Wave run-up on slender circular cylindrical foundations for offshore wind turbines in nonlinear random waves

A practical method for estimating the wave run-up height on a slender circular cylindrical foundation for wind turbines in nonlinear random waves is provided. The approach is based on the velocity stagnation head theory and Stokes second order wave theory by assuming the basic harmonic wave motion to be a stationary Gaussian narrow-band random process. Comparisons are made with measurements by De Vos et al. (2007), and some of the highest wave run-up events that were predicted agree with those measured.     

岛礁工程海水拌养珊瑚礁、砂混凝土修补与应用研究

对用海水拌养珊瑚礁、砂混凝土修补与抢修远离大陆的岛碾损坏工程进行应用研究和调研,对该种混凝土的原材料和物理力学性能进行检测,研究了修补界面剂的配合比与修补工艺以及操作方法,并进行了海水拌养珊瑚礁、砂混凝土与海水拌养普通混凝土修补的粘结强度对比测试和海水拌养快凝快强混凝土快速抢修的工程应用实践检验,为岛礁工程修补和抢修提供技术参考资料。     

基于随机振动模型的强地面运动数值模拟及其在广西灵山M6(3/4)地震中的应用

1936年4月1日广西灵山县平山镇东南罗阳山附近发生M6(3/4)地震,该地震是华南大陆自有地震记载以来发生的最大地震。本研究收集整理了灵山M6(3/4)地震的地质资料、活动断层探测最新成果等,选取适当的研究区域,利用随机振动有限断层模型计算区域内网格点的峰值加速度(PGA)及峰值速度(PGV)等参数,并且加入浅层横波速度结构V_s³⁰对地震动参数的影响,最终得到此次地震的地震动分布并分析了地震动特征。本研究将模拟结果与野外调查烈度数据和地震动衰减关系进行对比,结果显示模拟结果与调查烈度值和衰减关系在整体衰减特征、极震区的分布等方面均符合较好,模拟结果可为该地区未来地震危害性评估提供依据。本研究所使用的方法流程亦可应用于本地区地震烈度速报,为震后应急救援及决策指挥提供帮助。     

储层地质建模的现状与展望

储层地质建模对于科学的油藏评价、油藏开发管理以及三维油藏数值模拟具有很大的意义。目前已有的建模算法和商业软件可满足地质特征三维分布的图形要求,并可进行初步的井间预测,但预测精度有待于进一步提高。简要介绍了各种建模方法研究现状,分析了已有算法中亟需改进的问题,并从建模算法的改进、原型模型的丰富、地震信息的整合以及加强地质约束等方面论述了储层地质建模的发展前景。     

Development of stochastic dynamic Nash game model for reservoir operation II. The value of players’ information availability and cooperative behaviors

Stochastic dynamic game models can be applied to derive optimal reservoir operation policies by considering interactions among water users and reservoir operator, their preferences, their levels of information availability and cooperative behaviors. The stochastic dynamic game model with perfect information (PSDNG) has been developed by [Ganji A, Khalili D, Karamouz M. Development of stochastic dynamic Nash game model for reservoir operation. I. The symmetric stochastic model with perfect information. Adv Water Resour, this issue]. This paper develops four additional versions of stochastic dynamic game model of water users interactions based on the cooperative behavior and hydrologic information availability of beneficiary sectors of reservoir systems. It is shown that the proposed models are quite capable of providing appropriate reservoir operating policies when compared with alternative operating models, as indicated by several reservoir performance characteristics. Among the proposed models, the selected model by considering cooperative behavior and additional hydrologic information (about the randomness nature of reservoir operation parameters), as exercised by reservoir operator, provides the highest attained level of performance and efficiency. Furthermore, the selected model is more realistic since it also considers actual behavior of water users and reservoir operator in the analysis.     

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.     

