Assessment of radionuclide transport uncertainty in the unsaturated zone of Yucca Mountain

The present study assesses the uncertainty of flow and radionuclide transport in the unsaturated zone at Yucca Mountain using a Monte Carlo method. Matrix permeability, porosity, and sorption coefficient are considered random. Different from previous studies that assume distributions of the parameters, the distributions are determined in this study by applying comprehensive transformations and rigorous statistics to on-site measurements of the parameters. The distribution of permeability is further adjusted based on model calibration results. Correlation between matrix permeability and porosity is incorporated using the Latin Hypercube Sampling method. After conducting 200 Monte Carlo simulations of three-dimensional unsaturated flow and radionuclide transport for conservative and reactive tracers, the mean, variances, and 5th, 50th, and 95th percentiles for quantities of interest (e.g., matrix liquid saturation and water potential) are evaluated. The mean and 50th percentile are used as the mean predictions, and their associated predictive uncertainties are measured by the variances and the 5th and 95th percentiles (also known as uncertainty bounds). The mean predictions of matrix liquid saturation and water potential are in reasonable agreement with corresponding measurements. The uncertainty bounds include a large portion of the measurements, suggesting that the data variability can be partially explained by parameter uncertainty. The study illustrates propagation of predictive uncertainty of percolation flux, increasing downward from repository horizon to water table. Statistics from the breakthrough curves indicate that transport of the reactive tracer is delayed significantly by the sorption process, and prediction on the reactive tracer is of greater uncertainty than on the conservative tracer because randomness in the sorption coefficient increases the prediction uncertainty. Uncertainty in radionuclide transport is related to uncertainty in the percolation flux, suggesting that reducing the former entails reduction in the latter.     

Estimating magnetic dike parameters using a non‐linear constrained inversion technique: an example from the Särna area,west central Sweden

In this paper, we describe a non‐linear constrained inversion technique for 2D interpretation of high resolution magnetic field data along flight lines using a simple dike model. We first estimate the strike direction of a quasi 2D structure based on the eigenvector corresponding to the minimum eigenvalue of the pseudogravity gradient tensor derived from gridded, low‐pass filtered magnetic field anomalies, assuming that the magnetization direction is known. Then the measured magnetic field can be transformed into the strike coordinate system and all magnetic dike parameters – horizontal position, depth to the top, dip angle, width and susceptibility contrast – can be estimated by non‐linear least squares inversion of the high resolution magnetic field data along the flight lines. We use the Levenberg‐Marquardt algorithm together with the trust‐region‐reflective method enabling users to define inequality constraints on model parameters such that the estimated parameters are always in a trust region. Assuming that the maximum of the calculated g_zz (vertical gradient of the pseudogravity field) is approximately located above the causative body, data points enclosed by a window, along the profile, centred at the maximum of g_zz are used in the inversion scheme for estimating the dike parameters. The size of the window is increased until it exceeds a predefined limit. Then the solution corresponding to the minimum data fit error is chosen as the most reliable one. Using synthetic data we study the effect of random noise and interfering sources on the estimated models and we apply our method to a new aeromagnetic data set from the Särna area, west central Sweden including constraints from laboratory measurements on rock samples from the area.     

Non‐linear prestack seismic inversion with global optimization using an edge‐preserving smoothing filter

Estimating elastic parameters from prestack seismic data remains a subject of interest for the exploration and development of hydrocarbon reservoirs. In geophysical inverse problems, data and models are in general non‐linearly related. Linearized inversion methods often have the disadvantage of strong dependence on the initial model. When the initial model is far from the global minimum, inversion iteration is likely to converge to the local minimum. This problem can be avoided by using global optimization methods. In this paper, we implemented and tested a prestack seismic inversion scheme based on a quantum‐behaved particle swarm optimization (QPSO) algorithm aided by an edge‐preserving smoothing ( EPS) operator. We applied the algorithm to estimate elastic parameters from prestack seismic data. Its performance on both synthetic data and real seismic data indicates that QPSO optimization with the EPS operator yields an accurate solution.     

2007年宁洱6.4级地震研究

根据云南宁洱地区地质构造、 历史强震资料、 云南监测中心区域台及现场流动台数字化观测台网测定的2007年宁洱6.4级地震序列资料及1970年以来宁洱地区6级地震序列等, 深入分析研究了宁洱地区中强地震活动规律、 宁洱6.4级地震的余震时空展布以及参数变化等特征, 并利用2007年宁洱6.4级地震地震现场数字化观测流动台测定的余震波资料研究了该序列地震波动力学特征。 研究结果认为, 宁洱6级地震活动在空间上具有较高的原地重复性, 在时间上具有强弱交替活动的韵律; 2007年6月3日宁洱6.4级地震的余震展布方向与穿过震区NW向宁洱断裂的走向大致一致, 宁洱6.4级地震可能是由无量山断裂活动构造加剧所引起;根据2007年6月3日宁洱6.4级地震序列及历次宁洱6级地震序列时序发展特征分析研究得出, 宁洱6.4级地震序列能量主要集中在震后3天内释放, 4.9级以上余震发生在主震当天, 地震序列早期参数和3.0级以上余震的垂直方向P波最大振幅与S波最大振幅非线性关系等显示, 宁洱6.4级地震序列具有较明显的主-余震型特征。     

