Deterioration Forecasting in Flexible Pavements Due to Floods and Snow Storms

Shahini Shamsabadi, Salar ; Hashemi Tari, Yasamin Sadat ; Birken, Ralf ; Wang, Ming

HAL, hal-01021211 / Harvested from HAL

Résumé

Roadway agencies and state DOTs utilize Pavement Management Systems (PMS) to implement cost-effective maintenance strategies. A reliable yet easily applicable model for deterioration process of pavements is an integral part of any Pavement Management System. As pavement condition grows to be one of the crucial problems facing our nation, the reliability of these deterioration prediction models becomes more important. While numerous endevours have been made to capture the effect of the environment, load and pavementÕs structure on pavement failures, only few have realized the impact of severe events such as Snow Storms and Floods on road infrastructures. First, this impact was quantified using Long Term Pavement Performance (LTPP) and National Oceanic and Atmospheric Administration (NOAA) databases with a dependable natural deterioration model. Then, a regression-based statistical approach has been undertaken to model the effect of snow storms and floods on pavement serviceablilites based on the severity of the events and condition of the pavement prior to these event. Final models rendered more than 90% correlation with the quantified impact values of snow storms and floods.

Détail

Publié le : 2014-07-08
Classification:  Data fusion,  Multiphysics,  Prediction and Estimation by Calcul,  [PHYS.MECA]Physics [physics]/Mechanics [physics],  [SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph],  [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST],  [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]