Journal of Earthquake Engineering

This study attempts to reproduce in an artificial way, at a given magnitude-distance couple, the statistical characteristics of damage caused by real accelerograms. The structure adopted is a low-rise shear wall, modelled as a nonlinear, one degree of freedom system with a degrading frequency as a function of a non-cumulative damage variable. Strong-motion records, contained in a large database, are characterised in terms of seismological and seismic parameters. Artificial accelerograms are generated from response spectra representative of real accelerograms belonging to different magnitude-distance zones. Although the mean damage is consistent, the low dispersion of damage caused by the artificial accelerograms with respect to that caused by the real accelerograms is highlighted. In order to reproduce the damage dispersion in addition to the mean damage, a generation method of representative artificial accelerograms is proposed. This method introduces the standard deviation drawn from attenuation relationships into a dispersion pre-process with respect to the regressed spectrum at a given magnitude-distance point. The method turns out to be capable of reproducing the statistical features of damage produced by real strong-motion records.

A road-network reliability analysis for a scenario seismic event is performed for a region of southern Italy characterised by a large number of small to medium municipalities quite close to each other and served by a dense network of roads. Among the many functions of the road network, whose links may fail after an earthquake due to the collapse of the bridges within them, the one selected for the present study is that of allowing rescue operations to be carried out at the sites of collapsed schools. For this to be possible, connection must be maintained between schools that survived, rescue centres and hospitals. Required elements for the study are the fragility curves of the bridges, the schools, the hospitals and the rescue centres. Output of the study is the expected value of the fraction of the total population in the area that is in need of assistance and cannot be hospitalised due to either failure of the network or other vulnerable components.

For modelling the consequences of any large-scale disaster, a fundamental input into the model is a quantifiable description of the built environment at risk. Accurate inventories of the built environment are essential to the model in order to realise social, economic and engineering consequences of the disaster. This paper describes current efforts in developing urban building inventories and their descriptors using advanced technologies and methods, as part of the Mid-America Earthquake Center's initiative to minimise consequences of earthquakes in the Mid-America region. The paper illustrates the use of advanced data such as Lidar, and advanced aerial photographs, cutting-edge quantitative models such as multinomial logistic regression and artificial neural networks and innovative approaches to spatial computing in the preparation of urban inventories for earthquake risk modelling.

Civil structures could undergo hysteresis cycles due to cracking or yielding, when subjected to severe earthquake motions. Seismic instrumentation, structural monitoring and system identification techniques have been used in the past years to assess civil structures under lateral loads. The present research makes use of a continuous-time Least Squares Method, modified herein to consider the nonlinear behaviour of the structure. The proposed on-line algorithm simultaneously estimates the hysteretic component and structural parameters such as damping and stiffness of a shear building structure. Simulations are carried out using the El Centro and the Mexico City seismic records. Fair convergence speed is obtained for the identification of the parameters and the estimation of the hysteretic component.

A reliable estimate of the actual capacity and deformability of existing reinforced concrete buildings in earthquake prone areas is essential in pre- or post-earthquake interventions. This study is concerned with the evaluation of the structural overstrength, the global ductility and available behaviour factor of existing reinforced concrete buildings, designed and constructed according to past generations of earthquake resistant design codes. For the estimation of these global performance characteristics different failure criteria are incorporated in a methodology established to predict the failure mode of the buildings. As an application, a typical five-storey building of the 1960s, designed according to the prevailing design codes, is selected and analysed in the inelastic range. Both bare and infilled structural forms of this building are studied. For this structure, the plastic hinge rotation capacity is the critical failure criterion. The same structure, designed according to current design codes, is re-evaluated using the same methodology, in order to calibrate the procedure and to compare the static and dynamic inelastic performances of the two frames. The results indicate that existing buildings exhibit higher overstrength than their contemporary counterparts, but with much reduced ductility capacity. Perimeter infill walls correct for their lack of ductility by augmenting their stiffness and their overall lateral resistance. The methodology is subsequently applied to a larger inventory of typical existing buildings, as described in a companion publication.

Industrialised nations have dedicated significant investments toward the development of civil infrastructure. To preserve this investment, attention must be given to proper maintenance. Structural Health Monitoring (SHM) has emerged as a tool to support this task. Networks of smart sensors, built upon wireless communication, have the potential to significantly improve SHM. Numerous platforms for smart sensors have been developed, most of which utilise proprietary hardware/software. The Berkeley Mote, utilised in this study, was the first open hardware/software platform to be developed. However, the Berkeley Mote was designed for generic applications and therefore the available sensors are not optimised for use in civil infrastructure applications. Acceleration and strain are among the most important physical quantities to judge the health of a structure. Although commercially available sensor boards have accelerometers, their applicability towards civil infrastructure is limited. This paper presents the development of new acceleration and strain sensor boards based on the Berkely-Mote platform and provides experimental verification of their performance within civil infrastructure applications.