便携式水泥灌浆数据记录仪

介绍一种便携式水泥灌浆数据记录仪的设计原理、框图、软硬件组成及试验结果，并分析了其性能特点。     

Non-local memory effects of the electromotive force by fluid motion with helicity and two-dimensional periodicity

In mean-field dynamo theory, the electromotive force term 〈u′ × B′〉 due to small-scale fields connects the small-scale magnetic field with the large-scale field. This term is usually approximated as the α-effect, assumed to be instantaneous in time and local in space. However, the approximation is valid only when the magnetic Reynolds number Rm is much less than unity, and is inappropriate when Rm ? 1, which is the condition satisfied in the Earth's core or solar convection zone. We introduce a function φ _qr as a non-local and non-instantaneous generalization of the usual α-effect and examine its behaviour as a function of Rm in the range 1/64 ≤ Rm ≤ 10 for a kinematic dynamo model. We use the flow of G.O. Roberts 1972 Roberts, GO. 1972. Dynamo action of fluid motions with two-dimensional periodicity. Phil. Trans. Roy. Soc. London Ser. A, 271: 411–454. [Crossref], [Web of Science ®] , [Google Scholar] (Phil, Trans. Roy. Soc. London Ser. A, 1972, 271, 411–454), which is steady and has non-zero helicities and two-dimensional periodicity. As a result, we identify three regions in Rm space according to the behaviour of the function φ _qr : (i) Rm ? 1/4, where the function φ _qr is local and instantaneous and can be approximated by the traditional α and β effects, (ii) 1/4 ? Rm ? 4, where the deviation from the traditional α and β effects increases and non-localness and non-instantaneousness increase, and (iii) Rm ? 4, where boundary layers develop fully and non-localness and non-instantaneousness are prominent. We show that the non-local memory effect for Rm ? 4 strongly affects the dynamo action and explains an observed augmentation of the growth rate in the dispersion relation. The results imply that the non-local memory effect of the electromotive force should be important in the geodynamo or the solar dynamo.     

新一代的地震预报专家系统NGESEP中的推理子系统

本文介绍了第一代专家系统和第二代专家系统的特点以及新一代地震预报专家系统中的推理子系统。该系统根据地震预报知识的特点设计了推理机,解决了推理子系统中的一系列问题。     

A memory-matrix-based identification methodology for structural and mechanical systems

This paper uses an associative memory approach to identify the properties of structural and mechanical systems. The methodology differs from standard identification methods in that it uses a set of parameter vectors simultaneously to generate the estimated parameter vector. The method develops a technique for sequentially generating genetically engineered relevant parameter vectors whose use results in accurate identification, while still using small data sets. This makes the approach promising for on-line, rapid, identification of structures and their health monitoring. © 1998 John Wiley & Sons, Ltd.     

A fast multipole boundary element method for three-dimensional potential flow problems

A fast multipole methodology (FMM) is developed as a numerical approach to reduce the computational cost and memory requirements in solving large-scale problems. It is applied to the boundary element method (BEM) for three-dimensional potential flow problems. The algorithm based on mixed multipole expansion and numeric, al integration is implemented in combination with an iterative solver. Numerical examinations, on Dirichlet and Neumann problems, are carried out to demonstrate the capability and accuracy of the present method. It has been shown that the method has evident advantages in saving memory and computing time when used to solve huge-scale problems which may be prohibitive for the traditional BEM implementation.     

Spin glass dynamics in RKKY interacting disordered magnetic system

Using the dynamical Monte Carlo method we investigate the nonequilibrium effects in RKKY-coupling disordered spin glass. By the simulation we reproduce the well-known aging and memory phenomena and find the energy relaxation at a certain temperature happens only to the corresponding spins, which directly causes the nonequilibrium effects. Combining the master equation and the energy relaxation we analyse these phenomena and explain them from the dynamical perspective.     

