Magnetically-aided evolution of protoplanetary disks

We investigate the global evolution of a turbulent protoplanetary disk incorporating the effects of Maxwell stress due to a large-scale magnetic field permeating the disk. A magnetic field is produced continuously by an dynamo and the resultant Maxwell stress assists the viscous stress in p roviding the means for disk evolution. The most striking feature of magnetized disk evolution is the presence of the surface density bulge located in the magnetic gap, the region of the disk where the degree of ionization is too low to allow for coupli ng between the magnetic field and the gas. The bulge persists for a time of the order of 10⁵–10⁶ yr. The presence and persistence of the surface density bulge may have important implications for the process of planet formation and the overall characteristics of resultant planetary systems.Operated by USRA under contract No. NASW-4574 with NASA.     

云南大地热流及地热地质问题

本文报道了云南20多个大地热流测试数据。据热流分布特点并参考前人有关资料,结合地球物理测深资料、岩石热物性与放射性生热率测试数据,对各区地壳深度范围的温度、热流配分组成作了粗略分析,划分出各有特征的若干地质-热流区。云南普遍地热偏高(滇东南小范围除外)的主要原因是新构造运动强烈;怒江以西近代岩浆活动亦强烈,具有典型的板块交汇带的基本地热特点     

220 ka以来萨拉乌苏河流域地层磁化率与气候变化

 萨拉乌苏河流域滴哨沟湾剖面磁化率变化结果表明:近220 ka来我国北方气候变化极不稳定,存在着不同尺度的频繁变化,特别是寒冷气候阶段变化尤为频繁,其中倒数第二次冰期存在5个气候旋回,末次冰期存在10个气候旋回。这些气候变化与深海氧同位素、极地冰芯反映的全球变化具有良好的对应关系,反映了该区气候变化与全球变化的一致性。控制本区气候变化的主要因素是全球冰量变化及太阳辐射影响的东亚季风变化。     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.     

Effects of magnetic interactions in anisotropy of magnetic susceptibility: Models, experiments and implications for igneous rock fabrics quantification

Besides granites of the ilmenite series, in which the anisotropy of magnetic susceptibility (AMS) is mainly controlled by paramagnetic minerals, the AMS of igneous rocks is commonly interpreted as the result of the shape-preferred orientation of unequant ferromagnetic grains. In a few instances, the anisotropy due to the distribution of ferromagnetic grains, irrespective of their shape, has also been proposed as an important AMS source. Former analytical models that consider infinite geometry of identical and uniformly magnetized and coaxial particles confirm that shape fabric may be overcome by dipolar contributions if neighboring grains are close enough to each other to magnetically interact. On these bases we present and experimentally validate a two-grain macroscopic numerical model in which each grain carries its own magnetic anisotropy, volume, orientation and location in space. Compared with analytical predictions and available experiments, our results allow to list and quantify the factors that affect the effects of magnetic interactions. In particular, we discuss the effects of (i) the infinite geometry used in the analytical models, (ii) the intrinsic shape anisotropy of the grains, (iii) the relative orientation in space of the grains, and (iv) the spatial distribution of grains with a particular focus on the inter-grain distance distribution. Using documented case studies, these findings are summarized and discussed in the framework of the generalized total AMS tensor recently introduced by Cañon-Tapia (Cañon-Tapia, E., 2001. Factors affecting the relative importance of shape and distribution anisotropy in rocks: theory and experiments. Tectonophysics, 340, 117–131.). The most important result of our work is that analytical models far overestimate the role of magnetic interaction in rock fabric quantification. Considering natural rocks as an assemblage of interacting and non-interacting grains, and that the effects of interaction are reduced by (i) the finite geometry of the interacting clusters, (ii) the relative orientation between interacting grains, (iii) their heterogeneity in orientation, shape and bulk susceptibility, and (iv) their inter-distance distribution, we reconcile analytical models and experiments with real case studies that minimize the role of magnetic interaction onto the measured AMS. Limitations of our results are discussed and guidelines are provided for the use of AMS in geological interpretation of igneous rock fabrics where magnetic interactions are likely to occur.     

The distribution of radiogenic heat production as a function of depth in the Sierra Nevada Batholith, California

Geochemical analyses and geobarometric determinations have been combined to create a depth vs. radiogenic heat production database for the Sierra Nevada batholith, California. This database shows that mean heat production values first increase, then decrease, with increasing depth. Heat production is 2 μW/m³ within the 3-km-thick volcanic pile at the top of the batholith, below which it increases to an average value of 3.5 μW/m³ at 5.5 km depth, then decreases to 0.5–1 μW/m³ at 15 km depth and remains at these values through the entire crust below 15 km. Below the crust, from depths of 40–125 km, the batholith's root and mantle wedge that coevolved beneath the batholith appears to have an average radiogenic heat production rate of 0.14 μW/m³. This is higher than the rates from most published xenolith studies, but reasonable given the presence of crustal components in the arc root assemblages. The pattern of radiogenic heat production interpreted from the depth vs. heat production database is not consistent with the downward-decreasing exponential distribution predicted from modeling of surface heat flow data. The interpreted distribution predicts a reasonable range of geothermal gradients and shows that essentially all of the present day surface heat flow from the Sierra Nevada could be generated within the 35 km thick crust. This requires a very low heat flux from the mantle, which is consistent with a model of cessation of Sierran magmatism during Laramide flat-slab subduction, followed by conductive cooling of the upper mantle for 70 m.y. The heat production variation with depth is principally due to large variations in uranium and thorium concentration; potassium is less variable in concentration within the Sierran crust, and produces relatively little of the heat in high heat production rocks. Because silica content is relatively constant through the upper 30 km of the Sierran batholith, while U, Th, and K concentrations are highly variable, radiogenic heat production does not vary directly with silica content.     

Comparison of methods to model the gravitational gradients from topographic data bases

A number of methods have been developed over the last few decades to model the gravitational gradients using digital elevation data. All methods are based on second-order derivatives of the Newtonian mass integral for the gravitational potential. Foremost are algorithms that divide the topographic masses into prisms or more general polyhedra and sum the corresponding gradient contributions. Other methods are designed for computational speed and make use of the fast Fourier transform (FFT), require a regular rectangular grid of data, and yield gradients on the entire grid, but only at constant altitude. We add to these the ordinary numerical integration (in horizontal coordinates) of the gradient integrals. In total we compare two prism, two FFT and two ordinary numerical integration methods using 1" elevation data in two topographic regimes (rough and moderate terrain). Prism methods depend on the type of finite elements that are generated with the elevation data; in particular, alternative triangulations can yield significant differences in the gradients (up to tens of Eötvös). The FFT methods depend on a series development of the topographic heights, requiring terms up to 14th order in rough terrain; and, one popular method has significant bias errors (e.g. 13 Eötvös in the vertical–vertical gradient) embedded in its practical realization. The straightforward numerical integrations, whether on a rectangular or triangulated grid, yield sub-Eötvös differences in the gradients when compared to the other methods (except near the edges of the integration area) and they are as efficient computationally as the finite element methods.