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Author: Amin Ahmadi
Publisher:
ISBN: 9781321361933
Category :
Languages : en
Pages :
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Book Description
The effectiveness of Ground Motion Selection and Modification (GMSM) methodologies is generally assessed by their ability to minimize the effect of ground motion variability during structural demand estimation. This study is concerned with issues and challenges in ground motion selection and modification as well as the consequences of the adopted modification schemes in developing reliable seismic demand models. The estimation of the nonlinear dynamic structural response to a specified level of seismic demand requires hazard consistent ground motion records. The most common way of imposing the hazard consistency is through the scaling of the acceleration intensity value of the ground motion record at the fundamental period of the structure to a target value; this target value (i.e., intensity measure) is estimated by the attenuation models for a specified earthquake scenario. Previous studies have not made a distinction between the dominant modes that result in a specific maximum inter-story drift ratio (MIDR). In this study, by considering the conditional MIDR (dominant mode dependent), it is shown that the aforementioned scaling procedure results in a biased estimation of the median MIDR if the selected records do not contain an equal number of records in each dominant mode set. An alternative scaling scheme is proposed which reduces the dependency of the MIDR estimation on the dominant response mode. A seismic demand model attempts to describe the behavior of a structure in terms of a set of predictor variables that represents the loading. Such predictive demand models are expected to establish a stable and reliable relationship between the dependent variable (structural response) and the independent variables (spectral accelerations). This expectation, however, is problematic in the presence of multicollinearity of the predictor variables because it undermines the performance of the demand model. It is demonstrated that biased estimation of the regression coefficients remedies both the overfitting problem and the instability of the regression coefficients. Finally, the dominant dynamic modes imposed by the ground motion suite are found to have a significant effect on the model predictions. In this study, this influence is quantified in terms of the coefficient of partial determination. It is shown that the marginal contribution of the included variables in the demand model is dependent on the response mode that yields the MIDR. An alternative method of estimating the regression coefficients, i.e., the Ridge estimation, is discussed as an approach that minimizes the influence of the dominant mode on the demand model. The performance of the Ridge estimation is compared with the least squares (unbiased) counterpart using the cross-validation method. Findings from this study have a major impact on the selection and modification of ground motions for seismic assessment of structures.
Author: Amin Ahmadi
Publisher:
ISBN: 9781321361933
Category :
Languages : en
Pages :
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Book Description
The effectiveness of Ground Motion Selection and Modification (GMSM) methodologies is generally assessed by their ability to minimize the effect of ground motion variability during structural demand estimation. This study is concerned with issues and challenges in ground motion selection and modification as well as the consequences of the adopted modification schemes in developing reliable seismic demand models. The estimation of the nonlinear dynamic structural response to a specified level of seismic demand requires hazard consistent ground motion records. The most common way of imposing the hazard consistency is through the scaling of the acceleration intensity value of the ground motion record at the fundamental period of the structure to a target value; this target value (i.e., intensity measure) is estimated by the attenuation models for a specified earthquake scenario. Previous studies have not made a distinction between the dominant modes that result in a specific maximum inter-story drift ratio (MIDR). In this study, by considering the conditional MIDR (dominant mode dependent), it is shown that the aforementioned scaling procedure results in a biased estimation of the median MIDR if the selected records do not contain an equal number of records in each dominant mode set. An alternative scaling scheme is proposed which reduces the dependency of the MIDR estimation on the dominant response mode. A seismic demand model attempts to describe the behavior of a structure in terms of a set of predictor variables that represents the loading. Such predictive demand models are expected to establish a stable and reliable relationship between the dependent variable (structural response) and the independent variables (spectral accelerations). This expectation, however, is problematic in the presence of multicollinearity of the predictor variables because it undermines the performance of the demand model. It is demonstrated that biased estimation of the regression coefficients remedies both the overfitting problem and the instability of the regression coefficients. Finally, the dominant dynamic modes imposed by the ground motion suite are found to have a significant effect on the model predictions. In this study, this influence is quantified in terms of the coefficient of partial determination. It is shown that the marginal contribution of the included variables in the demand model is dependent on the response mode that yields the MIDR. An alternative method of estimating the regression coefficients, i.e., the Ridge estimation, is discussed as an approach that minimizes the influence of the dominant mode on the demand model. The performance of the Ridge estimation is compared with the least squares (unbiased) counterpart using the cross-validation method. Findings from this study have a major impact on the selection and modification of ground motions for seismic assessment of structures.
