Induced Seismic-Site Effects on the Vulnerability Assessment Of

geosciences

Article Induced Seismic-Site Eﬀects on the Vulnerability Assessment of a Historical Centre in the Molise Region of Italy: Analysis Method and Real Behaviour Calibration Based on 2002 Earthquake

Nicola Chieﬀo 1 and Antonio Formisano 2,*

1 Faculty of Architecture and Urbanism, Politehnica University of Timi¸soara,300223 Timi¸soara, Romania; nicola.chieﬀ[email protected] 2 Department of Structures for Engineering and Architecture, School of Polytechnic and Basic Sciences, University of Naples “Federico II”, 80125 Naples, Italy * Correspondence: [email protected]

Received: 2 December 2019; Accepted: 30 December 2019; Published: 3 January 2020

Abstract: The present research aims to estimate the influence of site amplification on the seismic vulnerability of the historical centre of the municipality of Baranello in the Molise Region of Italy. Firstly, a structural and typological characterization of the investigated area has been done according to the EMS-98 scale. Subsequently, the vulnerability assessment of the historical buildings located there has been carried out through an appropriate survey form in order to identify the buildings which are most susceptible to seismic damage. To this purpose, the seismic event occurring in October of 2002 has been selected as a reference earthquake. Moreover, according to the AeDES form implemented by the Italian Civil Protection Department to evaluate the usability of constructions after seismic events, the calibration of the typological vulnerability curves of the built-up area has been done, and a quantitative assessment of the local seismic response has been achieved, based on the seismic motions recorded after the 2002 Molise earthquake. Finally, the local amplification factor, which negatively influences the severity of the seismic damage on the structures, has been taken into account in order to more correctly foresee the expected damage of the inspected urban sector, so as to use more appropriately the achieved results for reliable seismic risk mitigation plans.

Keywords: site-eﬀects; vulnerability assessment; masonry building compounds; damage scenarios; calibrated vulnerability curves

1. Introduction The recent tragic earthquakes which have occurred in Italy during the last decades are a living testimony of the bad seismic behaviour of the historical centres of many municipalities. This is due to a series of hazardous factors, such as the age of buildings, the poor quality of materials and the insufficient maintenance of constructions, which lead towards the high seismic vulnerability of several built-up areas. In fact, the seismic vulnerability of a given built area indicates the expected amount of damage triggered by an earthquake of a specific magnitude [1]. Therefore, the seismic vulnerability assessment of an urban environment is devoted to estimating the capacity of the built-up area to withstand without failures a series of seismic events, which are responsible for huge economic losses and casualties. Generally, in an overall perspective, the Vulnerability (V), through a multi-factorial combination with other two parameters, namely Exposure (E) and Hazard (H), leads towards the definition of the seismic risk, which can have direct or indirect influence on a specific area.

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Reducing the seismic risk requires researchers to assess the seismic behaviour of buildings towards earthquakes (Vulnerability), the amount of human and material resources that could be lost in the case of seismic events (Exposure) and the intensity and recurrence of earthquakes (Hazard). In fact, focusing on the urban scale, rapid urbanization has dramatically increased the vulnerabilities and risks of urban dwellers in densely populated areas. The high population, combined with the presence of numerous buildings that do not comply with seismic regulations, significantly increase the problem of seismic safety in urbanized areas [2,3]. At urban-scale, the management of a large number of variables, such as different types of buildings, people, roads, etc., is an important issue to accomplish, since the expected damage probability must be foreseen. The identification of the most vulnerable buildings in an urban context is not a simple task due to their heterogeneity and complexity. In general, the predisposition of a building to be damaged by a seismic impact depends upon many aspects that are mainly concerned with the type of construction, the quality of the materials used, the construction methods and the preservation state. Many studies [4–6] have shown that the lack of these features make structures ineffective against earthquakes. In fact, masonry buildings especially, which are located within historic centres, are very often characterized by a static inadequacy, mainly due to antiquated and unsuitable construction techniques, which do not guarantee an adequate security level. To this purpose, an inventory of buildings is an essential procedure for the acquisition of data aiming at evaluating the large-scale seismic vulnerability [7,8]. The available strategies usually take into consideration survey forms [9,10] to collect information on historical centre buildings mainly based on several seismic parameters, i.e., the seismic-resistant system type to lateral loading, the structural regularity, the maintenance conditions and the presence of existing damages. The application of these survey forms allows us to fully understand the various structural types located within heterogeneous urban centres [11]. Thus, in this perspective, the impact of an earthquake can be assessed in terms of expected losses. Therefore, the formulation of an earthquake loss model in a given region is not only of interest for the economic impact of future earthquakes, but it is also important for risk mitigation. A specific loss model makes possible to predict damage to the built environment for a specific data scenario, in the framework of a deterministic approach model, and can be particularly important for responding to emergencies planning with targeted actions in order to safeguard people and the historical heritage of a given area [12–14]. Nowadays, the evaluation of the geological effects has been taken into consideration in the framework of risk assessment in order to have a better and correct forecast of the expected damage [15]. In this circumstance, the soil layers amplify or reduce the seismic waves on the crustal surface. Site effects are thus dangerous when the amplification of seismic waves in surface geological layers occurs. In fact, surface motion can be strongly amplified if geological conditions are unfavourable [16]. Generally, specific geological, geomorphologic and geo-structural settings of restricted areas can induce a high level of shaking on the ground surface even in occasions of low-intensity/magnitude earthquakes. This effect is called site or local amplification. Furthermore, the characterization of site effects can be carried out considering the ground model as a one-dimensional (1D) or two-dimensional (2D) half-space. The substantial difference between the two ground models is that in a 1D analysis, only the depth of the half-space is taken into consideration, neglecting the lateral confinement effect. On the other hand, the more accurate 2D analysis takes into account the significant volume of the soil in the longitudinal and vertical directions. The study of site effects can be conducted using two distinct approaches, namely time domain or frequency domain. In the first case, the local amplification factor is estimated by means of the time sequence (time history) at the bedrock with respect to the amplification at the ground surface. In the second case, the amplification coefficient is achieved considering the Fourier amplitude spectra or the response spectrum [17]. A reliable and easy method for large scale analysis developed by Giovinazzi [15] and Chieffo and Formisano [18] allows us to estimate the macroseismic intensity increment derived from specific Geosciences 2019, 9, x FOR PEER REVIEW 3 of 27 Geosciences 2020, 10, 21 3 of 27 soil category, so as to properly define, taking into account the local amplification factors, the global vulnerabilitysoil category, of so building as to properly stocks define,according taking to the into EMS-98 account scale. the local amplification factors, the global vulnerabilityBased on of these building considerations, stocks according the municipality to the EMS-98 of scale.Baranello, in the province of Campobasso, has beenBased selected on these as a considerations, case study to evaluate the municipality the possible of Baranello,damages under in the seismic province events. of Campobasso, has beenThe proposed selected as work a case aims study to evaluate to evaluate the thelocal possible amplification damages effects under considering seismic events. the time domain of a 1DThe half-space proposed ground work aims model. to evaluate The main the goal local of amplification this work is e fftoects investigate considering the theinfluence time domain of soil amplificationof a 1D half-space on the ground seismic model. behaviour The of main typical goal masonry of this work aggregates is to investigate with the final the target influence to plot of soilthe damageamplification scenarios on the expected seismic behaviour under different of typical ea masonryrthquake aggregates moment withmagnitudes the final targetand site–source to plot the distances.damage scenarios expected under different earthquake moment magnitudes and site–source distances.

2. The The Municipality Municipality of Baranello

2.1. The The Historical Historical Background Background Baranello (Figure 1 1)) isis aa smallsmall towntown locatedlocated inin thethe provinceprovince ofof CampobassoCampobasso inin thethe MoliseMolise RegionRegion of Italy. TheThe municipalitymunicipality has has 2759 2759 inhabitants inhabitants and and rises rises at 610at 610 m abovem above sea sea level level with with an extended an extended area 2 areaof 25 of km 25. Thekm2. town The hastown medieval has medieval origins, origins, and it is and bordered it is bordered by the towns by the of Busso,towns Colleof Busso, d’Anchise, Colle d’Anchise,Spinete and Spinete Vinchiaturo. and Vinchiaturo.

Figure 1. TheThe geographical geographical localization of the municipality of Baranello.

There is limited historical information about the evolution of the centre during time. The village was mentioned for the firstfirst time in the fourteenth century as a possession of Capece Galeota dating back to Norman ages. Only Only in in 1591 the feud was sold by the Carafa family (one of whom had been Pope Paul IV) to the Marquis and then to Angelo Angelo Barone. Barone. Until Until the the nineteenth nineteenth century, century, Baranello was part of the Aragonese domain,domain, andand finallyfinally of of the the Ru Ruffoffo family. family. One One example example of of Norman Norman architecture architecture is isthe the Ru Ruffoffo castle, castle, owned owned by by the the homonymous homonymous family family until until the the nineteenth nineteenth century.century. ItIt waswas built at the highest pointpoint ofof the the ancient ancient village, village, performing performing its function its function of defence of defence and control and control of the entire of the territory. entire territory.It is inserted It is inside inserted a building inside a complexbuilding that complex puts itth inat communicationputs it in communication with the tower, with the which tower, represents which representsthe highest the part highest of the part construction. of the construction. Nowadays, thethe territoryterritory presents presents the the characteristics characteristics of a of mountain a mountain centre: centre: narrow narrow and steep and streetssteep streetsthat become that become wider and wider easier and towards easier thetowards area of the new area settlement. of new Thesettlement. urban centre The urban is characterized centre is characterizedby houses, that by preserve houses, theirthat preserve original appearancetheir original and appearance are located and around are located the church around and the along church the andmain along streets, the whilemain streets, the modern while buildingsthe modern are buildings placed in are other placed districts in other belonging districts tobelonging the municipal to the municipalterritory [19 territory]. [19].

