A stochastic approach to synthesizing response spectrum compatible seismic accelerograms

Regulatory agencies require the use of artificial accelerograms satisfying specific criteria of compatibility with a given design spectrum, as input for certain types of analyses for the aseismic design of critical facilities. Most of the numerical methods for simulating seismic motions compatible with a specified design (target) spectrum proposed by various researchers require that a number of real recorded seismic accelerograms of appropriate frequency content is available. To by-pass this requirement, a previously established in the literature probabilistic approach to yield simulated earthquake records whose response spectrum achieves on average a certain level of agreement with a target spectrum is employed in the present paper. At the core of the above method lies the adoption of an appropriate parametric power spectrum model capable of accounting for various site-specific soil conditions. In this regard, the potential of two different, commonly, used spectral forms is evaluated for this purpose in context with the design spectrum defined by the European Code provisions. Next, an iterative wavelet-based matching procedure is applied to the thus acquired records to enhance, individually, the agreement of the corresponding response spectra with the targeted one. Special attention is paid to ensure that the velocity and the displacement time histories associated with the finally obtained artificial accelerograms are physically sound by means of appropriate baseline correction techniques

Wavelet-based response spectrum compatible synthesis of accelerograms-Eurocode application (EC8)

An integrated approach for addressing the problem of synthesizing artificial seismic accelerograms compatible with a given displacement design/target spectrum is presented in conjunction with aseismic design applications. Initially, a stochastic dynamics solution is used to obtain a family of simulated non-stationary earthquake records whose response spectrum is on the average in good agreement with the target spectrum. The degree of the agreement depends significantly on the adoption of an appropriate parametric evolutionary power spectral form, which is related to the target spectrum in an approximate manner. The performance of two commonly used spectral forms along with a newly proposed one is assessed with respect to the elastic displacement design spectrum defined by the European code regulations (EC8). Subsequently, the computational versatility of the family of harmonic wavelets is employed to modify iteratively the simulated records to satisfy the compatibility criteria for artificial accelerograms prescribed by EC8. In the process, baseline correction steps, ordinarily taken to ensure that the obtained accelerograms are characterized by physically meaningful velocity and displacement traces, are elucidated. Obviously, the presented approach can be used not only in the case of the EC8, for which extensive numerical results/examples are included, but also for any code provisions mandated by regulatory agencies. In any case, the presented numerical results can be quite useful in any aseismic design process dominated by the EC8 specifications

Synthesis of accelerograms compatible with the Chinese GB 50011-2001 design spectrum via harmonic wavelets: artificial and historic records

A versatile approach is employed to generate artificial accelerograms which satisfy the compatibility criteria prescribed by the Chinese aseismic code provisions GB 50011-2001. In particular, a frequency dependent peak factor derived by means of appropriate Monte Carlo analyses is introduced to relate the GB 50011-2001 design spectrum to a parametrically defined evolutionary power spectrum (EPS). Special attention is given to the definition of the frequency content of the EPS in order to accommodate the mathematical form of the aforementioned design spectrum. Further, a one-to-one relationship is established between the parameter controlling the time-varying intensity of the EPS and the effective strong ground motion duration. Subsequently, an efficient auto-regressive moving-average (ARMA) filtering technique is utilized to generate ensembles of non-stationary artificial accelerograms whose average response spectrum is in a close agreement with the considered design spectrum. Furthermore, a harmonic wavelet based iterative scheme is adopted to modify these artificial signals so that a close matching of the signals’ response spectra with the GB 50011-2001 design spectrum is achieved on an individual basis. This is also done for field recorded accelerograms pertaining to the May, 2008 Wenchuan seismic event. In the process, zero-phase high-pass filtering is performed to accomplish proper baseline correction of the acquired spectrum compatible artificial and field accelerograms. Numerical results are given in a tabulated format to expedite their use in practice

Impact of gaps in the asteroseismic characterization of pulsating stars. I. On the efficiency of pre-whitening

It is known that the observed distribution of frequencies in CoRoT and Kepler {\delta} Scuti stars has no parallelism with any theoretical model. Pre-whitening is a widespread technique in the analysis of time series with gaps from pulsating stars located in the classical instability strip such as {\delta} Scuti stars. However, some studies have pointed out that this technique might introduce biases in the results of the frequency analysis. This work aims at studying the biases that can result from pre-whitening in asteroseismology. The results will depend on the intrinsic range and distribution of frequencies of the stars. The periodic nature of the gaps in CoRoT observations, just in the range of the pulsational frequency content of the {\delta} Scuti stars, is shown to be crucial to determine their oscillation frequencies, the first step to perform asteroseismolgy of these objects. Hence, here we focus on the impact of pre-whitening on the asteroseismic characterization of {\delta} Scuti stars. We select a sample of 15 {\delta} Scuti stars observed by the CoRoT satellite, for which ultra-high quality photometric data have been obtained by its seismic channel. In order to study the impact on the asteroseismic characterization of {\delta} Scuti stars we perform the pre-whitening procedure on three datasets: gapped data, linearly interpolated data, and ARMA interpolated data. The different results obtained show that at least in some cases pre-whitening is not an efficient procedure for the deconvolution of the spectral window. therefore, in order to reduce the effect of the spectral window to the minimum it is necessary to interpolate with an algorithm that is aimed to preserve the original frequency content, and not only to perform a pre-whitening of the data.Comment: 27 pages, 47 figures Tables and typos fixe

