Probabilistic seismic demand analysis using advanced ground motion intensity measures

2007 ◽  
Vol 36 (13) ◽  
pp. 1837-1860 ◽  
Author(s):  
Polsak Tothong ◽  
Nicolas Luco
Keyword(s):  
Ground Motion ◽  
Demand Analysis ◽  
Seismic Demand ◽  
Intensity Measures ◽  
Probabilistic Seismic Demand Analysis ◽  
Probabilistic Seismic Demand

Improved intensity measures for probabilistic seismic demand analysis. Part 2: application of the improved intensity measures

2011 ◽  
Vol 38 (1) ◽  
pp. 89-99 ◽  
Author(s):  
Lan Lin ◽  
Nove Naumoski ◽  
Murat Saatcioglu ◽  
Simon Foo
Keyword(s):  
Demand Analysis ◽  
Seismic Demand ◽  
Intensity Measure ◽  
Reinforced Concrete Frame ◽  
Intensity Measures ◽  
Seismic Demands ◽  
Concrete Frame ◽  
Probabilistic Seismic Demand Analysis ◽  
Frame Buildings ◽  
Probabilistic Seismic Demand

This is the second of two companion papers on improved intensity measures of strong seismic ground motions for use in probabilistic seismic demand analysis of reinforced concrete frame buildings. The first paper discusses the development of improved intensity measures. This paper describes the application of the developed intensity measures in probabilistic seismic demand analysis. The application is illustrated on the three reinforced concrete frame buildings (4, 10, and 16-storey high) that were used in the first paper. This involved computations of the seismic responses of the structures and the seismic hazard using the improved intensity measures. The response and the hazard results were then combined by means of probabilistic seismic demand analysis to determine the mean annual frequencies of exceeding specified response levels due to future earthquakes (i.e., the probabilistic seismic demands). For the purpose of comparison, probabilistic seismic demand analyses were also conducted by employing the spectral acceleration at the fundamental structural periods (Sa(T1)) as an intensity measure, which is currently the most used in practice. It was found that the use of the improved intensity measures results in significantly lower seismic demands relative to those corresponding to the intensity measure represented by Sa(T1), especially for long period structures.

Improved intensity measures for probabilistic seismic demand analysis. Part 1: development of improved intensity measures

2011 ◽  
Vol 38 (1) ◽  
pp. 79-88 ◽  
Author(s):  
Lan Lin ◽  
Nove Naumoski ◽  
Murat Saatcioglu ◽  
Simon Foo
Keyword(s):  
Demand Analysis ◽  
Seismic Demand ◽  
Reinforced Concrete Frame ◽  
Intensity Measures ◽  
Intermediate Period ◽  
Concrete Frame ◽  
Probabilistic Seismic Demand Analysis ◽  
Frame Buildings ◽  
Probabilistic Seismic Demand ◽  
Nonlinear Dynamic Analyses

This is the first of two companion papers on improved intensity measures of strong seismic ground motions for use in probabilistic seismic demand analysis. It describes the formulation and the development of new intensity measures. The second paper illustrates the application of the developed intensity measures in probabilistic seismic demand analysis. The development of the intensity measures was based on investigations of the seismic responses of three reinforced concrete frame buildings (4, 10, and 16-storey high) designed for Vancouver. The buildings were subjected to a selected set of seismic motions scaled to different intensity levels. Maximum interstorey drifts obtained from nonlinear dynamic analyses were used as response parameters. Based on the results from the analyses, two intensity measures are proposed: one for short- and intermediate-period buildings, and another one for long-period buildings. The proposed intensity measures are superior compared to that represented by the spectral acceleration at the fundamental building period (Sa(T1)), which is currently the most widely used intensity measure in probabilistic seismic demand analysis.

