Parametric Resonance Analyses for Spar Platform in Irregular Waves

The parametric instability of a spar platform in irregular waves is analyzed. Parametric resonance is a phenomenon that may occur when a mechanical system parameter varies over time. When it occurs, a spar platform will have excessive pitch motion and may capsize. Therefore, avoiding parametric resonance is an important design requirement. The traditional methodology includes only a prediction of the Mathieu stability with harmonic excitation in regular waves. However, real sea conditions are irregular, and it has been observed that parametric resonance also occurs in non-harmonic excitations. Thus, it is imperative to predict the parametric resonance of a spar platform in irregular waves. A Hill equation is derived in this work, which can be used to analyze the parametric resonance under multi-frequency excitations. The derived Hill equation for predicting the instability of a spar can include non-harmonic excitation and random phases. The stability charts for multi-frequency excitation in irregular waves are given and compared with that for single frequency excitation in regular waves. Simulations of the pitch dynamic responses are carried out to check the stability. Three-dimensional stability charts with various damping coefficients for irregular waves are also investigated. The results show that the stability property in irregular waves has notable differences compared with that in case of regular waves. In addition, using the Hill equation to obtain the stability chart is an effective method to predict the parametric instability of spar platforms. Moreover, some suggestions for designing spar platforms to avoid parametric resonance are presented, such as increasing the damping coefficient, using an appropriate RAO and increasing the metacentric height.     

一种基于Partial EIV模型的圆曲线拟合解法

针对圆曲线拟合问题,以圆曲线的参数方程为基础建立圆曲线拟合的EIV模型,根据系数矩阵的特点将模型转化为更合理的Partial EIV模型,通过公式变形为最小二乘形式,采用两步迭代法求解模型参数,保证系数矩阵中相同元素的改正数一致,常数元素的改正数为零。算例数据结果表明,所提算法的可行性、拟合精度相对较优。     

深海浮式结构物锚泊阻尼参数研究

阐述了锚泊阻尼定义以及当前各种研究方法,选取一组用于实际工程中的锚泊线参数.通过改变预张力、振幅、振荡频率、轴向刚度、法向拖曳力系数和表面流速等参数,研究各参数对锚泊水平阻尼及垂向阻尼的影响.为使研究一般化,文中锚泊阻尼以及预张力等参数采取无量纲形式.     

Non-Linear Response of Tethers Subjected to Parametric Excitation in Submerged Floating Tunnels

For the study of the non-linear response of inclined tethers subjected to parametric excitation in submerged floating tunnels,a theoretical model for coupled tube-tether vibration is developed.Upon the assumption that the static equilibrium position of the tether is a quadratic parabola,the governing differential equations of the tether motion are derived by use of the Hamilton principle.An approximate numerical solution is obtained by use of Galerkin method and Runge-kutta method.The results show that,when the static equilibrimn position of the tether is assumed to be a quadratic parabola,the tether sag effect on its vibration may be reflected;the tether sag results in the asymmetry of tether vibration amplitude;for the reduction of the tether amplitude,the buoyant unit weight of the tether should approach to zero as far as possible during the design.     

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隧道断面截取曲面拟合优化的点云简化方法

为了提高变形监测中地铁隧道断面点截取的效率,文章提出了基于kd-tree和法向量估计的局部点云简化方法,对BaySAC算法的三维激光点云二次参数曲面拟合方法进行改进:利用kd-tree建立点云数据的空间拓扑关系,计算出每个数据点的k邻域;然后使用平面拟合方法获取法矢量;最后根据点云数据法矢量变化程度,采用法矢量自适应得到压缩后的点云数据。实验证明该方法既能较大程度地简化点云,简化结果比较均匀,又具有不破坏细小特征的特点,进一步改进了BaySAC算法的二次参数曲面拟合方法。     

Long‐term change of seasonal snow cover and its effects on river runoff in the Tarim River basin,northwestern China

Spatio‐temporal variation of snow depth in the Tarim River basin has been studied by the empirical orthogonal function (EOF) based on the data collected by special sensor microwave/imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) during the period from 1979 to 2005. The long‐term trend of snow depth and runoff was presented using the Mann‐Kendall non‐parametric test, and the effects of the variations of snow depth and climatic factors on runoff were analysed and discussed by means of the regression analysis. The results suggested that the snow depth variation on the entire basin was characterised by four patterns: all consistency, north–south contrast, north‐middle‐south contrast and complex. The first pattern accounting 39·13% of the total variance was dominant. The entire basin was mainly affected by one large‐scale weather system. However, the spatial and temporal differences also existed among the different regions in the basin. The significant snow depth changes occurred mainly in the Aksu River basin with the below‐normal snow depth anomalies in the 1980s and the above‐normal snow depth anomalies in the 1990s. The long‐term trend of snow depth was significant in the northwestern, western and southern parts of the basin, whereas the long‐term trend of runoff was significant in the northwestern and northeastern parts. The regression analysis revealed that the runoff of the rivers replenished by snow melt water and rainfall was related primarily to the summer precipitation, followed by the summer temperature or the maximum snow depth in the cold season. Our results suggest that snow is not the principal factor that contributes to the runoff increase in headstreams, although there was a slow increase in snow depth. It is the climatic factors that are responsible for the steady and continuous water increase in the headstreams. Copyright © 2009 John Wiley & Sons, Ltd.     