Application of deep learning technique to the sea surface height prediction in the South China Sea

A deep-learning-based method, called ConvLSTMP3, is developed to predict the sea surface heights(SSHs).ConvLSTMP3 is data-driven by treating the SSH prediction problem as the one of extracting the spatial-temporal features of SSHs, in which the spatial features are "learned" by convolutional operations while the temporal features are tracked by long short term memory(LSTM). Trained by a reanalysis dataset of the South China Sea(SCS), ConvLSTMP3 is applied to the SSH prediction in a region of the SCS east off Vietnam coast featured with eddied and offshore currents in summer. Experimental results show that ConvLSTMP3 achieves a good prediction skill with a mean RMSE of 0.057 m and accuracy of 93.4% averaged over a 15-d prediction period. In particular,ConvLSTMP3 shows a better performance in predicting the temporal evolution of mesoscale eddies in the region than a full-dynamics ocean model. Given the much less computation in the prediction required by ConvLSTMP3,our study suggests that the deep learning technique is very useful and effective in the SSH prediction, and could be an alternative way in the operational prediction for ocean environments in the future.     

基于鲸鱼优化算法的长短期记忆模型水库洪水预报

洪涝灾害是世界主要自然灾害之一,优化洪水预报方案对防洪决策至关重要,然而传统水文模型存在参数多、调参受人为因素影响,泛化能力弱等问题。针对上述问题,本文提出基于改进的鲸鱼优化算法和长短期记忆网络构建自动优化参数的WOA-LSTM模型,通过优化神经网络结构进一步增强该模型的稳定性和精确度,并且建立不同预见期下的洪水预报模型来分析讨论神经网络结构与预报期之间的关系。以横锦水库流域1986—1997年洪水资料为例,其中以流域7个雨量站点的降雨以及横锦站水文资料为输入,不同预见期下洪水过程作为输出,以1986—1993年作为模型的率定期,1994—1997年作为模型的检验期,研究结果表明:(1)以峰现时差、确定性系数、径流深误差和洪峰流量误差作为评价指标,相比较于LSTM模型和新安江模型对检验期的模拟结果表明WOA-LSTM模型拥有更高的精度、预报结果更稳定;(2)结合置换特征值和SHAP法分析模型特征值重要性,增强了神经网络模型的可解释性;(3)通过改变神经网络结构在一定程度避免由于预见期增加和数据关联性下降而导致的模型预报精度下降的问题,最终实验表明该模型在预见期1~6 h下都可以满足横锦水库的洪水预报要求,可以为当地的防洪决策提供依据。     

矿山复合采动效应的时空属性

在各类矿产资源的开采过程中,有许多矿区属于地下与露天复合开采情况,依据采区的空间对应关系,两种采动影响域中的一部分相互重叠,致使其采动汀互作用和相互叠加,从而组成一个复合动态系统,本文在理论与实例分析的基础上,研究地下与露天复合采动体系中岩体的变形机理及其不同时序开挖间的影响特点的记忆关系与空间变化特征,并在此基础上总结出矿山复合开挖岩体变形特点与规律性。     

YANGTZE DISCHARGE MEMORY

We present a review on studies focusing on memories in hydrological time series in the Yangtze Basin based on observational and reconstructed historical data.Memory appears as scaling of power spectra,S(f)～f-β,with 0 <β≤ 1.The presence of scaling is noteworthy in daily river discharge time series:1)from weeks to a couple of years,power spectra follow flicker noise,that is β≈ 1;2)beyond years,spectral scaling appraaclTes β≈0.3.In historical time series of floods and draughts,power spectra also shows scaling with β≈ 0.38 ～0.52.Furthermore,a 70-year peak is detected in historical maritime events series,which also appears in other past climate indicators.Presence of memory in these hydrological time series implies clustering of extremes and scaling of their recurrence times,therefore,probabilistic forecast potential for extremes can be derived.On the other hand,although several physical processes,for example,soil moisture storage and high intermittency of precipitation,have been suggested to be the possible candidates contributing to the presence of long term memory,they remain open for future research.