2016Journal of Infrastructure SystemsRequires access

Bridge Weigh-in-Motion Algorithms Based on the Field Calibrated Simulation Model

Zhisong Zhao, Nasim Uddin, Eugene J. OBrien

Open publisher page 12 citations

Abstract

Most of the commercially available bridge weigh-in-motion (B-WIM) systems are based on an algorithm developed by Moses. The performance of this method was generally acceptable for estimating gross vehicle weight (GVW) but can be inadequate for estimating single axle load. Two alternative algorithms for the identification of vehicle axle loads are presented in this paper based on field verified simulation model using the semirigid frame system with multiple simplified span bridges. Both algorithms are based on the simulation of the entire bridge, representing realistic boundary conditions, bridge geometry properties, and field environment from field B-WIM testing results. The first alternative algorithm includes adjusting the experimental weight-in-motion (WIM) moment of the testing span from the simulation model to perform vehicle weight calculation. The second algorithm includes applying the simulated influence line from the simulation model to calculate the vehicle weight. Both approaches demonstrate significant improvements on the accuracy of vehicle weight for a bridge on the U.S. Highway 78 (US-78) by B-WIM testing.

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What this paper is about

Most of the commercially available bridge weigh-in-motion (B-WIM) systems are based on an algorithm developed by Moses. The performance of this method was generally acceptable for estimating gross vehicle weight (GVW) but can be inadequate for estimating single axle load. Two alternative algorithms for the identification of vehicle axle loads are presented in this paper based on field verified simulation model using the semirigid frame system with multiple simplified span bridges. Both algorithms are based on the simulation of the entire bridge, representing realistic boundary conditions, bridge geometry properties, and field environment from field B-WIM testing results. The first alternative algorithm includes adjusting the experimental weight-in-motion (WIM) moment of the testing span from the simulation model to perform vehicle weight calculation. The second algorithm includes applying the simulated influence line from the simulation model to calculate the vehicle weight. Both approaches demonstrate significant improvements on the accuracy of vehicle weight for a bridge on the U.S. Highway 78 (US-78) by B-WIM testing.

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Available abstract

Most of the commercially available bridge weigh-in-motion (B-WIM) systems are based on an algorithm developed by Moses. The performance of this method was generally acceptable for estimating gross vehicle weight (GVW) but can be inadequate for estimating single axle load. Two alternative algorithms for the identification of vehicle axle loads are presented in this paper based on field verified simulation model using the semirigid frame system with multiple simplified span bridges. Both algorithms are based on the simulation of the entire bridge, representing realistic boundary conditions, bridge geometry properties, and field environment from field B-WIM testing results. The first alternative algorithm includes adjusting the experimental weight-in-motion (WIM) moment of the testing span from the simulation model to perform vehicle weight calculation. The second algorithm includes applying the simulated influence line from the simulation model to calculate the vehicle weight. Both approaches demonstrate significant improvements on the accuracy of vehicle weight for a bridge on the U.S. Highway 78 (US-78) by B-WIM testing.

Key concepts: Weigh in motion, Bridge (graph theory), Influence line, Algorithm, Engineering, Axle, Field (mathematics), Structural engineering

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