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contributor authorAnanta Sinha
contributor authorMi G. Chorzepa
contributor authorJidong J. Yang
contributor authorS. Sonny Kim
contributor authorStephan A. Durham
date accessioned2022-05-07T20:50:34Z
date available2022-05-07T20:50:34Z
date issued2022-02-03
identifier other(ASCE)CF.1943-5509.0001709.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4282982
description abstractTemporal discounting is a cognitive behavior with important implications in preparing for high-impact and low-probability events. Evaluation of live-load effects has a great influence on the design, maintenance, and rehabilitation of bridges in the US. This study employed statistical methods to evaluate high-impact and low-probability bridge overloading events and proposes a cognitive approach to evaluating live-load factors because stakeholders discount the probability of observing overweight vehicles based on Kahneman and Tversky’s prospect theory. This paper quantified the likelihood of observing extreme weights on bridges from 10 Weigh-In-Motion sites in Georgia using the extreme value theory. A sensitivity analysis showed how predicted live-load factors vary in response to the choice of a threshold or an extreme percentile. Subsequently, the process of predicting maximum live-load factors was validated using another state’s data. It was concluded that a live-load factor is affected by a shape parameter and is numerically quantifiable for each site, and that near-term live-load factors are more salient for preparing bridges for high-risk, low-probability overloading events.
publisherASCE
titleCognitive Approaches to Hyperbolic Discounting of High-Impact Low-Probability Bridge Overload Events and Live-Load Factors
typeJournal Paper
journal volume36
journal issue2
journal titleJournal of Performance of Constructed Facilities
identifier doi10.1061/(ASCE)CF.1943-5509.0001709
journal fristpage04022009
journal lastpage04022009-11
page11
treeJournal of Performance of Constructed Facilities:;2022:;Volume ( 036 ):;issue: 002
contenttypeFulltext


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