000013668 001__ 13668
000013668 005__ 20161114170127.0
000013668 04107 $$aeng
000013668 046__ $$k2011-05-25
000013668 100__ $$aElenas, A.
000013668 24500 $$aClassification of Seismic Damages in Buildings Using Fuzzy Logic Procedures

000013668 24630 $$n3.$$pComputational Methods in Structural Dynamics and Earhquake Engineering
000013668 260__ $$bNational Technical University of Athens, 2011
000013668 506__ $$arestricted
000013668 520__ $$2eng$$aIt is well known that damage observations on buildings after severe earthquakes exhibit interdependence with the seismic intensity parameters, like peak ground acceleration, response-spectra, Arias intensity and strong motion duration. Numerical elaboration of structural systems quantified the interrelation degree by correlation coefficients. In addition, the seismic response of buildings is directly depended on the ground excitation. Consequently, the seismic response of buildings evaluated by a numerical analysis is directly depended on the used accelerogram and its intensity parameters. Among the several response quantities, the focus is on the overall damage indices (DIs) because they summarize the post-earthquake status of buildings on a single value, which can be easily handled. The Maximum Inter-Storey Drift Ratio (MISDR) and the damage index as defined by Park/Ang (DIG,PA) characterize effectively the structural damages caused to buildings during earthquakes. Intervals for the values of the damage indices are defined to classify the damage degree in low, medium, large and total. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the classification of seismic damages. The structural damage is presented by means of the two previously mentioned damage indices (MISDR and DIG,PA). The seismic excitations are simulated by a set of artificial accelerograms and their intensity is described by a set of wellknown seismic parameters. The proposed system was trained (using nonlinear dynamic analyses) and tested on an eighth-story reinforced concrete structure. The numerical results have shown that the fuzzy technique that is implemented in the proposed method contributes to the development of an efficient blind prediction of the seismic damage potential that an accelerogram possesses. The recognition scheme achieves correct classification rates over 90%.

000013668 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000013668 653__ $$aSeismic Parameters, Damage Indices, Seismic Ground Motion, Damage Potential, Reinforced Concrete, Adaptive Neuro-Fuzzy Inference System.

000013668 7112_ $$aCOMPDYN 2011 - 3rd International Thematic Conference$$cIsland of Corfu (GR)$$d2011-05-25 / 2011-05-28$$gCOMPDYN2011
000013668 720__ $$aElenas, A.$$iVrochidou, E.$$iAlvanitopoulos, P.$$iAndreadis, I.
000013668 8560_ $$ffischerc@itam.cas.cz
000013668 8564_ $$s334538$$uhttps://invenio.itam.cas.cz/record/13668/files/472.pdf$$yOriginal version of the author's contribution as presented on CD, section: MS 11 Fuzzy Methods in Computational Dynamics.
000013668 962__ $$r13401
000013668 980__ $$aPAPER