The Experts below are selected from a list of 6129 Experts worldwide ranked by ideXlab platform

Justin Chow Hollenback - One of the best experts on this subject based on the ideXlab platform.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

Norman A Abrahamson - One of the best experts on this subject based on the ideXlab platform.

  • a non ergodic effective Amplitude ground motion model for california
    Bulletin of Earthquake Engineering, 2021
    Co-Authors: Grigorios Lavrentiadis, Norman A Abrahamson, Nicolas Kuehn
    Abstract:

    A new non-ergodic ground-motion model (GMM) for effective Amplitude spectral (EAS) values for California is presented in this study. EAS, which is defined in Goulet et al. (Effective Amplitude Spectrum (eas) as a metric for ground motion modeling using Fourier Amplitudes, 2018), is a smoothed rotation-independent Fourier Amplitude Spectrum of the two horizontal components of an acceleration time history. The main motivation for developing a non-ergodic EAS GMM, rather than a spectral acceleration GMM, is that the scaling of EAS does not depend on spectral shape, and therefore, the more frequent small magnitude events can be used in the estimation of the non-ergodic terms. The model is developed using the California subset of the NGAWest2 dataset (Ancheta in PEER NGA-West2 database. Tech. rep., PEER, Berkeley, CA, 2013). The Bayless and Abrahamson (Bull Seismol Soc Am 109(5): 2088-2105, https://doi.org/10.1785/0120190077 , 2019b) (BA18) ergodic EAS GMM was used as backbone to constrain the average source, path, and site scaling. The non-ergodic GMM is formulated as a Bayesian hierarchical model: the non-ergodic source and site terms are modeled as spatially varying coefficients following the approach of Landwehr et al. (Bull Seismol Soc Am 106(6):2574-2583. https://doi.org/10.1785/0120160118 , 2016), and the non-ergodic path effects are captured by the cell-specific anelastic attenuation attenuation following the approach of Dawood and Rodriguez-Marek (Bull Seismol Soc Am 103(2B):1360-1372, https://doi.org/10.1785/0120120125 , 2013). Close to stations and past events, the mean values of the non-ergodic terms deviate from zero to capture the systematic effects and their epistemic uncertainty is small. In areas with sparse data, the epistemic uncertainty of the non-ergodic terms is large, as the systematic effects cannot be determined. The non-ergodic total aleatory standard deviation is approximately 30 to $$40\%$$ smaller than the total aleatory standard deviation of BA18. This reduction in the aleatory variability has a significant impact on hazard calculations at large return periods. The epistemic uncertainty of the ground motion predictions is small in areas close to stations and past events.

  • A Non-Ergodic Effective Amplitude Ground-Motion Model for California
    Research Square Platform LLC, 2021
    Co-Authors: Grigorios Lavrentiadis, Norman A Abrahamson, Nicolas M. Kuehn
    Abstract:

    Abstract A new non-ergodic ground-motion model (GMM) for effective Amplitude spectral (EAS) values for California is presented in this study. EAS, which is defined in Goulet et al. (2018), is a smoothed rotation-independent Fourier Amplitude Spectrum of the two horizontal components of an acceleration time history. The main motivation for developing a non-ergodic EAS GMM, rather than a spectral acceleration GMM, is that the scaling of EAS does not depend on spectral shape, and therefore, the more frequent small magnitude events can be used in the estimation of the non-ergodic terms. The model is developed using the California subset of the NGAWest2 dataset Ancheta et al. (2013). The Bayless and Abrahamson (2019b) (BA18) ergodic EAS GMM was used as backbone to constrain the average source, path, and site scaling. The non-ergodic GMM is formulated as a Bayesian hierarchical model: the non-ergodic source and site terms are modeled as spatially varying coefficients following the approach of Landwehr et al. (2016), and the non-ergodic path effects are captured by the cell-specific anelastic attenuation attenuation following the approach of Dawood and Rodriguez-Marek (2013). Close to stations and past events, the mean values of the non-ergodic terms deviate from zero to capture the systematic effects and their epistemic uncertainty is small. In areas with sparse data, the epistemic uncertainty of the non-ergodic terms is large, as the systematic effects cannot be determined. The non-ergodic total aleatory standard deviation is approximately 30 to 40% smaller than the total aleatory standard deviation of BA18. This reduction in the aleatory variability has a significant impact on hazard calculations at large return periods. The epistemic uncertainty of the ground motion predictions is small in areas close to stations and past event.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

