Selection Of Intensity Measures Research Articles

Optimal intensity measure selection in incremental dynamic analysis: methodology improvements and application to a high-speed railway bridge

Optimal intensity measure selection in incremental dynamic analysis: methodology improvements and application to a high-speed railway bridge

Optimizing seismic fragility assessments for high-speed railway track bridges: a novel multi-parameter methodology and intensity measure selection

This research innovatively presents a multi-parameter seismic fragility analysis methodology anchored on Blending ensemble learning tailored for the high-speed railway track-bridge (HSRTB) system. Leveraging ensemble machine learning models, a seismic demand model encapsulating multiple earthquake intensity measures (IMs) is formulated. The research progresses to deduce the mean seismic fragility representations for single, dual, and composite earthquake parameters. Key findings of this investigation underscore that the advanced methodology aligns well with the Monte Carlo (MC) fragility, signifying its robustness. Crucially, earthquake IM parameters, Sa(0.5) and Sa(0.3)_ASI, emerged as the optimal choices for singular and dual-parameter seismic fragility delineations. Further enriching this research, a composite parameter optimization technique rooted in multi-CPU genetic algorithms is proposed. This avant-garde method remarkably minimizes the fragility estimation error, emphasizing its unparalleled efficacy in enhancing the precision of fragility evaluations.

Optimal intensity measure selection and probabilistic seismic demand model of pile group supported bridges in sandy soil considering variable scour effects

Scour of pile group foundations is a common hazard for cross-river bridges and can produce considerable damage to piles in earthquake-prone regions. The fragility-based performance assessment for pile group supported bridges subjected to earthquake and scour hazards has drawn increasing attention from engineering practice and academic communities. Such assessment requires numerical models that are computationally efficient and accurate in describing the mechanical behavior associated with the complex soil-pile interaction of these soil-bridge systems. Additionally, selecting an optimal ground motion intensity measure (IM) is generally required for such assessments. However, modeling the pile group effect for seismically excited pile groups and the optimal IM for the scoured bridges have not been well addressed in previous related studies. To this end, a practical pile group effect modeling approach is adopted in this study and validated by a set of shake table tests on scoured pile group bridge available in the literature. Based on the validated numerical modeling approach for the soil pile interaction, a series of coupled soil-bridge models are generated considering the structural and soil parameter uncertainty and analyzed in the OpenSees platform. The optimal IM for various engineering demand parameters (EDPs) is identified from thirty-nine scalar IM candidates through the criteria of efficiency, practicality, sufficiency, and hazard computability. Finally, a straightforward form of probabilistic seismic demand model (PSDM), incorporating the effect of scour depth changes, is developed for pile group supported bridges. Results show that the increase of scour depth significantly increases the curvature demand of a pile group and statistically reduces the embedded depth of the belowground plastic hinge of the pile shaft. The rank of optimal IM candidates directly depends on the selection criteria of an optimal IM and the selection of EDP. In addition, the scour depth slightly affects the rank of optimal IMs. Generally, VSI, PGV, and Sv,1.0 are recommended for the probabilistic seismic demand analysis of pile group supported bridges in sandy soils with scour potentials.

Optimal intensity measure selection and probabilistic seismic demand models for dam-reservoir-layered foundation system

This study evaluates the optimal intensity measures (IMs) for the seismic fragility analysis of dam-reservoir-layered foundation (DRLF) system. Probabilistic seismic demand models (PSDMs) for the DRLF system are developed that are plotted between engineering demand parameters (EDPs) and intensity measures. Optimal IMs are evaluated based on the selection measures: efficiency, practicality, proficiency, sufficiency, and hazard computability. In addition, finest IM, based on coefficient of determination (COD) in linear regression analysis, is assessed. Prior to that, the numerical model of DRLF system is developed in finite element method software, Abaqus. The concrete damaged plasticity model and Mohr-Coulomb failure model are adopted to provide the non-linear behavior to dam and foundation, respectively. The screening experiments are performed to examine the modeling parameter's effect on the tensile cracking failure in the dam. Ground motions are selected using the conditional mean spectrum approach. Dynamic structural analysis is performed through the incremental dynamic analysis method and a total of 110 non-linear time-history analyses are performed. Further, based on damage index, an analytical approach is used to construct the seismic fragility curves. Various damage states, based on tensile crack failure, are proposed. The screening experiment shows that concrete damping, rock to rock elastic modulus of different layers, concrete elastic modulus, concrete mass density and rock to rock frictional angle have a significant effect on the seismic response of the dam. While investigating the uncertainties associated with the modeling parameters of DRLF system, the elastic modulus of different layers should be chosen with care. Further, based on the IMs selection measures, ASI, EDA, MIV, IP_I and PGD are recognized as optimal IMs. However, ASI and EDA are observed to have excellent predictability and show best correlation for the considered EDPs of the dam.

