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101.
The creep degradation is a common phenomenon for soft structured clays. In this paper, the creep degradation behavior for soft structured clays is first studied by combining intrinsic creep behavior and the structure indicator. A creep-implicit model and a creep-explicit model corresponding to a stress-based and a creep-based structure indicators are developed, respectively, under one-dimensional condition. Parameters determination for both models is straightforward from oedometer tests. Coupled with consolidation theory, both models are used to simulate oedometer tests with different structural levels and load durations on three clays. The predictive ability of the two models on creep behavior, creep degradation behavior and evolution of structure indicator is analyzed. The relationship between the two structure indicators is discussed based on experimental results. The comparison between experimental and numerical results demonstrates that both models can accurately describe the creep degradation behavior of soft structured clay under one-dimensional loading. 相似文献
102.
Occultations and eclipses from ancient times down to the present are analysed to determine changes in the length of the day. By subtracting the expected tidal contribution from the observed changes, the non-tidal variations are obtained. The non-tidal varations are shown to occur on time-scales of decades and millennia. 相似文献
103.
The mixed layer depth (MLD) front and subduction under seasonal variability are investigated using an idealized ocean general circulation model (OGCM) with simple seasonal forcings. A sharp MLD front develops and subduction occurs at the front from late winter to early spring. The position of the MLD front agrees with the curve where \({\rm D}T_{\rm s}/{\rm D}t = \partial T_{\rm s} /\partial t + {\user2{u}}_{\rm g} \cdot \nabla T_{\rm s} = 0\) is satisfied (t is time, \({\user2{u}}_{\rm g}\) is the upper-ocean geostrophic velocity, \(T_{\rm s}\) is the sea surface temperature (SST), and \(\nabla\) is the horizontal gradient operator), indicating that thick mixed-layer water is subducted there parallel to the SST contour. This is a generalization of the past result that the MLD front coincides with the curve \({\user2{u}}_{\rm g} \cdot \nabla T_{\rm s} = 0\) when the forcing is steady. Irreversible subduction at the MLD front is limited to about 1 month, where the beginning of the irreversible subduction period agrees with the first coincidence of the MLD front and \({\rm D}T_{\rm s}/{\rm D}t =0\) in late winter, and the end of the period roughly corresponds to the disappearance of the MLD front in early spring. Subduction volume at the MLD front during this period is similar to that during 1 year in the steady-forcing model. Since the cooling of the deep mixed-layer water occurs only in winter and SST can not fully catch up with the seasonally varying reference temperature of restoring, the cooling rate of SST is reduced and the zonal gradient of the SST in the northwestern subtropical gyre is a little altered in the seasonal-forcing case. These effects result in slightly lower densities of subducted water and the eastward shift of the MLD front. 相似文献
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A. V. Melnikov S. G. Agafonenko I. V. Babichev Yu. G. Piskunov V. G. Moiseenko 《Doklady Earth Sciences》2013,449(2):380-385
The Upper Selemdzha minerogenic zone, which has the potential for noble metal mineralization in the Upper Amur, has been studied. It is confined to the thick strata of Paleozoic terrigeneous-sedimentary rocks (sandstones, siltstones, clay schists, packages of their thin rhythmical interlayering, sedimentary breccias, and conglomerates) in the Tokura subzone of the Selemdzha-Kerbinsk zone in the Amur-Okhotsk area of the Mongol-Okhotsk system, overlain by Early Cretaceous volcanogenic sedimentary rocks and intruded by Early Cretaceous quartz diorites, granodiorites, and dacites. In the Malomyr and Sagur-Semertak ore clusters, there are a few known potential deposits of noble metals and ore occurrences; when studied and prospected, they can exhibit vein-veinlet noble metal mineralization with rich contents of gold and platinoids in ore columns and metasomatic deposits. 相似文献
106.
Dorrik A. V. Stow 《Geo-Marine Letters》1983,3(2-4):217-222
The Brae oilfield reservoir in the North Sea comprises Upper Jurassic resedimented conglomerates and sandstones interbedded with organic-rich silstone and mudstone thin-bedded turbidites. The system represents a series of small overlapping fans that form a thick (300 m) slope-apron accumulation of sediments deposited in a narrow (<10 km wide) belt along an active fault zone. The complex lateral and vertical distribution of facies was due mainly to variable tectonic activity, and partly also to sediment supply and sea-level changes. 相似文献
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For many years, information on the solar mean magnetic field (SMMF) of the Sun—an important heliophysical and astrophysical parameter—was restricted to magnetographic measurements in only one spectral line, FeI λ525.02 nm. More informative observations of the Stokes-meter parameters of the SMMF were first initiated on a regular basis at the Sayan Solar Observatory. The availability of I and V data obtained simultaneously in several spectral lines has made it possible to study fundamentally new physical problems. In this paper, based on a comparison of SMMF observations in several spectral lines, we find high correlations in the data and important systematic differences in the magnetic-field strength B, which we interpret as a manifestation of kilogauss magnetic fields in fine-structure magnetic elements. Results of theoretical modeling of the SMMF strength ratios for the FeI λ525.02 nm-FeI λ524.70 nm and FeI λ630.15 nm-FeI λ630.25 nm lines are presented. The asymmetries of the V profiles of four lines near the FeI λ525.02 nm line are examined; these lines are important diagnostics for studies of small-scale dynamical processes. The Sayan Solar Observatory SMMF measurements are in good consistency with the Wilcox Solar Observatory data for 2003: for a comparison of N = 137 pairs of points in the two data sets, the correlation coefficient ρ is 0.92 for the linear regression between the datasets BWSO = 0.03(±0.05) + 0.93(±0.03)BSSO. 相似文献