SOME ECLENSIONS OF EISMIC RISK NALYSIS FOR … · engineering ground motion parameters for...

SOME DECLENSIONS OF SEISMIC RISK ANALYSIS FOR PERFORMANCE-BASED EARTHQUAKE ENGINEERING

Iunio Iervolino

Dipartimento di Ingegneria Strutturale, Università degli Studi di Napoli Federico II, via Claudio 21, 80125, Naples, Italy. [email protected].

1 INTRODUCTION

The research presented in the paper is generally related to the seismic risk analysis of engineering systems. For what concerns the analysis of individual structures the works deploys along some advanced hazard analysis issues toward earthquake engineering practice. In other words, some tools and extensions useful to take advantage of hazard analysis in code-based risk assessment in Europe are investigated and/or developed. This includes computation of design earthquake maps from disaggregation, conditional hazard analysis, near-source hazard adjustment, and finally software for computer aided code-based record selection. Hazard analysis also extends to two more recent issues which are the real-time prediction of engineering ground motion parameters for earthquake early warning purposes and the regional hazard analysis for lifelines or regional building stock seismic risk assessment. On the structural side of earthquake engineering the research includes vulnerability analysis of structural typologies and estimates of response parameters. Not all of these research topics, along with others, may be reviewed below where only the most recent are briefly discussed pointing to the major publications of the author related to them.

Keywords: Risk and hazard analysis, Record selection, Performance-based Earthquake Engineering, Real-Time Engineering and Earthquake Early Warning.

2 COMPUTER AIDED CODE-BASED RECORD SELECTION

In code-based seismic structural design and assessment it is often allowed the use of real records as an input for nonlinear dynamic analysis. On the other hand, international seismic guidelines, concerning this issue, have been found hardly applicable by practitioners (Iervolino et al., 2008a; Iervolino et al., 2009a). This is related to both the difficulty in rationally connecting the ground motions to the hazard at the site and the required selection criteria, which often do not favor the use of real records, but rather various types of spectral matching signals. To overcome some of these obstacles a software tool for code-based real records selection was developed (Iervolino et al., 2008b; Iervolino et al. 2009b). REXEL, freely available at the website of the Italian network of earthquake engineering university labs (http://www.reluis.it/index_eng.html), allows to search for suites of waveforms, currently from the European strong motion database and the Italian accelerometric archive, compatible to reference spectra user-defined or automatically generated according to Eurocode 8 and the recently released Italian seismic code. The selection reflects the prescriptions of the considered codes and others found important by recent research on the topic. In particular, the computer program was developed to search for combinations of seven accelerograms

I. Iervolino – Earthquake Engineering by the Beach Workshop, July 2-4, 2009, Capri, Italy.

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compatible in the average with the reference spectra according to code criteria discussed above. It is also possible to reflect in selection the characteristics of the source (see also section 3) and site, in terms of magnitude, epicentral distance, and soil site classification. The software searches for combinations of: (i) 7 1-component accelerograms whose average matches the reference spectrum in the specified range of periods and with the provided upper- and lower-bound tolerances. (ii) 7 pairs of 2-components recordings (both X and Y components of 7 recording stations only), which on average are compatible with the reference spectrum; (iii) 7 triplets of accelerograms which include the two horizontal and the vertical component of seven recording stations. An important feature of the code is that the list of records the software searches within are preliminarily ordered in ascending order of a parameter which gives a measure of how much the spectrum of an individual record deviates from the reference spectrum. This ensures the first combinations returned to be those with the smallest individual scattering in respect to the reference spectrum. In fact, REXEL 2.4 beta (Figure 1) allows to obtain combinations of accelerograms compatible with the target spectrum which do not need to be scaled, but it also allows choosing sets of accelerograms compatible with the reference spectrum if linearly scaled. This allows to have combinations whose spectra are similar to reference spectrum, then reducing the record-to-record spectral variability within a set, which is a desirable feature if one has to estimate the seismic demand on the basis of 7 analyses only. Other functions are related to visualization of results, return of selected waveforms to the user, and secondary options, as search for combinations of size larger than 7.