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2.2. The 2002 Molise Seismic Event Occurred on 31st October 2.2. The 2002 Molise Seismic Event Occurred on 31 October The 2002 Molise earthquake was a significant event which historically occurred on October 31st 2002,The with 2002 the Moliseepicentre earthquake localized wasin the a signiﬁcantprovince of event Campobasso which historically between the occurred municipalities on 31 October of San Giuliano2002, with di the Puglia, epicentre Colletorto, localized Santa in the Croce province di ofMagliano, Campobasso Bonefro, between Castellino the municipalities del Biferno of and San Provvidenti.Giuliano di Puglia, This Colletorto,event, having Santa magnitude Croce di Magliano, Mw = 5.7, Bonefro, was perceived Castellino in del a Bifernolarge area and Provvidenti.of Central- SouthernThis event, Italy, having causing magnitude significant Mw = damage5.7, was in perceived a restricted in a largearea between area of Central-Southern Frentani, Sannio Italy, and causingFoggia (Figuresigniﬁcant 2) [20–22]. damage in a restricted area between Frentani, Sannio and Foggia (Figure2)[20–22]. The source source of of the the earthquake earthquake was was located located about about 20 km 20 from km a from deep a seismogenic deep seismogenic structure structure located belowlocated the below Apula the ApulaPlatform. Platform. The replicas The replicas (aftersh (aftershocks,ocks, more more than than 1900 1900 seismic seismic events) events) showed showed a predominantlya predominantly vertical vertical seismogenic seismogenic structure, structure, betwee betweenn 10 10 and and 25 25 km km deep, deep, oriented oriented in in an an east–west direction and and consisting consisting of of two two main main segments segments havi havingng a length a length of about of about 15 km 15 each. km each.Moreover, Moreover, a 10.5 2 a 10.5 28.0 km fault plan, that extends between 12 and 19.9 km in depth [20], is associated with the × 8.0 km× fault plan, that extends between 12 and 19.9 km in depth [20], is associated with the October 31st31 October event. event.

FigureFigure 2. Distribution 2. Distribution of earthquake of earthquake intensities intensities occurring occurring on Thursday, on Thursday, October 31 October 31st 2002 2002 [22]. [22 ]. The affected centre falls within a highly seismic zone, which is directly connected to both the The affected centre falls within a highly seismic zone, which is directly connected to both the Gargano promontory and the Molise Apennine. In this area historical earthquakes with high magnitude Gargano promontory and the Molise Apennine. In this area historical earthquakes with high (6 and 7) occurred, as shown in Figure3[23,24]. magnitude (6 and 7) occurred, as shown in Figure 3 [23,24]. From the historical point of view, by means of the Parametric Catalogue of Italian Earthquakes [24], it has been possible to identify the strongest events located near the study area. Particular interest should be given to the spatial distribution of epicentres in the time period between 1456 and 1962. In this time interval the most important events are: the Apennine sequence, which occurred on Sunday, 5 December 1456 (O.S.) (Mw = 7.2, I = XI in the Mercalli-Cancani-Sieberg (MCS) scale), that produced serious damage to the Municipality of Casacalenda; next there was the Garganica sequence of July–September 1627 (Mw = 7.7, I = X in the MCS scale), which caused significant damage in Termoli (I = VIII–IX in the MCS scale) and in Campomarino (I = VIII in the MCS scale); this was followed by the Friday, 26 July 1805 (N.S.) event (Mw = 6.6, I = X in the MCS scale) in the Matese region, whose effects did not exceed the VI MCS in Larino. Referring to the event that occurred on 31 October 2002, the focal mechanism types induced by the mainshocks are strike slip-faults, characterized by vertical fractures with horizontal movements in the E–W and N–S directions and a focal depth of 15–20 km (Figure4)[23]. Figure 3. Historical earthquakes in the inspected area [24].

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2.2. The 2002 Molise Seismic Event Occurred on 31st October The 2002 Molise earthquake was a significant event which historically occurred on October 31st 2002, with the epicentre localized in the province of Campobasso between the municipalities of San Giuliano di Puglia, Colletorto, Santa Croce di Magliano, Bonefro, Castellino del Biferno and Provvidenti. This event, having magnitude Mw = 5.7, was perceived in a large area of Central- Southern Italy, causing significant damage in a restricted area between Frentani, Sannio and Foggia (Figure 2) [20–22]. The source of the earthquake was located about 20 km from a deep seismogenic structure located below the Apula Platform. The replicas (aftershocks, more than 1900 seismic events) showed a predominantly vertical seismogenic structure, between 10 and 25 km deep, oriented in an east–west direction and consisting of two main segments having a length of about 15 km each. Moreover, a 10.5 × 8.0 km2 fault plan, that extends between 12 and 19.9 km in depth [20], is associated with the October 31st event.

Figure 2. Distribution of earthquake intensities occurring on Thursday, October 31st 2002 [22].

The affected centre falls within a highly seismic zone, which is directly connected to both the GeosciencesGargano2020, 10promontory, 21 and the Molise Apennine. In this area historical earthquakes with5 of 27high Geosciencesmagnitude 2019, 9 ,(6 x FORand PEER 7) occurred, REVIEW as shown in Figure 3 [23,24]. 5 of 27

From the historical point of view, by means of the Parametric Catalogue of Italian Earthquakes [24], it has been possible to identify the strongest events located near the study area. Particular interest should be given to the spatial distribution of epicentres in the time period between 1456 and 1962. In this time interval the most important events are: the Apennine sequence, which occurred on Sunday, December 5th 1456 (O.S.) (Mw = 7.2, I = XI in the Mercalli-Cancani-Sieberg (MCS) scale), that produced serious damage to the Municipality of Casacalenda; next there was the Garganica sequence of July– September 1627 (Mw = 7.7, I = X in the MCS scale), which caused significant damage in Termoli (I = VIII–IX in the MCS scale) and in Campomarino (I = VIII in the MCS scale); this was followed by the Friday, July 26th 1805 (N.S.) event (Mw = 6.6, I = X in the MCS scale) in the Matese region, whose effects did not exceed the VI MCS in Larino. Referring to the event that occurred on October 31st 2002, the focal mechanism types induced by the mainshocks are strike slip-faults, characterized by vertical fractures with horizontal movements in the E–W and N–S directions and a focal depth of 15– 20 km (Figure 4) [23]. FigureFigure 3. 3.Historical Historical earthquakes earthquakes in in the the inspected inspected area area [24 [24].].

(b)

(a) (c)

FigureFigure 4.4.Macroseismic Macroseismic intensitiesintensities ((aa),), seismogenic-faultsseismogenic-faults distributiondistribution inin thethe studystudy areaarea ((bb)) andand focal focal mechanismsmechanisms ofof thethe fault fault model model ( c(c).).

FigureFigure4 a4a shows shows the macroseismicthe macroseismic intensities intensities which occurredwhich occurred after the eventsafter the previously events mentioned.previously Inmentioned. the area near In the the area epicentre, near the the epicentre, maximum the intensity maximum recorded intensity was recorded VI according was VI to according the MCS scale.to the FigureMCS scale.4b illustrates Figure 4b the illustrates distribution the distribution of the composite of the seismogenic composite seismogenic sources (orange sources area) (orange based area) on geologicalbased on geological and geophysical and geophysical data, which data, are characterizedwhich are characterized by geometric by (strike, geometric dip, (strike, width anddip, depth) width andand kinematicdepth) and (rake) kinematic parameters. (rake) Figureparameters.4c describes Figurethe 4c surfacedescribes projections the surface and projections focal mechanisms and focal ofmechanisms the fault model of the forfault the model 31 October for the 2002October Molise 31st earthquakes.2002 Molise earthquakes. Moreover, inMoreover, the central in the panel central the accelerometricpanel the accelerometric stations (that stations recorded (that the recorded mainshocks the ofmainshocks the seismic of sequence) the seismic have sequence) been marked have withbeen triangles;marked with instead, triangles; dashed instead, and solid dashed rectangles and solid point rect outangles the stations point out used the to stations select the used source to select models the andsource the models epicentral and area the [epicentral25]. area [25].

Geosciences 2019, 9, x FOR PEER REVIEW 6 of 27 Geosciences 2020, 10, 21 6 of 27 3. Typological and Structural Survey of the Built Area 3. Typological and Structural Survey of the Built Area 3.1. The CARTIS Form 3.1. TheThe CARTIS structural Form and typological characterization is to be considered indispensable for the census of theThe buildings structural exposed and typological at risk, which characterization is used for classification is to be considered purposes indispensable into typological for the classes. census of the buildingsIn particular, exposed the atCARTIS risk, which form ishas used been for herein classification used in purposes order to intodetect typological the prevalent classes. ordinary buildingIn particular, typologies the in CARTISmunicipal form or submunicipal has been herein territorial used in parts, order called to detect urban the sectors, prevalent characterized ordinary buildingby typological typologies and structural in municipal homogeneity. or submunicipal territorial parts, called urban sectors, characterized by typologicalThe CARTIS and form structural has been homogeneity. conceived by the PLINIVS research centre of the University of NaplesThe “Federico CARTIS form II” hasduring been conceivedthe ReLUIS by the201 PLINIVS4–2016 researchproject centre“Development of the University of a systematic of Naples “Federicomethodology II” duringfor the theassessment ReLUIS of 2014–2016 exposure project on a te “Developmentrritorial scale based of a systematicon the typological/structural methodology for thecharacteristics assessment of of buildings”, exposure on in a collaboration territorial scale with based the Italian on the typologicalCivil Protection/structural Department characteristics [26]. of buildings”,The form in collaborationis divided into with four the sections: Italian Civil Section Protection 0, for the Department identification [26]. of the municipality and the sectorsThe form identified is divided therein; into fourSection sections: 1, for Sectionthe recognition 0, for the of identification each of the ofrelevant the municipality typologies andcharacterizing the sectors the identified generic sub-sector therein; Section of the 1,assigned for the municipality; recognition of Se eachction of 2,the for relevantthe detection typologies of the characterizinggeneral characteristics the generic of sub-sectoreach typology of the of assigned constructions; municipality; Section Section 3, for 2, the for thecharacterization detection of theof generalstructural characteristics elements of ofall each indivi typologyduated ofconstruction constructions; typologies. Section 3, for the characterization of structural elementsFocusing of all individuatedon the case study, construction the historical typologies. centre of Baranello is composed by one unique compartment,Focusing indicated on the case as C01, study, made the of historical 300 buildings centre (Figure of Baranello 5). is composed by one unique compartment,From the indicatedhistorical aspoint C01, of made view, of the 300 analysed buildings mu (Figurenicipality5). is characterized by the presence of constructionFrom the techniques historical pointthat over of view, the centuries the analysed have municipalitymaintained their is characterized original “asset”, by the dating presence back ofto constructionthe fourteenth techniques century. that over the centuries have maintained their original “asset”, dating back to the fourteenthMost of the century. buildings have been built using rough-hewn stones assembled according to the techniqueMost ofofthe sack buildings or mixed have walls, been which built using in some rough-hewn cases have stones greatly assembled affected according the characteristics to the technique and ofquality sack orof mixedconstructions, walls, which resulting in some in substantial cases have deficiencies greatly affected in terms the characteristicsof global response and quality towards of constructions,seismic actions. resulting in substantial deficiencies in terms of global response towards seismic actions.

