福建云霄石榴子石宝石矿物学特征

福建云霄是我国重要的宝石级石榴子石产地,然而该区石榴子石的致色机理不清,制约了对其形成机制的理解及后续开发利用。本文选取7件福建云霄橙黄-橙红色石榴子石样品,利用傅立叶红外光谱、紫外-可见光光谱和拉曼光谱分析其谱学特征,使用电子探针及激光剥蚀电感耦合等离子体质谱仪(LA-ICP-MS)分析限定其主量、微量元素组成。结果表明云霄石榴子石主要为锰铝榴石,其颜色主要与二价锰(Mn²⁺)和铁离子(Fe²⁺)对可见光的吸收有关,Mn²⁺导致其主体呈橙色,少量Fe²⁺控制其橙红色调,微量Ti⁴⁺使其呈褐色调。福建云霄石榴子石样品核部锰含量相对较低而铁、镁含量较高,锰元素含量由核部向边部逐渐升高,且具有重稀土元素富集、轻稀土元素亏损的左倾配分模式和Eu负异常,表明其形成于岩浆结晶作用晚期。     

基于PIES观测东沙群岛附近声传播变化

本研究旨在将PIES观测数据应用于海洋水声环境的监测。利用一次南海PIES观测数据,反演得到温盐剖面,进而计算声场信息。结合观测期间的暖涡及台风事件对反演及计算结果进行了分析验证。结果表明,PIES能够在长期连续观测中较为敏感地捕获上层水体及表面声道的变化特征,为水声通信、探测及潜航路径规划等提供参考,在水声研究及海洋军事环境保障中都具有良好的应用前景。     

对GML3.0应用模式的研究

阐述了GML3.0的主要模式,论述了GML应用模式开发的若干技术问题,并通过一个实例阐述了如何创建一个领域内的应用模式。     

714C天气雷达收发机的维护

天气雷达是探测天气变化的重要工具,尤其是机场短时天气预报的重要手段,是保证航班安全正常的可靠保障。针对呼和浩特机场714C天气雷达收发机维护过程中的一些问题方法进行总结,从中总结可行性经验。     

Assessing the relative contributions of the flood tide and the ebb tide to tidal channel network dynamics

Flood and ebb currents provide different contributions to the initiation and evolution of tidal channel networks, generating diverse network structures and channel cross-sections. In order to separate the effects of these contributions, a physical model of a sloping tidal-flat basin was set up in the laboratory. Depending on the degree of tidal asymmetry imposed offshore, either flood or ebb currents can be enhanced. The experimental results show that the ebb current has a higher capability to initiate and shape tidal networks than the flood current. Headward erosion is mainly induced by the ebb flow. The slightly inclined flat surface tends to reduce the energy of the flood current and to enhance the ebb current, thus prolonging the duration of morphodynamic activity as well as sediment motion. Overall, flood-dominated tides favour the formation of small-scale channel branches in the upper basin zone, while long lasting ebb-dominated tides result in more complex, wider and deeper tidal networks. © 2019 John Wiley & Sons, Ltd.     

Scattering pattern analysis and true-amplitude generalized Radon transform migration for acoustic transversely isotropic media with a vertical axis of symmetry

In multi-parameter ray-based anisotropic migration/inversion, it is essential that we have an understanding of the scattering mechanism corresponding to parameter perturbations. Because the complex nonlinearity in the anisotropic inversion problem is intractable, the construction of true-amplitude linearized migration/inversion procedures is needed and important. By using the acoustic medium assumption for transversely isotropic media with a vertical axis of symmetry and representing the anisotropy with P-wave normal moveout velocity, Thomsen parameter δ and anelliptic parameter η, we formalize the linearized inverse scattering problem for three-dimensional pseudo-acoustic equations. Deploying the single-scattering approximation and an elliptically anisotropic background introduces a new linear integral operator that connects the discontinuous perturbation parameters with the multi-shot/multi-offset P-wave scattered data. We further apply the high-frequency asymptotic Green's function and its derivatives to the integral operator, and then the scattering pattern of each perturbation parameter can be explicitly presented. By naturally establishing a connection to generalized Radon transform, the pseudo-inverse of the integral operator can be solved by the generalized Radon transform inversion. In consideration of the structure of this pseudo-inverse operator, the computational implementation is done pointwise by shooting a fan of rays from the target imaging area towards the acquisition system. Results from two-dimensional numerical tests show amplitude-preserving images with high quality.     

基于Seislet-TV双正则化约束的地震随机噪声压制方法

人工地震数据总是受到随机噪声的干扰,地震数据时-空变的特性使得常规去噪方法处理效果并不理想,容易导致有效信号的损失.目前广泛应用的预测滤波类方法存在处理时变数据能力不足的问题.随着压缩感知理论的不断完善,稀疏变换阈值算法能够解决时变地震数据噪声压制问题,但是常规的稀疏变换方法,如傅里叶变换,小波变换等,并不是特殊针对地震数据设计的,很难提供地震数据最佳的压缩特征,同时,常规阈值算法容易导致去噪结果过于平滑.因此开发更加有效的时-空变地震数据信噪分离方法具有重要的工业价值.本文将地震数据信噪分离问题归纳为数学基追踪问题,在压缩感知理论框架下,利用特殊针对地震数据设计的VD-seislet稀疏变换方法,结合全变差(TV)算法,构建seislet-TV双正则化条件,并利用分裂Bregman迭代算法求解约束最优化问题,实现地震数据的有效信噪分离.通过理论模型和实际数据测试本文方法,并且与工业标准FXdecon方法进行比较,结果表明基于seislet-TV双正则化约束条件的迭代方法能够更加有效地保护时-空变地震信号,压制地震数据中的强随机噪声.     

