年轻星天体的质量

质量是恒星最基本、最重要的物理量之一,它在恒星形成和演化过程中起着至关重要的作用.年轻星天体的形成机制以及早期演化过程是彻底解决恒星形成问题的关键所在,而年轻星天体形成过程中的物质下落、质量吸积以及外流等物理过程都与年轻星天体的质量密切相关.该文介绍了确定年轻星天体质量的一些常用方法,包括利用开普勒定律的动力学方法、赫罗图方法、年轻星天体脉动方法和磁层吸积方法等.并对这些方法的适用范围及测量精度进行了评述,还综述了各种方法的研究进展及未来可能的发展.     

Prediction of local scour around circular piles under waves using a novel artificial intelligence approach

Abstract

The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.     

Updated Support Vector Machine for Seismic Liquefaction Evaluation Based on the Penetration Tests

Simplified techniques based on in situ testing methods are commonly used to predict liquefaction potential. Many of these simplified methods are based on finding the liquefaction boundary separating two categories (the occurrence or non-occurrence of liquefaction) through the analysis of liquefaction case histories. As the liquefaction classification problem is highly nonlinear in nature, it is difficult to develop a comprehensive model taking into account all the independent variables, such as the seismic and soil properties, using conventional modeling techniques. Hence, in many of the conventional methods that have been proposed, simplified assumptions have been made. In this study, an updated support vector machine (SVM) based on particle swarm optimization (PSO) is used to evaluate liquefaction potential in two separate case studies. One case is based on standard penetration test (SPT) data and the other is based on cone penetration test (CPT) data. The SVM model effectively explores the relationship between the independent and dependent variables without any assumptions about the relationship between the various variables. This study serves to demonstrate that the SVM can “discover” the intrinsic relationship between the seismic and soil parameters and the liquefaction potential. Comparisons indicate that the SVM models perform far better than the conventional methods in predicting the occurrence or non-occurrence of liquefaction.     

A model with rigid rotations and slip deficits for the GPS-derived velocity field in Southwest Japan

We interpret the GPS-derived velocity field in southwest Japan by a superposition of the elastic deformation caused by fault interactions (slips or slip deficits) on the rigid motion of tectonic blocks (or plates). Based on the strain rate field and crustal seismicity, we apply a model with three blocks (Inner Arc, Outer Arc, and the northern Ryukyu block) and slip deficits along the block boundaries.Several characteristics of the synthesized contributions are found:

(1) Westward motion of the outer arc relative to the Amurian plate and the inner arc,

(2) southeastward motion of the northern Ryukyu block relative to the Amurian plate,

(3) 2−4 mm/yr deficits of left lateral slip rates along the boundary at 32°N in southern Kyushu,

(4) 0−8 mm/yr deficits of right lateral slip rates along the Median Tectonic Line and the Beppu-Shimabara Graben,

(5) slip deficit rates on the plate interface smaller than those in the case without any consideration for rigid block motions,

(6) clockwise deflection of slip deficit rate vector on the plate interface from that estimated when not taking rigid block motions into consideration.

基于数字图像分析的土工合成材料加筋砂土拉拔试验研究

由于加筋土界面作用的复杂性,加筋土工程建设中铺设土工格栅时往往采用经验的方法,很大程度上造成了土工格栅的浪费及工程安全隐患,理清不同填料筋土界面作用的影响范围,有助于确定加筋土结构的合理加筋间距。为了揭示不同填料筋土界面作用的影响范围,采用4种不同类型的砂土与格栅在不同法向应力下进行了一系列的拉拔试验,并结合数字图像量测技术,分析了不同类型砂土下界面剪切带厚度、颗粒位移矢量、格栅拉拔阻力峰值及应变等演变规律。研究表明：界面剪切带厚度H随法向应力σ_v与砂土平均粒径d₅₀的增加而增大,通过多变量拟合的方法,得到了H、σ_v与d₅₀三者之间的函数表达式;格栅在拉拔过程中,砂土颗粒位移矢量以土工格栅为界有着显著的差别,格栅上部的颗粒位移矢量明显大于下部颗粒,且在格栅上下一定范围内会形成颗粒位移矢量集中带;拉拔阻力峰值随σ_v及d₅₀的增加而增大;不同类型砂土各区段的格栅应变均表现出由前向后依次递减的趋势。     

