细胞自动机的多重分形特征和动力学根源

用大量弹簧滑块组成的模型可以模拟地震的复杂性，本文以细胞自动机（ＣＡ）为数学工具，结合地震学和岩石力学的结果，考虑了能量的输入和损耗，进行了地震事件的数字模拟。对模型中输出的“地震”事件进行了时间和空间的多分形分析，并对自组织临界（ＳＯＣ）状态进行了讨论，进而得到事件至少在时间域里的分布呈现出层次结构，符合自相似特征。本文的ＣＡ模型属于确定性的混沌系统，而对于处在ＳＯＣ状态下的大量事件的频度和大小的统计与Ｇ－Ｒ指数律很好地吻合。结果表明，虽然自组织（ＳＯ）可能是更准确的地震表征，但ＳＯＣ仍然是研究地震现象的很好的模式。     

细胞自动机的多重分形特征和动力学根源

用大量弹簧滑块组成的模型可以模拟地震的复杂性,本文以细胞自动机(CA)为数学工具,结合地震学和岩石力学的结果,考虑了能量的输入和损耗,进行了地震事件的数字模拟。对模型中输出的"地震"事件进行了时间和空间的多分形分析,并对自组织临界(SOC)状态进行了讨论,进而得到事件至少在时间域里的分布呈现出层次结构,符合自相似特征。本文的CA模型属于确定性的混沌系统,而对于处在SOC状态下的大量事件的频度和大小的统计与G-R指数律很好地吻合。结果表明,虽然自组织(SO)可能是更准确的地震表征,但SOC仍然是研究地震现象的很好的模式。     

天山地区地貌系统的自仿射分形与多重分形特征研究

利用标准偏差法和固定质量法，研究了新疆天山地区跨越多个不同构造地貌单元的两条地形剖线的自仿射分形和多重分形特征。结果表明：在所研究的标度范围内，两条剖线均表现出了不同特征的多度域分形性质，多重分形谱Dq的形态和值域范围也呈现出不同特征研究认为，地貌形态并不是完全随机的，而是一种确定性随机，不同标度区间的分维值表征了内外营力作用的方式，强度和空间尺度，同时提出地貌宏观与微观作用尺度的分界点在5km左右。这些结果对地貌动力学定量研究具有重要意义。     

近地磁尾方位角流能量转换过程

高速流是磁尾等离子体片中质量、能量和磁通量最重要的输运形式.高速流在地向运动到近地磁尾后流速会降低,主导方向也经常转为晨昏方向.在等离子体流速及其主导分量、密度和温度等宏观参数变化的过程中,可能伴随有不同类型的能量转换.为此,我们分析近地磁尾方位角流事件期间的能量转换过程.基于整体流速的主导分量为晨昏向,及事件期间的平均温度比其前后增强的选取原则,从2008—2020年期间THEMIS中的三颗卫星（THA,THD,THE）运行在磁尾时的观测数据中,共筛选出821个平均温度比其前/后（事件之前或事件之后10 min）升高的方位角流事件.2011年5月16日的方位角流事例研究发现：能量超过1 keV尤其是超过10 keV的高能离子通量增加,可导致低速低温等离子体的密度、温度和流速增加;磁场减小及磁场功率谱密度的分析表明等离子体和磁能的转换发生在频率为0.01~0.334 Hz的低频波动,仅1%能量耗散.统计给出方位角流事件的平均温度约为3.7 keV,比其前后增加的幅度大部分集中在100~1000 eV.事件期间的平均数密度可能升高或者降低,二者概率大致相当.约96%的平均温度和密度同时大于其前后的方位角流事件,当地等离子体通量管熵也皆大于事件的前后值;电磁能流密度增大,34%的事件期间电磁能流密度主要沿着背景磁力线方向,可影响电离层内方位角方向上的极光膨胀过程.我们的研究结果表明温度和密度同时增加的方位角流事件等离子体宏观参数变化可能暗含磁层-电离层能量耦合过程,有助于理解极光椭圆带赤道向边界的局部增亮现象和磁尾等离子体片中的磁通量.