Figure 1. Image of the software GUI.

As examples of the scaled and unscaled record suites the software returns, one- and two-components combinations selected for a site in southern Italy are given. Figure 2 refers to the life-safety limit state spectrum on soil A according to the latest seismic code, Figure 3 reports the scaled combinations found using, for the same site, the uniform hazard spectrum related to a 50 years return period.

Some Tools for Performance-Based Earthquake Engineering

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Figure 2. Unscaled combinations found for Sant’Angelo dei Lombardi (southern Italy) in the case of

horizontal 1-component (a) and 2-components (b) ground motions (adapted from Iervolino et al., 2009).

Figure 3. Scaled combinations found for Sant’Angelo dei Lombardi (southern Italy) in the case of

horizontal 1-component (a) and 2-components (b) ground motions (adapted from Iervolino et al., 2009).

3 MAPS OF DESIGN EARTHQUAKES

When selection of recorded waveforms for seismic design of structures is concerned, the current state of best engineering practice is based on the uniform hazard spectrum (UHS) which is an elastic response spectrum derived from the analysis of the probabilistic seismic hazard at the site (Iervolino and Cornell, 2005). Once the UHS has been defined, the waveforms’ selection proceeds with the disaggregation of seismic hazard, by magnitude (M), distance (R), and ε (epsilon – defined as the number of logarithmic standard deviations by which the logarithmic ground motion departs from the median predicted by an appropriate attenuation relationship) for the level of spectral acceleration given by the UHS at the first mode period of the structure. Disaggregation allows the identification of the earthquakes which dominate the hazard as a function of the structural oscillation period, location, and return period. Those contributions are typically expressed in terms of probability density functions (PDFs) of M, R and ε conditional to the occurrence or exceedance of the level of spectral acceleration, Sa(T), for which the hazard is disaggregated. The analysis of these PDFs, allows the definition of the design earthquake identifying the values of the variables giving the largest contribution to the hazard or considered representative in some other statistical sense. Given the dominant M, R, and ε sets, along with other earthquake-specific factors, such as directivity, faulting style and duration, site-specific realistic time histories can be


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recommended for engineering analyses. In fact, after the so-defined design earthquake is identified, a database is accessed and a number of time histories is selected to match, within tolerable limits, the values of these parameters believed to be important for a correct estimation of the structural response. Time histories obtained in this way are used as the input for a set of nonlinear dynamic analyses to evaluate the behavior of the structure in the case of the ground motion represented by the UHS. The study briefly presented (see Convertito et al., 2009), investigates the implications of mapping the design earthquakes for spectral accelerations corresponding to different spectral frequency ranges via an application to the Campania-Lucania region in southern Apennines (Italy). In fact, the hazard data made publicly available for Italy by INGV (Istituto Nazionale di Geofisica e Vulcanologia) include disaggregation for peak ground acceleration (PGA) only; however, short and long period ranges of the UHS may be affected by different seismic sources in terms of magnitude and distance. This is important because design of moderate-to-long period structures has to consider dominant events which may be not well represented by the results of PGA hazard disaggregation. For the area considered, maps of the first two modal magnitudes, distances and epsilons sets were computed from disaggregation of seismic hazard on rock sites, specifically calculated, for two spectral ordinates, PGA and Sa(T=1sec), see Figure 4.

Figure 4. Design earthquakes’ maps for PGA and Sa(T1) for a return period of 475 years. For each hazard variable, left panels refer to the first mode of the joint PDFs while right panels refer to the second mode of

the joint PDFs. The selected hazard level corresponds to 10% exceedance of probability in 50 years, which is a reference return period for the life-safety limit-state of ordinary constructions in Europe.


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These maps may be tools to define the dominating earthquakes for each site, and to assess how frequencies of the design spectrum of engineering interest are differently contributed by seismogenic sources in the area.

