基于实测波浪的单桩式海上风电基础波浪力计算研究

基于实测波面的波浪力获取作为结构动力响应分析以及数字孪生模型建立的必备环节,对海上风电数字化运维至关重要。为了满足更大的装机容量需求,单桩式海上风电基础趋于大型化,其尺度因子D/L也随之增大;并且实际海域均为非规则波,以尺度因子划分波浪力计算理论的方法对非规则波的适用性尚不明确。通过建立数值水槽,依据实际工况对不规则波与桩基的作用进行数值模拟,得到入射波浪场与桩基所受波浪力,在此基础上,基于入射波浪场分别采用Morison方程以及绕射理论求解波浪力并将之与数值模拟结果进行对比,分析了不同波浪力计算理论关于尺度因子的适用性,同时探究了波浪要素对计算精度的影响。结果表明：Morison方程在波高较大时精度下降;相对于Morison方程,绕射理论在该尺度下的精度更高。最后,通过分析实测数据进一步探讨了典型工况下的波浪力特征,以期通过实测波面计算波浪力的方法为实际服役风机波浪力计算提供技术支持。     

西北太平洋九州-帕劳海脊北部KPR12岩芯40万年来有机碳来源、埋藏特征及其环境响应

西北太平洋海陆相互作用强烈,受黑潮和亚洲大陆风尘输入影响显著,是研究海洋沉积物中有机碳埋藏与陆源输入、海洋初级生产力和海洋环境演化关系的理想靶区。本研究基于采自九州-帕劳海脊北部的重力活塞647 cm长的KPR12岩芯,分析了总有机碳（TOC）、总氮（TN）、有机碳稳定碳同位素组成（δ¹³C_TOC）、蛋白石（Opal）以及粒度等指标,初步探讨了近40万年来轨道尺度沉积有机碳的来源、埋藏特征及其影响机制。岩芯的TOC含量平均值为0.214%,呈冰期较高、间冰期较低的旋回特征。岩芯沉积物粒度的不同端元反映了研究区风尘输入大致呈冰期较高的趋势。岩芯的δ¹³C_TOC（-25.24‰~-21.04‰,平均值为-22.59‰）显示有机质以海源为主（约62%）,海源有机碳含量趋势与TOC的变化一致。研究区不同时期陆源物质的输入受风尘输送和黑潮的综合控制,黑潮增强可能对该区间冰期陆源有机碳贡献的升高有一定影响。岩芯中TOC与Opal含量的相关性分析表明,海洋初级生产力可能不是控制该岩芯有机碳含量变化的主要原因。冰期-间冰期旋回中的深层水通风条件、黑潮和北太平洋中层水的发育以及陆源细颗粒物质输入可能共同影响着本区沉积有机碳的降解与埋藏保存。

     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Recent evolution of Lake Arreo,northern Spain: influences of land use change and climate

We present a high-resolution, multiproxy reconstruction of the depositional history of Lake Arreo, northern Spain, for the last 60 years. We conducted sedimentological, geochemical and diatom analyses in short cores and made a detailed comparison with regional instrumental climate data (1952–2007), limnological monitoring of the lake (1992–2008) and recent land use changes that affect the lake catchment. Chronology is based on “floating” discontinuous varve counts and ¹³⁷Cs and ¹⁴C dates. Four periods were identified in the Lake Arreo recent history: (1) prior to 1963, varved facies intercalated with fine turbidite deposits, and diatom assemblages dominated by Cyclotella taxa indicate predominantly meromictic conditions, (2) from 1964 to 1978, permanent anoxia persisted in bottom waters, as shown by similar facies and diatom assemblages as before, though detrital layers were coarser, (3) from 1979 to 1994, sediment delivery to the lake increased and laminated, clastic facies were deposited, and (4) from 1995 to 2008, dominance of massive facies and an increase in Fragilaria tenera and Achnanthes minutissima reflect relatively lower lake levels, less frequent bottom anoxia with more frequent water column mixing, similar to modern conditions. The period 1952–1979 was a time of meromixis and varved facies deposition, and was characterized by higher rainfall and less intense agricultural pressure in the watershed. There were two short humid periods (1992–1993 and 1996–1998) when monitoring data show more anoxic weeks per year and relatively higher lake levels. Increased cultivation of small landholdings in 1963, and particularly after 1979, caused a large increase in sediment delivery to the lake. The inferred lake evolution is in agreement with monitoring data that suggest a transition from dominantly meromictic conditions prior to 1993–1994 to a predominantly monomictic pattern of circulation since then, particularly after 2000. The synergistic effects of intensive water extraction for irrigation and lower rainfall since 1979, and particularly since 1994, brought the long period of meromictic conditions in Lake Arreo to an end. Water balance and sediment delivery to the lake are dominant factors that control the limnological and mixing conditions in Lake Arreo and they must be considered in management and restoration plans.     