Numerical modeling of the central Black Sea ecosystem functioning during the eutrophication phase

A one-dimensional coupled physical-biogeochemical model has been developed to simulate the ecosystem of the central Black Sea at the end of the 1980s when eutrophication and invasion by gelatinous organisms seriously affected the stability and dynamics of the system. The physical model is the General Ocean Turbulence Model (GOTM) and the biogeochemical model describes the foodweb from bacteria to gelatinous carnivores through 24 state variables including three groups of phytoplankton: diatoms, small phototrophic flagellates and dinoflagellates, two zooplankton groups: micro- and mesozooplankton, two groups of gelatinous zooplankton: the omnivorous and carnivorous forms, an explicit representation of the bacterial loop: bacteria, labile and semi-labile dissolved organic matter, particulate organic matter. The model simulates oxygen, nitrogen, silicate and carbon cycling. In addition, an innovation of this model is that it explicitly represents processes in the anoxic layer. Biogeochemical processes in anaerobic conditions have been represented using an approach similar to that used in the modeling of diagenetic processes in the sediments lumping together all the reduced substances in one state variable [Soetaert, K., Herman, P., 1996. A model of early diagenetic processes from the shelf to abyssal depths. Geochimica et Cosmochimica Acta 60 (6) 1019-1040]. In this way, processes in the upper oxygenated layer are fully coupled with anaerobic processes in the deep waters, allowing to perform longterm simulations.The mathematical modeling of phytoplankton and zooplankton dynamics, detritus and the microbial loop is based on the model developed by Van den Meersche et al. [Van den Meersche, K., Middelburg, J., Soetaert, K., van Rijswijk P.H.B., Heip, C., 2004. Carbon-nitrogen coupling and algal-bacterial interactions during an experimental bloom: Modeling a 13c tracer experiment. Limnology and Oceanography 49 (3), 862-878] and tested in the modeling of mesocosm experiments and of the Ligurian sea ecosystem [Raick, C., Delhez, E., Soetaert, K., Gregoire, M., 2005. Study of the seasonal cycle of the biogeochemical processes in the Ligurian sea using an 1D interdisciplinary model. Journal of Marine Systems 55 (3-4) 177-203]. This model has been extended to simulate the development of top predators, the aggregation of detritus as well as the degradation and chemical processes in suboxic/anoxic conditions (e.g. denitrification, anoxic remineralization, redox reactions).The coupled model extends down to the sediments ( depth) and is forced at the air-sea interface by the 6 hourly ERA-40 reanalysis of ECMWF data. The model has been calibrated and validated using a large set of data available in the Black Sea TU Ocean Base. The biogeochemical model involves some hundred parameters which are first calibrated by hand using published values. Then, an identifiability analysis has been performed in order to determine a subset of identifiable parameters (i.e. ensemble of parameters that can be together estimated from the amount of data we have at our disposal, see later in the text). Also a subset of 10 identifiable parameters was isolated and an automatic calibration subroutine (Levenberg Marquart) has been used to fine tune these parameters. Additionally, in order to assess the sensitivity of model results to the parameterization of the two gelatinous groups, Monte Carlo simulations were performed perturbing all the parameters governing their dynamics.In order to calibrate the particle dynamics and export, the chemical model was run off-line with the particle and microbial loop model in order to check its capacity of simulating anoxic waters. After a 10⁴ year run, the model simulated profiles similar to observations but steady state was not reached suggesting that the Black Sea deep waters are not at steady state. The fully coupled model was then used to simulate the period 1988-1992 of the Black Sea ecosystem. The model solution exhibits a complex dynamics with several years of transient adjustment. This complexity is imparted by the explicit modeling of top predators. The integrated chlorophyll and phytoplankton biomasses, the maximum concentration and depth of maximum, mesozooplankton biomass, depth of oxycline, primary production, bacterial production, surface concentrations of nutrients and plankton simulated by the model and obtained from available data analysis were compared and showed a satisfactory agreement. Also, as in the data, the model shows a continuous development of phytoplankton throughout the year, with an intense spring bloom dominated by diatoms and a fall bloom dominated by dinoflagellates. Dinoflagellates dominate from summer until late fall while small phototrophic flagellates are never dominant in terms of biomass, but are present almost throughout the year except in winter. The model simulates an intense silicate removal associated to increased diatoms blooms which were promoted by increased nutrient conditions, and by the presence of gelatinous zooplankton. This silicate pumping leads to silicate limitation of diatoms development in summer allowing the development of dinoflagellates.     