4 CONDITIONAL HAZARD ANALYSIS

Vector-valued ground motion intensity measures have been extensively investigated recently. Proposed measures are mainly related to pairs of spectral ordinates because the spectral shape has been shown to be useful in the probabilistic assessment of structural and non-structural response of buildings. This is especially appropriate in the case of structures following modern earthquake resistant design principles, in which structural damage is mainly due to displacements experienced in non-linear behavior. Although it is generally believed that, under some hypotheses, integral ground motion parameters associated to duration are less important for structural demand assessment with respect to peak quantities of ground motion, there are cases in which the cumulative damage potential of the earthquake is also of concern. In the study the joint distribution of peak ground acceleration and a parameter which may account for the cumulative damage potential of ground motion, is investigated with respect to some engineering seismology issues. The chosen energy related measure is the so-called Cosenza and Manfredi index (ID), Eq. (4.1), the ratio of the integral of the acceleration squared to the PGA and peak ground velocity (PGV). A ground motion prediction relationship has been retrieved for ID on the basis of an empirical dataset of Italian records already used for well known attenuation laws proposed in the past by other researchers (Iervolino et al., 2008c). Subsequently, the residuals have been tested for correlation and for joint normality, which allowed to obtain close form for the parameters of ID conditional on PGA. In Eq. (4.2), the left hand sides are the parameters of the Gaussian conditional distributions of the log of ID to the log of PGA as a function of: the average and standard deviation from attenuation relationship of ID ( )10 D 10 Dlog I log I;μ σ ; the correlation coefficient

between the logs of PGA and ID ( )ρ ; and the average and standard deviation from attenuation

relationship of PGA ( )10 10log PGA log PGA;μ σ .

( )

Et2

0D

a t dtI

PGA PGV=

⋅

∫ (4.1)

10

10 D 10 10 D 10 D

10

10 D 10 10 D

*log PGA

log I |log PGA log I log Ilog PGA

2log I |log PGA log I 1

a

a

aρ

μμ μ σ

σ

σ σ ρ

=

=

⎧ −= +⎪⎪

⎨⎪

= −⎪⎩

(4.2)

Results (Iervolino et al, 2009c) have been used to compute the distribution of ID conditional on PGA, with a return period of 475 years for each node of a regular grid having about 2 km spacing and covering the territory of the Campania region (southern Italy). These results, presented in the form of maps (for two different percentiles), provide information on the values of ID which should be taken into account in respect to the hazard in terms of PGA at the site (Figure 5).


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(a)

(c)

(b)

(d)

Figure 5. (a) Seismic zones considered in the analysis (b) 475 years return period PGA on rock hazard map for the Campania region (southern Italy); (c) Hazard map in term of median ID

conditional on PGA of panel (b); (d) Hazard map in term of median ID with a 10% exceedance probability conditional on PGA of panel (b).

5 ENGINEERING ISSUES OF FORWARD DIRECTIVITY

Near-source ground motion records affected by “directivity” may show unusual features resulting in low frequency pulses in the velocity time-history, especially in the fault-normal component. Although not all near-source recordings show pulses, such an effect is of particular interest for practitioners as it may cause the seismic demand for structures to deviate from that of, so-called, “ordinary” records (Figure 6, left). Consequently many seismology and earthquake engineering researchers have tried to parameterize the causes and the effects of directivity pulses. In the framework of the probabilistic seismic assessment of structures in near-source conditions, a quantification of the pulse threat is required (Iervolino and Cornell, 2008). In fact, the recently developed probabilistic seismic hazard analysis for near-source sites requires a probabilistic model for the occurrence of pulses in ground motion. In fact, assuming that all seismic sources are within 30km from a certain site of interest and given that, as discussed, not all near-source (NS) ground motions are pulse-like, the PSHA, expressed as the mean annual frequency ( ),aS NSλ of Sa exceeding a certain value (x), should be separated into two terms (Eq., 5.1). ( ) ( ) ( ), , & , &a a aS NS S NS pulse S NS no pulsex x xλ λ λ= + (5.1)


