Optimal Assessment Of Weigh-In-Motion Data For Structural Reliability Based Rating Of Bridge Superstructures

The first objectives of this research are to propose a simplified procedure to reduce the vehicle dataset need to be considered for load rating of bridge superstructures. The second objective is to explore the effectiveness of Reliability Based Design Optimization (RBDO) to develop a State-specific rating load model for a set of bridge superstructures. Finally, an alternative novel approach to develop rating models as effective as an ideal RBDO solution is proposed. The proposed solutions can substantially reduce the computational effort while not compromising the level of accuracy

Load Truncation Approach for Development of Live Load Factors for Bridge Rating

Various local governments have developed state-specific vehicular live load factors for bridge rating. However, a significant computational demand is often associated with such an effort. This is due to the large size of the weigh-in-motion (WIM) databases frequently used in the procedure. In this study, a method is proposed that can significantly reduce the computational cost of the analysis, while still maintaining reasonable accuracy. The proposed approach develops approximate live load random variable statistics by truncating the WIM database based on gross vehicle weight, then a complete reliability analysis is conducted to develop new live load factors that meet AASHTO-specified rating standards. Two WIM databases, one based on typically legal vehicles and another based on unusually heavy vehicles, are considered for evaluation. Results of the proposed approach are compared to an exact assessment as well as to a simplified method suggested by AASHTO. It was found that the proposed approach may provide very large reductions in computational cost with minimal loss of accuracy, whereas significant inaccuracies were found with the existing simplified approach

Development of Traffic Live Load Models for Bridge Superstructure Rating with RBDO and Best Selection Approach

Reliability-based design optimization (RBDO) is frequently used to determine optimal structural geometry and material characteristics that can best meet performance goals while considering uncertainties. In this study, the effectiveness of RBDO to develop a rating load model for a set of bridge structures is explored, as well as the use of an alternate Best Selection procedure that requires substantially less computational effort. The specific problem investigated is the development of a vehicular load model for use in bridge rating, where the objective of the optimization is to minimize the variation in reliability index across different girder types and bridge geometries. Moment and shear limit states are considered, where girder resistance and load random variables are included in the reliability analysis. It was found that the proposed Best Selection approach could be used to develop rating model as nearly as effective as an ideal RBDO solution but with significantly less computational effort. Both approaches significantly reduced the range and coefficient of variation of reliability index among the bridge cases considered

Dynamic Distributor Routing in Supply Chain Networks with Stochastic Travel Time

Minimizing the distribution time in supply chain networks is critical. By minimizing the total time of distribution in the network we can reduce the cost as well as decrease the product wastage for goods with fast approaching expiration date such as dairy products. In real-world the traveling time in supply chain network is not deterministic most of the time and uncertainties in the form of randomness are not avoidable. For this reason, for finding the optimal path of distributor vehicles in the distribution network that has the lowest travel time, a probabilistic dynamic optimization model has been used in this study and the results of a numerical example are discussed

Long-term Durability of FRP Bond in the Midwest United States for Externally-Strengthened Bridge Components

In this study, the bond strength of a typical FRP system subjected to long-term natural weathering in the Midwest United States is experimentally investigated, and the rate of degradation is estimated. To do this, the bond strength of an FRP system exposed to over fifteen years of weathering is determined with pull-off testing, and a relationship between strength reduction and exposure time is developed using regression analysis. For unweathered specimens, it was found that the attachment strength of the FRP system was governed by the concrete substrate, while for weathered specimens, the FRP system could detach by either a failure of the substrate, at the FRP/concrete interface, or FRP failure. It was found that a logarithmic curve best matches bond deterioration