对应分析方法在粤西水东湾动力沉积环境分析的应用

本文以粤西水东湾表层沉积物样品的粒度分布为基本数据,使用对应分析方法并结合地形与波流特征,分析了海湾动力沉积环境。分析结果表明,海湾现代沉积环境可划分为4个动力沉积区。     

Seasonally Hypersaline Estuaries in Mediterranean-climate Regions

Data collected in three Californian estuaries indicate that hypersaline conditions exist during the dry summers typical of a Mediterranean climate. The generalised seasonal and longitudinal hydrographic structures are described and explained. It is argued that this seasonal hypersalinity is common and that it represents a major class of estuaries. The observed accumulation of salt indicates surprisingly long residence times in small basins which have free exchange with the ocean. This semi-isolation of the inner basin leads to a large build-up or severe depletion of nutrients, pollutants and plankton in these systems. Of concern are the trends to increase pollutant loading in the same systems that are experiencing an increase in residence times owing to freshwater extraction in the watershed.     

相对位移反分析的DFP优化方法及其工程应用

洞室围岩的某些参数,如弹性模量、强度参数等,对地下洞室的施工和设计具有极其重要的作用,直接进行这些参数的现场测量势必要耗费大量的物资和精力,在这种背景下,位移反分析的工程应用具有很重要的理论和实用价值。但洞室工程中大量不确定性因素的存在使得监测结果不可避免地存在随机性,有时会使得变形监测结果产生较大的误差,甚至失真。因此以监测结果的绝对值所反演得到的参数可能是错误的。在这种情况下,以监测数据的相对值进行参数反演在一定程度上可以消除测量误差。基于相对位移的随机反分析法并结合DFP优化算法开发了基于相对位移的随机反分析法,将其应用于一具体洞室工程中反演其弹性模量取得了较为理想的效果。     

城市微博数据驱动的群体疫情情感响应时空特征——以武汉市和石家庄市新冠疫情为例

研究城市大规模人群对疫情的情感响应时空特征,对于安抚人们情感状态以及优化防控措施具有重要意义。该文以带有地理标签的新浪微博数据为主要数据源,结合实地调查问卷,提出疫情场景下城市用户群体多维情感响应时空特征分析框架,该框架重点构建了城市用户群体对于疫情的多维情感强度的精确评估方法;在此基础上,分析疫情情感响应在时空维度上的变化特征,解析情感响应的显著影响因子。研究结果表明:1)该文提出的疫情情感响应评估方法,可准确量化疫情场景下城市群体多维情感响应强度;2)疫情防控期间政府采取的防控措施能够有效安抚城市群体愤怒、恐惧等负面情感;3)喜悦情感是疫情防控期间城市群体情感响应的主体情感;4)面对疫情再次发生,城市群体负面情感强度上升幅度会显著下降。该研究可为政府部门增强疫情情感监测能力、提升情感治理水平提供方法参考和决策依据。     

Arctic sea-ice motion and its relation to pressure field

Daily Arctic sea-ice motion maps during the winter seasons (December–March) from December 1988 to March 2003 derived from NSCAT, QuikSCAT, SSM/I, and AMSRE data by a wavelet analysis method have been merged with those derived from buoy data. These merged sea-ice motion data have been used to study the circulation regimes and winter-to-winter variability of Arctic sea-ice motion. The relation between sea-ice motion and the pressure field in the Arctic Ocean was also studied by applying Principal Component Analysis (PCA) to the monthly merged sea-ice motion data and the monthly pressure field data from IABP. The mean Arctic sea-ice motion map of the 15 winter seasons has two distinct features: the Beaufort Gyre and a cyclonic circulation system in the Eurasian Basin, which moves ice from the Laptev Sea to Fram Strait. The strengths and sizes of the two features change from one winter season to another. Seasons with a strong or normal Beaufort Gyre alternate with seasons with a weak or no Beaufort Gyre every one to three seasons. The principal components of the first two modes of PCA of the monthly sea-ice motion are closely correlated with their counterparts of the monthly pressure field in the Arctic Ocean. The mode-one components of these two anomalies alternate between anticyclonic and cyclonic circulation systems. The correlation between Arctic Oscillation indexes and the principal components of the first mode of PCA of the monthly Arctic sea-ice motion is low but statistically significant.     

Numerical simulation of ground flow caused by seismic liquefaction

Flow failure of sandy subsoil induced by seismic liquefaction is known to cause significant damage to structures. It is induced not only by the dynamic forces exerted by seismic acceleration but also by the static gravity force in consequence of the topography of the ground. The ground flow may sometimes continue after the end of the seismic loading and finally the ground is significantly deformed to cause a failure.This paper numerically predicts the magnitude of flow that could occur when soil liquefaction continues for a sufficiently long period. It is considered that liquefied soil behaves like a viscous liquid, and hence, ground flow is governed by the principle of minimum potential energy. In the calculation, liquefied sand is assumed to be a viscous liquid that deforms in undrained conditions with its volume remaining constant. To consider the non-linearity due to large displacement, the updated Lagrangian method is used to solve the equation of motion. The Newmark β method is employed to calculate the time history of the ground motion. Finally, a simulation using this calculation method shows that the proposed method gives reasonable results for the conditions indicated.     