Author: Yoshifumi Yamamoto
Publisher: Stanford University
ISBN:
Category :
Languages : en
Pages : 329
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Book Description
For performance-based design, nonlinear dynamic structural analysis for various types of input ground motions is required. Stochastic (simulated) ground motions are sometimes useful as input motions, because unlike recorded motions they are not limited in number and because their properties can be varied systematically to study the impact of ground motion properties on structural response. This dissertation describes an approach by which the wavelet packet transform can be used to characterize complex time-varying earthquake ground motions, and it illustrates the potential benefits of such an approach in a variety of earthquake engineering applications. The proposed model is based on Thr´ainsson and Kiremidjian (2002), which use Fourier amplitudes and phase differences to simulate ground motions and attenuation models to their model parameters. We extend their model using wavelet packet transform since it can control the time and frequency characteristic of time series. The time- and frequency-varying properties of real ground motions can be captured using wavelet packets, so a model is developed that requires only 13 parameters to describe a given ground motion. These 13 parameters are then related to seismological variables such as earthquake magnitude, distance, and site condition, through regression analysis that captures trends in mean values, standard deviations and correlations of these parameters observed in a large database of recorded strong ground motions. The resulting regression equations then form a model that can be used to predict ground motions for a future earthquake scenario; this model is analogous to widely used empirical ground motion prediction models (formerly called "attenuation models") except that this model predicts entire time series rather than only response spectra. The ground motions produced using this predictive model are explored in detail, and are shown to have elastic response spectra, inelastic response spectra, durations, mean periods, etc., that are consistent in both mean and variability to existing published predictive models for those properties. That consistency allows the proposed model to be used in place of existing models for probabilistic seismic hazard analysis (PSHA) calculations. This new way to calculate PSHA is termed "simulation-based probabilistic seismic hazard analysis" and it allows a deeper understanding of ground motion hazard and hazard deaggregation than is possible with traditional PSHA because it produces a suite of potential ground motion time histories rather than simply a distribution of response spectra. The potential benefits of this approach are demonstrated and explored in detail. Taking this analysis even further, this suite of time histories can be used as input for nonlinear dynamic analysis of structures, to perform a risk analysis (i.e., "probabilistic seismic demand analysis") that allows computation of the probability of the structure exceeding some level of response in a future earthquake. These risk calculations are often performed today using small sets of scaled recorded ground motions, but that approach requires a variety of assumptions regarding important properties of ground motions, the impacts of ground motion scaling, etc. The approach proposed here facilitates examination of those assumptions, and provides a variety of other relevant information not obtainable by that traditional approach.
Author: Neal Simon Kwong
Publisher:
ISBN:
Category :
Languages : en
Pages : 195
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Book Description
This dissertation investigates the issue of selecting and scaling ground motions as input excitations for response history analyses of buildings in performance-based earthquake engineering. Many ground motion selection and modication (GMSM) procedures have been developed to select ground motions for a wide variety of objectives. In this research, we focus on the selection and scaling of single, horizontal components of ground motion for estimating seismic demand hazard curves (SDHCs) of multistory frames at a given site. In Chapter 2, a framework is developed for evaluating GMSM procedures in their ability to provide accurate estimates of the SDHC. The notion of a benchmark SDHC is introduced, enabling biases caused by GMSM procedures to be isolated from other sources of bias. More importantly, the ability to quantify bias facilitates the identication of intensity measures (IMs) that are sufficient. However, this approach is limited by the availability of recorded ground motions and of prediction models for engineering demand parameters (EDPs) of structures. The framework developed in Chapter 2 is applied to synthetic ground motions in Chapter 3, where biases in estimates of SDHCs caused by GMSM procedures can be estimated for any structural system and any EDP. However, the use of synthetic ground motions gives rise to the issue of developing benchmark-consistent ground motion prediction models. Based on the results from Chapters 2-3, it is hypothesised that the potential bias in any SDHC estimate is caused directly by two important properties of the particular selection of ground motions: (i) hazard consistency, and (ii) IM sufficiency. A novel ground motion selection procedure, rooted in the theory of Importance Sampling, is developed in Chapter 4 that allows: (i) hazard consistency of the selected motions to be directly enforced for a user-specified collection of IMs, and (ii) SDHCs of a structure to be estimated from a single ensemble of ground motions, with the option of avoiding record scaling altogether. This procedure, together with two other contemporary GMSM procedures -- (i) "exact" Conditional Spectrum and (ii) Generalized Conditional Intensity Measure -- are evaluated in Chapters 5-6 for a variety of structural systems and EDPs at a specified site. In these chapters, the amount of effort involved in implementing these procedures for estimating SDHCs is summarized in a step-by-step form, and the magnitude of biases caused by these procedures are documented.
