桥梁节段施工过程中混凝土时变模式分析

文章讨论了混凝土时变性能的分析模式及在时变荷载和时变位移下的徐变应变的数学模式，建立求徐变增量的递推公式，正确计算施工阶段的变位，实现施工控制。递推公式中徐变柔度系数ａｉ用最小二乘曲线拟合方法求得，较以往的递推公式有明显的优点。

急性肺动脉栓塞心电图多指标关联时变模式研究

目的:研究急性肺动脉栓塞(APE)的临床心电图动态演化规律,阐明其多样性表现的机制。方法:收集42个APE病例的心电图系列,每一例按记录时间顺序对7个特征性指标(心率,SⅠ、QⅢ、TⅢ、TV1,、STV、RV1或r'V1波)采样。分析该7个特征指标的时变特征,并总结归纳出APE心电图的多指标关联时变模式。结果:该时变理论模式表明,典型APE患者心电图随病程的动态变化,以TV1波倒置达峰时间为界,可化分为3个阶段。发病至TV1波倒置达峰前为第一阶段,TV1波倒置逐渐加深,表现为下降线,其它各指标在该阶段即已迅速完成上升或下降的演变而进入快速回复期,其时变模式曲线呈"反S"型或"S"型;第二阶段即为TV1波倒置达峰阶段,其时间大概处于TVI波总演变时间的前1/3处;自TVI波倒置达峰后至回复发病前水平为第三阶段。结论:临床APE心电图表现之多样性,是不同阶段各指标的联合表现特征和形式多样性的反映。该时变模式曲线可应用于临床判断疾病阶段。

重大洪涝灾害过程灾情时变模式挖掘

重大洪涝灾害过程中,各个不同时间节点上报的灾情指标形成了时间序列,其时变模式表征了灾情随时间的变化,反映了灾情的出现、发展、平稳的全过程,能够为洪涝灾害风险评估和损失研判提供重要依据。针对民政部近年来积累的重大洪涝灾害过程灾情数据,建立了灾情指标时间序列的负指数模型,提出了时变模式的挖掘方法,并通过案例数据对模型和方法进行了数值仿真验证。实验结果表明,所提模型能够较好地拟合洪涝灾害过程中灾情随时间的变化规律。

时变的准三维“红闪”电场模式研究

利用数值模拟的方法,研究了雷暴放电后,由雷暴电荷、感应电荷和晴天大气的背景电荷共同产生的准静电场(Quasi electrostaticfield ,简称QEF)的时变过程,以及准静电场对中性大气的加热和电离.结果表明:在考虑电离层电势和晴天大气背景电场的影响后,时变的准三维的准静电场(QEF)模式能较好地解释“红闪”(Redsprites)的时空特征,特别是能模拟出“红闪”中的一种———“闪晕”(spritehalo)向上弯曲的空间结构.

时变对流模式下混凝土厚壁结构内生热场分布

针对高墩混凝土箱梁墩顶块水化热温度场分布状况,考虑了风速的影响,建立了时变对流热传导模式,利用ANSYS分别对时变对流换热系数和稳定对流换热系数下混凝土箱梁墩顶块水化热温度场进行了分析,总结了时变对流模式下混凝土箱梁墩顶块水化热温度场的分布规律,并与实测值进行了对比。研究结果表明:时变对流计算模式适合计算高墩混凝土箱梁墩顶块的水化热温度场;混凝土箱梁墩顶块水化热温度分布以腹板、顶板、底板与横隔板的交合部分为球心呈层状向外逐渐减小;随着时间的延伸,水化热温度分布形状相似,相应区域内温度值降低;时变对流换热系数下水化热温度峰值出现时间约为56 h,稳定对流换热系数下水化热温度峰值出现时间约为80h;风速对各测点的水化热温度峰值及其发生的时间影响较大,增大风速可降低水化热温度峰值,缩减温度峰值出现的时间。

考虑穿透性太阳辐射的一维时变海洋混合层数值模式

文章针对目前海洋分层模式中确定混合层深度方法的不足,利用最新发展的描述穿透性太阳短波辐射的经验公式,提出了一种易于在海洋分层模式中应用的一维时变混合层模式。并用模式结果与太平洋2°N95°W站点的观测资料进行了比较,结果吻合较好。研究还表明,由于考虑了穿透性太阳短波辐射的影响,新方法能很好地刻画混合层深度的短周期变化。

