Simultaneous identification of time and space variant dynamic soil properties during the 1995 Hyogoken-Nanbu earthquake

Time and space variant soil properties at a liquefied site were simultaneously identified in the time domain by using borehole array strong motion records. During soil liquefaction at a site, soils usually show a wide variety of non-linear behavior along the depth as well as non-stationary behavior. Strong ground motion records were obtained at Port Island borehole array observatory, Kobe, during the 1995 Hyogoken-Nanbu earthquake. In this study, the instrumented soil was modeled by the equivalent linear MDOF system, and an extended Kalman filter with local iteration was employed for the identification of the soils. The identification process was successfully conducted, and the stress–strain relationships of the soils at the liquefied site were obtained from different depths all at once.     

Non-stationary covariance function modelling in 2D least-squares collocation

Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the observed data. However, the assumption that the spatial dependence is constant throughout the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage for dealing with non-stationarity in geodetic data. We then compared stationary and non- stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC.     

Non-stationary random vibrations of a shear beam under high frequency seismic effects

Band-limited, non-stationary random vibrations of a shear beam are studied in order to investigate high frequency seismic effects on building structures. A solution for the evolutionary spectral density of the shear beam response to a time segment of band-limited white noise is given in a closed form. The root mean square (rms) and peak response of the shear beam are studied for two characteristic frequency bands: the conventional 1–4 Hz and higher frequency 4–16 Hz, characteristic for rockburst ground motion. Applying the criterion of equal excitation intensity with constant rms velocity, both responses are analyzed in detail and compared. The “switching off” fundamental mode for high frequency excitations results in characteristic overshoot of the stationary response level by the non-stationary rms response and an amplification of the response in the upper part of the shear beam.     

Revising the paradigm of tidal analysis – the uses of non-stationary data

Surface elevation and current records contain non-tidal variance, often dismissed as noise. The processes responsible for the non-tidal component may also modulate the tidal signal, altering its strength and frequency structure. Because of their manner of generation and propagation, internal tides are inherently irregular. The non-stationary character of these and other tidal processes provides an integral and useful property of tidal records, because it provides an opportunity to obtain insights into tidal dynamics and the interaction of tidal and non-tidal processes. It is, moreover, productive to use multiple approaches in analyzing coastal and estuarine tidal processes so that both the time-varying and average frequency content are determined. Only by confronting the causes of non-stationary behaviour in this way can some of the remaining challenges in tidal analysis and prediction be overcome, e.g. shelf and estuarine currents, river tides, internal tides, tide-surge interactions and tidally influenced ecological processes. Several examples illustrate the utility of non-stationary tidal analysis methods.Responsible Editor: Jens Kappenberg     

基于FFT-MA的随机介质建模方法

随机介质是描述地球介质小尺度非均匀性的有效模型,在地震散射波场分析、储层描述等领域具有广泛应用,快速准确的随机介质建模方法是开展相关研究的基础与前提.本文首次将FFT-MA（Fast Fourier Transform Moving Average）算法引入到随机介质建模研究中,分析了该方法与传统随机介质建模方法相比具有的优势,并提出了基于FFT-MA的非平稳随机介质建模方法.建模实验表明,与传统的基于谱分解定理的随机介质建模方法相比,基于FFT-MA的方法在空间域产生随机数序列,使随机数序列与结构参数分离,因此,随机数序列与所建模型存在空间上的对应关系,可以分区域建模和局部修改模型.在非平稳随机介质模型建模时,滑动窗口的大小可以根据自相关长度变化而变化,避免了每个采样点都建立一次完整大小的模型,提高了建模效率.因此,FFT-MA随机介质建模方法能准确构建满足自相关函数要求的平稳及非平稳随机介质模型,具有建模效率高、灵活、实用的优点.     

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space–time heterogeneity of rainfall observations make space–time estimation of precipitation a challenging task. In this paper we propose a Box–Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space–time monthly precipitation in the monsoon periods during 1974–2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space–time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.     

An investigation of the multi-scale temporal variability of beach profiles at Duck using wavelet packet transforms

In an earlier paper a particular discrete wavelet transform (DWT) was used to study the complex variation of beach profile changes. However, use of the DWT requires that the sequence of spatial and temporal resolution is fixed as a dyadic sequence, which means that the variability over longer intervals is not characterised well. Here we introduce the discrete wavelet packet transform (DWPT) that uses an adaptive scaling to partition the data variance, according to an entropy cost function. The advantages of this approach are demonstrated by its application to the study of temporal variability of a 22 year record of beach profile data from the Field Research Facility (FRF) at Duck, North Carolina, USA. Time series of beach elevations at three locations across a particular profile are investigated in detail. We conclude that the DWPT provides a superior analysis of non-stationary time series to that of the DWT, with improved resolution of the scale intervals of the variability. The beach elevation around the shoreline is shown to respond at both sub-annual and interannual scales, but variability at an annual scale is weak. Moving seaward into deeper water, the variance is partitioned into fewer and longer scales. It is confirmed that elevation changes around the inner bar at Duck exhibit a strong interannual variation consistent with Plant et al. (Plant, N.G., Holman, R.A. and Freilich, M.H., 1999. A simple model for interannual sandbar behaviour. Journal of Geophysical Research 104(C7), 15755–15776). Around 23% of the variance around the inner bar is explained at the temporal scale of 64–128 months, which is consistent with the bar behaviour of 6 years found by Ruessink et al. (Ruessink, B. G., Wijnberg, K. M., Holman, R. A., Kuriyama, Y. and Van Enckevort, I. M. J., 2003. Intersite comparison of interannual nearshore bar behaviour. Journal of Geophysical Research, 108 (C8): 1–12). A significant new finding is, however, that about 26% of the variance is attributable to temporal scales of 16–21.3 months. Reconstruction of the wavelet packet components for individual temporal scales is shown to provide a means for identifying the impact and scale of non-stationary events, such as storms, on the beach response. This provides further information that can be used to interpret the morphological changes in terms of the forcing processes and also serves to inform morphodynamic modelling.     

Even–odd analysis on a complex shoreline

An even–odd signal decomposition is performed on a complex shoreline having a longshore sediment transport gradient. The expected impact of erosion due to a navigation channel and structures is discussed and implications of the transport gradient on the decomposed shoreline signal are noted.     

Assessment of the seismic non-linear behavior of ductile wall structures due to synthetic earthquakes

In this paper, different methods for generating synthetic earthquakes are compared in terms of related non-linear seismic response of ductile structures. The objective of the investigation is to formulate recommendations for the use of synthetic earthquakes for reliable seismic analysis. The comparison is focused on the accuracy of the reproduction of the characteristics of the structural non-linear response due to recorded earthquakes. First the investigations are carried out for non-linear single-degree-of-freedom systems. Later, the results are validated for a set of realistic buildings modelled as multi-degree-of-freedom systems. Various options of the classical stationary simulation procedure of SIMQKE and a non-stationary simulation procedure proposed by Sabetta and Pugliese are examined and compared. The adopted methodology uses a set of recorded earthquakes as a reference. Hundred synthetic accelerograms are generated for each examined simulation option with the condition that the related elastic responses are similar to those of the reference set. The non-linear single-degree-of-freedom systems are defined using six recognized hysteretic models and four levels of increasing non-linearity. The non-linear responses computed for the reference set and the studied simulation options are then statistically compared in terms of displacement ductility and energy. The results show that the implementation of the classical stationary procedure always leads to a significant underestimation of the ductility demand and a significant overestimation of the energy demand. By contrast, non-stationary time histories produce much better results. The results with the multi-degree-of-freedom systems are shown to confirm these conclusions.