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The second term in the right hand side, the near-source non-pulse-like, should be from, say, “ordinary” PSHA, which requires a near-source attenuation law computed with records not showing pulses but still coming from short source-to-site distances (i.e., within 30km). The other part should be the near-source term due to pulse-like records. In this case the attenuation law will not only depend on magnitude and distance but also on a vector of other parameters ( )Z , which are assumed to be meaningful to predict directivity effects. The total hazard is the linear combination of the two hazard curves weighted by the pulse occurrence probability as in Eq. (5.2) and Eq. (5.3), in which a single fault is assumed. ( ) [ ] ( ), & | , , | ,| , , , , ,| , , | , , ,

a pa p

p

S NS pulse T M R M RS pulse M R Z T p Z Z M R pm r z t

x f f d d zP pulse m r z G x m r z t f t dm drλ ν= ∫ ∫ ∫ ∫ (5.2)

( ) [ ]( ) ( ), & | ,| , , ,1 | , , | ,a aS NS no pulse M RS no pulse M R Z M R

m r z

x f dP pulse m r z G x m r f z dm drλ ν= −∫ ∫ ∫ (5.3)

In Eq. (5.2) ν is the mean rate of events on the fault, M is the magnitude of the event, and R is the source-to-site distance. pdt and d z are the integration intervals of the variables pulse period, pT , and Z , respectively. | , , , ,a pS pulse M R Z TG is the complementary cumulative distribution function of aS conditional on M, R, Z , and pT ; | , ,pT Z M Rf is the probability density function of

pT given M, R, and Z . Similarly, | ,M RZf is the conditional distribution of Z given M and R, while ,M Rf is the joint PDF of M and R. The same meaning of the symbols applies to Eq. (5.3). Models for the probability of occurrence were investigated and models are obtained via logistic regression of a set of pulse-like records from the NGA database. Analyses were limited to ground motions recorded within 30km. Occurrence probability of velocity pulses were computed as conditional in respect to those factors considered by seismologists to affect the amplitude of directivity effects. One of the models for strike-slip events is given in Figure 6 (right).

θ [deg]

Epicenter

Site

Rupture

Figure 6. Peculiar spectral shape of pulse-like records (left) and a model for probability of occurrence of

pulses for strike-slip events (right). In Figure 7 the model for non-strike-slip events has been applied to near-source data of the recent L’Aquila earthquake. In the same figure some pulse-like feature of the record of the L’Aquila earthquake are also given (Chioccarelli and Iervolino, 2009).


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Figure 7. From up left corner clockwise: probability of occurrence model applied to the April 2009

L’Aquila fault; Tp pulse periods found in near-source L’Aquila mainshock records; One of the pulse identified records and its response spectra unrotated and rotated in fault normal (FN) and fault parallel

(FP) directions.

6 REAL-TIME PERFORMANCE-BASED EARTHQUAKE ENGINEERING

Due to a large development of regional networks in recent years worldwide, and because of the current advances of real-time seismology, the question of using earthquake early warning systems (EEWSs) for site-specific applications (Figure 8) is rising. Hybrid EEWS’ are of current interest as cost-effective solutions for seismic risk mitigation, although efficiency evaluation and feasibility analysis for earthquake engineering applications is still debated.

Source-to-site

distance

Seismic

network

Ground

motion at

the site

IM (i.e. PGA)

Structural/non-structural

performance/loss

EDP (i.e. Maximum

Interstory Drift Ratio)

Epicenter

Signal at

the network

stations Figure 8. Hybrid EEWS sketch.

