Dereverberation of marine reflection seismic data by a spatial combination of predictive deconvolution and velocity filtering

Contamination of seismic reflection records at early times by first-order water reverberations can be especially severe during survey operations over hard and flat sea floors on the continental shelf or in lake environments. A new dereverberation scheme based on two classical techniques — predictive deconvolution and velocity filtering — has been developed to address this problem. The techniques are combined spatially to take advantage of their complementary offset- and time-dependent properties. Stage I of the scheme consists of applying predictive deconvolution at short offset. The data are previously conditioned by a normal moveout correction with the water velocity which restores the periodicity of the reverberations in the offset-time plane and enhances the performance of deconvolution. Stage II of the scheme involves velocity filtering in the common-midpoint domain which is particularly effective at long offset where the moveout difference between primary reflections and reverberations is largest. The dereverberation scheme is well suited for the initial processing of large volumes of data due to the general availability of cost-effective deconvolution and velocity filtering algorithms in seismic processing software packages. Practical implementation issues are illustrated by a field example from the GLIMPCE survey in Lake Superior.Lithoprobe Publication No. 475.     

基于预测控制的结构振动半主动控制研究

建立了半主动控制系统的理论模型，分析了半主动控制机理，并结合现代控制理论，将预测控制应用于结构半主动控制中，提出了在线预测控制算法，建立了预测模型，并成功的解决了时滞问题，最后作了计算机仿真分析，证明该系统有较好的控制效果。将预测控制思想应用于结构半主动控制中，为结构控制注入了新的思路，通过研究及仿真分析也说明了这种思想是可行的并且具有很大的发展前途。     

河南省短期区域性暴雨动力诊断及综合预报方案

介介绍了（１）用Ｔ６３数值预报产品对河南省省６－８月区域性暴雨进行物理量诊断分析。（２）用人工智能研制的河南省６－８月分片大－暴雨短短期自动化预报系统与用Ｔ６３数值预报产品资料采用逐步回归分析法和预测误差平方和最不上准则两种选取回归自变量的方法，建立处分片预报方程的综合判别预报。（３）在１９９５，１９９６年７－８月业务预报中试验结果。     

主动变刚度-阻尼系统预测最优控制的理论与试验研究

介绍了一种具有自主知识产权的新型开关控制型半主动控制系统——主动变刚度.阻尼(AVS.D)系统的减振控制机理,建立了AVS.D结构振动控制体系的运动方程。为了合理补偿AVS.D系统实时控制过程中不可避免地存在着的控制时滞,本文提出一种预测最优控制算法,推导了其开关控制律。为了检验AVS.D系统的减震控制效果及预测最优控制算法的有效性,我们设计研制出AVS.D装置,编制了AVS.D系统预测最优控制的实时控制软件,在某单层钢框架模型上进行了AVS.D系统的模拟地震振动台试验,比较了不同控制方式时的减震效果。研究结果表明,本文所提出的预测最优控制算法是非常有效的,可推广应用于所有开关控制型半主动控制系统。AVS.D系统具有反应放大功能,经济可靠、安全有效,可望有较好的工程应用前景。     

Semi-active model predictive control for 3rd generation benchmark problem using smart dampers

A semi-active strategy for model predictive control (MPC), in which magneto-rheological dampers are used as an actuator, is presented for use in reducing the nonlinear seismic response of high-rise buildings. A multi-step predictive model is developed to estimate the seismic performance of high-rise buildings, taking into account of the effects of nonlinearity, time-variability, model mismatching, and disturbances and uncertainty of controlled system parameters by the predicted error feedback in the multi-step predictive model. Based on the predictive model, a Kalman-Bucy observer suitable for semi-active strategy is proposed to estimate the state vector from the acceleration and semi-active control force feedback. The main advantage of the proposed strategy is its inherent stability, simplicity, on-line real-time operation, and the ability to handle nonlinearity, uncertainty, and time-variability properties of structures. Numerical simulation of the nonlinear seismic responses of a controlled 20-story benchmark building is carried out, and the simulation results are compared to those of other control systems. The results show that the developed semi-active strategy can efficiently reduce the nonlinear seismic response of high-rise buildings.     