Figure 5. IdentificationIdentiﬁcation of the urban sector of Baranello. The houses characterising the historical centre are composed of walls with an average thickness The houses characterising the historical centre are composed of walls with an average thickness of 0.65 m and an average inter-storey height of 3.50 m. Except for the masonry vaults, the horizontal of 0.65 m and an average inter-storey height of 3.50 m. Except for the masonry vaults, the horizontal structures, as well as roofs, are generally made of timber or steel beams (Figure6). structures, as well as roofs, are generally made of timber or steel beams (Figure 6). The data collected through the CARTIS form has allowed, through statistical elaborations, to provide indications on the constructive age, number of storeys, average surface area and wall type of the sample of buildings surveyed within the municipality examined. The results obtained are summarized in the cumulative distributions reported in Figure7.

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Figure 6. Street views of some building typologies inside the inspected historical centre of Baranello.

The data collected through the CARTIS form has allowed, through statistical elaborations, to provide indications on the constructive age, number of storeys, average surface area and wall type of the sample of buildings surveyed within the municipality examined. The results obtained are summarizedFigureFigure 6. 6.Street in Street the views cumulativeviews of of some some distri building buildingbutions typologies typologies reported inside inside in the Figurethe inspected inspected 7. historical historical centre centre of of Baranello. Baranello.

(a) (b)

FigureFigure 7. 7.Preliminary Preliminary characteristics characteristics of of buildings buildings surveyed surveyed in in the the municipality municipality of of Baranello. Baranello.

From the data surveyed on the 300 inspected buildings, the prevailing typological class is the

MUR2 (rough-hewn stone) one, which has been detected in 73% of the cases (220 buildings). Moreover, (c) (d)

Figure 7. Preliminary characteristics of buildings surveyed in the municipality of Baranello.

Geosciences 2019, 9, x FOR PEER REVIEW 8 of 27 Geosciences 2020, 10, 21 8 of 27 From the data surveyed on the 300 inspected buildings, the prevailing typological class is the MUR2 (rough-hewn stone) one, which has been detected in 73% of the cases (220 buildings). Moreover,the other classes the other detected classes in thedetected study areain the are: stud MUR3y area (rough-hewn are: MUR3 masonry(rough-hewn stone masonry or pseudo-regular stone or pseudo-regularstone, 2% of the sample),stone, 2% MUR4 of the (regularsample), masonry MUR4 (r withegular squared masonry or brick with stones,squared 13%) or brick and A. stones, B. (unused 13%) andbuildings, A. B. (unused 12%). buildings, 12%). 3.2. The Observed Damage Assessment 3.2. The Observed Damage Assessment Since the 1976 Friuli earthquake (il Terremoto del Friuli, Thursday 6 May 1976 (N.S.)), Since the 1976 Friuli earthquake (il Terremoto del Friuli, Thursday May 6th, 1976 (N.S.)), the the investigation of post-earthquake damage to ordinary buildings has become a crucial necessity investigation of post-earthquake damage to ordinary buildings has become a crucial necessity for for emergency management and the recovery phase of Italian historical towns and cities. The visual emergency management and the recovery phase of Italian historical towns and cities. The visual inspection methods, based upon in situ investigations, have been subjected to substantial changes inspection methods, based upon in situ investigations, have been subjected to substantial changes over time mainly induced by the growth of technical and scientiﬁc knowledge in the ﬁeld of over time mainly induced by the growth of technical and scientific knowledge in the field of seismic seismic vulnerability. vulnerability. First of all, the Post-Earthquake Damage and Safety Assessment (AeDES) form was introduced in First of all, the Post-Earthquake Damage and Safety Assessment (AeDES) form was introduced 1997 as an operational tool, recognized by the Italian Civil Protection Department for the detection and in 1997 as an operational tool, recognized by the Italian Civil Protection Department for the detection management of post-earthquake emergencies (Figure8)[27]. and management of post-earthquake emergencies (Figure 8) [27].

Figure 8. FrameworkFramework of of the the main main section of the Post Post-Earthquake-Earthquake Damage and Safety Assessment (AeDES) form.

Subsequently, in 2014, the Italian Civil Protection Department promoted a new scientific scientific project project with the the aim aim of of creating creating a anew new database database at atthe the nati nationalonal level level to simulate to simulate seismic seismic risk scenarios. risk scenarios. The project,The project, in collaboration in collaboration with the with Eucentre the Eucentre Foundation Foundation (European (European Centre for Centre the training for the and training research and ofresearch Earthquake of Earthquake Engineering), Engineering), led to ledthe todevelop the developmentment of the of theWeb-GIS Web-GIS platform platform called called Da.D.O (Observed Damage Database) [[28].28]. This tool tool is is of of support support to to the the scientific scientific community, community, since it collects collects and and catalogues catalogues the the data data related related toto the the damages damages which which occurred occurred in in the the past past nine nine ea earthquakesrthquakes (Friuli (Friuli 1976, 1976, Irpinia Irpinia 1980, 1980, Abruzzo Abruzzo 1984, 1984, Umbria and Marche Marche 1997, 1997, Pollino Pollino 1998, 1998, Molise Molise and and Puglia Puglia 2002, 2002, Emilia-Romagna Emilia-Romagna 2003, 2003, L’Aquila L’Aquila 2009 2009 and Emilia-RomagnaEmilia-Romagna 2012), 2012), surveyed surveyed through through the AeDES the AeDES form, as form, well as as the well structural as the characteristics structural characteristicsof inspected buildings. of inspected buildings. Thus, for the quantificationquantification of of the the observed observed damage, damage, using using the the Da.D.O Da.D.O database database and and exploiting exploiting the theinformation information collected collected in the in linkedthe linked AeDES AeDES forms, forms, the Damagethe Damage Probability Probability Matrices Matrices (DPM) (DPM) have have been beenstatistically statistically processed processed using the using binomial the binomial distribution distribution function according function toaccording the following to the equation following [29]: equation [29]: 5! µ k µ 5 k p = D 1 D − , (1) k ( ) k5-k5 5 5!k! 5 k !μμ× × − −××DD  p=k  1- , (1) k!(5-k)! 5 5 

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µ wherewhere k k denotes denotes the the damage damage threshold threshold variable variable fr fromom 0 0 to to 5 5 according according to to the the EMS-98 scale scale and and µD representsrepresents the the weighted weighted average average of of damages. damages. Moreover,Moreover, selecting selecting the the event event which which occurred occurred in in Molise Molise in in 2002, 2002, with with the the epicentre epicentre located located in in Bonefro,Bonefro, itit hashas been been possible possible to deduce to deduce the typological the typological classes, theclasses, damage the levels damage and thelevels macroseismic and the macroseismicintensity of the intensity study area. of the Subsequently, study area. Subsequent the graphically, representation the graphical representation of DPM has been of done,DPM has as shown been done,in Figure as shown9[28]. in Figure 9 [28].

(a)

(b) (c)

FigureFigure 9. 9. DamageDamage observation: observation: (a (a) )Da.D.O Da.D.O database, database, (b (b) )damage damage probability probability matrix matrix and and (c (c) )cumulative cumulative damagedamage distribution. distribution.

Furthermore,Furthermore, for for the the typological typological classification classification of of the the surveyed surveyed buildings, buildings, a a parallelism parallelism has has been been conductedconducted between between the the CARTIS, CARTIS, Da.D.O Da.D.O and and EMS-98 EMS-98 me methods,thods, as as illustrated illustrated in in Table Table 1,1, in order to contextualizecontextualize the the prevalent prevalent typolo typologicalgical vulnerability vulnerability classes. classes. InIn Table Table 11,, itit isis noticednoticed thatthat thethe vulnerabilityvulnerability classesclasses are identifiedidentified on the basisbasis of thethe verticalvertical structurestructure features. features. In In particular, particular, the the compared compared methods methods use use the the vertical vertical structures structures typologies typologies as asa commona common prerogative prerogative for for classification classification purposes, purposes, which which sees sees the the vulnerability vulnerability level level reduction reduction from from MUR1MUR1 (irregular (irregular stones) stones) masonry masonry buildings buildings to to RC RC framed framed structures. structures. Likewise, Likewise, the the other other methods, methods, whichwhich useuse acronyms acronyms or definitionsor definitions to identify to identify the vertical the structurevertical materials,structure thematerials, EMS-98 macroseismicthe EMS-98 macroseismicmethod adopts method four classes adopts for four their classes definition for their from definition A (the worst) from toA (the E (the worst) best). to E (the best).