Univariate Fragility Models for Seismic Vulnerability Assessment of Refinery Piping Systems

2017 ◽  
Author(s):  
Stefano Caprinozzi ◽  
Mohammad M. Ahmed ◽  
Fabrizio Paolacci ◽  
Oreste S. Bursi ◽  
Vincenzo La Salandra
Keyword(s):  
Seismic Vulnerability ◽  
Critical Role ◽  
Demand Analysis ◽  
Piping System ◽  
Seismic Demand ◽  
Support Structure ◽  
Probabilistic Seismic Demand Analysis ◽  
Piping Systems ◽  
Damage States ◽  
Probabilistic Seismic Demand

Piping systems of energy industries in oil & gas play a critical role in meeting the increasing global energy demand. A great portion of these pipelines is located in high seismic-prone areas. Such systems have been found to be quite vulnerable to seismic events. Current seismic design approaches to piping systems are mainly based on the allowable stress method, even though more modern design methods are currently available for buildings or nuclear power plants; for example, the Performance-Based Earthquake Engineering (PBEE) framework has not been applied yet to piping systems and relevant structures. In this respect, both information about the quantification of limit states for pipes and adequate non-linear structural models for seismic analysis of piping systems and relevant structures are very limited. One of the key ingredients of PBEE approach for the assessment of the seismic vulnerability of existing structures is the evaluation of fragility curves, namely the probability of exceeding a certain level of damage for a given seismic intensity measure (IM). However, the contributions in the literature on this delicate aspect are very limited. This paper deals with such a problem by using a very popular method, namely the Cloud Analysis, originally developed as a method for probabilistic seismic demand analysis of civil structures. This method is here applied to a typical piping system for process plants. For this purpose, the structure is properly modelled, especially support structure and pipe, including pipe fittings like elbows and bolted flange joints. Using natural accelerograms selected from the PEER database and in accordance with given hazard conditions, the probabilistic seismic demand analysis is performed adopting different engineering demand parameters (EDP) consistent with the damage states expected in the pipes and fittings and in the support structure. According to the results of experimental tests campaign performed in the past by some of the authors on flanged joints, and elbows, different damage states (leakage, yielding, rupture) have been identified and related to the corresponding EDP and the corresponding probability of exceeding has been determined by assuming a lognormal distribution of the response. The analysis intends to recognise the most probable damage condition in a refinery piping system subjected to a seismic input.

scholarly journals Improved seismic hazard model with application to probabilistic seismic demand analysis

2007 ◽  
Vol 36 (14) ◽  
pp. 2211-2225 ◽  
Author(s):  
Brendon A. Bradley ◽  
Rajesh P. Dhakal ◽  
Misko Cubrinovski ◽  
John B. Mander ◽  
Greg A. MacRae
Keyword(s):  
Seismic Hazard ◽  
Hazard Model ◽  
Demand Analysis ◽  
Seismic Demand ◽  
Probabilistic Seismic Demand Analysis ◽  
Probabilistic Seismic Demand

Probabilistic Seismic Demand Analysis of Structures Using Reliability Approaches

2020 ◽  
pp. 2150011
Author(s):  
M. Kia ◽  
A. Amini ◽  
M. Bayat ◽  
P. Ziehl
Keyword(s):  
Earthquake Engineering ◽  
Demand Curve ◽  
Demand Analysis ◽  
Model Parameters ◽  
Total Probability ◽  
Seismic Demand ◽  
Finite Sample ◽  
Probabilistic Seismic Demand Analysis ◽  
Reliability Method ◽  
Probabilistic Seismic Demand

The Probabilistic Seismic Demand Analysis (PSDA) which is frequently implemented in the first generation performance-based earthquake engineering quantifies seismic behavior of a structure by computing mean annual frequency of exceeding a specific value of a desired demand parameter given all anticipated earthquakes. This framework, based on the total probability integration formula, provides a technical basis on which aleatory uncertainties, uncertainties originated due to inherent randomness of the phenomena, are explicitly addressed. However, variability in the mean value of different model parameters, referred to as epistemic uncertainties and mainly due the finite-sample size of observations, is neglected. In this study, as an alternative to total probability integration, a reliability-based formulation tailored to effortlessly reflect both aleatory and epistemic uncertainties is put-forward to perform unified PSDA. Next, as an application of the proposed methodology, a reliability-based seismic demand curve of a 4-story example building is developed. Results demonstrate that the Second-Order Reliability Method (SORM) and important sampling method (ISM) along with multi-step Monte Carlo simulation (MSMCS) methods are appropriate candidates for computing reliability-based PSDA with differentiable and nondifferentiable performance functions, respectively.

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