000019433 001__ 19433
000019433 005__ 20170118182318.0
000019433 04107 $$aeng
000019433 046__ $$k2017-01-09
000019433 100__ $$aCorotis, Ross
000019433 24500 $$aUncertainty Quantification of Seismic Structural Systems: the Role of Generalized Information Theory

000019433 24630 $$n16.$$pProceedings of the 16th World Conference on Earthquake Engineering
000019433 260__ $$b
000019433 506__ $$arestricted
000019433 520__ $$2eng$$aUncertainty is inherent in the assessment and prediction of the seismic performance of structures and community infrastructure when evaluating risk, hazard mitigation and community vulnerability/resilience. Increasingly, community risk-informed infrastructure decisions need to reflect multiple issues of society, including social, political, economic and cross-disciplinary factors. This breadth introduces challenges regarding information/partial knowledge and disparate characteristics of uncertainty from different sources. Traditionally, probabilistic methods have been employed to systematically treat the uncertainty for structural reliability theory. Although these methods or probabilistic methods can address partial information in the face of uncertainty, they are not the most appropriate or powerful approaches for comprehensive incorporation of broader contexts of uncertainty reflecting expert judgement, imprecision, and possibility and evidence theories. Certainly, subjective probabilities can capture expert judgments, but the combination of conflicting opinions remain a challenge. Limitations in probability theory have often led to a failure to fully understand the implications of the broader aspects of uncertainty in human decision-making incorporating judgement and unpredictability. Methods under the umbrella of Generalized Information Theory (GIT) provide a natural framework for linguistic and imprecise data, as is typical from field evaluations both before and after an earthquake. One particular technique, fuzzy classification, has been explored recently to examine general tendencies of damage to concrete buildings from seismic events. This current paper provides some additional background and analysis of that study, and utilizing actual data based on individual building observations, seeks to uncover the existence of building damage patterns among structural, geotechnical and hazard parameters. Additional methods of generalized uncertainty, such as monotone measures, are discussed in the context of augmenting traditional probability approaches to better predict the behavior of buildings during earthquakes.

000019433 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000019433 653__ $$abuilding performance; field evaluation; fuzzy classification; risk assessment; seismic performance

000019433 7112_ $$a16th World Conference on Earthquake Engineering$$cSantiago (CL)$$d2017-01-09 / 2017-01-13$$gWCEE16
000019433 720__ $$aCorotis, Ross
000019433 8560_ $$ffischerc@itam.cas.cz
000019433 8564_ $$s221953$$uhttps://invenio.itam.cas.cz/record/19433/files/361.pdf$$yOriginal version of the author's contribution as presented on USB, paper 361.
000019433 962__ $$r16048
000019433 980__ $$aPAPER