Seismologists have recently developed several methods to estimate the magnitude of an event given limited information of the P-waves for real-time applications. Similarly, the source-to-site distance may be rapidly determined by analyzing the time and order of the seismic


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stations detect the developing earthquake. Consequently, given a vector of measures informative for the magnitude, { }2, , ,1 n τ τ τ… , and the sequence of stations triggered by the event, { }2, , ,1 ns s s… , the probability density functions of M and R, ( )2, ,...,1 nf m|τ τ τ and ( ),...,1 2 nf r|s ,s s respectively, may be available. Thus, it is possible to compute in real-time the

probabilistic distribution (or hazard curve) of a ground motion intensity measure at a site of interest (Iervolino et al., 2006; Convertito et al. 2008; Iervolino et al. 2009d) as in Eq. (6.1), which also requires an attenuation relationship, ( )f im|m,r , available for the chosen IM. ( ) ( ) ( ) ( )2, ,..., ,...,n 1 n 1 2 n

m r

f im f im|m,r f m| f r|s ,s s dr dmτ τ τ= ∫ ∫ (6.1)

Real-Time probabilistic seismic hazard analysis (RTPSHA) above was implemented in ERGO (EaRly warninG demO), which is a visual terminal developed to test the potential of hybrid EEWSs (Festa et al., 2009). The system was developed by staff of the RISSC lab (www.rissclab.unina.it) and of the Department of Structural Engineering of the University of Naples Federico II (www.dist.unina.it) under the umbrella of AMRA scarl (www.amracenter.com). It was installed in the office of the dean of the school of engineering of the University of Naples Federico II on July 25 2008 and continuously operates since then. ERGO processes in real-time the accelerometric data provided by a sub-net of ISNet and it is able to perform RTPSHA and eventually to issue an alarm in the case of events occurring with magnitude larger than 3 in the southern Appennines region. ERGO is composed of four panels (Figure 9):

1. Real-time monitoring and event detection: in this panel two kind of data are given: (a) the real-time accelerometric signals of the stations associated to the EEW terminal, shown on a two minutes time window; and (b) the portion of signal that, based on a signal-to-noise ratio determined the last trigger (i.e., event detection) for a specific station (on the left). Because it may be the case that local noise (e.g., traffic or wind) determine a station to trigger, the system declares an event (M larger than 3) only if at least three station trigger within the same two seconds time interval;

2. Estimation of earthquake parameters: this panel activates when the first panel declares an event. If this condition occurs the magnitude and location are estimated in real-time as a function of evolving information from the first panel. Here the expected value of the magnitude as a function of time from the origin of the detected event and the associated standard error are given. Moreover, on a map where also the stations are located, it shows the estimated epicenter, its geographical coordinates and the origin time;

3. Lead-time and peak-shaking map: this panel shows the lead-time associated to S-waves for the propagating event in the whole region. As a further information, on this panel the expected PGA on rock soil is given on the same map. As per the second panel, this one activates only if an event is declared from panel 1 and its input information come from panel 2.

4. RTPSHA and alarm issuance decision: This panel performs RTPSHA for the site where the system is installed based on information on magnitude and distance from panel 2. In particular, it computes and shows real-time evolving PDFs of PGA at the site. Because a critical PGA value has been established for the site (arbitrarily set equal to 0.01g) the system is able to compute the risk this PGA is exceeded


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conditional to the estimates for the ongoing event as a function of time. If such a risk exceeds 20%, the alarm is issued and a otherwise green light turns into red. This panel also gives, as summary information, the actual risk that the critical PGA value is exceeded along with the lead-time available from the site and the false alarm probability.

Figure 9. A real event detected and processed in real-time by ERGO on November 19 2008. The system estimated the event as a M 3.1 earthquake located close to Potenza (capital of the Basilicata region), with an epicenter 115km far from the site. Because the event was a low-magnitude large-distance one, the risk

the critical PGA could be exceeded was negligible and the alarm was, correctly, not issued.

After presenting RTPSHA, it is worth a brief discussion on how magnitude and distance distributions conditional to the measurements of the seismic network can also be used for a real-time estimation of the risk which includes the expected losses from the impending earthquake (Iervolino et al., 2007a). In fact, if an EEWS exists, in the framework of performance-based earthquake engineering, the estimation of the expected losses for a specific building may be computed as in Eq. (6.2).