Author: Levent Isbiliroglu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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The observed variability is very large among natural earthquake records, which are not consolidated in the engineering applications due to the cost and the duration. In the current practice with the nonlinear dynamic analysis, the input variability is minimized, yet without clear indications of its consequences on the output seismic behavior of structures. The study, herein, aims at quantifying the impact of ground motion selection with large variability on the distribution of engineering demand parameters (EDPs) by investigating the following questions:What is the level of variability in natural and modified ground motions?What is the impact of input variability on the EDPs of various structural types?For a given earthquake scenario, target spectra are defined by ground motion prediction equations (GMPEs). Four ground motion modification and selection methods such as (1) the unscaled earthquake records, (2) the linearly scaled real records, (3) the loosely matched spectrum waveforms, and (4) the tightly matched waveforms are utilized. The tests on the EDPs are performed on a record basis to quantify the natural variability in unscaled earthquake records and the relative changes triggered by the ground motion modifications.Each dataset is composed by five accelerograms; the response spectrum compatible selection is then performed by considering the impact of set variability. The intraset variability relates to the spectral amplitude dispersion in a given set, and the interset variability relates to the existence of multiple sets compatible with the target.The tests on the EDPs are performed on a record basis to quantify the natural variability in unscaled earthquake records and the relative changes triggered by the ground motion modifications. The distributions of EDPs obtained by the modified ground motions are compared to the observed distribution by the unscaled earthquake records as a function of ground motion prediction equations, objective of structural analysis, and structural models.This thesis demonstrates that a single ground motion set, commonly used in the practice, is not sufficient to obtain an assuring level of the EDPs regardless of the GMSM methods, which is due to the record and set variability. The unscaled real records compatible with the scenario are discussed to be the most realistic option to use in the nonlinear dynamic analyses, and the 'best' ground motion modification method is demonstrated to be based on the EDP, the objective of the seismic analysis, and the structural model. It is pointed out that the choice of a GMPE can provoke significant differences in the ground motion characteristics and the EDPs, and it can overshadow the differences in the EDPs obtained by the GMSM methods.
