The Experts below are selected from a list of 22869 Experts worldwide ranked by ideXlab platform
Victor E. Saouma - One of the best experts on this subject based on the ideXlab platform.
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probabilistic seismic demand model and optimal Intensity Measure for concrete dams
Structural Safety, 2016Co-Authors: Mohammad Amin Haririardebili, Victor E. SaoumaAbstract:Abstract This paper addresses the probabilistic seismic demand model (PSDM) which is the relationship between the Intensity Measure (IM) (such as spectral acceleration) and the engineering demand parameter (EDP) (such as displacement and crack ratio – ratio of crack length to total crack path). It expresses the probability that a system experiences a certain level of demand for a given IM level. Formulation is for a concrete gravity dam. First, IMs are categorized and the criteria for the selection of an optimal one presented. Then, cloud analysis is performed where the structure is subjected to a large set of un-scaled ground motions and the maximum responses are extracted for each one and plotted as a cloud of results. This methodology is applied to Pine Flat gravity dam. Model is first presented followed by results and conclusions. When the results of the cloud analysis are aggregated, then one can plot the seismic fragility curve which is the probability of EDP exceedance in terms of the IM parameter.
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probabilistic seismic demand model and optimal Intensity Measure for concrete dams
Structural Safety, 2016Co-Authors: Mohammad Amin Haririardebili, Victor E. SaoumaAbstract:Abstract This paper addresses the probabilistic seismic demand model (PSDM) which is the relationship between the Intensity Measure (IM) (such as spectral acceleration) and the engineering demand parameter (EDP) (such as displacement and crack ratio – ratio of crack length to total crack path). It expresses the probability that a system experiences a certain level of demand for a given IM level. Formulation is for a concrete gravity dam. First, IMs are categorized and the criteria for the selection of an optimal one presented. Then, cloud analysis is performed where the structure is subjected to a large set of un-scaled ground motions and the maximum responses are extracted for each one and plotted as a cloud of results. This methodology is applied to Pine Flat gravity dam. Model is first presented followed by results and conclusions. When the results of the cloud analysis are aggregated, then one can plot the seismic fragility curve which is the probability of EDP exceedance in terms of the IM parameter.
Jamie E. Padgett - One of the best experts on this subject based on the ideXlab platform.
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Toward confident regional seismic risk assessment of spatially distributed structural portfolios via entropy-based Intensity Measure selection
Bulletin of Earthquake Engineering, 2020Co-Authors: Ao Du, Jamie E. PadgettAbstract: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.
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Influence of Intensity Measure selection on simulation-based regional seismic risk assessment:
Earthquake Spectra, 2020Co-Authors: Jamie E. Padgett, Abdollah ShafieezadehAbstract: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-sim...
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Fractional order Intensity Measures for probabilistic seismic demand modeling applied to highway bridges
Earthquake Engineering & Structural Dynamics, 2012Co-Authors: Abdollah Shafieezadeh, Jamie E. Padgett, Karthik Ramanathan, Reginald DesrochesAbstract:SUMMARY Probabilistic seismic analysis of structures involves the construction of seismic demand models, often stated as probabilistic models of structural response conditioned on a seismic Intensity Measure. The uncertainty introduced by the model is often a result of the chosen Intensity Measure. This paper introduces the concept of using fractional order Intensity Measures (IMs) in probabilistic seismic demand analysis and uses a single frame integral concrete box-girder bridge class and a seismically designed multispan continuous steel girder bridge class as case studies. The fractional order IMs considered include peak ground response and spectral accelerations at 0.2 and 1.0 s considering a single degree of freedom system with fractional damping, Sad−Tnα, as well as a linear single degree of freedom system with fractional response, Sar−Tnα. The study reveals the advantage of fractional order IMs relative to conventional IMs such as peak ground acceleration, peak ground velocity, or spectral acceleration at 0.2 and 1.0 s. Metrics such as efficiency, sufficiency, practicality, and proficiency are Measured to assess the optimal nature of fractional order IMs. The results indicate that the proposed fractional order IMs produce significant improvements in efficiency and proficiency, whereas maintaining practicality and sufficiency, and thus providing superior demand models that can be used in probabilistic seismic demand analysis. Copyright © 2011 John Wiley & Sons, Ltd.