Optimal ground motion intensity measure selection for probabilistic seismic demand modeling of fixed pile-founded offshore platforms

The safety and serviceability of fixed pile-founded offshore platforms during and after an earthquake will ensure their continuous operation and prevent irreparable economic and environmental loss in a seismically prone area. The probabilistic seismic demand model is a performance-based earthquake engineering design method for offshore platforms. The level of uncertainty in PSDMs depends on the selected seismic intensity measures (IMs), although these models are traditionally conditioned with a single IM. The optimal IM selection used in the present study has not yet been investigated for offshore platforms. Because of the geometrical uncertainties of these types of structure, they were examined using 3D models of five braced configurations of fixed pile-founded offshore platforms by considering the soil-pile-structure interaction (SPSI). Twenty-seven optimal IMs were chosen with regard to their effectiveness, efficiency, practicality, proficiency, sufficiency, relative sufficiency, and hazard computability assessments. Probabilistic seismic demand analysis was performed and each model was subjected to 80 unscaled ground motions. The optimal velocity-related IMs performed well, especially those for the Housner intensity (HI) and velocity spectrum intensity (VSI) for predicting a fixed pile-founded offshore platforms response measured in terms of drift ratio and differential settlement. On the other hand, peak ground velocity (PGV) and HI for the ductility demand parameter present optimal pairs. These most informative IMs were able to provide improved probabilistic seismic demand models (PSDMs) and accurate fragility analysis of the structures.

Toward confident regional seismic risk assessment of spatially distributed structural portfolios via entropy-based intensity measure selection

Intensity measure (IM) selection is a crucial step in regional seismic risk assessment (RSRA) of spatially distributed structural portfolios. In order to facilitate more confident regional seismic risk estimates, this study proposes an entropy-based IM selection methodology, offering the first systematic and quantitative regional-level IM selection approach. By conceptualizing the spatially distributed structural portfolio as an integrated multi-response structural system, the joint entropy of the system’s unconditional seismic demands is leveraged as an IM evaluation criterion. Owing to the adaptation of a newly developed advanced IM co-simulation method and multivariate surrogate demand modeling techniques, this entropy-based IM selection approach is able to holistically incorporate uncertainties rising from the spatial IM random field, structural parameters, and surrogate demand models, during the course of uncertainty propagation in RSRA. The efficacy of the proposed methodology is demonstrated along with practical heuristics for alleviating the computational burden, based on a hypothetical highway bridge portfolio. Different application cases in the context of RSRA are considered, including pre-event RSRA considering a single scenario-earthquake as well as a stochastic earthquake catalog, and post-event RSRA considering record updating. The results consistently highlight the significance of the proposed IM selection method in facilitating more confident regional seismic risk estimates. Moreover, this study also provides valuable insights into record updating in reducing the level of uncertainty of the spatial IM random field, and its implication on IM selection in post-event RSRA.

Entropy‐based intensity measure selection for site‐specific probabilistic seismic risk assessment

SummaryIntensity measure (IM) selection is a critical step in probabilistic seismic risk assessment (PSRA). In many past studies, the efficiency of an IM, which quantifies its explanatory power within a probabilistic seismic demand model, has been a predominant IM evaluation criterion. However, because PSRA requires convolution of the conditional demand model and the probabilistic seismic hazard, IM selection solely based on efficiency ignores the influence of uncertainty contribution particularly from the ground motion prediction equations (GMPEs), which is also dependent on the IMs, and may lead to biased IM selection. In the present study, the concept of joint entropy from information theory is introduced to quantify the uncertainty of unconditional multivariate seismic demands for general multiresponse structural systems, offering a holistic consideration of different sources of uncertainties. We propose a novel entropy‐based IM evaluation criterion that can serve as the basis for IM selection and develop a practical framework to facilitate the implementation of the entropy‐based IM selection in site‐specific PSRA. Based on two case‐study highway bridges, the merit of the proposed IM selection methodology is demonstrated, and the influence of IM selection on demand entropy and loss estimation in PSRA is evaluated. From the results, the proposed entropy‐based IM selection manifests improved capability in considering different sources of uncertainties and is found to deliver much more consistent and confident seismic risk estimates.