Author: Ting Lin
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Performance-based earthquake engineering (PBEE) quantifies the seismic hazard, predicts the structural response, and estimates the damage to building elements, in order to assess the resulting losses in terms of dollars, downtime, and deaths. This dissertation focuses on the ground motion selection that connects seismic hazard and structural response, the first two elements of PBEE, to ensure that the ground motion selection method to obtain structural response results is consistent with probabilistic seismic hazard analysis (PSHA). Structure- and site-specific ground motion selection typically requires information regarding the system characteristics of the structure (often through a structural model) and the seismic hazard of the site (often through characterization of seismic sources, their occurrence frequencies, and their proximity to the site). As the ground motion intensity level changes, the target distribution of important ground motion parameters (e.g., magnitude and distance) also changes. With the quantification of contributing ground motion parameters at a specific spectral acceleration (Sa) level, a target response spectrum can be computed using a single or multiple ground motion prediction models (GMPMs, previously known as attenuation relations). Ground motions are selected from a ground motion database, and their response spectra are scaled to match the target response spectrum. These ground motions are then used as seismic inputs to structural models for nonlinear dynamic analysis, to obtain structural response under such seismic excitations. This procedure to estimate structural response results at a specific intensity level is termed an intensity-based assessment. When this procedure is repeated at different intensity levels to cover the frequent to rare levels of ground motion (expressed in terms of Sa), a risk-based assessment can be performed by integrating the structural response results at each intensity level with their corresponding seismic hazard occurrence (through the seismic hazard curve). This dissertation proposes a more rigorous ground motion selection methodology which will carefully examine the aleatory uncertainties from ground motion parameters, incorporate the epistemic uncertainties from multiple GMPMs, make adaptive changes to ground motions at various intensity levels, and use the Conditional Spectrum (CS) as the new target spectrum. The CS estimates the distribution (with mean and standard deviation) of the response spectrum, conditioned on the occurrence of a target Sa value at the period of interest. By utilizing the correlation of Sa values across periods, the CS removes the conservatism from the Uniform Hazard Spectrum (which assumes equal probabilities of exceedance of Sa at all periods) when used as a target for ground motion selection, and more realistically captures the Sa distributions away from the conditioning period. The variability of the CS can be important in structural response estimation and collapse prediction. To account for the spectral variability, aleatory and epistemic uncertainties can be incorporated to compute a CS that is fully consistent with the PSHA calculations upon which it is based. Furthermore, the CS is computed based on a specified conditioning period, whereas structures under consideration may be sensitive to multiple periods of excitation. Questions remain regarding the appropriate choice of conditioning period when utilizing the CS as the target spectrum. To advance the computation and the use of the CS in ground motion selection, contributions have been made in the following areas: The computation of the CS has been refined by incorporating multiple causal earthquakes and GMPMs. Probabilistic seismic hazard deaggregation of GMPMs provides the essential input for such refined CS computation that maintains the rigor of PSHA. It is shown that when utilizing the CS as the target spectrum, risk-based assessments are relatively insensitive to the choice of conditioning period when ground motions are carefully selected to ensure hazard consistency. Depending on the conditioning period, the structural analysis objective, and the target response spectrum, conclusions regarding appropriate procedures for selecting ground motions may differ.
Author: Yoshifumi Yamamoto
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
For performance-based design, nonlinear dynamic structural analysis for various types of input ground motions is required. Stochastic (simulated) ground motions are sometimes useful as input motions, because unlike recorded motions they are not limited in number and because their properties can be varied systematically to study the impact of ground motion properties on structural response. This dissertation describes an approach by which the wavelet packet transform can be used to characterize complex time-varying earthquake ground motions, and it illustrates the potential benefits of such an approach in a variety of earthquake engineering applications. The proposed model is based on Thráinsson and Kiremidjian (2002), which use Fourier amplitudes and phase differences to simulate ground motions and attenuation models to their model parameters. We extend their model using wavelet packet transform since it can control the time and frequency characteristic of time series. The time- and frequency-varying properties of real ground motions can be captured using wavelet packets, so a model is developed that requires only 13 parameters to describe a given ground motion. These 13 parameters are then related to seismological variables such as earthquake magnitude, distance, and site condition, through regression analysis that captures trends in mean values, standard deviations and correlations of these parameters observed in a large database of recorded strong ground motions. The resulting regression equations then form a model that can be used to predict ground motions for a future earthquake scenario; this model is analogous to widely used empirical ground motion prediction models (formerly called "attenuation models") except that this model predicts entire time series rather than only response spectra. The ground motions produced using this predictive model are explored in detail, and are shown to have elastic response spectra, inelastic response spectra, durations, mean periods, etc., that are consistent in both mean and variability to existing published predictive models for those properties. That consistency allows the proposed model to be used in place of existing models for probabilistic seismic hazard analysis (PSHA) calculations. This new way to calculate PSHA is termed "simulation-based probabilistic seismic hazard analysis" and it allows a deeper understanding of ground motion hazard and hazard deaggregation than is possible with traditional PSHA because it produces a suite of potential ground motion time histories rather than simply a distribution of response spectra. The potential benefits of this approach are demonstrated and explored in detail. Taking this analysis even further, this suite of time histories can be used as input for nonlinear dynamic analysis of structures, to perform a risk analysis (i.e., "probabilistic seismic demand analysis") that allows computation of the probability of the structure exceeding some level of response in a future earthquake. These risk calculations are often performed today using small sets of scaled recorded ground motions, but that approach requires a variety of assumptions regarding important properties of ground motions, the impacts of ground motion scaling, etc. The approach proposed here facilitates examination of those assumptions, and provides a variety of other relevant information not obtainable by that traditional approach.