Estimating wave crest distributions using the method of L-moments

The design of fixed or floating offshore structures requires accurate information of the met-ocean data at the intended offshore site. In the design process it is recognized that this environmental data is modified in the near-field by the interaction with the particular geometrical configuration of the offshore structure. This transformation of the incident wave field around and beneath an offshore structure presents a challenge for ocean engineers when specifying the wave gap elevation to avoid impact loads on the underside of the deck and inundation of the topsides. Thus, the accurate estimation of the wave crest distributions from measurements at various locations near and under the offshore structure during model test studies is essential. A semi-empirical approach is presented herein that builds upon the findings of previous studies and introduces the Method of L-moments. A three parameter model for a wave crest probability distribution function is presented and explicit relationships between the parameters of the distribution and its’ first three L-Moments are established. Furthermore, three narrow-band models from earlier research studies are reviewed and compared with the new model. Wave measurements from a mini-TLP model test program are used as the basis for comparison of the four distributions. The root-mean-square error is used as a metric to quantify the overall fit of the data and its accuracy in the high end tail of the data. The L-Moment model is shown to be more robust in representing the data in both the far-field and beneath the deck of the mini-TLP where the wave field demonstrates increased non-linear behavior.     

Artificial neural network-based storm surge forecast model: Practical application to Sakai Minato,Japan

The present study describes a novel way of a systematic and objective selection procedure for the development of an Artificial Neural Network-based storm Surge Forecast Model (ANN-SFM) with the 5, 12 and 24 h-lead times and its application to Sakai Minato area on the Tottori coast, Japan. The selection procedure guides how to determine the superiority of the best performing model in terms of the appropriate combination of unit number in the hidden layer and parameter in the input layer. In the application of ANN-SFM to Sakai Minato, it is found that the best 5 and 12 h-forecast ANN-SFMs are established with the most suitable set of 70 units (the number of hidden neurons) and the input components of surge level, sea level pressure, the depression rate of sea level pressure, longitude, latitude, central atmospheric pressure and highest wind speed. The best 24 h-forecast ANN-SFM is determined with 160 units and the input parameters of surge level, sea level pressure, the depression rate of sea level pressure, longitude and latitude. The proposed method of the selection procedure is able to be adaptable to other coastal locations for the development of the artificial neural network-based storm surge forecast model as establishing the superiority of the most relevant set combining unit numbers and input parameters.     

An inverse problem methodology for multiple parameter estimation in bend stiffeners

The flexible riser top connection is a critical region for lifetime assessment due to large tension/curvature variations and modeling uncertainties. The bend stiffener polyurethane mechanical response not only presents a nonlinear loading rate and temperature dependency but is also subjected to weather ageing during operation, which may affect its mechanical behavior over time. The top tension, employed for riser local cross-section stress calculation, is usually obtained from global dynamic analyses performed under selected environmental conditions, if direct measurement is not available. As a consequence, both the bend stiffener effect on the curvature distribution and the top tension time series present inherent uncertainties for riser lifetime (re)assessment. In the present work, a proposed monitoring approach composed by gyrometers installed along flexible riser/bend stiffener top connection system length combined with an inverse problem methodology is numerically investigated to estimate the following parameters: (i) polyurethane hyperelastic response and (ii) effective top tension. The top connection system is modeled using a large deflection beam bending model and the parameters are estimated using a damped least-square minimization approach with the Levenberg–Marquardt algorithm. For the preliminary feasibility investigation, the gyrometer experimental data is numerically estimated through Monte Carlo simulations. A case study is carried out to investigate the influence that the number of sensors, sensors arrangement, loading conditions and top connection model have on the inverse parameters estimation. The results indicate that the proposed monitoring approach and inverse parameter estimation methodology may effectively reduce flexible riser lifetime calculation uncertainties.     

Statistical estimation of corner frequency and its application to seismic event-identification

A statistical method is proposed for estimation of the corner frequency. It is based on inference for a stochastic model whose short-term behavior resembles the established source time functions. Properties of the estimates are investigated and some numerical examples are presented. A discussion concerning earthquake–explosion discrimination and the way corner frequency can be related to the rate of zero-crossings is also included. The paper is concluded with some numerical examples.     

河谷深度与地震液化的相关性研究

沿河工程多修建在可液化的河谷场地。地震导致的场地液化是造成沿河工程严重震害的重要原因。河谷场地具有明显的地形效应。不同尺寸的河谷场地,会呈现不同的地震液化响应。将地形效应与场地液化相关联进行系统研究具有重要的工程意义和研究价值。在本研究阶段,采用OpenSees计算分析了5个具有不同河谷深度的可液化场地模型,详细探讨了河谷深度的变化对场地地震液化判定指标值的影响。研究发现,地震过程中,在距离谷底一定深度范围内,谷深参数与饱和砂土孔隙水压力存在显著相关性。河谷不断变深,自由水体从无到有,谷底浅表区域受到的剪缩作用逐渐减弱,剪胀作用逐渐增强,瞬时液化区由坡脚浅表区域逐渐向更深处迁移。此外,相对于河谷中点处,坡脚处饱和砂土孔隙水压力与河谷深度的相关性更为显著。本文提出的含自由水体的数值建模技术以及将地形效应与场地液化关联研究所获得的结论可以为新建沿河工程的选址、场地抗液化方案设计等提供一些借鉴和指导。