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<div>The design of bridges prior to 1994 was carried out by either the Load Factor Design (LFD) or the Allowable Stress Design (ASD) methodologies. Load rating of these bridges was primarily conducted by Load Factor Rating (LFR). In 1994, the American Association of State Highway and Transportation Officials (AASHTO) developed and encouraged the use of a probabilistic-based method titled Load and Resistance Factor Design (LRFD) for carrying out bridge design. A new methodology consistent with LRFD was also developed and adopted for conducting load rating. Thus, a new Load and Resistance Factor Rating (LRFR) was adopted by AASHTO in 2001 for load rating. Today, the bridges that were designed by the old LFD methodology are rated by both LFR and LRFR. Continued development suggests that load rating in future will be based only on LRFR, therefore LRFR is the recommended method for carrying out load rating of bridges even if they were designed by LFD. </div><div><br></div><div>The Indiana Department of Transportation (INDOT) came across some LFD designed bridges which were adequate by LFR methodology, i.e., produced a rating factor of more than 1.0, but inadequate for LRFR. The load ratings were carried out using AASHTOWare Bridge Rating (BrR) software. These bridges belonged to five different limit states: lateral torsional buckling, changes in cross-section along the member length, tight stringer spacings, girder end shear and moment over continuous piers. </div><div><br></div><div>This research study explores the inherent differences between LFR and LRFR to justify the inconsistencies in the rating values. To find an explanation for these discrepancies, load ratings of these bridges were carried out extensively on AASHTOWare BrR. To verify the results produced by BrR, a separate analysis was also conducted using Mathcad and structural analysis results from SAP2000 for comparison purposes. Finally, the study also recommends some modifications in the BrR software that can be adopted for each of the above-mentioned limit states to resolve inconsistencies found between LFR and LRFR rating values. </div><div><br></div>

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Objective condition assessment is essential to make better decisions for safety and serviceability of existing civil infrastructure systems. This study explores the condition of an existing transit guideway system that has been in service for thirty-five years. The structural system is composed of six-span continuous prestressed concrete bridge segments. The overall transit system incorporates a number of continuous bridges which share common design details, geometries, and loading conditions. The original analysis is based on certain simplifying assumptions such as rigid behavior over supports and simplified tendon/concrete/steel plate interaction. The current objective is to conduct a representative study for a more accurate understanding of the structural system and its behavior. The scope of the study is to generate finite element models (FEMs) to be used in static and dynamic parameter sensitivity studies, as well load rating and reliability analysis of the structure. The FEMs are used for eigenvalue analysis and simulations. Parameter sensitivity studies consider the effect of changing critical parameters, including material properties, prestress loss, and boundary and continuity conditions, on the static and dynamic structural response. Load ratings are developed using an American Association for State Highway Transportation Officials Load and Resistance Factor Rating (AASHTO LRFR) approach. The reliability of the structural system is evaluated based on the data obtained from various finite element models. Recommendations for experimental validation of the FEM are presented. This study is expected to provide information to make better decisions for operations, maintenance and safety requirements; to be a benchmark for future studies, to establish a procedure and methodology for structural condition assessment, and to contribute to the general research body of knowledge in condition assessment and structural health monitoring.