     

形变场多重分形谱异常与强震关系研究

以平均形变速率梯度概率为变量, 研究了唐山地区、甘肃河西地区和北京地区多期垂直形变场图像的动态多重分形特征及其与强震的关系。结果表明, 震前一至数年形变场图像的多重分形谱Dq 值域变宽, 即- q 区上翘, + q区下降现象, 在强震孕育发生的过程中, 形变场时空表现出从准均匀到不均匀的演化趋势。结合地震活动和岩石力学实验结果认为, 形变场不均匀化可能是中长期地震复杂性前兆的一个重要标志。     

Rainfall stochastic disaggregation models: Calibration and validation of a multiplicative cascade model

The simulation of long time series of rainfall rates at short time steps remains an important issue for various applications in hydrology. Among the various types of simulation models, random multiplicative cascade models (RMC models) appear as an appealing solution which displays the advantages to be parameter parsimonious and linked to the multifractal theory. This paper deals with the calibration and validation of RMC models. More precisely, it discusses the limits of the scaling exponent function method often used to calibrate RMC models, and presents an hydrological validation of calibrated RMC models. A 8-year time series of 1-min rainfall rates is used for the calibration and the validation of the tested models. The paper is organized in three parts. In the first part, the scaling invariance properties of the studied rainfall series is shown using various methods (q-moments, PDMS, autocovariance structure) and a RMC model is calibrated on the basis of the rainfall data scaling exponent function. A detailed analysis of the obtained results reveals that the shape of the scaling exponent function, and hence the values of the calibrated parameters of the RMC model, are highly sensitive to sampling fluctuation and may also be biased. In the second part, the origin of the sensivity to sampling fluctuation and of the bias is studied in detail and a modified Jackknife estimator is tested to reduce the bias. Finally, two hydrological applications are proposed to validate two candidate RMC models: a canonical model based on a log-Poisson random generator, and a basic micro-canonical model based on a uniform random generator. It is tested in this third part if the models reproduce faithfully the statistical distribution of rainfall characteristics on which they have not been calibrated. The results obtained for two validation tests are relatively satisfactory but also show that the temporal structure of the measured rainfall time series at small time steps is not well reproduced by the two selected simple random cascade models.     

Prediction of Chemical Oxygen Demand (COD) Based on Wavelet Decomposition and Neural Networks

The chemical oxygen demand (COD) parameter of a wastewater treatment plant is predicted based on wavelet decomposition, entropy, and neural networks (NN) for rapid COD analysis. This paper also describes the usage of wavelet and NNs for parameter prediction. Data from a wastewater treatment plant in Malatya, Turkey, were used. This dataset consists of daily values of influents and effluents for a year. To reduce the dimension of input parameters and to decrease the NN training time, wavelet decomposition and entropy were used. Test results were presented graphically. The test results of the trained model were found to be closer to the measured COD values.     

The role of hydrologic information in reservoir operation – Learning from historical releases

Closing the gap between theoretical reservoir operation and the real-world implementation remains a challenge in contemporary reservoir operations. Past research has focused on optimization algorithms and establishing optimal policies for reservoir operations. In this study, we attempt to understand operators’ release decisions by investigating historical release data from 79 reservoirs in California and the Great Plains, using a data-mining approach. The 79 reservoirs are classified by hydrological regions, intra-annual seasons, average annual precipitation (climate), ratio of maximum reservoir capacity to average annual inflow (size ratio), hydrologic uncertainty associated with inflows, and reservoirs’ main usage. We use information theory – specifically, mutual information – to measure the quality of inference between a set of classic indicators and observed releases at the monthly and weekly timescales. Several general trends are found to explain which sources of hydrologic information dictate reservoir release decisions under different conditions. Current inflow is the most important indicator during wet seasons, while previous releases are more relevant during dry seasons and in weekly data (as compared with monthly data). Inflow forecasting is the least important indicator in release decision making, but its importance increases linearly with hydrologic uncertainty and decreases logarithmically with reservoir size. No single hydrologic indicator is dominant across all reservoirs in either of the two regions.     

垂直地壳运动的均衡失稳条件探讨

根据Lyapunov稳定理论和耗散结构理论,分析了在均衡力作用下,地壳的均衡调整运动和地壳的反均衡运动的稳定性;推导了判断均衡地壳垂直运动失稳时的熵产生判据和条件;讨论了非线性运动过程中均衡地壳运动系统的反馈性质。作为均衡地壳非稳定性运动的两个实际例子,对青海门源6.4级地震前的重力水准资料和甘肃礼县5.0级地震前的重力水准资料进行了计算,得出了与理论基本一致的结果。