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GeosciencesTable2020, 1.10 ,Correlation 21 of vulnerability classes among the CARTIS, Da.D.O and EMS-98 methods. 10 of 27

Typological Vulnerability Classes TableCARTIS 1. Correlation of vulnerability classesDa.D.O among the CARTIS, Da.D.O and EMS-98 EMS-98 methods. MUR 1 Irregular Masonry Consisting of shapeless Irregular masonry with elementsTypological (small and Vulnerability medium-sized Classes river roundedCARTIS stones pebbles, smoothed Da.D.O and with rounded Masonry with EMS-98 weak or bad MUR 1 edges or quarry bachelors) or elements of quality MUR 2 Irregular masonry with differentIrregular sizes Masonry with sharp Consisting edges, generally of shapeless RoundedMasonry or rough-hewn with weak or Irregular masonry with rounded stones elementsin (smalllimestone and medium-sizedor lava stone. river pebbles,stone masonrybad of qualityweak or bad rough stone smoothed and with rounded edges or quarry Rounded or rough-hewn MUR 2 quality Irregular masonry with bachelors) or elements of diﬀerent sizes with stone masonry of weak MUR 3 Rough masonry Composed of not Class-A rough stone sharp edges, generally in limestone or lava stone. or bad quality Rough-hewn masonry perfectly squared elements, which appear Class-B MUR 3 Rough masonry Composed of not perfectly Class-A Rough-hewnstone or pseudo-regular masonry stone in pseudo-regularsquared elements, form or which with appearwarping in Class-B or pseudo-regularstone stone pseudo-regularstone form orslabs. with warping stone slabs. RegularRegular masonry masonry stone stone MUR 4 RegularRegular masonry masonry Composed Composed of of squared squared elements Class-AClass-A Regular masonry with elementsor or solid solid brick. brick. Class-BClass-B squared or brick stones. Class-CClass-C Frame structure CAR 1 Frame structure CAR 1 Other structures RC frame. Class-B RC frame Other structures RC frame. Class-B RC frame Class-D Class-D

According toto thethe EuropeanEuropean Macroseismic Macroseismic Scale Scale (EMS-98), (EMS-98), the the typological typological vulnerability vulnerability classes classes of theof the investigated investigated urban urban area area are are shown shown in Figurein Figure 10. 10.

Figure 10. Typological vulnerability classes in the municipality of Baranello. Figure 10. Typological vulnerability classes in the municipality of Baranello. 3.3. Large Scale Seismic Vulnerability Assessment 3.3. LargeA seismic Scale vulnerabilitySeismic Vulnerability assessment Assessment at the urban scale has been implemented in order to evaluate the propensityA seismic vulnerability for the damage assessment of buildings at the exposed urban sc toale earthquakes. has been implemented In this context, in order a vulnerability to evaluate index-basedthe propensity method for the has damage been adopted. of buildings exposed to earthquakes. In this context, a vulnerability index-basedThe peculiarity method has of this been method, adopted. proposed by Formisano et al. (2015) [30] and Formisano et al. (2018)The peculiarity [31], is the of possibility this method, of investigating proposed by the Formisano seismic vulnerabilityet al. (2015) [30] of buildingsand Formisano grouped et al. in compounds(2018) [31], throughis the possibility the vulnerability of investigating form depicted the seismic in Table 2vulnerability. of buildings grouped in compounds through the vulnerability form depicted in Table 2.

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Table 2. Vulnerability form for historical clustered buildings.

Class Score, Si Parameters Weight, Wi ABCD 1. Organization of vertical structures 0 5 20 45 1.00 2. Nature of vertical structures 0 5 25 45 0.25 3. Location of the building and the type of foundation 0 5 25 45 0.75 4. Distribution of plan-resisting elements 0 5 25 45 1.50 5. In-plane regularity 0 5 25 45 0.50 6. Vertical regularity 0 5 25 45 0.50 7. Type of floor 0 5 15 45 0.80 8. Roofing 0 15 25 45 0.75 9. Details 0 0 25 45 0.25 10. Physical conditions 0 5 25 45 1.00 11. Presence of an adjacent building with a different height 20 0 15 45 1.00 − 12. Position of the building in the aggregate 45 25 15 0 1.50 − − − 13. Number of staggered floors 0 15 25 45 0.50 14. Structural or typological heterogeneity among adjacent S.U. 15 10 0 45 1.20 − − 15. Percentage difference of opening areas among adjacent facades 20 0 25 45 1.00 −

This form, based on the method proposed by Benedetti and Petrini many decades ago [32,33], is appropriate for masonry building aggregates, and uses five new parameters, additional with respect to the original form ten parameters proposed by the above-mentioned researchers, which take into account the effects of mutual interaction under earthquakes among aggregated Structural Units (S.Us). With regard to the five new added parameters, in order to obtain a form totally homogeneous with the previous one, the scores and weights assigned were calibrated numerically on the basis of the results of specific numerical parametric non-linear analyses. These analyses were performed by the 3MURI software, which uses the Frame by the Macro-Elements (FME) computational method. Further information on how scores and classes were determined are found in the aforementioned work by Formisano et al. (2015) [30]. Methodologically, the vulnerability index, IV, for each S.U., is intended as the weighted sum of the class selected for each of the 15 parameters listed in Table2 multiplied by the respective weight. The estimated parameters are grouped into four vulnerability classes (A, B, C and D, from the best to the worst), characterised by a specific score (also with a negative sign in case of a vulnerability reduction), to which a correspondent weight, Wi, is assigned, this weight being variable from a minimum of 0.25 for the less important parameters, and up to a maximum of 1.50 for the most important one. Thus, the vulnerability index, IV, is calculated according to the following equation:

X15 I = S W , (2) V i × i i=1 where, Si, are the speciﬁc scores associated with each parameter, and Wi are the assigned weights. Subsequently, the vulnerability index value IV is normalized in the range [0–1] by means of Equation (3), assuming, from this moment, the notation VI:    P15   I ( S W )   V min i   − i=1 ×  VI =  , (3)  15   P   [(Smax Wi) (Smin Wi)]  i=1 × − × where I is the vulnerability index deriving from the previously form; (S W ), equal to 125.50, V min · i − represents the sum of scores associated to the vulnerability class A of each parameter multiplied by respective weights; (Smax W ), equal to 495.00, represents the sum of scores associated with the · i Geosciences 2020, 10, 21 12 of 27

Geosciences 2019, 9, x FOR PEER REVIEW 12 of 27 vulnerability class D of each parameter multiplied by the respective weights; and the denominator, vulnerability class D of each parameter multiplied by the respective weights; and the denominator, equal to 620.50, represents the vulnerability total interval. equal to 620.50, represents the vulnerability total interval. According to what has been above speciﬁed, the distribution of the typological vulnerability is According to what has been above specified, the distribution of the typological vulnerability is represented in Figure 11. represented in Figure 11.

FigureFigure 11. 11.VulnerabilityVulnerability distribution distribution in the in the municipality municipality of Baranello. of Baranello.

As it is seen in the previous ﬁgure, the distribution of the vulnerability results is quite homogeneous, As it is seen in the previous figure, the distribution of the vulnerability results is quite with an expected medium–high vulnerability enclosed in the range [0.4–0.6] for typological class A, homogeneous, with an expected medium–high vulnerability enclosed in the range [0.4–0.6] for while only 30% of the samples have a vulnerability index (VI) equal to 0.76. Moreover, for the analysed typological class A, while only 30% of the samples have a vulnerability index (VI) equal to 0.76. typological class B, the expected frequency is in the range [0.2–0.4], which corresponds to a moderate Moreover, for the analysed typological class B, the expected frequency is in the range [0.2–0.4], which vulnerability level. corresponds to a moderate vulnerability level. Subsequently, vulnerability curves [34–36] have been obtained to estimate the propensity for the Subsequently, vulnerability curves [34–36] have been obtained to estimate the propensity for damage of the analysed building stock (Figure 12). the damage of the analysed building stock (Figure 12). More in detail, these curves express the level of damage achieved as a function of macroseismic More in detail, these curves express the level of damage achieved as a function of macroseismic intensity “IEMS-98”, which is deﬁned according to the European macroseismic scale EMS-98. intensity “IEMS-98”, which is defined according to the European macroseismic scale EMS-98. In particular, as shown in Equation (4), the vulnerability curves depend upon the vulnerability In particular, as shown in Equation (4), the vulnerability curves depend upon the vulnerability index (VI), on the seismic hazard, expressed in terms of macroseismic intensity (IEMS-98) and the index (VI), on the seismic hazard, expressed in terms of macroseismic intensity (IEMS-98) and the ductility factor Q, which describes the ductility of a certain typological class, and assumes, in the case ductility factor Q, which describes the ductility of a certain typological class, and assumes, in the case under study, the value of 2.3 [36]. under study, the value of 2.3 [36]. " !# I + 6.25 V 13.1 µ = + EMS-98 I D 2.5 1tan h I +6.25×× V− -13.1 (4) ×× EMS-98Q I μ=2.51+tanhD  (4) Q As reported in the previous Figure 12, the vulnerability curves are derived for a sample of buildings representative of the construction types found in the inspected area. However, for a more accurate representation of the expected damage, the mean typological vulnerability curves have been represented together with other curves, taking into account the statistical variability of damage in the vulnerability range (Vm σ,Vm + σ;Vm + 2σ,Vm 2σ)[2,36–38]. − −

(a) (b)

Geosciences 2019, 9, x FOR PEER REVIEW 12 of 27

vulnerability class D of each parameter multiplied by the respective weights; and the denominator, equal to 620.50, represents the vulnerability total interval. According to what has been above specified, the distribution of the typological vulnerability is represented in Figure 11.

Figure 11. Vulnerability distribution in the municipality of Baranello.