Data-worth analysis for multiobjective optimal design of pump-and-treat remediation systems

The design and the management of pump-and-treat (PAT) remediation systems for contaminated aquifers under uncertain hydrogeological settings and parameters often involve decisions that trade off cost optimality against reliability. Both design objectives can be improved by planning site characterization programs that reduce subsurface parameter uncertainty. However, the cost for subsurface investigation often weighs heavily upon the budget of the remedial action and must thus be taken into account in the trade-off analysis. In this paper, we develop a stochastic data-worth framework with the purpose of estimating the economic opportunity of subsurface investigation programs. Since the spatial distribution of hydraulic conductivity is most often the major source of uncertainty, we focus on the direct sampling of hydraulic conductivity at prescribed locations of the aquifer. The data worth of hydraulic conductivity measurements is estimated from the reduction of the overall management cost ensuing from the reduction in parameter uncertainty obtained from sampling. The overall cost is estimated as the expected value of the cost of installing and operating the PAT system plus penalties incurred due to violations of cleanup goals and constraints. The crucial point of the data-worth framework is represented by the so-called pre-posterior analysis. Here, the tradeoff between decreasing overall costs and increasing site-investigation budgets is assessed to determine a management strategy proposed on the basis of the information available at the start of remediation. The goal of the pre-posterior analysis is to indicate whether the proposed management strategy should be implemented as is, or re-designed on the basis of additional data collected with a particular site-investigation program. The study indicates that the value of information is ultimately related to the estimates of cleanup target violations and decision makers’ degree of risk-aversion.     

Update of likelihood-based ground-motion model selection for seismic hazard analysis in western central Europe

Scherbaum et al. [(2004) Bull Seismolo Soc Am 94(6): 2164–2185] proposed a likelihood-based approach to select and rank ground-motion models for seismic hazard analysis in regions of low-seismicity. The results of their analysis were first used within the PEGASOS project [Abrahamson et al. (2002), In Proceedings of the 12 ECEE, London, 2002, Paper no. 633] so far the only application of a probabilistic seismic hazard analysis (PSHA) in Europe which was based on a SSHAC Level 4 procedure [(Budnitz et al. 1997, Recommendations for PSHA: guidance on uncertainty and use of experts. No. NUREG/CR-6372-V1). The outcome of this project have generated considerable discussion (Klügel 2005, Eng Geol 78:285–307, 2005b) Eng Geol 78: 285–307, (2005c) Eng Geol 82: 79–85 Musson et al. (2005) Eng Geol 82(1): 43–55]; Budnitz et al. (2005), Eng Geol 78(3–4): 285–307], a central part of which is related to the issue of ground-motion model selection and ranking. Since at the time of the study by Scherbaum et al. [(2004.) Bull Seismolo Soc Am 94(6): 2164–2185], only records from one earthquake were available for the study area, here we test the stability of their results using more recent data. Increasing the data set from 12 records of one earthquake in Scherbaum et al. [(2004) Bull Seismolo Soc Am 94(6): 2164–2185] to 61 records of 5 earthquakes, which have mainly occurred since the publication of the original study, does not change the set of the three top-ranked ground-motion models [Abrahamson and Silva (1997) Seismolo Res Latt 68(1): 94–127; Lussou et al. (2001) J Earthquake Eng 5(1):13–33; Berge-Thierry et al. (2003) Bull Seismolog Soc Am 95(2): 377–389. Only for the lower-ranked models do we obtain modifications in the ranking order. Furthermore, the records from the Waldkirch earthquake (Dec, 5th, 2004, M _w = 4.9) enabled us to develop a new stochastic model parameter set for the application of Campbell’s [(2003) Bull Seismolo Soc Am 93(3): 1012–1033] hybrid empirical model to SW Germany and neighbouring regions.     

On stochastic stability of regional ocean models to finite-amplitude perturbations of initial conditions

We consider error propagation near an unstable equilibrium state (classified as an unstable focus) for spatially uncorrelated and correlated finite-amplitude initial perturbations using short- (up to several weeks) and intermediate (up to 2 months) range forecast ensembles produced by a barotropic regional ocean model. An ensemble of initial perturbations is generated by the Latin Hypercube design strategy, and its optimal size is estimated through the Kullback–Liebler distance (the relative entropy). Although the ocean model is simple, the prediction error (PE) demonstrates non-trivial behavior similar to that existing in 3D ocean circulation models. In particular, in the limit of zero horizontal viscosity, the PE at first decays with time for all scales due to dissipation caused by non-linear bottom friction, and then grows faster than (quasi)-exponentially. Statistics of a prediction time scale (the irreversible predictability time (IPT)) quickly depart from Gaussian (the linear predictability regime) and becomes Weibullian (the non-linear predictability regime) as amplitude of initial perturbations grows. A transition from linear to non-linear predictability is clearly detected by the specific behavior of IPT variance. A new analytical formula for the model predictability horizon is introduced and applied to estimate the limit of predictability for the ocean model.