provide a rigorous reservoir characterization study required for modeling Mary Lee coal group in the Blue Creek field of the Black Warrior basin; (b) to run fluid flow simulations to predict the performance of ECBM process applied to an under pressured zone of the Mary Lee coal group. According to the current well configuration of Blue Creek field, three applicable well patterns, namely a direct line drive, an inverted 5-spot and a normal 5-spot were separately (i.e., in three distinct cases) used for simulating ECBM. Simulations were run on an approximately 32 ha (80-acre) drainage area, and included coal matrix shrinkage/swelling effects. The injected gas was assumed to be pure CO2. Using an inverted 5-spot pattern, simulations predicted that after 7.5 years of CO2 injection, approximately 32,000 tonnes of CO2 would be sequestered per 32 ha of this zone and that methane recovery would be enhanced by 36 %. Using a normal 5-spot pattern, CO2 breakthrough would occur 2.4 years earlier, and about 40,000 tonnes CO2 would be sequestered. However, methane production would be enhanced by 33 %. Considering methane recovery enhancement, direct line drive pattern delivered poor results in comparison with two other patterns. As expected, the results also showed that CO2 injection would increase water production.  相似文献   
26.
The Niyasar plutonic complex, one of the Cenozoic magmatic assemblages in the Urumieh‐Dokhtar magmatic belt, was the subject of detailed petrographic and mineralogical investigations. The Niyasar magmatic complex is composed of Eocene to Oligocene mafic rocks and Miocene granitoids. Eleven samples, representing the major rock units in the Niyasar magmatic complex and contact aureole were chosen for mineral chemical studies and for estimation of the pressure, temperature, and oxygen fugacity conditions of mineral crystallization during emplacement of various magmatic bodies. The analyzed samples are composed of varying proportions of quartz, plagioclase, K‐feldspar, hornblende, biotite, titanite, magnetite, apatite, zircon, garnet, and clinopyroxene. Application of the Al‐in‐hornblende barometer indicates pressures of around 0.2 to 0.4 kbar for the Eocene–Oligocene mafic bodies and around 0.5 to 1.7 kbar for the Miocene granitoids. Hornblende‐plagioclase thermometry yields relatively low temperatures (661–780 °C), which probably reflect late stage re‐equilibration of these minerals. The assemblage titanite–magnetite–quartz as well as hornblende composition were used to constrain the oxygen fugacity and H2O content during the crystallization of the parent magmas in the Miocene plutons. The results show that the Miocene granitoids crystallized from magmas with relatively high oxygen fugacity and high H2O content (~5 wt% H2O). The Miocene granitoids show similar range of oxygen fugacity, H2O contents and mineral chemical compositions, which indicate a common source for their magmas. Although the crystallization pressures of the Miocene plutons discriminate various categories of plutonic bodies emplaced at depths of about 5.7–6.5 km (Marfioun pluton), about 4.2 km (Ghalhar pluton) and 1.9–2.3 km (Poudalg pluton), they were later uplifted to the same level by vertical displacement of faults. The emplacement depths of the Niyasar plutons suggest that the central part of the Urumieh‐Dokhtar magmatic belt has experienced an uplift rate of ca. 0.25–0.4 mm/yr from the Miocene onwards.  相似文献   
27.
Stochastic optimization methods are used for optimal design and operation of surface water reservoir systems under uncertainty. Chance-constrained (CC) optimization with linear decision rules (LDRs) is an old approach for determining the minimum reservoir capacity required to meet a specific yield at a target level of reliability. However, this approach has been found to overestimate the reservoir capacity. In this paper, we propose the reason for this overestimation to be the fact that the reliability constraints considered in standard CC LDR models do not have the same meaning as in other models such as reservoir operation simulation models. The simulation models have fulfilled a target reliability level in an average sense (i.e., annually), whereas the standard CC LDR models have met the target reliability level every season of the year. Mixed integer nonlinear programs are presented to clarify the distinction between the two types of reliability constraints and demonstrate that the use of seasonal reliability constraints, rather than an average reliability constraint, leads to 80–150 % and 0–32 % excess capacity for SQ-type and S-type CC LDR models, respectively. Additionally, a modified CC LDR model with an average reliability constraint is proposed to overcome the reservoir capacity overestimation problem. In the second stage, we evaluate different operating policies and show that for the seasonal (average) reliability constraints, open-loop, S-type, standard operating policy, SQ-type, and general SQ-type policies compared to a model not using any operation rule lead to 190–460 % (200–550 %), 100–200 % (80–300 %), 0–90 % (0–60 %), 30–90 % (0–20 %), and 10–90 % (0–10 %) excess capacity, respectively.  相似文献   
28.
Mineralogy and Petrology - The chloritization of biotite and stable isotopes of silicate have been studied for the Zafarghand porphyry copper deposit, Ardestan, Iran. The studied area, in the...  相似文献   
29.
A new method is proposed for generating artificial earthquake accelerograms from response spectra. This method uses the learning capabilities of neural networks to developed the knowledge of the inverse mapping from the response spectra to earthquake accelerogram. In the proposed method the neural networks learn the inverse mapping directly from the actual recorded earthquake accelerograms and their response spectra. A two-stage approach is used. In the first stage, a replicator neural network is used as a data compression tool. The replicator neural network compresses the vector of the discrete Fourier spectra of the accelerograms to vectors of much smaller dimension. In the second stage, a multi-layer feed-forward neural network learns to relate the response spectrum to the compressed Fourier spectrum. A simple example is presented, in which only 30 accelerograms are used to train the two-stage neural networks. This example demonstrates how the method works and shows its potential. © 1998 John Wiley & Sons, Ltd.  相似文献   
30.
We use a three-dimensional mixed-wet random network model representing Berea sandstone to extend our previous work on relative permeability hysteresis during water-alternating-gas (WAG) injection cycles [Suicmez, VS, Piri, M, Blunt, MJ, 2007, Pore-scale simulation of water alternate gas injection, Transport Porous Med 66(3), 259–86]. We compute the trapped hydrocarbon saturation for tertiary water-flooding, which is water injection into different initial gas saturations, Sgi, established by secondary gas injection after primary drainage. Tertiary water-flooding is continued until all the gas and oil is trapped. We study four different wettability conditions: water-wet, weakly water-wet, weakly oil-wet and oil-wet. We demonstrate that the amounts of oil and gas that are trapped show surprising trends with wettability that cannot be captured using previously developed empirical trapping models. We show that the amount of oil that is trapped by water in the presence of gas increases as the medium becomes more oil-wet, which is opposite from that seen for two-phase flow. It is only through a careful analysis of displacement statistics and fluid configurations that these results can be explained. This illustrates the need to have detailed models of the displacement processes that represent the three-phase displacement physics as carefully as possible. Further work is needed to explore the full range of behavior as a function of wettability and displacement path.  相似文献   
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