Modified Moving Particle Semi-implicit methods for the prediction of 2D wave impact pressure

As a gridless particle method, the MPS (Moving Particle Semi-implicit) method has proven useful in a wide variety of engineering applications including free-surface hydrodynamic flows. Despite its wide range of applicability, the MPS method suffers from some shortcomings such as non-conservation of momentum and spurious pressure fluctuation. By introducing new formulations for the pressure gradient and a new formulation of the source term of the Poisson Pressure Equation (PPE), and by allowing a slight compressibility, we have proposed modified MPS methods for the prediction of wave impact pressure on a coastal structure. The improved performance of the modified methods is shown through the simulation of numerous wave impact problems (including the impacts by a dam break flow, a flip-through and two cases of slightly-breaking waves) in comparison with the experimental data.     

低分子量肝素的制备及其结构与活性差异(英文)

低分子肝素作为一种抗血栓的多糖药物在临床中已应用了二十多年 ,目前已作为外科预防血栓形成药物 ,并在治疗急性静脉栓塞紊乱方面取代了未分级肝素。因肝素的来源和制备的方法不同使低分子肝素的精细结构不同 ,低分子肝素结构的复杂性 ,使得各产品的生物活性 ,例如抗蛋白酶活性不同 ,从而导致其临床使用的标准不同。该文将对低分子肝素的制备方法及其结构和抗蛋白酶活性的差异进行报导     

Laboratory study of deep-water breaking waves

In an attempt to elucidate the mechanics of deep-water wave breaking, a variety of breaking waves, including spilling and plunging waves, of different length scales and geometries was studied. The waves were generated through wave-wave interactions using wave packets with constant-steepness components, constant-amplitude components, and also components following the Pierson-Moskowitz distribution. Wave steepening prior to breaking were found to cause an increase in the high frequency spectral slope of the wave spectrum. The slopes were correlated to the type of breaking and the intensity of the breaking. The energy loss through breaking varied with the spectral characteristics of the wave packet. On the other hand, it was also noted that, irrespective of the wave packet, the losses were from the higher frequency end of the first harmonics.     

Statistical analysis of the effects on overland flow of spatial variability in soil hydraulic conductivity / Analyse statistique des effets de la variabilité spatiale de la conductivité hydraulique du sol sur l'écoulement de surface

Abstract

The effects of spatial variation of the saturated hydraulic conductivity (K _s ) of the soil on the variation of overland flow were tested by analysing 2000 synthetic rainfall—runoff events, all generated from real, observed rainfall events but with runoff modelled by a two-dimensional distributed model using different spatially variable K _s fields in a small (12 ha) agricultural catchment. The purpose is to determine the influence of spatial variation in K _s on runoff generation. The statistical measures used to describe the variation in the generated K _s were its coefficient of variation and correlation length. Both of these had two levels of typical values obtained from field measurements in other studies. The storms were analysed at a general event level, first using simple graphical and statistical methods and then using analysis of variance (ANOVA). The observed scale of the spatial variation of K _s does cause statistically significant variation in overland flow. The graphical analysis showed that the first flow peak in a multi-event storm had the largest variation and that differences were greater in the rising part of the hydrograph than in its recession. The greatest variation in overland flow was produced by the combination of the greater coefficient of variation and the longer correlation lengths. The smallest variation in overland flow was produced by the combination of the smaller coefficient of variation and the shorter correlation lengths. ANOVA showed that the coefficient of variation and correlation length alone did not explain all the variation of the total flow. ANOVA was not very useful due to the many restrictive assumptions that were not satisfied by the nature of the data and therefore analysis methods with less restrictive assumptions need to be tested.     