基于改进SOFM的矢量量化图像压缩

在介绍矢量量化和自组织特征映射神经网络的基础上，针对基于自组织特征映射神经网络的矢量量化算法，在初始码书生成、获胜神经元搜索策略以及调整获胜码字及其拓扑领域权值等方面进行改进。实验结果表明改进算法具有合理性和有效性。     

参数优化LSSVM的巷道围岩松动圈预测研究

最小二乘支持向量机方法(LSSVM)在处理小样本、高维数、非线性的问题时,具有求解速度快、易于描述非线性关系的优良特性。但是,该方法得到的模型拟合精度和泛化能力依赖于其相关参数,因此,提出基于粒子群优化算法(PSO)的LSSVM参数优选方法。最后,用该模型对巷道围岩松动圈进行了预测研究。结果表明,PSO优化的LSSVM模型具有收敛速度快、计算精度高的特点,说明该模型是合理、有效的。     

Late Cenozoic stress states around the Bolu Basin along the North Anatolian Fault, NW Turkey

This study defines the Late Cenozoic stress regimes acting around the Bolu Basin along the North Anatolian Fault in northwestern Turkey. The inferred regional stress regime, obtained from the inversion of measured fault-slip vectors as well as focal mechanism solutions, is significant and induces the right-lateral displacement of the North Anatolian Fault. The field observations have also revealed extensional structures in and around the Bolu Basin. These extensional structures can be interpreted as either a local effect of the regional transtensional stress regime or as the result of the interaction of the fault geometries of the dextral Duzce Fault and the southern escarpment of the North Anatolian Fault, bordering the Bolu Basin in the north and in the south, respectively.The inversion of slip vectors measured on fault planes indicates that a strike-slip stress regime with consistent NW- and NE-trending σ_Hmax(σ₁) and σ_Hmin(σ₃) axes is dominant. Stress ratio (R) values provided by inversion of slip vectors measured on both major and minor faults and field observations show significant variations of principal stress magnitudes within the strike-slip stress regime resulting in older transpression to younger transtension. These two stress states, producing dextral displacement along NAF, are coaxial with a consistent NE-trending σ₃ axis. The earthquake focal mechanism inversions confirm that the transtensional stress regime has continued into recent times, having identical horizontal stress axis directions, characterized by NW and NE-trending σ₁ and σ₃ axes, respectively. A locally consistent NE-trending extensional, normal faulting regime is also seen in the Bolu Basin. The stress-tensor change within the strike-slip stress regime can be explained by variations in horizontal stress magnitudes that probably occurred in Quaternary times as a result of the westward extrusion of the Anatolian block.     

A minimalistic approach for evapotranspiration estimation using the Prophet model

ABSTRACT

This study aimed to evaluate the potential of the recently introduced Prophet model for estimating reference evapotranspiration (ETo). A comparative study was conducted for benchmarking the model results with support vector regression (SVR) and temperature-based empirical models (Thornthwaite and Hargreaves) in southern Japan. The performance of the Prophet, SVR and temperature-based empirical models was evaluated by Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R²). The results indicate that temperature-based Prophet and SVR models have greater accuracy than the empirical models. The Prophet model with sole input of relative humidity, sunshine hours or windspeed showed acceptable accuracy (NSE > 0.80; R² > 0.80), while SVR models with similar inputs showed greater errors. Accuracy improved with increasing number of input parameters, giving excellent performance (NSE > 0.95; R² > 0.95) with all input parameters. Hence, the Prophet model is a new promising approach for modelling ETo with limited input variables.     

基于离散Gabor变换的磁暴识别

以地磁秒数据为研究对象,通过离散Gabor变换将时域的地磁数据转换至二维时频面,提取Gabor变换谱图的均值和方差作为特征值,使用支持向量机实现地磁正常数据与磁暴干扰数据的自动分类识别。对5个地磁台的200组地磁秒数据进行计算分析,结果表明该方法对测试样本数据的识别率可达94%。