Multi‐criteria decision making for seismic intensity measure selection considering uncertainty

SummarySeismic intensity measure (IM) selection is associated with consideration of multiple criteria, and there are uncertainties within the selection process. In this paper, a novel multi‐criteria decision making (MCDM) approach by incorporating stochastic multi‐criteria acceptability analysis (SMAA) with technique for order preference by similarity to ideal solution (TOPSIS) is proposed to solve the stochastic decision making problem of IM selection. TOPSIS provides an alternative rank function, and the SMAA is used to address the uncertainties within the IM selection. The performance criteria (e.g., efficiency, proficiency, practicality, sufficiency, and correlation) are evaluated for the investigated structural components, and the decision matrix is formulated based on the criteria of each IM alternative. Furthermore, the importance of the component to system reliability is quantified in a probabilistic manner using nonlinear time history analysis and serves as the weighting factors in MCDM stage. The holistic acceptability indices indicating the overall acceptability levels of IM alternatives are computed by the proposed approach. Additionally, the effects of different IMs (e.g., average spectral acceleration, peak ground velocity, and spectral acceleration) on probabilistic seismic loss and resilience are investigated to further support the IM selection. The proposed approach is illustrated on a highway bridge, and the results are presented.

Influence of intensity measure selection on simulation-based regional seismic risk assessment

This study investigates the influence of intensity measure (IM) selection on simulation-based regional seismic risk assessment (RSRA) of spatially distributed structural portfolios. First, a co-simulation method for general spectral averaging vector IMs is derived. Then a portfolio-level surrogate demand modeling approach, which incorporates the seismic demand estimation of the non-collapse and collapse states, is proposed. The derived IM co-simulation method enables the first comparative study of different IMs, including the conventional IMs and some more advanced scalar and vector IMs, in the context of RSRA. The influence of IM selection on the predictive performance of the portfolio-level surrogate demand models, as well as on the regional seismic risk estimates, is explored based on a virtual spatially distributed structural portfolio subjected to a scenario earthquake. The results of this study provide pertinent insights in surrogate demand modeling, IM co-simulation and selection, which can facilitate more accurate and reliable regional seismic risk estimates.

Optimal Seismic Intensity Measure Selection for Isolated Bridges under Pulse-Like Ground Motions

Isolated bridges are commonly designed in the near-fault region to balance excessive displacement and seismic force. Optimal intensity measures (IMs) of probabilistic seismic demand models for isolated bridges subjected to pulse-like ground motions are identified in this study. Four typical isolated girder bridge types with varied pier height (from 4 m to 20 m) are employed to conduct the nonlinear time history analysis. Totally seven structure-independent IMs are considered and compared. Critical engineering demand parameters (EDPs), namely, pier ductility demands and bearing deformation along the longitudinal and transverse directions, are recorded during the process. In general, PGV tends to be the optimal IM for isolated bridges under pulse-like ground motions based on practicality, efficiency, proficiency, and sufficiency criterions. The results can offer effective guidance for the optimal intensity measure selection of the probabilistic seismic demand models (PSDMs) of isolated bridges under pulse-like ground motions.

Updated evaluation metrics for optimal intensity measure selection in probabilistic seismic demand models

This study proposes an update on the criteria that are typically used to select the optimal intensity measures (IMs) for development of probabilistic seismic demand models (PSDMs), which relate the input seismic hazard and structural responses. Employing an optimal IM contributes to decreasing the uncertainty in the PSDMs, which, in turn, increases the reliability of the PSDMs used in performance-based earthquake engineering analyses. In the literature, the optimality of the IMs is generally evaluated by the following metrics: efficiency; practicality; proficiency, which is the composite of efficiency and practicality; sufficiency; and hazard computability. The present study shows that the current criteria for evaluating the practicality and proficiency features may mislead the selection of the optimal IM when IMs with different ranges and magnitudes are investigated. Moreover, the efficiency metric can provide biased results when comparing IMs for predicting demands of different structural components or types of systems. As a result, alternative solutions are proposed to investigate the efficiency, practicality, and proficiency features of the IMs. The suggested metrics are employed in a case study to evaluate the IMs used to develop PSDMs for multi-span continuous steel girder bridges in Texas subjected to human-induced seismic hazard.

