Algorithmic options for joint time-frequency analysis in structural dynamics applications

The purpose of this paper is to present recent research efforts by the authors supporting the superiority of joint time-frequency analysis over the traditional Fourier transform in the study of non-stationary signals commonly encountered in the fields of earthquake engineering, and structural dynamics. In this respect, three distinct signal processing techniques appropriate for the representation of signals in the time-frequency plane are considered. Namely, the harmonic wavelet transform, the adaptive chirplet decomposition, and the empirical mode decomposition, are utilized to analyze certain seismic accelerograms, and structural response records. Numerical examples associated with the inelastic dynamic response of a seismically-excited 3-story benchmark steel-frame building are included to show how the mean-instantaneous-frequency, as derived by the aforementioned techniques, can be used as an indicator of global structural damage

Joint time-frequency representation of simulated earthquake accelerograms via the adaptive chirplet transform

Seismic accelerograms are inherently nonstationary signals since both the intensity and frequency content of seismic events evolve in time. The adaptive chirplet transform is a signal processing technique for joint time-frequency representation of nonstationary data. Analysis of a signal via the adaptive chirplet decomposition in conjunction with the Wigner-Ville distribution yields the so-called adaptive spectrogram which constitutes a valid representation of the signal in the time-frequency plane. In this paper the potential of this technique for capturing the temporal evolution of the frequency content of strong ground motions is assessed. In this regard, simulated nonstationary earthquake accelerograms compatible with an exponentially modulated and appropriately filtered Kanai-Tajimi spectrum are processed using the adaptive chirplet transform. These are samples of a random process whose evolutionary power spectrum can be represented by an analytical expression. It is suggested that the average of the ensemble of the adaptive chirplet spectrograms can be construed as an estimate of the underlying evolutionary power spectrum. The obtained numerical results show, indeed, that the estimated evolutionary power spectrum is in a good agreement with the one defined analytically. This fact points out the potential of the adaptive chirplet analysis for as a tool for capturing localized frequency content of arbitrary data- banks of real seismic accelerograms

On the asymptotic theory of subsampling

A general approach to constructing confidence intervals by subsampling was presented in Politis and Romano (1994). The crux of the method is based on recomputing a statistic over subsamples of the data, and these recomputed values are used to build up an estimated sampling distribution. The method works under extremely weak conditions, it applies to independent, identically distributed (LLd.) observations as well as to dependent data situations, such as time series (possible non stationary) , random fields, and marked point processes. In this article, we present some new theorems showing: a new construction for confidence intervals that removes a previous condition, a general theorem showing the validity of subsampling for datadependent choices of the block size, and a general theorem for the construction of hypothesis tests (which is not necessarily derived from a confidence interval construction). The arguments apply to both the Li.d. setting as well as the dependent data case

Subsampling, symmetrization, and robust interpolation

The recently developed subsampling methodology has been shown to be valid for the construction of large-sample confidence regions for a general unknown parameter e under very minimal conditions. Nevertheless, in some specific cases -e.g. in the case of the sample mean of Li.d. data- it has been noted that the subsampling distribution estimators underperform as compared to alternative estimators such as the bootstrap or the asymptotic normal distribution (with estimated variance). In the present report we investigate the extent to which the performance of subsampling distribution estimators can be improved by a (partial) symmetrization technique, while at the same time retaining the robustness property of consistent distribution estimation even in nonregular cases; both i.i.d. and weakly dependent (mixing) observations are considered

Ship-hull shape optimization with a T-spline based BEM-isogeometric solver

In this work, we present a ship-hull optimization process combining a T-spline based parametric ship-hull model and an Isogeometric Analysis (IGA) hydrodynamic solver for the calculation of ship wave resistance. The surface representation of the ship-hull instances comprise one cubic T-spline with extraordinary points, ensuring C2 continuity everywhere except for the vicinity of extraordinary points where G1 continuity is achieved. The employed solver for ship wave resistance is based on the Neumann-Kelvin formulation of the problem, where the resulting Boundary Integral Equation is numerically solved using a higher order collocated Boundary Element Method which adopts the IGA concept and the T-spline representation for the ship-hull surface. The hydrodynamic solver along with the ship parametric model are subsequently integrated within an appropriate optimization environment for local and global ship-hull optimizations against the criterion of minimum resistance

