Weibull-Based Bridge Deterioration Models for Iowa Bridges Dimitrios Bilionis Basak Aldemir Bektas outline Introduction Data Methodology Refinement Results Example Implementation introduction Purpose Predict future condition introduction Deterioration models Deterministic models Stochastic models state-based e.g. Markov chains time-based e.g. Weibull methodology Survival analysis (failure time analysis) Occurrence and timing of events Hazard base models investigate the conditional probability that duration of time ends at a specific time t: 𝐹 𝑡 = 𝑃(𝑇 < 𝑡) Here F(t) is the c.d.f. of T The conditional probability that an event will occur between time t and t+dt, is given by the hazard function: 𝑓(𝑡) ℎ 𝑡 = 1 − 𝐹(𝑡) In other words, the hazard function gives the rate at which a duration terminates at time t methodology • the probability that a duration is greater than or equal to a specific time t is given by the survivor function: 𝑆 𝑡 = 𝑃(𝑇 ≥ 𝑡) = 1 − 𝐹 𝑡 • Weibull Survival function: 𝑆 𝑤 = exp − 𝑒𝑥𝑝 Probability density function: 𝑓 𝑤 = 𝑤−𝜇 𝜎 1 𝑤−𝜇 exp 𝜎 𝜎 exp −𝑒𝑥𝑝 𝑤−𝜇 𝜎 where w=log(t), 𝜇 = 𝑥 ′ 𝛽 , µ is the location parameter and σ is the scale parameter methodology Censoring T=a, uncensored T<b, right censored c<T<d, interval censored 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 8 7 7 7 7 7 7 7 7 7 6 6 data • NBI ratings • Deck • Superstructure • Substructure • 1983-2011 data • Process: • • • • Eliminate increases Gaps Explanatory variables Time-in-state Code Description N NOT APPLICABLE 9 EXCELLENT CONDITION 8 VERY GOOD CONDITION ( No problems noted) 7 GOOD CONDITION (Some minor problems) 6 SATISFACTORY CONDITION (Minor deterioration in structural elements) 5 FAIR CONDITION (Sound structural elements with minor section loss) 4 POOR CONDITION (Advanced section loss) 3 SERIOUS CONDITION (Affected structural elements from section loss) 2 CRITICAL CONDITION (Advanced deterioration of structural elements) 1 0 “IMMINENT” FAILURE CONDITION (Obvious movement affecting structural stability) FAILED CONDITION (Out of service) results Deck Rating 9 8 7 6 5 4 # observations Uncensored Right Censored 751* 280* 145* 166* 63* 21* 138* 314 425 239 202 145 Variables Median TIS Uncensored Right sample censored sample ADT 4 3 AGE, TR_ADT 8 6 AGE 17 5 AGE 10 4 AGE 5 5.5 4 6 Model 4.6 7.3 13 9.1 5.6 4.8 results Substructure Rating 9 8 7 6 5 4 # observations Uncensored Right Censored Variables 882* 181* 83* 172* 67* 16 AGE, ADT AGE 149 603 399 265 238 102 Median TIS Uncensored sample 5 8 16 8 4 2.5 Right censored sample 9 6 10 8 5 4 Model 6.2 7.6 13.7 7.6 5.2 2.8 results Superstructure Rating # observations Uncensored Right Censored 9 836* 236 8 133* 608 7 6 5 89 124 33 259 199 157 4 10 50 Variables AGE, ADT AGE, TR_ADT, CNRCSL DLSLCNR DMONCNR, SSMG Median TIS Uncensored sample 5 9 Right censored sample 7 5 Model 15 8 4 6 6 4 12.7 8.2 4.2 3.5 4.5 3.8 5.7 9 example Deck NBI CR=8 AGE TR_ADT 2 2 2 20 20 20 2 2 2 20 20 20 Prob Survival Median Time 636 0.5 11.08 100 0.5 12.15 9000 0.5 2.62 636 0.5 0.98 100 0.5 1.08 9000 0.5 0.23 636 0.5 11.08 100 0.5 12.15 9000 0.5 2.62 636 0.5 0.98 100 0.5 1.08 9000 0.5 0.23 example refinement Implementation Yearly time-in-state update Emphasis on models for ratings 4-7 Network level prioritization based on median time-instate estimates Thank you! Questions?
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