Ground motion intensity measures for seismically isolated RC tall buildings

Seismic isolation is an effective method for realizing resilient reinforced concrete (RC) tall buildings. The selection of intensity measures (IMs) is a critical issue for a resilience-based seismic design of seismically isolated RC tall buildings. The predictive capability of IM may be affected by various factors, including structural systems, heights, seismically isolated schemes, fundamental periods, and types of ground motions. With emphasis on these factors, the predictive capability of various IMs for predicting critical engineering demand parameters (EDPs) was evaluated. To achieve these, forty-eight cases are designed based on four real engineering practices. Two sets of ground motions, particularly pulse-like near-fault ground motions, are adopted. The efficiency and sufficiency of 25 IMs in predicting four EDPs are evaluated. The IMs with high efficiency and relatively good sufficiency are identified and the corresponding sensitivities are further evaluated. The research outcome can assist in providing a useful reference for seismic design of seismically isolated RC tall buildings.

Implications of Intensity Measure Selection for Seismic Loss Assessment of 3-D Buildings

Present building-specific loss assessment state-of-art involves the convolution of seismic hazard and building seismic demands. The latter is conditioned on spectral acceleration, Sa( T1), at the building's first mode as the ground motion intensity measure (IM) and is typically estimated by carrying out nonlinear dynamic analyses on a two-dimensional (2-D) model. By new proposals on the use of improved IMs that can introduce higher fidelity, the accuracy in loss estimation becomes an open question. In reply, we offer a uniform basis for comparing the loss estimates for a set of eight different scalar and vector IMs whose hazard can be predicted with existing GMPEs. Despite all eight being legitimate IMs, and despite the consistent use of conditional spectrum record selection, we find large differences in the estimated loss hazard. This points to the large uncertainty still lingering when connecting hazard to loss. Among the IMs considered here, the vector IMs and at least a scalar average of spectral accelerations showed a remarkable stability in their predictions for the three-dimensional (3-D) buildings, pointing to a potential for reliable applications.

Selecting Appropriate Intensity Measure in View of Efficiency

This study attempts to answer the question of distinguishing appropriate intensity measure parameter for performance-based design or assessment, taking into account the efficiency aspect. The comprehensive comparative tables proposed in this paper could be an effective support in the decision making procedure for intensity measure selection, comprising most of the frequently utilized intensity measures for low-rise buildings with different fundamental periods. In addition, since some specific intensity measures are commonly applied in codes, the amounts of standard deviation computed in this study could be very beneficial in answering the question of being worthy to consider another intensity measure, to improve the certitude of structural responses, noting expansion in calculationefforts.

Intensity measure selection for vulnerability studies of building classes

SummaryThe selection of a scalar Intensity Measure (IM) for performing analytical vulnerability (loss) assessment across a building class is addressed. We investigate the ability of several IM choices to downgrade the effect of seismological parameters (sufficiency) as well as reduce the record‐to‐record variability (efficiency) for both highrise and lowrise sets of ‘index’ buildings. These characteristics are explored in unprecedented detail, employing comparisons and statistical significance testing at given levels of local engineering demand parameters (story drift ratios and peak floor accelerations) that relate to losses, instead of global variables such as the maximum interstory drift. Thus, a detailed limit‐state‐specific view is offered for the suitability of different scalar IMs for loss assessment. As expected, typical single‐period spectral values are found to introduce unwanted bias at high levels of scaling, both for a single as well as a class of buildings. On the other hand, the geometric mean of the spectral acceleration values estimated at several periods between the class‐average second‐mode and an elongated class‐average first‐mode period offers a practical choice that significantly reduces the spectral‐shape bias without requiring the development of new ground motion prediction equations. Given that record selection remains a site‐ and building‐specific process, such an improved IM can help achieve reliable estimates for building portfolios, as well as single structures, at no additional cost. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of seismic hazard for the assessment of historical elements at risk: description of input and selection of intensity measures

The assessment of historical elements at risk from earthquake loading presents a number of differences from the seismic evaluation of modern structures, for design or retrofitting purposes, which is covered by existing building codes, and for the development of fragility curves, procedures for which have been extensively developed in the past decade. This article briefly discusses: the hazard framework for historical assets, including a consideration of the appropriate return period to be used for such elements at risk; the intensity measures that could be used to describe earthquake shaking for the analysis of historical assets; and available approaches for their assessment. We then discuss various unique aspects of historical assets that mean the characterisation of earthquake loading must be different from that for modern structures. For example, historical buildings are often composed of heterogeneous materials (e.g., old masonry) and they are sometimes located where strong local site effects occur due to: steep topography (e.g., hilltops), basin effects or foundations built on the remains of previous structures. Standard seismic hazard assessment undertaken for modern structures and the majority of sites is generally not appropriate. Within the PERPETUATE project performance-based assessments, using nonlinear static and dynamic analyses for the evaluation of structural response of historical assets, were undertaken. The steps outlined in this article are important for input to these assessments.