Considerations and Suggestions about the Seismic Assessment Procedures of Existing R.C. Frame Buildings According to OPCM 3431 and Eurocode 8

2009 ◽  
Vol 2 (1) ◽  
pp. 31-47
Author(s):  
V. Mpampatsikos ◽  
L. Petrini ◽  
R. Nascimbene
2014 ◽  
Vol 77 ◽  
pp. 129-142 ◽  
Author(s):  
Ricardo Monteiro ◽  
Mário Marques ◽  
Gopal Adhikari ◽  
Chiara Casarotti ◽  
Rui Pinho

Buildings ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 392
Author(s):  
Predrag Blagojević ◽  
Svetlana Brzev ◽  
Radovan Cvetković

The paper presents a study on the existing low-rise unreinforced masonry (URM) buildings constructed in the period from 1945 to 1980 in Serbia and neighbouring countries in the Balkans. Buildings of this typology experienced damage in a few earthquakes in the region, including the 2010 Kraljevo, Serbia earthquake and the 2020 Petrinja, Croatia earthquake. The focus of the study is a seismic design approach for Simple masonry buildings according to Eurocode 8, Part 1, which is based on the minimum requirements for the total wall area relative to the floor plan area, which is referred to as Wall Index (WI) in this paper. Although the intention of Eurocode 8 is to use WI for design of new buildings, the authors believe that it could be also used for seismic assessment of existing masonry buildings in pre- and post-earthquake situations. A study on 23 URM buildings damaged in the 2010 Kraljevo, Serbia earthquake has been presented to examine a relationship between the WI and the extent of earthquake damage. Seismic evaluation of a typical 3-storey URM building damaged in the 2010 earthquake was performed according to the requirements of seismic design codes from the former Yugoslavia and Eurocode 8.


Buildings ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. 151 ◽  
Author(s):  
João Estêvão

The selection of a given method for the seismic vulnerability assessment of buildings is mostly dependent on the scale of the analysis. Results obtained in large-scale studies are usually less accurate than the ones obtained in small-scale studies. In this paper a study about the feasibility of using Artificial Neural Networks (ANNs) to carry out fast and accurate large-scale seismic vulnerability studies has been presented. In the proposed approach, an ANN was used to obtain a simplified capacity curve of a building typology, in order to use the N2 method to assess the structural seismic behaviour, as presented in the Annex B of the Eurocode 8. Aiming to study the accuracy of the proposed approach, two ANNs with equal architectures were trained with a different number of vectors, trying to evaluate the ANN capacity to achieve good results in domains of the problem which are not well represented by the training vectors. The case study presented in this work allowed the conclusion that the ANN precision is very dependent on the amount of data used to train the ANN and demonstrated that it is possible to use ANN to obtain simplified capacity curves for seismic assessment purposes with high precision.


Author(s):  
Timothy J. Sullivan

The peak storey drift demands that an earthquake imposes on a building can be assessed through a detailed engineering seismic assessment or recorded if a building is instrumented. However, for the rapid seismic assessment of a large number of buildings, it is desirable to have a simplified means of estimating storey drift demands. Consequently, this paper proposes a simplified means of quickly estimating storey drift demands on reinforced concrete (RC) frame buildings. Expressions for peak storey drift demand as a function of ground motion intensity are developed by utilising concepts and simplifications available from displacement-based seismic design and assessment methods. The performance of the approach is gauged by comparing predicted storey drift demands with those obtained from rigorous non-linear time-history analyses for a number of case study buildings. The promising results suggest that the approach proposed will be useful for rapidly assessing the likelihood of damage to a range of drift-sensitive elements in modern RC frame buildings.


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