Linda Al Atik - One of the best experts on this subject based on the ideXlab platform.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

Albert R Kottke - One of the best experts on this subject based on the ideXlab platform.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

  • kappa scaling of ground motion prediction equations using an inverse random vibration theory approach
    Bulletin of the Seismological Society of America, 2014
    Co-Authors: Linda Al Atik, Albert R Kottke, Norman A Abrahamson, Justin Chow Hollenback
    Abstract:

    Abstract A method for deriving kappa ( κ ) scaling factors that can be applied to ground‐motion prediction equations (GMPEs) to account for site‐specific κ estimates is described. This method relies on inverse random vibration theory as implemented in the computer program Strata (Kottke and Rathje, 2008a,b) to derive a Fourier Amplitude Spectrum (FAS) that is consistent with the response Spectrum from the GMPE. The GMPE host κ values are estimated by fitting the high‐frequency FAS with the Anderson and Hough (1984) κ scaling function. The derived FAS are then scaled from their host κ value to a target κ . Random vibration theory (Cartwright and Longuet‐Higgins, 1956) is then used to convert the κ scaled FAS to response spectra, and κ scaling factors are computed by the ratio of the κ scaled response spectra to the GMPE response spectra. In contrast to the commonly used hybrid empirical method (Campbell, 2003), the proposed approach does not require a full seismological model for the stochastic parameters (stress drop, whole‐path attenuation, etc.) of the host and target regions and does not assume that response spectral shape of GMPE is consistent with that of the representative point‐source stochastic model for the host region, which can lead to inappropriate response spectral scaling factors. Finally, the effects of the well‐known trade‐off between κ and stress drop scaling are reduced. The method, when applied within the frequency limitations discussed in this paper, can be used to incorporate κ scaling into GMPEs.

Izuru Takewaki - One of the best experts on this subject based on the ideXlab platform.

  • Critical Excitation for Earthquake Energy Input in MDOF System
    Critical Excitation Methods in Earthquake Engineering, 2013
    Co-Authors: Izuru Takewaki
    Abstract:

    This chapter explores a new general critical excitation method for a damped linear elastic single-degree-of-freedom (SDOF) system. It introduces the input energy to the SDOF system during an earthquake as a new measure of criticality. It is shown that the formulation of the earthquake input energy in the frequency domain is essential for solving the critical excitation problem. It is also essential for deriving a bound on the earthquake input energy for a class of ground motions. The criticality is expressed in terms of degree of concentration of input motion components on the maximum portion of the characteristic function defining the earthquake input energy. It is remarkable that no mathematical programming technique is required in the solution procedure. The constancy of earthquake input energy for various natural periods and damping ratios is discussed from a new point of view based on an original sophisticated mathematical treatment. It is shown that the constancy of earthquake input energy is directly related to the uniformity of “the Fourier Amplitude Spectrum” of ground motion acceleration. It is not directly related to the uniformity of the velocity response Spectrum. The bounds under acceleration and velocity constraints are clarified through numerical examinations for recorded ground motions.

  • Instantaneous earthquake input energy and sensitivity in base-isolated building
    The Structural Design of Tall and Special Buildings, 2009
    Co-Authors: Kaoru Yamamoto, Kohei Fujita, Izuru Takewaki
    Abstract:

    The input energy and energy input rate to a base-isolated (BI) building during an earthquake are considered and formulated in the frequency domain. The frequency-domain approach for computation of input energy and energy input rate has different remarkable advantages compared with the conventional time-domain approach. It is demonstrated that the input energy can be of a compact form via the frequency integration of the product between the input component (squared Fourier Amplitude Spectrum of acceleration) and the structural model component (so-called energy transfer function). Furthermore, the energy input rate can also be of a similar form via the frequency integration of the product between the instantaneous power Spectrum and the energy transfer function. With the help of this compact form, it is shown that the formulation in the frequency domain is essential for deriving arbitrary-order closed-form sensitivities of the input energy and energy input rate with respect to uncertain stiffness and damping coefficients in the BI storey. The closed-form sensitivity expressions provide us with information on the most unfavourable variation of the uncertain parameters that leads to the maximum input energy and input rate. Copyright © 2009 John Wiley & Sons, Ltd.