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Which Ground Motion Intensity Measure Is Most Appropriate for Conditioning Demand Models for Bridge Portfolios
Structures Congress 2008, 2008Co-Authors: Jamie E. Padgett, Bryant G. Nielson, Reginald DesrochesAbstract:Probabilistic seismic demand analyses are central to performance-based evaluation of structures and seismic risk assessments. The anticipated structural response and demand under earthquake loading is often characterized using a tool known as a probabilistic seismic demand model (PSDM). However, the degree of uncertainty in the model is dependent on the ground motion Intensity Measure (IM) used for conditioning the response (e.g. peak ground acceleration, spectral acceleration). Vulnerability assessments of general classes, or portfolios of structures, are becoming more essential because of their use in risk assessment packages such as HAZUSMH, and hence the need for identification of optimal IMs increases. Appropriate Intensity Measures for general classes of bridges are evaluated as a part of this study, and the conditions under which various conclusions are valid. The influence of characteristics of the demand analysis on selecting an IM is assessed, such as the use of synthetic or recorded ground motions. The results are intended to offer guidance for appropriate Intensity Measure selection for probabilistic seismic demand models of bridge portfolios, which will considerably enhance future structural performance evaluations and regional risk assessments for transportation networks.
Peng Guan - One of the best experts on this subject based on the ideXlab platform.
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the Intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks
IEEE Transactions on Wireless Communications, 2016Co-Authors: Marco Di Renzo, Peng GuanAbstract:The Intensity matching approach for tractable performance evaluation and optimization of cellular networks is introduced. It assumes that the base stations are modeled as the points of a Poisson point process (PPP) and leverages stochastic geometry for system-level analysis. Its rationale relies on observing that system-level performance is determined by the Intensity Measure of transformations of the underlaying spatial PPP. By approximating the original system model with a simplified one, whose performance is determined by a mathematically convenient Intensity Measure, tractable yet accurate integral expressions for computing area spectral efficiency and potential throughput are provided. The considered system model accounts for many practical aspects that, for tractability, are typically neglected, e.g., line-of-sight (LOS) and non-LOS propagation, antenna radiation patterns, traffic load, practical cell associations, and general fading channels. The proposed approach, more importantly, is conveniently formulated for unveiling the impact of several system parameters, e.g., the density of base stations and blockages. The effectiveness of this novel and general methodology is validated with the aid of empirical data for the locations of base stations and for the footprints of buildings in dense urban environments.
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the Intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks
arXiv: Information Theory, 2016Co-Authors: Marco Di Renzo, Peng GuanAbstract:The Intensity matching approach for tractable performance evaluation and optimization of cellular networks is introduced. It assumes that the base stations are modeled as points of a Poisson point process and leverages stochastic geometry for system-level analysis. Its rationale relies on observing that system-level performance is determined by the Intensity Measure of transformations of the underlaying spatial Poisson point process. By approximating the original system model with a simplified one, whose performance is determined by a mathematically convenient Intensity Measure, tractable yet accurate integral expressions for computing area spectral efficiency and potential throughput are provided. The considered system model accounts for many practical aspects that, for tractability, are typically neglected, e.g., line-of-sight and non-line-of-sight propagation, antenna radiation patterns, traffic load, practical cell associations, general fading channels. The proposed approach, more importantly, is conveniently formulated for unveiling the impact of several system parameters, e.g., the density of base stations and blockages. The effectiveness of this novel and general methodology is validated with the aid of empirical data for the locations of base stations and for the footprints of buildings in dense urban environments.