不同地区雷暴电荷结构的模式计算

利用二维时变轴对称模式和实际探空资料 ,模式计算了南昌、兰州和昌都 3个地区雷暴云的电荷结构 ,并对形成机制进行了讨论。结果表明 :兰州地区雷暴的上升气流速度最大 ,雷暴发展最快 ;南昌地区雷暴次之 ;昌都地区雷暴最弱。南昌地区雷暴的持续时间最长。在雷暴的初始阶段 3个地区都存在雷暴下部次正电荷区 ,在雷暴的成熟阶段兰州地区在感应和非感应起电机制的共同作用下雷暴呈明显的 3极性电荷结构 ,南昌地区的雷暴主要在感应起电机制作用下形成偶极性电荷结构 ,而昌都地区的雷暴在非感应起电机制作用下形成偶极性电荷结构。 3个地区的雷暴负电荷区中心基本处于 - 1 0～ - 2 0℃的同一温度区内。中国北方地区的温度层结有利于形成 3极性电荷结构 ,且通过非感应起电机制来完成。

计及时间演变和空间相关的多风电场短期功率预测

针对多风电场站和多时间步的日前风电功率预测问题,提出了同时计及单风场功率时间演变和多风电场间空间相关的深度时空融合多风电场短期功率预测模型。它由门控循环单元、多核卷积层和时变模式注意力机制共同构成。首先通过门控循环单元和多核卷积层分别提取各风电场历史风电数据的时序和多周期特征;然后引入时变模式注意力机制对多风电场时变特征的演变模式赋予相关性权重,同时实现对多风电场功率时间演变规律的纵向追踪与横向对比。中国北方某风电基地实际算例结果表明,所提预测模型能有效利用风电功率时空特性,与现有多种预测模型相比具有更高的预测精度和更强的风功率时变模式学习能力。

基于时变滤波经验模式分解的齿轮箱故障诊断

经验模式分解(Empirical Mode Decomposition,EMD)经常出现模态混叠问题。集总经验模式分解(Ensemble EMD,EEMD)能够在一定程度上缓解模态混叠,但是辅助白噪声的引入却破坏了原始EMD方法的时变滤波特性。为了提高齿轮箱故障诊断的效果,将时变滤波经验模式分解(Time Varying Filter for EMD,TVFEMD)引入到齿轮箱振动信号分析领域,提出了基于TVFEMD的齿轮箱故障诊断方法。将该方法用于分析包含着输出轴不对中故障的齿轮箱振动信号,结果表明,该方法能够有效地诊断出齿轮箱的不对中故障,与基于EMD和EEMD的方法相比具有明显的优势。

FNM method for estimating reliability of existing bridges

Combined with current specifications and stress characteristics of concrete filled steel tubular （CFST） arch bridges, the determination principle of safe-middle-failure threestage mode is given. Accordingly, damage probability and failure probability and the corresponding reliability indices are calculated; a direct relationship between reliability indices and three-stage working status is made. Based on the three-stage working mode, a combined FNM （finite element-neural network- Monte-Carlo simulation） method is put forward to estimate the reliability of existing bridges. According to time-dependent reliability theory, subsequent service time is divided into several stages; minimum samples required by the Monte-Carlo method are generated by random sampling; training samples are calculated by the finite element method, and the training samples are extended by the neural network; failure probability and damage probability are calculated by the Monte-Carlo method. Thus, time dependent reliability indices are obtained, and the working status is judged. A case study is investigated to estimate the reliability of an actual bridge by the FNM method. The bridge is a CFST arch bridge with an 83.6 m span and it has been in operation for 10 years. According to analysis results, in the tenth year, the example bridge is still in safe status. This conclusion is consistent with the facts, which proves the feasibility of the FNM method for estimating the reliability of existing bridges.

A Real-time Modeling of Photovoltaic Array

This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.

Temporal variations in internal tide multimodal structure on the continental shelf, South China Sea

Temporal variations in multimodal structures of diurnal( D_1) and semidiurnal( D_2) internal tides were investigated on the continental slope of the Dongsha Plateau, based on 2-month moored acoustic Doppler current profiler observations. Harmonic analysis indicated that the D_1 components( K_1 and O_1) dominated the internal tide field. The vertical structure of the K_1 constituent presented a first-mode structure while the M_2 constituent seemed to exhibit a high-mode structure. Amplitude spectra analysis of the current data revealed differences in baroclinic current amplitudes between different water depths. Temporal variations in modal structures ware analyzed, based on the D_1 and D_2 baroclinic tides extracted from the baroclinic velocity field with band-pass filters. Analysis showed that the magnitude of the D_1 internal tide current was much larger than the D_2 current, and temporal variations in the modal structure of the D_1 internal tide occurred on an approximately fortnightly cycle. The EOF analyses revealed temporal transformation of multimodal structures for D_1 and D_2 internal tides. The enhancement of the D_1 internal tide was mainly due to the superposition of K_1 and O_1, according to the temporal variation of coherent kinetic energy.