Si diffusion in zircon

Self-diffusion of Si under anhydrous conditions at 1 atm has been measured in natural zircon. The source of diffusant for experiments was a mixture of ZrO₂ and ³⁰Si-enriched SiO₂ in 1:1 molar proportions; experiments were run in crimped Pt capsules in 1-atm furnaces. ³⁰Si profiles were measured with both Rutherford backscattering spectrometry (RBS) and nuclear reaction analysis with the resonant nuclear reaction ³⁰Si(p,γ)³¹P. For Si diffusion normal to c over the temperature range 1,350–1,550°C, we obtain an Arrhenius relation D = 5.8 exp(−702 ± 54 kJ mol⁻¹/RT) m² s⁻¹ for the NRA measurements, which agrees within uncertainty with an Arrhenius relation determined from the RBS measurements [62 exp(−738 ± 61 kJ mol⁻¹/RT) m² s⁻¹]. Diffusion of Si parallel to c appears slightly faster, but agrees within experimental uncertainty at most temperatures with diffusivities for Si normal to c. Diffusion of Si in zircon is similar to that of Ti, but about an order of magnitude faster than diffusion of Hf and two orders of magnitude faster than diffusion of U and Th. Si diffusion is, however, many orders of magnitude slower than oxygen diffusion under both dry and hydrothermal conditions, with the difference increasing with decreasing temperature because of the larger activation energy for Si diffusion. If we consider Hf as a proxy for Zr, given its similar charge and size, we can rank the diffusivities of the major constituents in zircon as follows: D _Zr < D _Si << D _{O, dry} < D _{O, ‘wet’}.     

Effect of spatial variability of cross‐correlated soil properties on bearing capacity of strip footing

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of cross‐correlated soil properties is presented and applied to study the bearing capacity of spatially random soil with different autocorrelation distances in the vertical and horizontal directions. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two‐dimensional cross‐correlated non‐Gaussian random fields are generated based on a Karhunen–Loève expansion in a manner consistent with a specified marginal distribution function, an autocorrelation function, and cross‐correlation coefficients. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses was performed to study the effects of uncertainty due to the spatial heterogeneity on the bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to geotechnical problems and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment. Copyright © 2009 John Wiley & Sons, Ltd.     

A stability analysis of a conduit flow model for lava dome eruptions

Periodic variations in magma discharge rate and ground deformation have been commonly observed during lava dome eruptions. We performed a stability analysis of a conduit flow model by Barmin et al. [Barmin, A., Melnik, O., Sparks, R.S.J., 2002. Periodic behavior in lava dome eruptions. Earth and Planetary Science Letters 199 (1-2), 173–184], in which the periodic variations in magma flow rate and chamber pressure are reproduced as a result of the temporal and spatial changes of the magma viscosity controlled by the kinetics of crystallization. The model is reduced to a dynamical system where the time derivatives of the magma flow rate (dQ/dt) and the chamber pressure (dP/dt) are functions of Q and P evaluated at a shifted time t − t_?. Here, the time delay t_? represents the time for the viscosity of fluid particle to increase in a conduit. The dynamical system with time delay is approximated by a simple two-dimensional dynamical system of Q and P where t_? is given as a parameter. The results of our linear stability analyses for these dynamical systems indicate that the transition from steady to periodic flow depends on nonlinearities in the steady state relation between Q and P. The steady state relation shows a sigmoidal curve in Q − P phase plane; its slope has negative values at intermediate flow rates. The steady state solutions become unstable, and hence P and Q oscillate periodically, when the negative slope of the steady state relation ([dP/dQ]_S) exceeds a critical value; that is [dP/dQ]_S < − t_?γ/(2V_ch), where V_ch is the chamber volume and γ is an elastic constant which is related to the rigidity of chamber wall. We also found that the period and the pattern of oscillation of the conduit flow primarily depend on a quantity defined by LV_ch/r⁴, where L is the conduit length and r is the conduit radius.     

Correlation study between ground motion intensity measure parameters and deformation demands for bilinear SDOF systems

The correlation between ground motion intensity measures （IM） and single-degree-of-freedom （SDOF） deformation demands is described in this study. Peak ground acceleration （APG）, peak ground velocity （VPG）, peak ground displacement （DPG）, spectral acceleration at the first-mode period of vibration [As（T1）] and ratio of VPG to APG are used as IM parameters, and the correlation is characterized by correlation coefficients p. The numerical results obtained by nonlinear dynamic analyses have shown good correlation between As（T1） or VPG and deformation demands. Furthermore, the effect of As（T1） and VPG as IM on the dispersion of the mean value of deformation demands is also investigated for SDOF systems with three different periods T=0.3 s, 1.0 s, 3.0 s respectively.