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The Intensity Matching Approach: A Tractable Stochastic Geometry Approximation to System–Level Analysis of Cellular Networks
IEEE Transactions on Wireless Communications, 2016Co-Authors: Marco Di Renzo, Peng GuanAbstract:The Intensity matching approach for tractable performance evaluation and optimization of cellular networks is introduced. It assumes that the base stations are modeled as the points of a Poisson point process (PPP) and leverages stochastic geometry for system-level analysis. Its rationale relies on observing that system-level performance is determined by the Intensity Measure of transformations of the underlaying spatial PPP. By approximating the original system model with a simplified one, whose performance is determined by a mathematically convenient Intensity Measure, tractable yet accurate integral expressions for computing area spectral efficiency and potential throughput are provided. The considered system model accounts for many practical aspects that, for tractability, are typically neglected, e.g., line-of-sight (LOS) and non-LOS propagation, antenna radiation patterns, traffic load, practical cell associations, and general fading channels. The proposed approach, more importantly, is conveniently formulated for unveiling the impact of several system parameters, e.g., the density of base stations and blockages. The effectiveness of this novel and general methodology is validated with the aid of empirical data for the locations of base stations and for the footprints of buildings in dense urban environments.
Mohammad Amin Haririardebili - One of the best experts on this subject based on the ideXlab platform.
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probabilistic seismic demand model and optimal Intensity Measure for concrete dams
Structural Safety, 2016Co-Authors: Mohammad Amin Haririardebili, Victor E. SaoumaAbstract:Abstract This paper addresses the probabilistic seismic demand model (PSDM) which is the relationship between the Intensity Measure (IM) (such as spectral acceleration) and the engineering demand parameter (EDP) (such as displacement and crack ratio – ratio of crack length to total crack path). It expresses the probability that a system experiences a certain level of demand for a given IM level. Formulation is for a concrete gravity dam. First, IMs are categorized and the criteria for the selection of an optimal one presented. Then, cloud analysis is performed where the structure is subjected to a large set of un-scaled ground motions and the maximum responses are extracted for each one and plotted as a cloud of results. This methodology is applied to Pine Flat gravity dam. Model is first presented followed by results and conclusions. When the results of the cloud analysis are aggregated, then one can plot the seismic fragility curve which is the probability of EDP exceedance in terms of the IM parameter.
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probabilistic seismic demand model and optimal Intensity Measure for concrete dams
Structural Safety, 2016Co-Authors: Mohammad Amin Haririardebili, Victor E. SaoumaAbstract:Abstract This paper addresses the probabilistic seismic demand model (PSDM) which is the relationship between the Intensity Measure (IM) (such as spectral acceleration) and the engineering demand parameter (EDP) (such as displacement and crack ratio – ratio of crack length to total crack path). It expresses the probability that a system experiences a certain level of demand for a given IM level. Formulation is for a concrete gravity dam. First, IMs are categorized and the criteria for the selection of an optimal one presented. Then, cloud analysis is performed where the structure is subjected to a large set of un-scaled ground motions and the maximum responses are extracted for each one and plotted as a cloud of results. This methodology is applied to Pine Flat gravity dam. Model is first presented followed by results and conclusions. When the results of the cloud analysis are aggregated, then one can plot the seismic fragility curve which is the probability of EDP exceedance in terms of the IM parameter.
Helen M. Goldsworthy - One of the best experts on this subject based on the ideXlab platform.
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Suitable Intensity Measure for probabilistic seismic risk assessment of non-ductile Australian reinforced concrete buildings
Bulletin of Earthquake Engineering, 2019Co-Authors: Anita Amirsardari, Pathmanathan Rajeev, Elisa Lumantarna, Helen M. GoldsworthyAbstract:This study investigates the suitability of various Intensity Measures for conducting probabilistic seismic risk assessment of low- to mid-rise non-ductile reinforced concrete buildings with various plan configurations located in low-to-moderate seismic regions. Probabilistic seismic demand models are developed by conducting three-dimensional nonlinear time history analyses. The building response is defined to be dependent on component response and interstorey drift limits. In total the suitability of eleven Intensity Measures is evaluated by examining five criteria: efficiency, practicality, proficiency, sufficiency, and hazard computability. Based on the first four criteria it is identified that peak ground velocity, peak ground displacement, and maximum spectral displacement response are the most suitable Intensity Measures. Hazard computability is then utilised to select the optimum Intensity Measure for a hazard model in accordance with the Australian standards.