Corticotropin-releasing hormone exerts direct effects on neuronal progenitor cells: implications for neuroprotection

Neurogenesis during embryonic and adult life is tightly regulated by a network of transcriptional, growth and hormonal factors. Emerging evidence indicates that activation of the stress response, via the associated glucocorticoid increase, reduces neurogenesis and contributes to the development of adult diseases.As corticotrophin-releasing hormone (CRH) or factor is the major mediator of adaptive response to stressors, we sought to investigate its involvement in this process. Accordingly, we found that CRH could reverse the damaging effects of glucocorticoid on neural stem/progenitor cells (NS/PCs), while its genetic deficiency results in compromised proliferation and enhanced apoptosis during neurogenesis. Analyses in fetal and adult mouse brain revealed significant expression of CRH receptors in proliferating neuronal progenitors. Furthermore, by using primary cultures of NS/PCs, we characterized the molecular mechanisms and identified CRH receptor-1 as the receptor mediating the neuroprotective effects of CRH. Finally, we demonstrate the expression of CRH receptors in human fetal brain from early gestational age, in areas of active neuronal proliferation. These observations raise the intriguing possibility for CRH-mediated pharmacological applications in diseases characterized by altered neuronal homeostasis, including depression, dementia, neurodegenerative diseases, brain traumas and obesity

Inconsistency of the MLE for the joint distribution of interval censored survival times and continuous marks

This paper considers the nonparametric maximum likelihood estimator (MLE) for the joint distribution function of an interval censored survival time and a continuous mark variable. We provide a new explicit formula for the MLE in this problem. We use this formula and the mark specific cumulative hazard function of Huang and Louis (1998) to obtain the almost sure limit of the MLE. This result leads to necessary and sufficient conditions for consistency of the MLE which imply that the MLE is inconsistent in general. We show that the inconsistency can be repaired by discretizing the marks. Our theoretical results are supported by simulations.Comment: 27 pages, 4 figure

Modelling wake effects in large wind farms in complex terrain: the problem, the methods and the issues

Computational fluid dynamic (CFD) methods are used in this paper to predict the power production from entire wind farms in complex terrain and to shed some light into the wake flow patterns. Two full three-dimensional Navier–Stokes solvers for incompressible fluid flow, employing k − ϵ and k − ω turbulence closures, are used. The wind turbines are modeled as momentum absorbers by means of their thrust coefficient through the actuator disk approach. Alternative methods for estimating the reference wind speed in the calculation of the thrust are tested. The work presented in this paper is part of the work being undertaken within the UpWind Integrated Project that aims to develop the design tools for next generation of large wind turbines. In this part of UpWind, the performance of wind farm and wake models is being examined in complex terrain environment where there are few pre-existing relevant measurements. The focus of the work being carried out is to evaluate the performance of CFD models in large wind farm applications in complex terrain and to examine the development of the wakes in a complex terrain environment

Wave-resistance computation via CFD and IGA-BEM solvers : a comparative study

This paper delivers a preliminary comparative study on the computation of wave resistance via a commercial CFD solver (STAR-CCM+®) versus an in-house developed IGA-BEM solver for a pair of hulls, namely the parabolic Wigley hull and the KRISO container ship (KCS). The CFD solver combines a VOF (Volume Of Fluid) free-surface modelling technique with alternative turbulence models, while the IGA-BEM solver adopts an inviscid flow model that combines the Boundary Element approach (BEM) with Isogeometric Analysis (IGA) using T-splines or NURBS. IGA is a novel and expanding concept, introduced by Hughes and his collaborators (Hughes et al, 2005), aiming to intrinsically integrate CAD with Analysis by communicating the CAD model of the geometry (the wetted ship hull in our case) to the solver without any approximation