Surrogate time series

Before we apply nonlinear techniques, for example those inspired by chaos theory, to dynamical phenomena occurring in nature, it is necessary to first ask if the use of such advanced techniques is justified "by the data". While many processes in nature seem very unlikely a priori to be linear, the possible nonlinear nature might not be evident in specific aspects of their dynamics. The method of surrogate data has become a very popular tool to address such a question. However, while it was meant to provide a statistically rigorous, foolproof framework, some limitations and caveats have shown up in its practical use. In this paper, recent efforts to understand the caveats, avoid the pitfalls, and to overcome some of the limitations, are reviewed and augmented by new material. In particular, we will discuss specific as well as more general approaches to constrained randomisation, providing a full range of examples. New algorithms will be introduced for unevenly sampled and multivariate data and for surrogate spike trains. The main limitation, which lies in the interpretability of the test results, will be illustrated through instructive case studies. We will also discuss some implementational aspects of the realisation of these methods in the TISEAN (http://www.mpipks-dresden.mpg.de/~tisean) software package.Comment: 28 pages, 23 figures, software at http://www.mpipks-dresden.mpg.de/~tisea

Nonlinear denoising of transient signals with application to event related potentials

We present a new wavelet based method for the denoising of {\it event related potentials} ERPs), employing techniques recently developed for the paradigm of deterministic chaotic systems. The denoising scheme has been constructed to be appropriate for short and transient time sequences using circular state space embedding. Its effectiveness was successfully tested on simulated signals as well as on ERPs recorded from within a human brain. The method enables the study of individual ERPs against strong ongoing brain electrical activity.Comment: 16 pages, Postscript, 6 figures, Physica D in pres

Digital Signal Processing

Contains an introduction and reports on seventeen research projects.U.S. Navy - Office of Naval Research (Contract N00014-77-C-0266)Amoco Foundation FellowshipU.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)National Science Foundation (Grant ECS80-07102)U.S. Army Research Office (Contract DAAG29-81-K-0073)Hughes Aircraft Company FellowshipAmerican Edwards Labs. GrantWhitaker Health Sciences FundPfeiffer Foundation GrantSchlumberger-Doll Research Center FellowshipGovernment of Pakistan ScholarshipU.S. Navy - Office of Naval Research (Contract N00014-77-C-0196)National Science Foundation (Grant ECS79-15226)Hertz Foundation Fellowshi

New ultrasonic signal processing techniques for NDE applications

New ultrasonic signal processing techniques have been developed for nondestructive evaluation (NDE) applications. This dissertation has two parts. The first part is about the application of the wavelet transform to ultrasonic flaw detection. Wavelet transform is a newly developed signal analysis tool that handles time-localized signals such as an ultrasonic flaw signal quite well. A wavelet transform based signal processing technique has been developed which uses only partial knowledge of the flaw signal waveform that may be obtained from a reference experiment. The detection performance of the proposed technique is found to be comparable to that of the matched filter which requires exact knowledge of the flaw signal waveform and the noise autocorrelation function to obtain good detection performance. The proposed technique based on the wavelet transform can therefore be quite useful in situations where the flaw signal waveform is unknown or partially known. The detection performance of the proposed technique which was evaluated for hard-alpha detection in titanium samples using experimentally obtained grain noise data and simulated flaw data was very close to that of the matched filter;The second part of this dissertation describes a Kalman filter based deconvolution algorithm for ultrasonic signals and its application to material characterization and hard-alpha detection. The Kalman filter based deconvolution algorithm is based on state-space modeling of the ultrasonic measurement system. Since the Kalman filter can handle time-varying systems and non-stationary statistics quite naturally, it is better suited for such situations than the Wiener filter approach. A signal processing technique using Kalman filter based deconvolution algorithm has been developed and applied to characterize materials with different grain sizes and to detect inclusions from host material. The proposed method was tested using experimentally obtained ultrasonic data from pure titanium samples with different grain sizes. The results showed good detection performance for detecting inclusions larger that 4 mm

MIARMA: An information preserving method for filling gaps in time series. Application to CoRoT light curves

The method here presented intends to minimize the effect of the gaps in the power spectra by gap-filling preserving the original information, that is, in the case of asteroseismology, the stellar oscillation frequency content. We make use of a forward-backward predictor based on autoregressive moving average modelling (ARMA) in the time domain. The method MIARMA is particularly suitable for replacing invalid data such as those present in the light curves of the CoRoT satellite due to the pass through the South Atlantic Anomaly, and eventually for the data gathered by the NASA planet hunter Kepler. We select a sample of stars from the ultra-precise photometry collected by the asteroseismic camera on board the CoRoT satellite: the {\delta} Scuti star HD 174966, showing periodic variations of the same order as the CoRoT observational window, the Be star HD 51193, showing longer time variations, and the solar-like HD 49933, with rapid time variations. We showed that in some cases linear interpolations are less reliable to what was believed. In particular: the power spectrum of HD 174966 is clearly aliased when this interpolation is used for filling the gaps; the light curve of HD 51193 presents a much more aliased spectrum than expected for a low frequency harmonic signal; and finally, although the linear interpolation does not affect noticeably the power spectrum of the CoRoT light curve of the solar-like star HD 49933, the ARMA interpolation showed rapid variations previously unidentified that ARMA interprets as a signal. In any case, the ARMA interpolation method provides a cleaner power spectrum, that is, less contaminated by spurious frequencies. In conclusion, MIARMA appears to be a suitable method for filling gaps in the light curves of pulsating stars observed by CoRoT since the method preserves their frequency content, which is a necessary condition for asteroseismic studies.Comment: 9 pages, 9 figures, submitted to A&