Author: Zoya Farajpour
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This dissertation concerns developing a new ground motion model (GMM) for small to moderate potentially induced seismic events in Central and Eastern United States (CEUS) and ranking worldwide and local GMMs for Iran. The body of research work is carried out in two related studies.The first study presents a new GMM. The proposed model is developed considering induced and potentially induced seismic events in CEUS. For this study, a comprehensive flatfile of potentially induced ground motions for moment magnitudes (Mw) between 3 and 6 and distances of less than 200 km is used. The Pezeshk et al. (2018) model, which is a hybrid empirical method, is selected as the base model for the development of the new GMM. The Pezeshk et al. (2018) model was developed and was calibrated for tectonic events in CEUS as part of the Pacific Engineering Earthquake Center (PEER) Next Generation of Attenuation (NGA) project referred to as the NGA-East project. This study follows the mixed-effect regression procedure to find the proposed model coefficients. The newly developed GMM is derived for peak ground acceleration and response-spectral ordinates at periods ranging from 0.01 to 10.0s, MW ranging from 3.0 to 5.8, and hypocentral distances of up to 200 km. As part of this study, the strength of the newly proposed model is discussed by performing a set of comprehensive residual analyses. In the second study, recently developed worldwide and local GMMs are selected, and the capabilities of these models for seismic hazard analysis in Iran are evaluated. The data-driven selection methods scores determine the GMM weights for applying in seismic hazard forecasts. This study is based on an independent test database of recently recorded major earthquakes in Iran, such as the 12 November 2017 MW 7.3 Ezgeleh earthquake and the 25 November 2018 MW 6.3 Sarpol-e Zahab earthquake, along with the several earthquake events from 2000 to 2019. Three data-driven selection methods, including the Log-Likelihood (LLH) method, the Euclidean Distance-based Ranking (EDR) method, and the Deviance Information Criterion (DIC) method, were employed..
Author: Aspasia Zerva
Publisher: CRC Press
ISBN: 1420009915
Category : Science
Languages : en
Pages : 488
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Book Description
The spatial variation of seismic ground motions denotes the differences in the seismic time histories at various locations on the ground surface. This text focuses on the spatial variability of the motions that is caused by the propagation of the waveforms from the earthquake source through the earth strata to the ground surface, and it brings toge
Author: Robert J. Hansen
Publisher: MIT Press (MA)
ISBN: 9780262080415
Category : Technology & Engineering
Languages : en
Pages : 489
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Book Description
The development of protective measures to guard against the spread of radioactive debris following reactor disasters has been given extensive and careful engineering attention over the past several years. Much of this attention has been devoted to eliminating or minimizing the effects of malfunctions of internal components. But reactors can also suffer externally caused disasters—for example, their radioactive cores can be damaged by earthquakes or by missiles generated by tornadoes. Earthquakes in particular will continue to render man vulnerable even to the "peaceful atom" as the number of nuclear power plants increases and as they come to be located in those parts of the world that have a history of seismic activity. It was to consider such problems that the seminar reported here was held. The conferees, who are leaders in this special and important field, gathered in Cambridge, Massachusetts, in spring 1969, to present the papers whose titles are listed below. Together they cover both the theoretical underpinnings of the subject and specific applications to nuclear reactors; they provide both useful summaries of what is known to date and some new thinking on the subject, not before published. Contents: Preface—T. J. Thompson. Foreword—R. J. Hansen. Introduction—R. V. Whitman. Geological and Seismological Factors Influencing the Assessment of a Seismic Threat to Nuclear Reactors—Daniel Linehan, S. J. Geophysics—Keiiti Aki. Design Seismic Inputs—C. Allin Cornell. Some Observations on Probabilistic Methods in the Seismic Design of Nuclear Power Plants—C. Allin Cornell. Seismic Risk and Seismic Design Decisions—Luis Esteva. Fundamentals of Soil Amplification—J. M. Roesset. Soil Structure Interaction—R. V. Whitman. Evaluation of Soil Properties for Site Evaluation and Dynamic Analysis of Nuclear Plants—R. V. Whitman. Structural Response to Seismic Input—J. M. Biggs. Seismic Analysis of Equipment Mounted on a Massive Structure—J. M. Biggs and J. M. Roesset. Modal Response of Containment Structures—Peter Jan Pahl. Provision of Required Seismic Resistance—M. J. Holley, Jr. A Measure of Earthquake Intensity—Arturo Arias. Closure—R. J. Hansen.