Diagnostic model construction and example analysis of habitat degradation in enclosed bay: II. spatiotemporal variations in habitat degradation in Sansha Bay

The process of habitat degradation varies in habitat type and driving force which shows certain spatial and temporal heterogeneity on regional scales. In the present study, a new diagnostic model for enclosed bay habitat degradation was established, with which the spatial and temporal variation patterns of habitat degradation during 1991–2012 in Sansha Bay, Fujian, China was investigated. The results show that anthropogenic disturbance is the major controlling factor for the habitat degradation in large temporal heterogeneity in the bay. On the other hand, the habitat degradation experienced signifi cant spatial variations among six sub-bays. Under the joint action of temporal and spatial heterogeneity, the degradation trend in growing scale shows a more signifi cant correlation with the distribution of local leading industries along shorelines. Therefore, we quantifi ed the main characters of habitat degradation in Sansha Bay, and have understood the relationship between the status of habitats spatio-temporal variation value and the main controlling factor leading to the changes. However, a defi ciency of this research is the lack of or inaccessible to the detailed data, which shall be better solved in the future study for accessing more data from more sources.

Improving the simulation of terrestrial water storage anomalies over China using a Bayesian model averaging ensemble approach

The ability to estimate terrestrial water storage(TWS)is essential for monitoring hydrological extremes(e.g.,droughts and floods)and predicting future changes in the hydrological cycle.However,inadequacies in model physics and parameters,as well as uncertainties in meteorological forcing data,commonly limit the ability of land surface models(LSMs)to accurately simulate TWS.In this study,the authors show how simulations of TWS anomalies(TWSAs)from multiple meteorological forcings and multiple LSMs can be combined in a Bayesian model averaging(BMA)ensemble approach to improve monitoring and predictions.Simulations using three forcing datasets and two LSMs were conducted over China's Mainland for the period 1979–2008.All the simulations showed good temporal correlations with satellite observations from the Gravity Recovery and Climate Experiment during 2004–08.The correlation coefficient ranged between 0.5 and 0.8 in the humid regions(e.g.,the Yangtze river basin,Huaihe basin,and Zhujiang basin),but was much lower in the arid regions(e.g.,the Heihe basin and Tarim river basin).The BMA ensemble approach performed better than all individual member simulations.It captured the spatial distribution and temporal variations of TWSAs over China's Mainland and the eight major river basins very well;plus,it showed the highest R value(>0.5)over most basins and the lowest root-mean-square error value(<40 mm)in all basins of China.The good performance of the BMA ensemble approach shows that it is a promising way to reproduce long-term,high-resolution spatial and temporal TWSA data.

Analysis of Nonstationary Wind Fluctuations Using the Hilbert-Huang Transform

Climatological patterns in wind fluctuations on time scales of 1–10 h are analyzed at a meteorological mast at the Yangmeishan wind farm, Yunnan Province,China, using a 2-yr time series of 10-min wind speed observations. For analyzing the spectral properties of nonstationary wind fluctuations in mountain terrain, the Hilbert-Huang transform(HHT) is applied to investigate climatological patterns between wind variability and several variables including time of year, time of day, wind direction, and pressure tendency. Compared with that for offshore sites, the wind variability at Yangmeishan wind farm has a more distinct diurnal cycle, but the seasonal discrepancies and the differences according to directions are not distinct, and the synoptic influences on wind variability are weaker. There is enhanced variability in spring and winter compared with summer and autumn. For flow from the main direction sector, the maximum wind variability is observed in spring. And the severe wind fluctuations are more common when the pressure tendency is rising.