The control of wind strength on the barchan to parabolic dune transition

The evolution of barchan-to-parabolic dunes can be driven by vegetation establishment, which may be linked to climate change and/or human activity. However, little is known of the impact of changes in wind strength on vegetation development and the resulting impacts on the evolution of dune morphology and sedimentological characteristics. To address this issue, we studied the morphology and grain-size characteristics of barchan, barchan-to-parabolic and parabolic dunes in the Mu Us Desert in north China, which was combined with an analysis of changes in normalized difference vegetation index (NDVI) and climatic variables during 1982–2018. The results reveal a trend of increasing growing-season NDVI which was related to a significant decrease in drift potential (DP). Therefore, we suggest that the initiation of dune transformation was caused by the reduced wind strength which favored the establishment and development of vegetation. To reveal the response of sedimentological reorganization during the processes of dune transformation, grain-size characteristics along the longitudinal profile of the three different types of dunes were examined. The decreasing wind strength led to the transport of fine sands on the upper part of the windward face of the dunes, resulting in a progressive coarsening of the grain-size distribution (GSD) and a reduction in dune height at the crest area. No distinct trend in sorting and mean grain-size was observed on the windward slope of the barchan-to-parabolic dune, indicating that the sand in transit had little influence on the GSD. Conversely, progressive sorting and coarsening of the sand occurred towards the crest of the parabolic dune. This indicates that vegetation development limited the transport of sand from upwind of the dune, and affected a shift in the dune source material to the underlying source deposits, or to reworked pre-existing aeolian deposits, and resulted in the trapping of sand in the crest area. © 2020 John Wiley & Sons, Ltd.     

Decadal link between longitudinal morphological changes in branching channels of Yangtze estuary and movement of the offshore depo-center

In estuaries, the morphology of inland and offshore areas usually evolves synergistically. This study examines the decadal link between longitudinal changes in morphology of branching channels and movement of the offshore depo-center (where sediment deposition rate is maximum) of the Yangtze River estuary, under intense human interference. Integrated data analysis is provided on morphology, runoff discharge, and ebb partition ratio from 1950 to 2017. Channel-volume reductions and change rates between isobaths in branching channels reflect the impact of estuarine engineering projects. Ebb partition ratio and duration of discharge ≥ 60 000 m³ s^-1 act as proxies for the water excavating force in branching channels and runoff intensity. It is found that deposition occurs in the lower/upper sub-reaches (or further downstream/upstream channels) of the inland north/south branching channels, and the offshore depo-center moves southward or southeastward, as runoff intensity grows; the reverse occurs as runoff intensity declines. This is because the horizontal circumfluence in the Yangtze estuary rotates clockwise as ebb partition ratios of the north/south branching channels increase/decrease for increasing runoff, and conversely rotates anticlockwise for decreasing runoff. Land reclamation activities, the Deepwater Channel Project, and the Qingcaosha Reservoir have impacted greatly on longitudinal changes of morphology in the North Branch and the South Passage and on ebb partition ratio variations in the North/South Channel and the North/South Passage. Dam-induced runoff flattening has enhanced deposition in the upper/lower sub-reaches of the north/south branching channels and caused northward movement of the offshore depo-center, except in areas affected by estuarine engineering projects. Dam-induced longitudinal evolution of branching channel morphology and offshore depo-center movement will likely persist in the future, given the ongoing construction of large cascade dams in the upper Yangtze and the completion of major projects in the Yangtze estuary. © 2020 John Wiley & Sons, Ltd.     

Time-frequency decomposition of seismic signals via quantum swarm evolutionary matching pursuit

Matching pursuit belongs to the category of spectral decomposition approaches that use a pre-defined discrete wavelet dictionary in order to decompose a signal adaptively. Although disengaged from windowing issues, matching point demands high computational costs as extraction of all local structure of signal requires a large size dictionary. Thus in order to find the best match wavelet, it is required to search the whole space. To reduce the computational cost of greedy matching pursuit, two artificial intelligence methods, (1) quantum inspired evolutionary algorithm and (2) particle swarm optimization, are introduced for two successive steps: (a) initial estimation and (b) optimization of wavelet parameters. We call this algorithm quantum swarm evolutionary matching pursuit. Quantum swarm evolutionary matching pursuit starts with a small colony of population at which each individual, is potentially a transformed form of a time-frequency atom. To attain maximum pursuit of the potential candidate wavelets with the residual, the colony members are adjusted in an evolutionary way. In addition, the quantum computing concepts such as quantum bit, quantum gate, and superposition of states are introduced into the method. The algorithm parameters such as social and cognitive learning factors, population size and global migration period are optimized using seismic signals. In applying matching pursuit to geophysical data, typically complex trace attributes are used for initial estimation of wavelet parameters, however, in this study it was shown that using complex trace attributes are sensitive to noisy data and would have lower rate of convergence. The algorithm performance over noisy signals, using non-orthogonal dictionaries are investigated and compared with other methods such as orthogonal matching pursuit. The results illustrate that quantum swarm evolutionary matching pursuit has the least sensitivity to noise and higher rate of convergence. Finally, the algorithm is applied to both modelled seismograms and real data for detection of low frequency anomalies to validate the findings.