As it is seen in the previous figure, the distribution of the vulnerability results is quite homogeneous, with an expected medium–high vulnerability enclosed in the range [0.4–0.6] for typological class A, while only 30% of the samples have a vulnerability index (VI) equal to 0.76. Moreover, for the analysed typological class B, the expected frequency is in the range [0.2–0.4], which corresponds to a moderate vulnerability level. Subsequently, vulnerability curves [34–36] have been obtained to estimate the propensity for the damage of the analysed building stock (Figure 12). More in detail, these curves express the level of damage achieved as a function of macroseismic intensity “IEMS-98”, which is defined according to the European macroseismic scale EMS-98. In particular, as shown in Equation (4), the vulnerability curves depend upon the vulnerability index (VI), on the seismic hazard, expressed in terms of macroseismic intensity (IEMS-98) and the ductility factor Q, which describes the ductility of a certain typological class, and assumes, in the case under study, the value of 2.3 [36].

I +6.25× V -13.1 × EMS-98 I μ=2.51+tanhD  (4) Geosciences 2020, 10, 21 Q 13 of 27

Geosciences 2019, 9, x FOR PEER REVIEW 13 of 27 (a) (b)

FigureFigure 12. 12. TheThe mean mean typological typological vulnerability vulnerability curv curveses for for examined examined building building typologies. typologies.

3.4. EstimationAs reported of Seismic in the Impactprevious Scenarios Figure 12, the vulnerability curves are derived for a sample of buildingsThe evaluation representative of possible of the seismic construction damage types scenarios found is in essential the inspected when planning area. However, a strategic for measure a more toaccurate mitigate representation the risk. Basically, of the the expected earthquake damage, is a naturalthe mean phenomenon typological generatedvulnerability by thecurves accumulation have been ofrepresented stresses in together particular with points other of thecurves, lithosphere, taking into among account the surfaces the statistical in contact variability with ancient of damage faults in or the in othervulnerability areas. The range energy (Vm is− σ released, Vm + σ; under Vm + 2 theσ, V formm − 2σ of) [2,36–38].P-waves and S-waves, which radiate at different velocities in all directions with roughly spherical wavefronts. There is, therefore, an attenuation of the seismic3.4. Estimation wave energy of Seismic from Impact the epicentre Scenarios to the different sites where earthquake effects are felt, since the amplitudeThe evaluation of the volume of possible waves decreases seismic accordingdamage scen to 1arios/D (D is is theessential site–source when distance), planning whereas a strategic for themeasure surface to wavesmitigate the the amplitude risk. Basically, decreases the about earthquake 1/√(D). is a natural phenomenon generated by the accumulationThe prediction of stresses of the seismicityin particular of apoints specific of sitethe canlithosphere, be evaluated among by adopting the surfaces appropriate in contact seismic with attenuationancient faults laws, or in which other areas. are empirical The energy formulations is released calibratedunder the form on the of statisticalP-waves and data S-waves, (instrumental which orradiate macroseismic) at different analysis velocities of in earthquakes all directions occurred. with roughly Generally, spherical these wavefronts. laws are based There on is, simplified therefore, modelsan attenuation in order of to the represent seismic seismic wave energy propagation. from the In epicentre practice, anto the empirical different relationship sites where is establishedearthquake betweeneffects are some felt, simple since the factors amplitude (energy of released the volume at the waves source decreases through the according magnitude to 1/D (Mw (D), distance is the site– (D) orsource hypocentre distance), (h) whereas distances for between the surfac thee epicentrewaves the and amplitude the site) decreases and some about synthetic 1/√(D). parameters (a, b, c andThe d) that prediction better reproduce of the seismicity the set of of instrumental a specific site or macroseismiccan be evaluated observations. by adopting appropriate seismicOther attenuation research activities laws, which [39,40 ]are were empirical conducted formulations to develop attenuation calibrated laws,on the generated statistical in termsdata of(instrumental spectral accelerations or macroseismic) (Sa) and anal peakysis ground of earthquakes accelerations occurred. (PGA), Generally, or in terms these of laws seismic are intensitybased on (MMI),simplified from models instrumental in order recordings to represent of pastseismic earthquakes propagation. which In practice, occurred. an empirical relationship is establishedIn the current between research, some simple the severity factors of (energy the seismic released effects at hasthe beensource analysed through by the predictive magnitude analyses (Mw), usingdistance the (D) following or hypocentre three seismic (h) distances attenuation betwee laws:n the epicentre and the site) and some synthetic parameters (a, b, c and d) that better reproduce the set of instrumental or macroseismic observations. I = 6.39 + 1.756 Mw 2.747 (R + 7) (5) Other research activitiesEMS-98 [39,40] were conducted× to develop− × attenuation laws, generated in terms of spectral accelerations (Sa) and peak ground accelerations (PGA), or in terms of seismic intensity (MMI), from instrumental recordings of past earthquakes which occurred. In the current research, the severity of the seismic effects has been analysed by predictive analyses using the following three seismic attenuation laws: ×× IEMS-98 =6.39+1.756 M w -2.747 (R+7) (5)

I =1.0157+1.2566××+ M -0.6547 lnR2 2 ) EMS-98 w ( (6)

×× IEMS-98 =1.45 M w -2.46 ln(R+8.16) (7) which were implemented by Crespellani et al. [41], Cauzzi et al. [42] and Esteva and Harris [43], respectively, using the moment magnitude Mw and the site–source distance R (measured in km). Therefore, the analysis conducted is based on an empirical-forecast method, where the probable damage scenarios are estimated by the disaggregation of the seismic risk obtained combining n-

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q ! 2 I = 1.0157 + 1.2566 Mw 0.6547 ln R + 2 (6) EMS-98 × − ×

I = 1.45 Mw 2.46 ln(R + 8.16) (7) EMS-98 × − × which were implemented by Crespellani et al. [41], Cauzzi et al. [42] and Esteva and Harris [43], respectively, using the moment magnitude Mw and the site–source distance R (measured in km). Therefore, the analysis conducted is based on an empirical-forecast method, where the probable Geosciencesdamage scenarios2019, 9, x FOR are PEER estimated REVIEW by the disaggregation of the seismic risk obtained combining n-sources.14 of 27 In detail, a deterministic approach has been used by selecting as its reference earthquakes, according to sources. In detail, a deterministic approach has been used by selecting as its reference earthquakes, the Parametric Catalogue of Italian Earthquakes (CPTI15) [44], three events of increasing magnitude (4, according to the Parametric Catalogue of Italian Earthquakes (CPTI15) [44], three events of increasing 5 and 6) having occurred in the past in the Molise Region. After these moment magnitudes have been magnitude (4, 5 and 6) having occurred in the past in the Molise Region. After these moment selected, the deﬁnition of diﬀerent epicentre distances (in the range from 5 to 35 km) has allowed us to magnitudes have been selected, the definition of different epicentre distances (in the range from 5 to plot the expected damage scenarios (Figure 13). 35 km) has allowed us to plot the expected damage scenarios (Figure 13).

Year: 2005; Mw = 4 Year: 1885; Mw = 5 (a) (b)

Year: 2002; Mw = 6 (c)

FigureFigure 13. 13. TheThe earthquakes earthquakes selected selected for for the the case case study study area area [43]. [43 ].

InIn particular, particular, based based on on the the three three attenuation attenuation laws laws above above mentioned, mentioned, the the macroseismic macroseismic intensities intensities havehave been been correlated correlated to to the the earthq earthquakeuake magnitudes magnitudes on on the the basis basis of ofEquations Equations (5)–(7), (5)–(7), leading leading towards towards thethe 27 27 damage damage scenarios scenarios reported reported in in Table Table 3.3. According to analysis results derived from the previous table, it is possible to notice how the attenuationTable model 3. The correlation proposed between by Esteva moment and Harris magnitude, [43] isM thew, and worst macroseismic case, since, intensity, unlike IEMS-98 the. other laws, it provides the highest macroseismic intensities. Therefore, the damage scenarios achieved according Magnitude Macroseismic Intensity IEMS-98 – Crespellani et al. (1992) [41] Mw R = 5 km R = 17 km R = 35 km 4 VII V III 5 VIII VI V 6 X VIII VII

Magnitude Macroseismic Intensity IEMS-98 – Cauzzi et al. (2008) [42] Mw R = 5 km R = 17 km R = 35 km 4 V IV V 5 VI VI V 6 VIII VII VII

Geosciences 2020, 10, 21 15 of 27 to Esteva and Harris’ attenuation law considering R = 5 Km have been adopted to represent the most conservative risk assessment case, as shown in Figure 14.

Table 3. The correlation between moment magnitude, Mw, and macroseismic intensity, IEMS-98.

Magnitude Macroseismic Intensity IEMS-98—Crespellani et al. (1992) [41] Mw R = 5 km R = 17 km R = 35 km 4 VII V III Geosciences 2019, 9, x 5FOR PEER REVIEW VIII VI V 15 of 27 6 X VIII VII

MagnitudeMagnitude MacroseismicMacroseismic Intensity Intensity IEMS-98 IEMS-98—Cauzzi – Esteva and et al. Harris (2008) (1970) [42] [43] M Mw R =R5 = km 5 km R R= =17 17 km km R = R35 = 35 km km 44 VX IVVII V V 55 VIXI VIVIII V VII 66 VIIIXII VIIX VIIVIII Magnitude Macroseismic Intensity IEMS-98—Esteva and Harris (1970) [43] According to analysis results derived from the previous table, it is possible to notice how the Mw R = 5 km R = 17 km R = 35 km attenuation model proposed by Esteva and Harris [43] is the worst case, since, unlike the other laws, it provides the highest4 macroseismic Xintensities. Therefore, VII the damage scenarios V achieved according 5 XI VIII VII to Esteva and Harris’ attenuation law considering R = 5 Km have been adopted to represent the most 6 XII X VIII conservative risk assessment case, as shown in Figure 14.

(a) (b)

(c)

FigureFigure 14.14. The impact damage scenariosscenarios inin thethe investigatedinvestigatedurban urban area area (for (for R R= = 55 KmKm andand MMww variable fromfrom 44 toto 6)6) accordingaccording toto EstevaEsteva andand Harris’Harris’ attenuationattenuation law.law.