Uncertainties in real‐time flood forecasting with neural networks

Although artificial neural networks (ANNs) have been applied in rainfall runoff modelling for many years, there are still many important issues unsolved that have prevented this powerful non‐linear tool from wide applications in operational flood forecasting activities. This paper describes three ANN configurations and it is found that a dedicated ANN for each lead‐time step has the best performance and a multiple output form has the worst result. The most popular form with multiple inputs and single output has the average performance. In comparison with a linear transfer function (TF) model, it is found that ANN models are uncompetitive against the TF model in short‐range predictions and should not be used in operational flood forecasting owing to their complicated calibration process. For longer range predictions, ANN models have an improved chance to perform better than the TF model; however, this is highly dependent on the training data arrangement and there are undesirable uncertainties involved, as demonstrated by bootstrap analysis in the study. To tackle the uncertainty issue, two novel approaches are proposed: distance analysis and response analysis. Instead of discarding the training data after the model's calibration, the data should be retained as an integral part of the model during its prediction stage and the uncertainty for each prediction could be judged in real time by measuring the distances against the training data. The response analysis is based on an extension of the traditional unit hydrograph concept and has a very useful potential to reveal the hydrological characteristics of ANN models, hence improving user confidence in using them in real time. Copyright © 2006 John Wiley & Sons, Ltd.     

Matched block bootstrap for resampling multiseason hydrologic time series

A nonparametric method for resampling multiseason hydrologic time series is presented. It is based on the idea of rank matching, for simulating univariate time series with strong and/or long‐range dependence. The rank matching rule suggests concatenating with higher likelihood those blocks that match at their ends. In the proposed method, termed ‘multiseason matched block bootstrap’, nonoverlapping within‐year blocks of hydrologic data (formed from the observed time series) are conditionally resampled using the rank matching rule. The effectiveness of the method in recovering various statistical attributes, including the dependence structure from finite samples generated from a known population, is demonstrated through a two‐level hypothetical Monte Carlo simulation experiment. The method offers enough flexibility to the modeller and is shown to be appropriate for modelling hydrologic data that display strong dependence, nonlinearity and/or multimodality in the time series depicting the hydrologic process. The method is shown to be more efficient than the nonparametric ‘k‐nearest neighbor bootstrap’ method in simulating the monthly streamflows that exhibit a complex dependence structure and bimodal marginal probability density. Even with short block sizes, this bootstrap method is able to predict the drought characteristics reasonably accurately. Copyright © 2005 John Wiley & Sons, Ltd.     

Changes and variation in the discharge regime of the Upper Suriname River Basin and its relationship with the tropical Pacific and Atlantic SST anomalies

Long‐term changes and variability in river flows in the tropical Upper Suriname River Basin in Suriname (2–6°N, 54–58°W) are analysed, including the relation to sea surface temperatures (SSTs) in the tropical Atlantic and Pacific Ocean. To analyse variability, lag correlation and statistical properties of the data series are used. Long‐term changes are analysed using parametric and non‐parametric statistical techniques. The analyses are performed for the period 1952–1985. The results show that both river discharge series at Semoisie and Pokigron are non‐stationary and have a negative trend. The negative rainfall trend in the centre of Suriname may be responsible for the negative trend in the annual river discharges in the basin. The highest correlation (Pearson's coefficient c) is obtained when the Tropical North Atlantic (TNA) SSTs lags the monthly discharges at Pokigron by 3–4 months (c = 0·7) and when the Tropical South Atlantic (TSA) SSTs lags the discharges by 4 months (c = ? 0·7). It also follows that the high (low) monthly flows, from April–August (September–March) are associated with increasing (decreasing) SSTs in the TNA and with decreasing (increasing) SSTs in the TSA. The results also reveal that years with low (high) discharges are more related to warmer (colder) SSTs during the year in the TNA region and a southward displacement of the Inter‐Tropical Convergence Zone (ITCZ). However, the Pacific El Niño (La Niña) events may also be responsible for low (high) flow years in this basin. Copyright © 2007 John Wiley & Sons, Ltd.