[ ] ( ) ( ) ( )| , | ,L DM EDP IM

E L s l f l dm f edp im f im s dL dDM dEDP dIMτ τ= ∫ ∫ ∫ ∫ (6.2)

Where ( )f l dm is the PDF of the loss (L) given the structural and non-structural damage

( )DM ; ( )f dm edp is the PDF of damages given the Engineering Demand Parameters

( )EDP , proxy for the structural response; ( )f edp im is the PDF of the EDPs conditional to

appropriate ground motion intensity measures (IM); ( , )f im sτ is the real-time hazard conditional to the real-time information, i.e., from Eq. (6.1).


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To estimate the expected loss in the case of a warning, [ ]| ,WE L sτ , or no warning,

[ ]| ,WE L sτ , it is sufficient to modify Eq. (6.2) posing ( ) ( )| |Wf l dm f l dm= , which is the loss function reflecting a loss reduction action following the alarm, or ( ) ( )| |Wf l dm f l dm= , which is the loss function in the case of no warning, i.e., no security

action is initiated. Being able to compute, before the ground motion hits the structure, both the expected losses in case of warning or not, is relevant for taking the optimal decision, which is: to alarm only if this reduces the expected losses Eq. (6.3).

[ , ] [ , ]:

[ , ] [ , ]

W W

W W

E L s E L s not to alarmIf

E L s E L s to alarm

τ τ

τ τ

⎧ ≤ ⇒⎪⎨

> ⇒⎪⎩ (6.3)

This it implicitly accounts for the costs of false and missed alarms. In fact, computing and comparing the expected losses, conditional to the real-time information coming from the EEWS in the case of alarming or not, allows the determination of the alarm threshold above which is convenient to issue the warning according to the maximum optimality criterion. As an example of the expected-loss approach to the early warning approach is given in Figure 10; in the figure the loss in the case of alarm or not is given for a school classroom in which it is supposed the loss may derive from injury because of structural collapse, injury because of collapse of non-structural elements, and false alarm. The security action is the sheltering of people in the classroom under desks if an alarm. Note that the intersection of the two curves gives the optimal alarm threshold as a function of the measures provided in real time by the seismic network part of the earthquake early warning system.

Ex

pe

cte

d L

oss

[€

]

[s]

No alarm

Alarm

τ̂ Figure 10. Expected loss for the warning and no warning cases as a function of the statistics of the

network measurements for a school building supposed located at 110 km from the epicenter, see Iervolino et al. (2007) for details.

7 OTHER TOPICS

Among other topics which may not be included here there is:

1. hazard analysis for spatially distributed systems; e.g., hazard analysis including spatial correlation of ground motion (Figure 11) for seismic risk analysis of lifelines;


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70 km

70 km

A [km2]PGA [g]

Pr[PGA>p

gain A>a]

Source 2 Figure 11

2. Vulnerability analysis of population of structures; which refers to retrieve fragility

parameters for classes of buildings (Iervolino et al., 2007b; Verderame et al., 2009) and in Figure 12.

Cs

Cd

)X(Cs

)X(Cd

)X(T

X=Geometrical and structuralparameters varying in the population

T

T = 0.135H0.67

T = 0.076H0.93

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

0 3 6 9 12 15 18 21 24 27 30

Height, H [m]

Elastic period, Tel [sec]

transverselongitudinal

Figure 12. The scheme for retreiving the vulnerablity curves for classes of buildings (a); a period-height

relationship for classes gravity-load-designed buildings (b).

8 ACKNOWLEDGEMENTS

Many people participated and still participate to the research discussed in the paper, they are mentioned as co-authors in the references given below, nevertheless I’d like to acknowledge them explicitly in recognition of their essential contribution. Other research not mentioned herein is developed with Dr. Fatemeh Jalayer and detailed discussion may be found in her paper presented at this same workshop and references therein. The Department of Structural Engineering of the University of Naples Federico II (http://www.dist.unina.it/), the AMRA center (http://www.amracenter.com/), and the Stanford University (http://www.stanford.edu/) are the institution in which the most of the research was carried out or from where the authors took the inspiration to do it.


