罗斯海海域大地水准面异常的成因研究

本文利用数值法求解瞬时地幔对流问题以模拟大地水准面异常.利用两个较新的S波速度异常层析模型SEMUCB_WM1和TX2019slab,将其转换为密度异常作为控制方程的浮力驱动项;采取的黏度结构模型中,上下地幔的黏度比为1∶50.为了研究地幔不同结构对罗斯海海域大地水准面异常的影响,分别提取上、下地幔的密度异常正/负值,作为对流控制方程的输入项,计算相应的模拟大地水准面异常.将模拟大地水准面异常与观测值进行对比,发现罗斯海海域的大地水准面异常主要来自下地幔及上地幔的负密度(波速)异常,下地幔正密度异常对该区域大地水准面负异常也有一定的贡献.本文认为,地幔密度负异常在罗斯海海域大地水准面异常的形成中占据主导作用,地幔对流的动力学效应对该区域大地水准面异常的形成影响较弱.     

Impact of the blockage ratio on the transport of sediment in the presence of a hydrokinetic turbine: Numerical modeling of the interaction sediment and turbine

Interactions between hydrokinetic turbines and near scale and far scale bed sediment particles are considered a critical area of assessment; however, a limited number of research studies have been published to address this issue. The current paper explores the influence of the blockage ratio on the morphology evolution downstream from a hydrokinetic turbine. A modeling framework is derived to predict the significant transport induced by a turbine installed on the erodible fluvial sandy bed surface, such as the Eulerian multi-phase model for the sediment and the Blade Element Momentum Theory (BEMT) for the turbine, using the open source platform OpenFOAM. Two configurations of different blockage ratios are considered. The configurations show differences in the bed morphology and the sediment transport. It has been shown for both configurations that the scour capabilities are enhanced below the turbine due to the acceleration of the flow and increasing local shear stress on the sediment.     

基于解析梯度的近地小天体探测机会搜索问题研究木

研究近地小天体的探测机会搜索问题．针对交会型探测任务,通过结合变分理论和状态转移矩阵推导了性能指标关于可调参数的解析偏导数,然后在搜索空间中随机生成初始点,并从这些初始点出发利用解析偏导数寻优,从而得到搜索空间内对应潜在发射机会的全部局部极小值点．此方法既在一定程度上保持了传统搜索方法全局搜索的特点,又克服了传统搜索方法的盲目性,因此计算速度获得很大提高．此外该方法可以对探测机会的搜索精度进行有效地控制．     

Object classification at the Nearby Supernova Factory

We present the results of applying new object classification techniques to the supernova search of the Nearby Supernova Factory. In comparison to simple threshold cuts, more sophisticated methods such as boosted decision trees, random forests, and support vector machines provide dramatically better object discrimination: we reduced the number of nonsupernova candidates by a factor of 10 while increasing our supernova identification efficiency. Methods such as these will be crucial for maintaining a reasonable false positive rate in the automated transient alert pipelines of upcoming large optical surveys. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Resource discovery with the VO registry

This article describes the VO registry concept and how it can be used to find resources – data sets, services and infrastructure – to support followup activities. It also discusses how VOEvent infrastructure components can be incorporated. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Automated probabilistic classification of transients and variables

There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic) follow‐up facilities with varied capabilities in terms of instruments, depth, cadence, wavelengths, etc., most of which are geared toward some specific astrophysical phenomenon. As the number of detected transient events grows, an automated, probabilistic classification of the detected variables and transients becomes increasingly important, so that an optimal use can be made of follow‐up facilities, without unnecessary duplication of effort. We describe a methodology now under development for a prototype event classification system; it involves Bayesian and Machine Learning classifiers, automated incorporation of feedback from follow‐up observations, and discriminated or directed follow‐up requests. This type of methodology may be essential for the massive synoptic sky surveys in the future. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

A modified peak‐bagging technique for fitting low‐𝓁 solar p‐modes

We introduce a modified version of a standard power spectrum ‘peak‐bagging’ technique which is designed to gain some of the advantages that fitting the entire low‐degree p‐mode power spectrum simultaneously would bring, but without the problems involved in fitting a model incorporating many hundreds of parameters. Employing Monte‐Carlo simulations we show that by using this modified fitting code it is possible to determine the true background level in the vicinity of the p‐mode peaks. In addition to this we show how small biases in other mode parameters, which are related to inaccurate estimates of the true background, are also consequently removed. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)