EAGER: Uncertainty Quantification of Structural Systems: Generalized Information Theory

点击翻译按钮获取中文摘要

Uncertainty is inherent in the assessment and prediction of the performance of structures and community infrastructure when evaluating risk, hazard mitigation and vulnerability/resiliency. Structural engineering needs to reflect multi-disciplinary societal issues, including social, political and economic, which introduce partial knowledge and disparate characteristics of uncertainty. While traditional probabilistic methods to treat the uncertainty can address partial and dissimilar information, they are not the most appropriate for comprehensive incorporation of broader contexts reflecting sources such as expert judgement and imprecision. This EArly-concept Grant for Exploratory Research (EAGER) project undertakes exploratory research on the broader aspects of uncertainty approaches to structural engineering safety, incorporating multi-attribute aspects of judgement and unpredictability in human decision-making. The research introduces varied sources of uncertainty into structural design, melding this with community issues that assess the value of the structure to economic, environmental and social/political sustainability. Quantitative and linguistic uncertainties are incorporated under a comprehensive design philosophy capable of handling vagueness, and ambiguity. These broadened approaches to structural engineering and community performance will lead to great benefits to society through enhancements of the built environment. The primary objective of this project is the development of methods under the umbrella of Generalized Information Theory that expand traditional probabilistic approaches to structural and community safety, enhancing the treatment of uncertainty by incorporating notions of ignorance, interactivity, and linguistic information. The scope of the project includes generalization of probability theory with uncertainty measures based on monotone theory and incorporating linguistic vagueness, ambiguity, evidence concepts (belief and plausibility), conflicting expert judgement, imprecision, partial knowledge, confidence, and subjective possibility. An initial application in this exploratory project will be for earthquake damage estimation and vulnerability assessment. With actual community data, fuzzy pattern recognition will be used to investigate the existence of building damage patterns and potential seismic vulnerability prediction.