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9 REFERENCES1

Chioccarelli E., Iervolino I. (2009) Direttività e azione sismica: discussion per l’evento de L’Aquila. Proc. of XIII Convegno ANIDIS, Bologna, Italy. (in Italian) [available at http://www.reluis.it]

Convertito V., Iervolino I., Herrero A. (2009) The importance of mapping the design earthquake: insights for southern Italy. Bulletin of the Seismological Society of America. (in press)

Convertito V., Iervolino I., Manfredi G., Zollo A. (2008) Prediction of response spectra via real-time earthquake measurements. Soil Dyn Earthquake Eng, 28:492–505.

Festa G., Martino C., Lancieri M., Zollo A., Iervolino I., Elia L., Iannaccone G., Galasso C. (2009) ERGO: a visual tool for testing earthquake early warning systems. (in preparation)

Iervolino I., Convertito V., Giorgio M., Manfredi G., Zollo A. (2006) Real time risk analysis for hybrid earthquake early warning systems. Journal of Earthquake Engineering, 10(6): 867–885.

Iervolino I., Cornell C.A. (2005) Record selection for nonlinear seismic analysis of structures. Earthquake Spectra, 21(3):685-713.

Iervolino I., Cornell C.A. (2008) Probability of occurrence of velocity pulses in near-source ground motions. Bulletin of the Seismological Society of America, 98(5): 2262-2277.

Iervolino I., Galasso C., Cosenza E. (2008b) Selezione assistita dell’input sismico e nuove Norme Tecniche per le Costruzioni, atti di Valutazione e riduzione della vulnerabilità sismica di edifici esistenti in c.a., Proc. of. Convegno ReLUIS, Rome. (in Italian) [available at http://www.reluis.it]

Iervolino I., Galasso C., Cosenza E. (2009b) REXEL: computer aided record selection for code-based seismic structural analysis. Bulletin of Earthquake Engineering. (submitted March 2009)

Iervolino I., Galasso C., Cosenza E. (2009c) REXEL 2.31 (beta) e la selezione normativa dell’input sismico per l’analisi dinamica non lineare delle strutture. Proc. of XIII Convegno ANIDIS, Bologna, Italy. (in Italian)

Iervolino I., Giorgio M., Galasso C., Manfredi G. (2008c) Prediction relationships for a vector-valued ground motion intensity measure accounting for cumulative damage potential, Proc. of 14th WCEE – 14th World Conference on Earthquake Engineering, Beijing, China, October 12-17.

Iervolino I., Giorgio M., Galasso G., Manfredi G. (2009d) Uncertainty in early warning predictions of engineering ground motion parameters: what really matters? Geophysical research letters, 36, L00B06.

Iervolino I., Giorgio M., Manfredi G. (2007a) Expected loss-based alarm threshold set for earthquake early warning systems. Earthquake Engineering and Structural Dynamics 2007; 36:1151–1168.

Iervolino I., Maddaloni G., Cosenza E. (2008a). Eurocode 8 compliant real record sets for seismic analysis of structures. Journal of Earthquake Engineering, 12(1):54-90.

Iervolino I., Maddaloni G., Cosenza E. (2009a). A note on selection of time-histories for seismic analysis of bridges in Eurocode 8. Journal of Earthquake Engineering. (in press)

Iervolino I., Manfredi G., Polese M., Verderame G.M., Fabbrocino G. (2007b). Seismic risk of R.C. building classes. Engineering Structures, 29:813–820.

Verderame G.M., Iervolino I., Manfredi G. (2009). Elastic period of sub-standard reinforced concrete moment resisting frame buildings. Bulletin of Earthquake Engineering. (submitted May 2009)

1 The most of the manuscripts in this list are available at http://wpage.unina.it/iuniervo.

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