Interpretation of sea surface wind interannual vector EOFs over the China seas

Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105°E-130°E, and we reported the monthly mean distributions of the sea surface wind field. A vector empirical orthogonal function （VEOF） method was employed to study the data and three temporal and spatial patterns were obtained. The first interannual VEOF accounts for 26% of the interannual variance and displays the interannual variability of the East Asian monsoon. The second interannual VEOF accounts for 21% of the variance and reflects the response of China sea winds to E1 Nifio events. The temporal mode of VEOF-2 is in good agreement with the curve of the Nifio 3.4 index with a four-month lag. The spatial mode of VEOF-2 indicates that four months after an E1 Nifio event, the southwesterly anomalous winds over the northern South China Sea, the East China Sea, the Yellow Sea, and the Bohai Sea can weaken the prevailing winds in winter, and can strengthen the prevailing winds in summer. The third interannual VEOF accounts for 10% of the variance and also reflects the influence of the ENSO events to China Sea winds. The temporal mode of VEOF-3 is similar to the curve of the Southern Oscillation Index. The spatial mode of VEOF-3 shows that the northeasterly anomalous winds over the South China Sea and the southern part of the East China Sea can weaken the prevailing winds, and southwesterly anomalous winds over the northern part of the East China Sea, the Yellow Sea, and the Bohai Sea can strengthen the prevailing winds when E1 Nifio occurs in winter. If E1 Nifio happens in summer, the reverse is true.

A comparative study on three EOF analysis techniques using decades of Arctic sea-ice concentration data

Change in Arctic sea ice extent is one of the indicators of global climate changes. Spatio-temporal change and change patterns can be identified using various methods to facilitate human understanding global climate changes. Three empirical orthogonal function(EOF) techniques are discussed and applied to decades of sea-ice concentration(SIC) dataset in Arctic area for identifying independent patterns. It was found that: 1) discrepancies exist in magnitude and scope for each EOF pattern, however, the first two leading EOFs of variability possess high similarities in structure and shape; 2) Even though there are somewhat differences in amplitude of each PC mode, the first two leading PC modes maintain consistent in overall trend and periodicity; 3) There are significant discrepancies and inconsistencies in the third and fourth leading EOF and PC modes. The accuracies of three techniques are further validated in representing the physical phenomena of SIC anomaly patterns.

重庆市土地承载力时变趋势与空间分异规律研究

在定义土地承载力时变模式、土地负载比和土地承载力类型内涵的基础上，用系统动力学方法，研究了重庆市土地承载力时变趋势与空间分异规律。认为重庆市各区县的土地承载力有三种时变趋势和五种承载力类型，并以土地承载力的时空趋势面表示了主要研究结果。

A Distributed Time-Variant Gain Hydrological Model Based on Remote Sensing

提出了一个完全采用遥感数据驱动的分布式时变增益水文模型,该模型通过融雪、产汇流等水文过程计算,给出流量的雪盖、蒸散发、径流等水文要素。在拉萨河流域,该模型采用遥感USGS-SRTM的3秒DEM、遥感TRMM(The Tropical RainfallMeasuring Mission)降水、Modis-LST(Land Surface Temperature)数据,建立分布式水文模型,模拟了2001-2008年日水文过程。模拟结果效率系数接近0.7,相关系数接近0.8,水量平衡误差5%以内。说明完全依靠遥感驱动水文模型进行水文水资源模拟可行。该模型为解决高寒山区无资料或缺资料地区水文水资源问题提供了一个新方法。

Variation of temporal and spatial patterns of NO_2 in Beijing using OMI and mobile DOAS

Control policies such as "odd-and-even license plate rule" were implemented by the Chinese government to restrict traffic and suspend factory production in Beijing and neighboring cities during the Asia-Pacific Economic Cooperation summit. We use ozone monitoring instrument(OMI), mobile differential optical absorption spectroscopy(DOAS), and multi-axis differential optical absorption spectroscopy(MAX-DOAS) to measure the variation of the spatial and temporal patterns of NO2 column densities from October 24, 2014 to November 22, 2014. It is found that the NO2 column densities during the episode of control policies are significantly lower than those during other periods, and the emission flux of NO2 calculated by mobile DOAS is also lower than the results from other periods. Some daily low NO2 column densities occur with the northwest wind direction. We then compare the relationship between OMI and mobile DOAS NO2 column density observations, and the results of mobile DOAS are approximately 2.7 times larger than the OMI values. The largest discrepancy occurs in the northern part of Beijing city. In other parts, the two instruments have a better correlation coefficient(R2) of 0.61. The low NO2 column densities that occur during the episode of control policies are affected by the control policies as well as meteorological conditions.