Then, the correlation between the mean damage grade, µD, and the damage thresholds, DK, have been developed according to the EMS-98 scale (Figure 15) [45,46]. From the analysis results, it appears that for Mw = 4 about 61% of the building suffers damage D2, while for Mw = 6, damage thresholds D4 (near-collapse) and D5 (collapse) are attained in 68% and 25% of the cases, respectively. Contrarily, when Mw = 5, a more variable damage distribution is achieved.

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Then, the correlation between the mean damage grade, µD, and the damage thresholds, DK, have been developed according to the EMS-98 scale (Figure 15)[45,46]. From the analysis results, it appears that for Mw = 4 about 61% of the building suﬀers damage D2, while for Mw = 6, damage thresholds D4 (near-collapse) and D5 (collapse) are attained in 68% and 25% Geosciencesof the cases, 2019,respectively. 9, x FOR PEER REVIEW Contrarily, when Mw = 5, a more variable damage distribution is achieved.16 of 27

Geosciences 2019, 9, x FOR PEER REVIEW 16 of 27

R = 5 Km; Mw = 4 R = 5 Km; Mw = 5 (a) (b) R = 5 Km; Mw = 4 R = 5 Km; Mw = 5 (a) (b)

R = 5 Km; Mw = 6 R = 5 Km;(c) Mw = 6 (c) FigureFigure 15. 15. DamageDamage distribution distribution in in the the urban urban sector sector under under investigation. investigation. Figure 15. Damage distribution in the urban sector under investigation. Consequently,Consequently, having deﬁneddefinedthe the damage damage distributions, distributions, a comparisona comparison has has been been made made between between the Consequently, having defined the damage distributions, a comparison has been made between damage obtained through the proposed attenuation models and the corresponding damage achieved the damagethe damage obtained obtained through through the the proposed proposed atteattenuationnuation modelsmodels andand the the corresponding corresponding damage damage achievedfromachieved the from AeDES from the survey theAeDES AeDES forms survey survey (Figure forms forms 16 (Figure ).(Figure 16). 16).

FigureFigure 16. Comparison16. Comparison among among damage damage frequencies frequencies in the in inspected the inspected area between area between the used the attenuation used Figuremodelsattenuation 16. and Comparison the models AeDES and forms. among the AeDES damage forms. frequencies in the inspected area between the used attenuation models and the AeDES forms. From results obtained it is noted that Esteva and Harris’ seismic attenuation law [43] allows us toFrom better results estimate obtained the damage it is noted effectively that foundEsteva on and site. Harris’ Nevertheless, seismic it attenuation should be observed law [43] that allows this us to betterseismic estimate attenuation the damage law tends effectively to underestimate found on site. the Nevertheless, damage thresholds it should D0 be andobserved D2, whilethat this seismicoverestimating attenuation the lawdamage tends level to D1. underestimate the damage thresholds D0 and D2, while overestimating the damage level D1.

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From results obtained it is noted that Esteva and Harris’ seismic attenuation law [43] allows us to better estimate the damage eﬀectively found on site. Nevertheless, it should be observed that this seismic attenuation law tends to underestimate the damage thresholds D0 and D2, while overestimating the damage level D1. Geosciences 2019, 9, x FOR PEER REVIEW 17 of 27 3.5. Calibration of Typological Vulnerability Curves 3.5. Calibration of Typological Vulnerability Curves Once we applied the vulnerability index methodology, and after having derived the damage scenariosOnce for we the applied whole the building vulnerability stock of index the citymethodology, centre of Baranello,and after having it is possible derived to the calibrate damage the typologicalscenarios vulnerabilityfor the whole curvesbuilding based stock on of the the events city cent whichre of occurredBaranello, in it the is possible examined to area.calibrate the typological vulnerability curves based on the events which occurred in the examined area. The proposed method aims at calibrating the typological vulnerability curves based on the The proposed method aims at calibrating the typological vulnerability curves based on the macroseismic data collected after the 2002 earthquake. The use of these curves is desirable, since they macroseismic data collected after the 2002 earthquake. The use of these curves is desirable, since they represent a useful tool for the evaluation of the vulnerability induced by a seismic event through represent a useful tool for the evaluation of the vulnerability induced by a seismic event through a a synthetic parameter, i.e., the mean damage grade (µD). synthetic parameter, i.e., the mean damage grade (µD). Furthermore,Furthermore, to to take take into into accountaccount thethe variability of of seismic seismic motion motion in in terms terms of ofmacroseismic macroseismic intensity,intensity, using using the the databasedatabase Da.D.O, Da.D.O, three three macrosei macroseismicsmic intensity intensity thresholds, thresholds, recorded recorded after the after 2002 the 2002Molise Molise earthquake, earthquake, have have been been considered. considered. To this To thispurpose, purpose, three three municipalities municipalities of the of province the province of ofCampobasso Campobasso have have been been selected selected as reference as reference cases. cases. In particular, In particular, the municipa the municipalitylity of Baranello, of Baranello, with withan anintensity intensity of V of (the V (the starting starting point point of ofthe the functi function),on), and and the the cities cities of ofSan San Giuliano Giuliano di diPuglia Puglia and and Bonefro,Bonefro, with with intensity intensity equal equal to to VII VII and and IX, IX, respectively, respectively, have have been been selected, selected, theythey beingbeing consideredconsidered as homogeneousas homogeneous from from typological typological and and structural structural points points of of view. view. Thus,Thus, based based on on these these considerations, considerations, a ﬁrsta first trial tria representationl representation of of the the damage–intensity damage–intensity curve curve has beenhas provided, been provided, as illustrated as illustrated in Figure in Figure 17[47 17]. [47].

(a) (b)

FigureFigure 17. 17.Calibration Calibration of vulnerability of vulnerability curves: curves: (a) interpolating (a) interpolating polynomial polynomial function; (bfunction;) representation (b) ofrepresentation the proposed curve.of the proposed curve.

FigureFigure 17 17aa shows shows a a third-degree third-degree interpolationinterpolation function able able to to associate associate the the observed observed damage damage grade,grade, achieved achieved by by means means of of the the AeDES AeDES form, form, to to the the mean mean damage damage grade, grade, calculated calculated for for the the V, V, VII VII and IXand macroseismic IX macroseismic intensities. intensities. In Figure In Figure 17 b17b is is shown shown the the mathematical mathematical representation representation of of the the curve curve proposedproposed to calibrateto calibrate the the observed observed damages. damages. In this In latterthis latter ﬁgure, figure, it is worth it is notingworth that,noting since that, intensities since intensities IEMS-98 > IX were not detected in the study area, the curve has a dashed part, corresponding IEMS-98 > IX were not detected in the study area, the curve has a dashed part, corresponding to undetectedto undetected damages, damages, leading leading probably probably towards towards a threshold a threshold damage damage D5 D5 (collapse). (collapse). The mathematic expression of the proposed law is given by the following equation: The mathematic expression of the proposed law is given by the following equation: I+6.25V-×Ψ "× EMS-98 I !# μ=2.51+tanhD I +6.25 V Ψ (8) µ = 2.5 1 + tan h EMS-98 Q × I − (8) D × Q where ψ and Q have assumed the values of 12.35 and 2.00 (the latter analogous to the ductility factor wheresuggestedψ and by Q haveEurocode assumed 8 for themasonry values buildings), of 12.35 and respectively, 2.00 (the latter in order analogous to have to the the mathematical ductility factor suggested(red) curve by perfectly Eurocode superimposable 8 for masonry buildings),to the third-degree respectively, interpolation in order relationship. to have the mathematical (red) curve perfectlyFinally, Figure superimposable 18 shows the to comparison the third-degree between interpolation the proposed relationship. curve and that deriving from the method presented by Lagomarsino and Giovinazzi [34] for the typological classes A and B, which are characterised by an average vulnerability index of 0.55 and 0.34, respectively.

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Finally, Figure 18 shows the comparison between the proposed curve and that deriving from the method presented by Lagomarsino and Giovinazzi [34] for the typological classes A and B, which are characterisedGeosciences 2019, by9, x anFOR average PEER REVIEW vulnerability index of 0.55 and 0.34, respectively. 18 of 27

(a) (b)

FigureFigure 18.18.Comparison Comparison between between the the proposed proposed curves curves and thoseand those derived derived from the from macroseismic the macroseismic method proposedmethod proposed by Lagomarsino by Lagomarsino (2006) [33 (2006)] for typological [33] for typological classes A classes and B. A and B.

ItIt cancan bebe seenseen howhow thethe proposedproposed curvecurve providesprovides expectedexpected damagedamage valuesvalues higherhigher thanthan thethe onesones derivedderived from the other method, method, which which is is based based on on the the empirical–mechanical empirical–mechanical procedure procedure developed developed in inthe the framework framework of ofthe the Risk-UE Risk-UE project project for for differ diﬀerentent samples samples of of buildings belonging to severalseveral EuropeanEuropean Countries. In In particular, particular, for for Class Class A Abu buildings,ildings, the the proposed proposed formulation formulation provides, provides, for formacroseismic macroseismic intensities intensities V, V,VII VII and and IX, IX, damage damage percentage percentage increases increases equal equal to to 12%, 12%, 41% 41% and 46%, respectively,respectively, in in comparison comparison to thoseto those foreseen foreseen by Lagomarsino. by Lagomarsino. On the On other the hand, other for hand, Class for B buildings Class B thesebuildings increments, these increments, corresponding corresponding to macroseismic to macros intensitieseismic intensities VII and IX VII only, and are IX equalonly, are to 26% equal and to 48%,26% and respectively. 48%, respectively. Deﬁnitely,Definitely, fromfrom thethe aboveabove TableTable4 ,4, it it appears appears that that the the proposed proposed formulation, formulation, if if compared compared to to the the LagomarsinoLagomarsino and GiovinazziGiovinazzi method, provides results on thethe safesafe sideside inin predictingpredicting thethe possiblepossible expectedexpected damagesdamages inin thethe examinedexamined area.area.