  • earthquake input energy to tall and base isolated buildings in time and frequency dual domains
    Structural Design of Tall and Special Buildings, 2009
    Co-Authors: Izuru Takewaki, Kohei Fujita
    Abstract:

    Earthquake input energies to tall and base-isolated buildings are examined by both time-domain and frequency-domain methods. Both methods support the validity of evaluating the earthquake input energy each other. It is shown that both methods have different advantages and can compensate for each other. While the time-domain method has a long history and is applicable to nonlinear models as well, the frequency-domain method is characterized by the energy transfer function and its equi-area property plays an important role in the discussion of the stability of earthquake input energy. This equi-area property can be derived by the residue theorem only in a simple model. It is also demonstrated that this equi-area property in multi-degree-of-freedom models can be derived by the time-domain method for an idealized model of input motions with a constant Fourier Amplitude Spectrum. This idea is applied to tall and base-isolated buildings. The equi-area property of the energy transfer function provides a stable characteristic on the input energy as far as the total mass of the buildings is constant. Copyright © 2008 John Wiley & Sons, Ltd.

  • Closed-form sensitivity of earthquake input energy to soil-structure interaction system
    Journal of Engineering Mechanics, 2007
    Co-Authors: Izuru Takewaki
    Abstract:

    The input energy to a soil-structure interaction (SSI) system during earthquake shaking is taken as a structural performance measure and is formulated in the frequency domain. The purpose of this paper is to derive the closed-form expression of the sensitivity of the input energy to the SSI system with respect to uncertain parameters representing soil stiffness and damping. It is demonstrated first that the input energy expression can be of a compact form consisting of the product between the input motion component (Fourier Amplitude Spectrum of acceleration) and the structural model component (so-called energy transfer function). With the help of this compact form, it is shown that the formulation of earthquake input energy in the frequency domain is essential for deriving the closed-form expressions of the sensitivity of the input energy to the SSI system with respect to uncertain parameters in contrast to the time-domain formulation including inevitable numerical error and instability. This formulation is then extended to a multidegree-of-freedom superstructure model. Numerical examples support the fact that the closed-form expressions enable one to find in a reliable and efficient way the most critical combination of the uncertain parameters that leads to the maximum energy input.

  • chapter 8 critical excitation for earthquake energy input in sdof system
    Critical Excitation Methods in Earthquake Engineering, 2007
    Co-Authors: Izuru Takewaki
    Abstract:

    Publisher Summary This chapter explores the critical excitation method for earthquake energy input in MDOF system. It is a new complex modal analysis-based method in frequency domain for computation of earthquake input energy to highly damped linear elastic passive control structures. The formulation of the earthquake input energy in the frequency domain is essential for deriving a bound on the earthquake input energy for a class of ground motions. This is because the formulation in the frequency domain only requires the computation of the Fourier Amplitude Spectrum of the input motion acceleration. Importance of over-damped modes in the energy computation of specific non-proportionally damped models is demonstrated. This is reflected by comparing the energy transfer functions and the displacement transfer functions. It demonstrates numerical examinations for four recorded ground motions. It is demonstrated that the modal analysis-based method in frequency domain is very efficient in the computation of earthquake input energy. Furthermore, it is shown that the formulation of earthquake input energy in the frequency domain is essential for understanding the robustness of passively controlled structures to disturbances with various frequency contents. This chapter treats a structure with high-level damping to demonstrate the importance of over-damped modes in the computation of earthquake input energy.