Invariants and spectral estimates for Laplacians on periodic graphs

Vertical to Horizontal UHS Ratios for Low to Medium Seismicity Regions with Deep Soil atop Deep Geological Sediments—An Example of the City of Osijek, Croatia

Applied Sciences ◽

10.3390/app11156782 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6782

Author(s):

Borko Đ. Bulajić ◽

Marijana Hadzima-Nyarko ◽

Gordana Pavić

Keyword(s):

Ground Motions ◽

Spectral Amplitude ◽

Eurocode 8 ◽

Uniform Hazard Spectra ◽

Study Region ◽

Spectral Estimates ◽

Local Soil ◽

The Impact ◽

Deep Soils ◽

The City

The severity of vertical seismic ground motions is often factored into design regulations as a component of their horizontal counterparts. Furthermore, most design codes, including Eurocode 8, ignore the impact of local soil on vertical spectra. This paper investigates vertical pseudo-absolute acceleration spectral estimates, as well as the ratios of spectral estimates for strong motion in vertical and horizontal directions, for low to medium seismicity regions with deep local soil and deep geological sediments beneath the local soil. The case study region encompasses the city of Osijek in Croatia. New regional frequency-dependent empirical scaling equations are derived for the vertical spectra. According to these equations, for a 0.3 s spectral amplitude at deep soils atop deep geological sediments compared to the rock sites, the maximum amplification is 1.48 times. The spectra of vertical components of various real strong motions recorded in the surrounding region are compared to the empirical vertical response spectra. The new empirical equations are used to construct a Uniform Hazard Spectra for Osijek. The ratios of vertical to horizontal Uniform Hazard Spectra are generated, examined, and compared to Eurocode 8 recommendations. All the results show that local soil and deep geology conditions have a significant impact on vertical ground motions. The results also show that for deep soils atop deep geological strata, Eurocode 8 can underestimate the vertical to horizontal spectral ratios by a factor of three for Type 2 spectra while overestimating them by a factor of two for Type 1 spectra.

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THE SAMPLING VARIABILITY OF THE AUTOREGRESSIVE SPECTRAL ESTIMATES FOR TWO-VARIATE HYDROMETEOROLOGICAL PROCESSES

Mathematical Statistics Theory and Applications ◽

10.1515/9783112319086-097 ◽

1987 ◽

pp. 651-654

Keyword(s):

Sampling Variability ◽

Spectral Estimates

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Homogenization of constrained optimal control problems for one-dimensional elliptic equations on periodic graphs

ESAIM Control Optimisation and Calculus of Variations ◽

10.1051/cocv:2008037 ◽

2008 ◽

Vol 15 (2) ◽

pp. 471-498 ◽

Cited By ~ 4

Author(s):

Peter I. Kogut ◽

Günter Leugering

Keyword(s):

Optimal Control ◽

Elliptic Equations ◽

Optimal Control Problems ◽

Control Problems ◽

Constrained Optimal Control ◽

One Dimensional ◽

Periodic Graphs

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A Frequency-Domain Filtering Technique for Triple Decomposition of Unsteady Turbulent Flow

Journal of Fluids Engineering ◽

10.1115/1.2909998 ◽

1992 ◽

Vol 114 (1) ◽

pp. 45-51 ◽

Cited By ~ 13

Author(s):

G. J. Brereton ◽

A. Kodal

Keyword(s):

Time Series ◽

Turbulent Flow ◽

Frequency Domain ◽

Measurement Data ◽

Averaging Technique ◽

Phase Averaging ◽

Spectral Estimates ◽

Improved Performance ◽

A New Technique ◽

Flow Variables

A new technique is presented for decomposing unsteady turbulent flow variables into their organized unsteady and turbulent components, which appears to offer some significant advantages over existing ones. The technique uses power-spectral estimates of data to deduce the optimal frequency-domain filter for determining the organized and turbulent components of a time series of data. When contrasted with the phase-averaging technique, this method can be thought of as replacing the assumption that the organized motion is identically reproduced in successive cycles of known periodicity by a more general condition: the cross-correlation of the organized and turbulent components is minimized for a time series of measurement data, given the expected shape of the turbulence power spectrum. The method is significantly more general than the phase average in its applicability and makes more efficient use of available data. Performance evaluations for time series of unsteady turbulent velocity measurements attest to the accuracy of the technique and illustrate the improved performance of this method over the phase-averaging technique when cycle-to-cycle variations in organized motion are present.

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