High-precision repeat-groundtrack orbit design and maintenance for Earth observation missions

The focus of this paper is the design and station keeping of repeat-groundtrack orbits for Sun-synchronous satellites. A method to compute the semimajor axis of the orbit is presented together with a station-keeping strategy to compensate for the perturbation due to the atmospheric drag. The results show that the nodal period converges gradually with the increase of the order used in the zonal perturbations up to \(J_{15}\). A differential correction algorithm is performed to obtain the nominal semimajor axis of the reference orbit from the inputs of the desired nodal period, eccentricity, inclination and argument of perigee. To keep the satellite in the proximity of the repeat-groundtrack condition, a practical orbit maintenance strategy is proposed in the presence of errors in the orbital measurements and control, as well as in the estimation of the semimajor axis decay rate. The performance of the maintenance strategy is assessed via the Monte Carlo simulation and the validation in a high fidelity model. Numerical simulations substantiate the validity of proposed mean-elements-based orbit maintenance strategy for repeat-groundtrack orbits.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

High-efficiency calculation method for watershed rainfall-runoff routing using one-dimensional dynamic wave equations

Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations (HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictor-corrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.     

Identification of Gleissberg Cycles and a Rising Trend in a 315-Year-Long Series of Sunspot Numbers

We show in this short note that the method of singular spectrum analysis (SSA) is able to clearly extract a strong, clean, and clear component from the longest available sunspot (International Sunspot Number, ISN) time series (1700?–?2015) that cannot be an artifact of the method and that can be safely identified as the Gleissberg cycle. This is not a small component, as it accounts for 13% of the total variance of the total original signal. Almost three and a half clear Gleissberg cycles are identified in the sunspot number series. Four extended solar minima (XSM) are determined by SSA, the latest around 2000 (Cycle 23/24 minimum). Several authors have argued in favor of a double-peaked structure for the Gleissberg cycle, with one peak between 55 and 59 years and another between 88 and 97 years. We find no evidence of the former: solar activity contains an important component that has undergone clear oscillations of \(\approx90\) years over the past three centuries, with some small but systematic longer-term evolution of “instantaneous” period and amplitude. Half of the variance of solar activity on these time scales can be satisfactorily reproduced as the sum of a monotonous multi-secular increase, a \(\approx90\)-year Gleissberg cycle, and a double-peaked (\(\approx10.0\) and 11.0 years) Schwabe cycle (the sum amounts to 46% of the total variance of the signal). The Gleissberg-cycle component definitely needs to be addressed when attempting to build dynamo models of solar activity. The first SSA component offers evidence of an increasing long-term trend in sunspot numbers, which is compatible with the existence of the modern grand maximum.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.     

基于多源数据的新疆人居环境质量评价

针对区域人居环境质量缺乏从自然和人文因子组合综合评价分析的现状,利用遥感影像、站点监测、交通网络等多源数据,获取与人居环境质量密切相关的自然和人文因素共17个影响因子。应用熵权法、GIS空间分析及现代大数据等方法,定量研究新疆人居环境质量综合评价指数的空间分异及其与经济、人口分布的协调性关系。结果表明：① 新疆自然环境本底受水资源及植被覆盖情况影响较大,自然环境本底评价指数高值区域的空间分布特征与绿洲分散分布的特点具有极大的相似性,县域尺度的高质量区聚集分布在天山北坡的伊犁河谷等地,低质量区和一般质量区大面积集中连片地分布在新疆南部和东部。② 人文环境受交通通达程度及基础支撑完善度影响较大,地级市、县级市优于其他县级地区,人文环境质量基本呈现以各地级市、县级市为中心向外辐射递减的空间分异规律。③ 人居环境质量综合评价指数空间分异显著,呈现出以乌鲁木齐、昌吉市等点为中心的局部圈层式递减的空间分异规律。木垒?皮山分界线东南部与西北部人居环境质量的平均水平相差悬殊。④ 整体人居环境质量水平较低,人口分布与人居环境质量综合评价指数空间分布的匹配度不足,一般质量区和低质量区的县域土地面积占比高达84.90%,分布了47.74%的人口,低质量区仍有较大的提升潜力。⑤ GDP水平与人居环境质量保持较高的匹配性,环境经济协调型县市数量较少,环境经济滞后型县市数量最多,经济发展与人居环境相互掣肘,制约着新疆的可持续性发展。