甘肃省金矿资源预测模型及潜力评价

为了更加科学有效地部署甘肃省金矿勘查找矿工作,必须对全省金资源总量作出定量预测,对省内各成矿带的金资源潜力作出定量评价。文章对甘肃省已发现的429处金矿床(点)的资料及全省1∶20万区域化探资料进行了统计和研究,建立了甘肃省金资源总量丰度估算模型、品位-储量回归预测模型及全省各成矿带金资源潜力分布模型。通过定量预测得知,甘肃省金资源总量的上限值为3166t,金资源总量为2420.6t;西秦岭成矿带的金资源潜力最大,占全省金资源潜力的37%,祁连成矿带次之,占24%,扬子成矿带占15%,北山成矿带占13%。据甘肃省岩金资源回归预测模型,岩金矿床在甘肃省具有极大的资源潜力。     

面向海上目标搜索任务的多无人机协同航路优化

提出了一种面向多无人机(unmanned aerial vehicle,UAV)协同搜索海上目标任务的航路优化方法。首先,分析多无人机协同航路优化问题的基本要素模型。然后,在对各UAV独立维护的目标概率图信息进行探测更新的基础上,采用状态预测一致性算法实现目标概率图信息的快速融合。最后,同时考虑局部搜索收益与未来搜索收益,采用分布式模型预测控制(distributed model predictive control,DMPC)方法优化各UAV的搜索航路。仿真结果表明,本研究提出的方法具有较高的搜索效率,可有效应用于海上目标的快速搜索任务,具有重要的应用价值。     

Estimation of the wave-related ripple characteristics and induced bed shear stress

A large data set on ripples was collected and examined. A set of new formulas for the prediction of the ripple characteristics is proposed with an emphasis on the disappearance of the ripples. The ripple wavelength was observed to be proportional to the bottom wave excursion but also to be a function of the grain-related Shields parameter and wave period parameter introduced by Mogridge et al. (1994). The ripple steepness was found to be nearly constant for orbital ripples, and with a sharp decrease for suborbital ripples. Two empirical functions are added including the effects of the critical Shields parameters (inception of transport and inception of sheet flow), i.e. giving the boundaries for the ripple existence's domain. The proposed formulas yield better prediction capabilities compared to the previously published formulas, especially when ripples are washed out. The effect of the ripple characteristics on the roughness height and the calculation of the bed shear stress is also discussed. It appeared that the bed shear stress calculation is more sensitive to the empirical coefficient a_r introduced in the estimation of the ripple-induced roughness height or to the limits of existence of the ripples than the ripple characteristics themselves.     

Adaptive Predictive Inverse Control of Offshore Jacket Platform Based on Rough Neural Network

The offshore jacket platform is a complex and time-varying nonlinear system,which can be excited of harmful vibration by external loads.It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model.In this paper,an adaptive inverse control method is proposed on the basis of novel rough neural networks (RNN) to control the harmful vibration of the offshore jacket platform,and the offshore jacket platform model is established by dynamic stiffness matrix (DSM) method.Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory,RNN is utilized to identify the predictive inverse model of the offshore jacket platform system.Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads,and to deal with the delay problem caused by signal transmission in the control process.The numerical results show that the constructed novel RNN has advantages such as clear structure,fast training speed and strong error-tolerance ability,and the proposed method based on RNN can effectively control the harmfid vibration of the offshore jacket platform.     

千岛岛弧大震前哈佛大学矩心矩张量（CMT）解一致性的预测意义s

千岛岛弧地区属于全球地震活动最为活跃的地区之一. 本文利用哈佛大学测定的千岛岛弧地区地震的矩心矩张量（CMT）解， 分析该地区震源机制的一致性特征， 提出利用震源机制和构造应力场的一致性参数a进行地震预测的思路. 研究结果表明，MＷge;7.5地震之前， 都有一致性参数a降低的现象，a的低值起始的时间在发生大震之前的10多天至110多天， a的低值截止的日期距大震在30多天至2天. 相互之间虽然并不完全一致， 但是差别不大. 这种现象的稳定性， 尚需时间的检验， 但是设想在长达数百公里的地区， 连续发生MＷge;5.3的地震的震源机制都与构造应力场一致， 应当不是随机的现象， 而是一种具有预测意义的现象. 当积累的震例足够多时， 则有可能确定统一的评判标准和预测准则.