TableTable 4.4. ComparisonComparison in in terms terms of of mean mean damage damage grades grades between between the theproposed proposed formulation formulation results results and andLagomarsino Lagomarsino and andGiovinazzi’s Giovinazzi’s relationship relationship ones ones for for the the macroseismic macroseismic intensities intensities recorded recorded in thethe investigatedinvestigated area.area.

MeanMean Damage Damage Grade, Grade, µDµ D AnalysisAnalysis Method Method and Typological and Typological Class Class V VVII VII IX IX LagomarsinoLagomarsino and Giovinazzi and Giovinazzi (2006) (2006) [34] —Class [34]—Class A A 0.072 0.072 0.38 0.38 1.61 1.61 CalibratedCalibrated curve—Class curve—Class A A 0.081 0.081 0.54 0.54 2.37 2.37 DamageDamage increment increment 12% 12% 41% 41% 46% 46% LagomarsinoLagomarsino and Giovinazzi and Giovinazzi (2006) (2006) [34] —Class [34]—Class B B 0.030 0.030 0.16 0.16 0.83 0.83 Calibrated curve—Class B 0.030 0.21 1.24 Calibrated curve—Class B 0.030 0.21 1.24 Damage increment - 26% 48% Damage increment - 26% 48%

4.4. InfluenceInfluence ofof thethe GeologicalGeological ConditionsConditions onon thethe GroundGround MotionMotion 4.1. Local Site Effects 4.1. Local Site Effects In the framework of large-scale vulnerability analysis, the evaluation of site effects plays In the framework of large-scale vulnerability analysis, the evaluation of site effects plays a a fundamental role for a correct prediction of the expected damage, and therefore, to implement fundamental role for a correct prediction of the expected damage, and therefore, to implement suitable risk mitigation measures to safeguard people’s life and to preserve the integrity of historical suitable risk mitigation measures to safeguard people’s life and to preserve the integrity of historical heritage constructions. heritage constructions. From the physical point of view, the local seismic response can be intended as a set of changes in amplitude, duration and frequency content that a seismic motion, relative to a bedrock basement, undergoes through the overlying layers of soil up to the surface. In other words, the ground layers can increase the amplitude of the seismic motion at some frequencies and reduce it for other ones. The schematization of seismic motion can be represented both in the domain of time and frequencies. In particular, considering the time domain, the parameters most frequently used to

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From the physical point of view, the local seismic response can be intended as a set of changes in amplitude, duration and frequency content that a seismic motion, relative to a bedrock basement, undergoes through the overlying layers of soil up to the surface. In other words, the ground layers can increase the amplitude of the seismic motion at some frequencies and reduce it for other ones. The schematization of seismic motion can be represented both in the domain of time and frequencies. In particular, considering the time domain, the parameters most frequently used to describe the earthquake characteristics are the peak value of the acceleration, the velocity, the displacements, and finally, the duration. In the second case (frequency domain), the parameters of seismic motion are characterized by either the Fourier spectrum or the response spectrum. The quantitative evaluation of the local seismic response can, therefore, be carried out on the basis of the comparison between different quantities representative of the surface seismic motion and the reference one (bedrock). The problem of geo-hazard effects has been already contemplated by two works of Chieffo and Formisano (both 2019) [18,48], where, under a macroseismic approach, and on the basis of macroelement numerical analysis on clustered buildings, the site effects were taken into account through a local amplification coefficient, fPGA, defined as the ratio between the maximum recorded acceleration at the ground surface (amax,s) and that at the bedrock (amax,r), as reported in Equation (9).

amax,s fPGA = (9) amax,r

4.2. Geological Conditions of the Study Area Focusing on the case study, the historic centre area of Baranello is characterized by a geological structure mainly derived from covering tectonics related to the formation of the Apennine chain and sub-Apennine reliefs. The sedimentary series, variously displaced and dismembered, were poured into the Molise basin causing anomalous overlaps and outcropping of very different units both for facies and for age and paleogeographic genesis. The territory is characterised by the presence of a heterogeneous soil constituted by a basal interval formed in large part by outcrops found along the middle-basal bands of the local slopes. Two lithofacies have been distinguished. The first, namely the dominant pelitic–flysch of St. Bartolomeo, is characterized by a cohesive behaviour type, represented by silt–sand clays and clay–silt marls of different colours, from gray–blue to brown, with sporadic intercalations of a calcareous and arenaceous nature. The clayey lithotypes are characterized by a modest technical quality, that tends to significantly reduce in the superficial layers more exposed to exogenous degradation, and in particular, to the erosive and plasticizing action produced by the corrosive and infiltration waters. The resistance characteristics are, therefore, globally linked to the clay component, and under the conditions of short-term periods, they are essentially regulated by the undrained cohesion parameter. Moreover, the permeability degree could be considered practically null, since there is no interstitial water circulation. On the other hand, the second lithofacies, mainly made of stones, are due to an irregularly stratified marly–limestone–arenaceous succession, in which layers of limestones and coarse sandstones are identified with centimetric alternations of arenaceous and silt–marly levels and dense, stratified, clay–silt layers. Finally, the formations described previously are generally surmounted by extensive coverings of both secondary genesis and areal thickness, represented essentially by colluvial deposits or by the localized accumulations of carryovers, whose presence is substantially connected to the local infrastructural development of the area. For the seismic microzonation of this historic centre, data from in situ surveys made available by the Municipal Administration of Baranello are used. Furthermore, in situ tests were carried out to identify the stratigraphy. Figure 19 shows the areas where the Down-Hole geological characterization tests were carried out. These tests provide the velocity of the propagation of seismic waves, compression and shear, at different depths. Geosciences 2020, 10, 21 20 of 27

Thus, measuring the time these waves go from the source (on the surface) to the receiver (located Geosciencesinside 2019 a properly, 9, x FOR PEER prepared REVIEW hole), it is possible to derive the parameters of the soils traversed.20 of 27

Figure 19. The identification of the in situ geological tests. Figure 19. The identification of the in situ geological tests. The positions of tests, indicated with S1 and S3 in Figure 19, give back the ground stratigraphy consistingThe positions of deposits of tests, ofindicated clay silt with and S1 silty and sand S3 in with Figure a bedrock 19, give basementback the ground located stratigraphy at 30 m of depth. consistingThe seismic of deposits subsoil of categoryclay silt and associated silty sand with with this a groundbedrock typebasement is the located B one accordingat 30 m of todepth. the Italian The technicalseismic subsoil standard category NTC18 associated [49]. with this ground type is the B one according to the Italian technical standard NTC18 [49]. 4.3. Evaluation of the Geological Amplification Factor 4.3. Evaluation of the Geological Amplification Factor The evaluation of the local amplification coefficient has been estimated according to a time domain, sinceThe evaluation the main purpose of the local of the amplification work is to characterize coefficient has the maximumbeen estimated ground according amplification to a time deriving domain,from since local sitethe main effects purpose to correctly of the predict work damageis to characterize scenarios. the Therefore, maximum the ground accelerogram amplification of the event derivingwhich from occurred local site in Molise effects into 2002correctly with predict its epicentre damage located scenarios. in Bonefro. Therefore, has beenthe accelerogram used. The event of was the event which occurred in Molise in 2002 with its epicentre located in Bonefro. has been used. The characterized by a magnitude, Mw, equal to 6 with a maximum PGA = 0.55 g. event wasTo characterized this purpose, by STRATA a magnitude, 1.0 software Mw, equal [50 to], 6 developedwith a maximum at the PGA University = 0.55 g. of Texas, was used forTo simplifiedthis purpose, 1D STRATA numerical 1.0 modelling software [50], of the developed geological at the conditions University of of seismic Texas, motionwas used at for bedrock. simplified 1D numerical modelling of the geological conditions of seismic motion at bedrock. More More precisely, noting the accelerogram at the crustal surfaces, it is possible to “transport” the seismic precisely, noting the accelerogram at the crustal surfaces, it is possible to “transport” the seismic input input to the bedrock. In this case, once the soil stratigraphy is defined, the software implicitly takes to the bedrock. In this case, once the soil stratigraphy is defined, the software implicitly takes into into account the “filter” effect of the soil layers. account the “filter” effect of the soil layers. The evaluation of the local seismic amplification factor, therefore, provides a clear and effective The evaluation of the local seismic amplification factor, therefore, provides a clear and effective representation of the filtering effect of a soil deposit on seismic waves. Thus, based on these representation of the filtering effect of a soil deposit on seismic waves. Thus, based on these considerations, starting from the accelerogram recorded after the Molise earthquake, in Figure 20 the considerations, starting from the accelerogram recorded after the Molise earthquake, in Figure 20 the accelerogram at the bedrock and the corresponding amplified on the crustal-surface have been derived accelerogram at the bedrock and the corresponding amplified on the crustal-surface have been and graphically depicted. derived and graphically depicted.