Author: Shrey Kumar Shahi
Publisher:
ISBN:
Category :
Languages : en
Pages : 184
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Growth of major population centers near seismically active faults has significantly increased the probability of a large earthquake striking close to a big city in the near future. This, coupled with the fact that near-fault ground motions are known to impose larger demands on structures than ground motions far from the fault, makes the quantitative study of near-fault seismic hazard and risk important. Directivity effects cause pulse-like ground motions that are known to increase the seismic hazard and risk in near-fault region. These effects depend on the source-to-site geometry parameters, which are not included in most ground-motion models used for probabilistic seismic hazard assessment computation. In this study, we develop a comprehensive framework to study near-fault ground motions, and account for their effects in seismic hazard assessment. The proposed framework is designed to be modular, with separate models to predict the probability of observing a pulse at a site, the probability distribution of the period of the observed pulse, and a narrow band amplification of the spectral ordinate conditioned on the period of the pulse. The framework also allows deaggregation of hazard with respect to probability of observing the pulse at the site and the period of the pulse. This deaggregation information can be used to aid in ground-motion selection at near fault sites. A database of recorded ground motions with each record classified as pulse-like or non-pulse-like is needed for an empirical study of directivity effects. Early studies of directivity effects used manually classified pulses. Manual classification of ground motions as pulse-like is labor intensive, slow, and has the possibility to introduce subjectivity into the classifications. To address these problems we propose an efficient algorithm to classify multi-component ground motions as pulse-like and non-pulse-like. The proposed algorithm uses the continuous wavelet transform of two orthogonal components of the ground motion to identify pulses in arbitrary orientations. The proposed algorithm was used to classify each record in the NGA-West2 database, which created the largest set of pulse-like motions ever used to study directivity effects. The framework to include directivity effects in seismic hazard assessment, as proposed in this study, requires a ground-motion model that accounts for directivity effects in its prediction. Most of the current directivity models were developed as a correction for already existing ground-motion models, and were fitted using ground-motion model residuals. Directivity effects are dependent on magnitude, distance, and the spectral acceleration period. This interaction of directivity effects with magnitude and distance makes separation of distance and magnitude scaling from directivity effects challenging. To properly account for directivity effects in a ground-motion model they need to be fitted as a part of the original model and not as a correction. We propose a method to include the effects of directivity in a ground-motion model and also develop models to make unbiased prediction of ground-motion intensity, even when the directivity parameters are not available. Finally, following the approach used to model directivity effects, we developed a modular framework to characterize ground-motion directionality, which causes the ground-motion intensity to vary with orientation. Using the expanded NGA-West2 database we developed new models to predict the ratio between maximum and median ground-motion intensity over all orientations. Other models to predict distribution of orientations of the maximum intensity relative to the fault and the relationship between this orientation at different periods are also presented. The models developed in this dissertation allow us to compute response spectra that are expected to be observed in a single orientation (e.g., fault normal, orientation of maximum intensity at a period). It is expected that the proposed spectra can be a more realistic representation of single orientation ground motion compared to the median or maximum spectra over all orientations that is currently used.