An approach for the determination of precipitation input for worst-case flood modelling

ABSTRACT

There is a lack of suitable methods for creating precipitation scenarios that can be used to realistically estimate peak discharges with very low probabilities. On the one hand, existing methods are methodically questionable when it comes to physical system boundaries. On the other hand, the spatio-temporal representativeness of precipitation patterns as system input is limited. In response, this paper proposes a method of deriving spatio-temporal precipitation patterns and presents a step towards making methodically correct estimations of infrequent floods by using a worst-case approach. A Monte Carlo approach allows for the generation of a wide range of different spatio-temporal distributions of an extreme precipitation event that can be tested with a rainfall–runoff model that generates a hydrograph for each of these distributions. Out of these numerous hydrographs and their corresponding peak discharges, the physically plausible spatio-temporal distributions that lead to the highest peak discharges are identified and can eventually be used for further investigations.

Editor A. Castellarin; Associate editor E. Volpi     

强矿震地球物理过程及短临阶段预测的研究

用区域强震震源机制解、现场地应力测量、三维有限差分数值模拟方法分析强矿震的孕震环境；通过定量观察采矿与矿震活动的相关性，分析强矿震的诱发原因；基于中尺度地震实验场高密度数字地震和前兆台网的现场观测，用地震学方法和小波工具分析强矿震孕震过程采集到的数据，提取短临阶段的异常信息；通过强矿震的震源机制解判断震源处的应力释放状态。提出地质构造环境、地应力场和采矿活动共同作用诱发强矿震的机理和次生应力场在孕育该震过程起主导作用的观点．发现震前短临阶段存在可信的b值、η值、频次、波速比等地震学异常和定点潮汐形变前兆异常，时异常信息的提取方法和强矿震短临阶段的预测进行了探讨。     

Missing precipitation data estimation using optimal proximity metric-based imputation,nearest-neighbour classification and cluster-based interpolation methods

Abstract

New optimal proximity-based imputation, K-nearest neighbour (K-NN) classification and K-means clustering methods are proposed and developed for estimation of missing daily precipitation records. Mathematical programming formulations are developed to optimize the weighting, classification and clustering schemes used in these methods. Ten different binary and real-valued distance metrics are used as proximity measures. Two climatic regions, Kentucky and Florida, (temperate and tropical) in the USA, with different gauge density and network structure, are used as case studies to evaluate the new methods. A comprehensive exercise is undertaken to compare the performances of the new methods with those of several deterministic and stochastic spatial interpolation methods. The results from these comparisons indicate that the proposed methods performed better than existing methods. Use of optimal proximity metrics as weights, spatial clustering of observation sites and classification of precipitation data resulted in improvement of missing data estimates.

Editor D. Koutsoyiannis; Associate editor C. Onof     

Beerkan multi-runs for characterizing water infiltration and spatial variability of soil hydraulic properties across scales

A method is presented for characterizing the spatial variability of water infiltration and soil hydraulic properties at the transect and field scales. The method involves monitoring a set of 10 Beerkan runs distributed over a 1-m length of soil, and running BEST (Beerkan estimation of soil transfer parameters) methods to derive hydraulic parameters. The Beerkan multi-runs (BMR) method provides a significant amount of data at the transect scale, allowing the determination of correlations between water infiltration variables and hydraulic parameters, and the detection of specific runs affected by preferential flow or water repellence. The realization of several BMRs at several transects on the same site allows comparison of the variation between locations (spatial variability at the field scale) and at the transect scale (spatial variability at the metre scale), using analysis of variance. From the results, we determined the spatial variability of water infiltration and hydraulic parameters as well as its characteristic scale (transect versus field).     

影响b值计算误差的Monte Carlo实验研究

本文假设地震的发生与时间的关系遵循稳态泊松模型,假设地震震级M服从参数为1/β的指数分布,其中β=b/loge,在此基础上生成地震目录.用最小二乘法估算b值,分别从样本数量、震级间隔、震级误差三方面分析b值误差的大小.统计分析结果表明,b值的标准偏差随着样本数量的增多而减小;随着震级间隔的增大而减小;震级误差使b值的标准误差变大.本文可以为利用真实地震目录求b值时选择适当的方法提供参考.