Daily precipitation concentration in Central Coast Vietnam

Theoretical and Applied Climatology - Empirical frequency distribution of daily precipitation amounts can be fitted by a negative exponential distribution, because anywhere there are many small...     

Effects of spectrum band width on the distribution of wave heights and periods

The statistical distribution of the crest-to-trough heights of narrowband nonlinear sea waves is derived in a semi-closed form. A quantitative comparison of the resulting density and exceedance probability distributions with those of the linear theory is given. It is shown that the nonlinearity of waves, even with steepnesses typical of extreme sea states, has an insignificant influence on the distribution of crest-to-trough heights.     

A second order Jupiter-Saturn planetary theory

We present a second order secular Jupiter-Saturn planetary theory through Poincaré canonical variables, von Zeipel's method and Jacobi-Radau referential. We neglect in our expansions terms of power higher than the fourth with respect to eccentricities and sines of inclinations. We assume that the disturbing function is composed of secular and critical terms only. We shall deriveF _2si and writeF _2s in terms of Poincaré canonical variables in Part II of this problem.     

The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment

This paper discusses patterns of annual and monthly precipitation variability at seven weather stations in east central Europe (1851–2007). Precipitation patterns were compared to three simple regional indices of atmospheric circulation, i.e., western circulation, southern circulation and the cyclonicity (C) index and a relationship between precipitation and the North Atlantic Oscillation index was identified. Correlations of the monthly records and multiple regression, using a principal components’ analysis, helped determine the statistical significance of the dependence of precipitation on the circulation indices. The Mann–Kendall test revealed no trend to change in any of the precipitation series, but a certain spatial regularity could be discerned in the phase of the annual periodic component. A common feature of the variability in central European annual precipitation is the dry period identified in the 1980s and the first half of the 1990s. In the northern part of the region, above-average precipitation was noted from the 1960s through to the mid-1970s as a result of the frequent prevalence of depressions. South of the divide, the wettest period was recorded at the turn of 1930s/1940s. After a number of very wet years in the last decade of the twentieth century and the beginning of the twenty-first century, precipitation began to fall at all of the region’s weather stations. The C index is the strongest circulation-linked factor influencing precipitation in central Europe and it accounts for more than 40% of the variance in spatially averaged wintertime precipitation.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化

The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover h...     

A New Equation for the Shear Strength of Cable Bolts Incorporating the Energy Balance Theory

The application of cable bolts as a secondary support system is an increasing trend in underground coal mines worldwide. The performances of cable bolts have been evaluated under both axial and shear loading conditions. Two methods of testing cables for shear, single and double shear, have been recognised. This paper examines the shear behaviour of a variety of cable bolts under different pre-tension loads by double shear testing. Plain, spiral and the combination of both cable types were used in this study. The initial axial load and the type of cable bolts are the main factors affecting their shear strength. By increasing the axial pre-tension load, the peak shear load occurs at lower shear displacement. The failure angle due to cable bending across the joint at different pre-tension loads varied between 41° and 49°. This demonstrates that the ratio of axial and perpendicular displacements is almost constant and on average the failure occurs at about 45°. A novel analytical model is proposed to evaluate the shear behaviour of pre-tensioned fully grouted cable bolts subjected to double shearing. Energy and Fourier Series methods were incorporated in the model to simulate the shear behaviour of cable bolts. The comparison of the experimental results with the proposed model shows a good agreement.     

The use of optimization to construct critical accelerograms for given structures and sites

In this paper a methodology has been presented for constructing the most critical accelerogram from among a be class of candidate accelerograms for a given site and structure. This most critical accelerogram could be used to assess seismic resistance of a structure with a high level of confidence. Specifically, the method superimposes accelerograms recorded at similar sites to create the candidate accelerograms, then uses optimization and approximation techniques find the most critical accelerogram. The most critical accelerogram is defined as the one which maximizes damage is structure, as computed by non-linear dynamic structural analysis, as well as satisfies constraints on ground parameters to ensure credibility. The damage has been defined as cumulative inelastic energy dissipation or sure of interstorey drifts. The method is applied to ten examples in the paper.     

Optimization of nonconventional wells under uncertainty using statistical proxies

The determination of the optimal type and placement of a nonconventional well in a heterogeneous reservoir represents a challenging optimization problem. This determination is significantly more complicated if uncertainty in the reservoir geology is included in the optimization. In this study, a genetic algorithm is applied to optimize the deployment of nonconventional wells. Geological uncertainty is accounted for by optimizing over multiple reservoir models (realizations) subject to a prescribed risk attitude. To reduce the excessive computational requirements of the base method, a new statistical proxy (which provides fast estimates of the objective function) based on cluster analysis is introduced into the optimization process. This proxy provides an estimate of the cumulative distribution function (CDF) of the scenario performance, which enables the quantification of proxy uncertainty. Knowledge of the proxy-based performance estimate in conjunction with the proxy CDF enables the systematic selection of the most appropriate scenarios for full simulation. Application of the overall method for the optimization of monobore and dual-lateral well placement demonstrates the performance of the hybrid optimization procedure. Specifically, it is shown that by simulating only 10% or 20% of the scenarios (as determined by application of the proxy), optimization results very close to those achieved by simulating all cases are obtained.