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SUMMARY:Real-time Statistical Bridge Condition Assessment using Girder Dis
 tribution Factors
DTSTART:20160711T110000
DTEND:20160711T120000
DTSTAMP:20260411T124405Z
UID:aed024b1aed07f02cb3b7c999a63207a37b41bdf6da74a85c0f61904
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Masoud Sanayei\nDepartment of Civil and Environmental En
 gineering\, Tufts University\n200 College Avenue\, Medford\, MA  02155\, 
 USA\nA hypothesis-testing framework is introduced for bridge condition ass
 essment\, which enables a rigorous\, decision-oriented approach for detect
 ion of bridge damage when it exists. A bridge damage detection hypothesis 
 test is developed using bridge girder distribution factors (GDF) under ope
 rational\, output-only strain monitoring. GDFs are calculated from measure
 d strain data collected during traffic events at the Powder Mill Bridge in
  Barre\, Massachusetts. A sample of GDFs is drawn to establish a baseline 
 over the course of one week\, representing the probabilistic behavior of a
  healthy bridge under normal operating conditions. A new sample can be com
 pared with the baseline at the end of each day\, providing a timely and ef
 fective operational damage detection method. A calibrated finite element m
 odel is used to simulate damaged bridge GDF samples under four damage scen
 arios. The damaged bridge GDF samples are compared with the healthy baseli
 ne sample using the rank-sum test\, and the results are employed to develo
 p a damage index capable of alerting bridge owners of potential damage. A 
 simple bootstrap resampling scheme is used to evaluate the probability of 
 failing to issue an alert when the bridge is damaged (Type I error)\, as w
 ell as the likelihood of issuing a false alarm (Type II error). A three-di
 mensional statistical bridge signature is developed to aid damage localiza
 tion and assessment. Nonparametric prediction intervals corresponding to a
  baseline signature are generated using the bootstrap method\, creating an
  envelope of possible baseline bridge signatures. When a bridge signature 
 falls outside the baseline bridge signature envelope\, damage is detected.
  Damage was successfully identified for all four artificial damage cases c
 onsidered. The overall damage detection method is designed to alert bridge
  owners when damage is detected and to provide a probabilistic tool to aid
  damage assessment and localization while controlling for both Type I and 
 Type II errors.
LOCATION:GC G1 515
STATUS:CONFIRMED
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