1,721,022 research outputs found
Implementing Incremental Dynamic Analysis for measuring entropy-based sufficiency of an Intensity Measure
No full textSeismic reliability assessment and the nonergodicity in the modelling parameter uncertainties
No full textModelling uncertainty can significantly affect the structural seismic reliability assessment. However, the limit state excursion due to this type of uncertainty may not be described by a Poisson process as it lacks renewal properties with the occurrence of each earthquake event. Furthermore, considering uncertainties related to ground motion representation by employing recorded ground motions together with modelling uncertainties is not a trivial task. Robust fragility assessment, proposed previously by the authors, employs the structural response to recorded ground motion as data in order to update prescribed seismic fragility models. Robust fragility can be extremely efficient for considering also the structural modelling uncertainties by creating a dataset of one-to-one assignments of structural model realizations and as-recorded ground motions. This can reduce the computational effort by more than 1 order of magnitude. However, it should be kept in mind that the fragility concept itself is based on the underlying assumption of Poisson-type renewal. Using the concept of updated robust reliability, considering both the uncertainty in ground motion representation based on as-recorded ground motion and non ergodic modelling uncertainties, the error introduced through structural reliability assessment by using the robust fragility is quantified. It is shown through specific application to an existing RC frame that this error is quite small when the product of the time interval and the standard deviation of failure rate is small and is on the conservative side
Sequence-based Parameter Estimation for an Epidemiological Temporal Aftershock Forecasting Model using Markov Chain Monte Carlo Simulation
No full textSelection of seismic intensity measures for prescribed limit states using alternative nonlinear dynamic analysis methods
No full textIn performance-based earthquake engineering, the suitability of an intensity measure (IM) is expressed through its efficiency and sufficiency. An efficient IM leads to a small record-to-record variability in the estimation of demand given seismic intensity. A sufficient IM is one that renders the estimation of demand for all intensity levels independent of all other ground motion parameters. Given that establishing sufficiency is not a trivial task, the relative sufficiency measure (RSM) has been proposed previously based on information theory concepts. RSM can be employed for quantifying the relative sufficiency of an IM with respect to another IM by the amount of extra information that it relays on average about the ground motion for the estimation of a demand parameter of interest. RSM has been so far conditioned on a linear logarithmic regression probability model, better known as the Cloud Analysis (CA), which relies on unscaled ground-motion records. This work lays out the methodology for estimating both the efficiency and RSM in terms of the damage measure directly (instead of demand parameter) and by employing alternative nonlinear dynamic analysis procedures (NDAPs), such as, a modified version of CA that considers the collapse-cases explicitly and the incremental dynamic analysis. It is demonstrated that the RSM can be sensitive to the NDAP employed, while it does not demonstrate significant sensitivity to the limit state of interest. An alternative measure of efficiency (known in literature as proficiency), directly measured as the dispersion in the fragility curve, shows more sensitivity to the limit state
Modello di rappresentazione del sistema urbano: definizione delle componenti e delle interazioni sistemiche
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Considering structural modelling uncertainties using Bayesian cloud analysis
No full textQuantifying the impact of modelling uncertainty on the seismic performance assessment is a crucial issue for existing buildings, considering the partial information available related to material properties, construction details and the uncertainty in the capacity models. The effect of structural modelling uncertainties on the seismic performance of existing buildings can be -under certain circumstances- comparable to that of uncertainty in ground motion representation. In this work, a modified version of Cloud analysis considering the (eventual) cases of global dynamic instability and adopting the critical demand to capacity ratio as the damage measure/decision variable, based on coupling the simple regression in the logarithmic space of structural response versus seismic intensity for a suite of registered records with logistic regression, has been implemented to consider the record-to-record variability, structural modelling uncertainties and the uncertainties in the parameters of the adopted fragility model. For each of the registered records within the suite of ground motion records, a different realization of the structural model has been generated through a standard Monte Carlo Simulation procedure. A Bayesian version of the Cloud method is employed, in which the uncertainty in the structural fragility model parameters is considered. This leads to a robust fragility estimate-reflecting both record-to-record variability and structural modeling uncertainties-- and a desired confidence interval defined around it -reflecting the uncertainty in the fragility model parameters. The longitudinal frame of an existing building in Van Nuys, CA, modeled in OpenSees considering the flexural-shear-axial interaction, has been employed in order to demonstrate this procedure. The critical demand to capacity ratio adopted as the damage measure/decision variable, corresponding to the component or mechanism that leads the structure closest to the onset of limit state (e.g., near collapse), is adopted as the structural response parameter. This structural response parameter can encompass both ductile and fragile failure mechanisms. Moreover, it can register a possible shift in the governing failure mechanism with increasing intensity. The selection of the suite of ground motion records has been based on a set of criteria that ensure the statistical significance of the linear regression in predicting the structural response as a function of the intensity measure
Intensity-based demand and capacity factor design: a visual format for safety checking
No full textQuantitative safety checking is an essential part of performance-based design and retrofit of new and existing construction. The intensity-based demand and capacity factor design (DCFD) is a practical closed-form safety-checking format that lends itself quite well to visual interpretation. Adopting the critical demand to capacity ratio as a global damage measure directly, skipping the engineering demand parameter, helps in identifying the onset of the prescribed performance levels. For each intensity level, the contribution to the error in the DCFD format in logarithmic domain is visualized as the distance between the hazard curve and its tangent at median intensity at the onset of the performance level weighted by the probability density of the intensity-based capacity. The latter reaches its maximum value at the median intensity at the onset of the performance level, where the error in hazard is zero, and decays with a rate that depends on the logarithmic standard deviation of fragility. The proposed intensity-based DCFD provides accurate safety-checking estimates that are always on the safe side for concave mono-curvature hazard curves in the logarithmic scale
Record-to-record variability and code-compatible seismic safety-checking with limited number of records
No full textThe Italian code requires spectrum compatibility with mean spectrum for a suite of accelerograms selected for time-history analysis. Although these requirements define minimum acceptability criteria, it is likely that code-based non-linear dynamic analysis is going to be done based on limited number of records. Performance-based safety-checking provides formal basis for addressing the record-to-record variability and the epistemic uncertainties due to limited number of records and in the estimation of the seismic hazard curve. “Cloud Analysis” is a non-linear time-history analysis procedure that employs the structural response to un-scaled ground motion records and can be directly implemented in performance-based safety-checking. This paper interprets the code-based provisions in a performance-based key and applies further restrictions to spectrum-compatible record selection aiming to implement Cloud Analysis. It is shown that, by multiplying a closed-form coefficient, code-based safety ratio could be transformed into simplified performance-based safety ratio. It is shown that, as a proof of concept, if the partial safety factors in the code are set to unity, this coefficient is going to be on average slightly larger than unity. The paper provides the basis for propagating the epistemic uncertainties due to limited sample size and in the seismic hazard curve to the performance-based safety ratio both in a rigorous and simplified manner. If epistemic uncertainties are considered, the average code-based safety checking could end up being unconservative with respect to performance-based procedures when the number of records is small. However, it is shown that performance-based safety checking is possible with no extra structural analyses
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