Geosciences 2019, 9, x FOR PEER REVIEW 21 of 27 Geosciences 2020, 10, 21 21 of 27 Geosciences 2019, 9, x FOR PEER REVIEW 21 of 27

Figure 20. The elaborated accelerograms. Figure 20. The elaborated accelerograms. Figure 20. The elaborated accelerograms. As it is seen in the previous figure, local site effects provide an increase of accelerations detected As it is seen in the previous figure, local site effects provide an increase of accelerations detected at at theAs bedrock. it is seen In inparticular, the previous the amplification figure, local site factor effects fPGA computedprovide an according increase ofto accelerationsEquation (9) provides detected the bedrock.results illustrated In particular, in Table the amplification5. factor fPGA computed according to Equation (9) provides at the bedrock. In particular, the amplification factor fPGA computed according to Equation (9) provides the results illustrated in Table5. the results illustrated in Table 5. Table 5. Amplification factor based on time domain. Table 5. Amplification factor based on time domain. TimeTable 5. Amplification factorAcceleration based on [g]time domain. Acceleration [g] Time HistoryHistory max, s max, r PGA Time Amplified—a Acceleration Bedrock—a [g] f Amplified—amax,s Bedrock—amax,r fPGA History10 s Amplified—a 0.56 max, s Bedrock—a 0.42 max, r 1.33fPGA 10 s 0.56 0.42 1.33 In the presented table,10 s the recorded 0.56amplificatio n coefficient 0.42 is equal 1.33to 1.33, which means that the increment of the seismic motion from the bedrock basement to the crustal surface is equal to 33%. InIn thethe presentedpresented table, table, the the recorded recorded amplification amplificatio coen coefficientfficient is equalis equal to 1.33,to 1.33, which which means means that that the From these obtained results, and depending on the geologic conditions detected for the case incrementthe increment of the of seismicthe seismic motion motion from from the bedrockthe bedrock basement basement to the to the crustal crustal surface surface is equal is equal to 33%. to 33%. study area, the mean damage degree, µD, of the investigated structural units determined in Section From thesethese obtained obtained results, results, and and depending depending on theon the geologic geologic conditions conditions detected detected for the for case the study case 3.3 can be amplified by the above fPGA factor, leading to a more correct expected damage grade µD,s area,study the area, mean the damage mean damage degree, µdegree,D, of the µD investigated, of the investigated structural structural units determined units determined in Section in3.3 Section can be [43]: amplified3.3 can be byamplified the above by f PGAthe abovefactor, f leadingPGA factor, to aleading more correct to a more expected correct damage expected grade damageµD,s [ 43grade]: µD,s [43]: µD,sμ=μf= µD ×fPGA (10) D,s D× PGA × μ=μfD,s D PGA (10) Finally, a synthetic representation ofof the new damagesdamages achieved has been shown in Figure 21 for the already considered combinations of magnitudes and site–source distances. the alreadyFinally, considered a synthetic combinations representation of of magnitudes the new da andmages site–source achieved distances.has been shown in Figure 21 for the already considered combinations of magnitudes and site–source distances.

R = 5 Km; Mw = 4 R = 5 Km; Mw = 5 (a) (b) R = 5 Km; Mw = 4 R = 5 Km; Mw = 5 (a) Figure 21. Cont. (b)

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RR == 55 Km;Km; MM ww = = 66 ((cc))

FigureFigure 21.21. DamageDamage distributiondistribution consideringconsidering locallocal seismicseismic amplificationamplification ampliﬁcation effects. eeffects.ﬀects.

ComparingComparing the the new new damage damage scenario scenario to to that that reported reported in in Section Section 3.43.4 (Figure(Figure 15),1515),), it it is is possible possible to to estimateestimate the the damage damage increase increase due due to to site site effects, eeffects,ﬀects, asas reportedreported inin FigureFigure 22 22.22..

RR == 55 Km;Km; MMww = = 44 R R == 55 Km;Km; MMww = = 55 ((aa)) ((bb))

RR == 55 Km;Km; MM ww = = 66 ((cc))

FigureFigure 22. 22. TheThe damagedamage scenariosscenarios withwith andand withoutwithout loca locallocall seismic seismic effects: eeffects:ﬀects: comparisoncomparison of of results. results.

AsAs observedobserved in in thethe aboveabove figure,figure, ﬁgure, the the locallocal sitesite effeeffe eﬀectsctscts produceproduce a a veryvery highhigh increaseincrease of of thethe expectedexpected damage.damage. InIn In particular,particular, particular, itit itisis notedisnoted noted that,that, that, forfor foranan epicentreepicentre an epicentre distancedistance distance ofof 55 km,km, of 5 thethe km, damagedamage the damage distributiondistribution distribution tendstends totendsto increaseincrease to increase towardstowards towards higherhigher higher levelslevels levels ofof damagedamage of damage... ThisThis This resultresult result isis much ismuch much moremore more evidentevident evident whenwhen when MM ww === 666 is is considered,considered, since since the the D4 D4 damage damagedamage level level is is drastically drastically reduced, reduced, whilewhile thethe D5D5 oneone isis stronglystrongly increased.increased.

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5. Concluding Remarks This study proposes a simplified methodology to analyse the seismic vulnerability of masonry building aggregates located in historic centres considering the influence of geo-hazard conditions. An urban sector of 300 buildings in the historical centre of Baranello, in the district of Campobasso (Italy), has been identified as study area for the application of the proposed analysis method. Firstly, the characterisation of the typological classes of the urban sector examined has been done by means of the CARTIS form, which has allowed us to classify the building compounds from the structural point of view. From on-site recognition, it has been detected that the prevailing typological class of masonry buildings is the MUR2 (rough-stone) one, which represents 75% of the building stock examined. Timber or steel beams and masonry vaults have been detected in the inspected buildings as the main horizontal structures. For the quantification of the observed damage, the AeDES formed conjunctly with the Da.D.O database have been adopted to statistically derive the damage probability matrices. The gotten results have shown that 38% of the buildings have damage D0 (null), while 36% of them reached a damage level D1 (negligible to slight damage). Subsequently, the seismic vulnerability of the inspected urban sector has been estimated through a vulnerability index method conceived for building aggregates. In the urban area, two distinct typological classes, namely A and B, have been identified according to the EMS-98 scale. It is worth noting that the distribution of vulnerability results for typological class A is quite homogeneous, with an expected medium-high vulnerability enclosed in the range [0.4–0.6], while only 30% of the building sample has a vulnerability index equal to 0.76. Contrarily, for the analysed typological class B, the expected frequency is in the range [0.2–0.4], which corresponds to a moderate vulnerability level. The damage scenarios of the investigated urban sector, based on a specific seismic attenuation law, have been estimated for different moment magnitudes and site–source distances. The results obtained have shown how Esteva and Harris’ attenuation model, if compared to the other attenuation laws, provides the most unfavourable condition in terms of expected damage. In fact, from the statistical processing of expected damages for a moment magnitude equal to 6, a damage threshold D4 (near-collapse) has been attained in 68% of the cases, whereas only 25% of buildings has reached a damage D5 (collapse). Furthermore, once the damage scenarios have been derived for the whole building stock, the typological vulnerability curves, based on the macroseismic data collected after the 2002 earthquake, have been calibrated on the basis of the seismic damages detected in the examined area. More in detail, three hazard-levels expressed in terms of macroseismic intensity have been considered. In particular, according to the Molise seismic event which occurred in 2002, for the Municipality of Baranello an intensity of V has been considered, whereas for the cities of San Giuliano di Puglia and Bonefro the intensities recorded have been VII and IX, respectively. Thus, the classical formulation of the mean damage grade has been slightly modified in order to calibrate the experimental evidences in terms of damage. To this purpose, a value equal to 12.35 has been associated with the coefficient ψ, that affects the slope of the curve, whereas the ductility factor, Q, has been assumed equal to 2, according to the provisions of Eurocode 8 for masonry buildings. Considering the typological class, A, the proposed curve provides, considering the aforementioned hazard thresholds, a damage percentage increase of 12%, 41% and 46% for seismic intensities V, VII and IX, respectively. On the other hand, the class B buildings have damage increments of 26% and 48% for seismic intensities VII and IX, respectively. Finally, a local seismic amplification factor has been defined according to the time-domain method. To this purpose, a simplified 1D numerical modelling of the geological conditions of seismic motion has been considered. More precisely, noting the accelerogram at the crustal surfaces, it has been possible to “transport” the seismic input to the bedrock. In this case, once the soil stratigraphy has been defined, the used software implicitly has taken into account the “filter” effect of the soil layers. The evaluation of the local seismic amplification factor has, therefore, provided a clear and effective representation of the filtering effect of soil deposits on seismic waves. Geosciences 2020, 10, 21 24 of 27

Looking at the analysis results, the esteemed amplification factor has been found as equal to 1.33, which means that the seismic motion increment from the bedrock basement to the crustal surface is equal to 33%. From the new damage scenarios considering local effects, it has been detected as a considerable damage increment. In particular, it has been noted that for the epicentre distance of 5 km and moment magnitude of 4, damage thresholds D2 and D3 have been attained with a damage occurrence probability less than that of the basic case in which the soil influence has been neglected. Contrary to this, the D4 and D5 damage levels significantly increase due to the site effects. On the other hand, considering the worst scenario (R = 5 km and Mw = 6), the site effects have reduced drastically the damage levels D3 and D4, but they have increased the D5 threshold with the collapse of 98% of the buildings in the analysed area. In conclusion, the proposed work has represented an important starting point for large-scale vulnerability and risk analysis considering site effects, so providing a comprehensive method to predict more precisely damage scenarios into historical centres. In this context, the applicability and feasibility of the proposed research can be considered extendable also to other seismic regions characterized by different types of masonry buildings. To this purpose, the characterization of the sample of buildings is an essential tool for large-scale analysis, since it allows us to evaluate the distribution and frequency of expected vulnerabilities. This issue is of fundamental importance, since the proposed approach, which will allow us to take into account in a simplified way the influence of site effects on the overall response of buildings, can be used for planning effective seismic risk mitigation interventions.

Author Contributions: Methodology, A.F.; Investigation, N.C.; Data Curation, N.C. and A.F.; Writing-Original Draft Preparation, N.C.; Writing-Review & Editing, A.F. All authors have read and agreed to the published version of the manuscript. Funding: This research did not receive any external funding. Acknowledgments: The authors would like to acknowledge the Vice Mayor Domenico Boccia for the interest demonstrated towards the present study, the Surveyor Gianni Caruso for his profuse availability during the site-inspections and Eng. Umberto Capriglione of the Regional Civil Protection Department for providing the macroseismic data of the 2002 earthquake. Also, the financial support given by the WP2 Cartis “Inventory of existing structural and building types” research line of the DPC-ReLUIS 2019-2021 project, where the current research activity was developed, is gratefully acknowledged. Conflicts of Interest: The authors declare no conflict of interest.

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