Chapter
Apr 17, 2018
Structures Congress 2018

Automating Refined Load Ratings for Girder Bridges

Publication: Structures Congress 2018: Bridges, Transportation Structures, and Nonbuilding Structures

ABSTRACT

Current industry trends in bridge load ratings acknowledge both the benefits of refined ratings and the added expense. Refined ratings are used sparingly in part because of the added level of resources needed produce and evaluate analytical models. This additional effort consists of critical broad engineering decisions such as selecting a modeling approach as well as more specific and laborious tasks like manipulating a finite element analysis program via a graphical user interface (GUI) to build and analyze a model. By separating the broad engineering decisions and passing them as input into a series of automated algorithms that carry out model building, analysis, and results extraction, the refined rating process can be made much more efficient and consistent. The biggest challenge of automating this process is balancing the flexibility and robustness of the process with the amount of engineering effort required to develop the necessary input. The objective of this paper is to demonstrate the value that an automated approach can bring to a refined load rating. Automation also makes a process completely repeatable and more transparent than traditional refined analysis. This paper discusses the refined rating process, as well as the challenges and benefits of automating this process for multi-girder bridges.

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REFERENCES

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Published In

Go to Structures Congress 2018
Structures Congress 2018: Bridges, Transportation Structures, and Nonbuilding Structures
Pages: 261 - 274
Editor: James Gregory Soules, CB&I
ISBN (Online): 978-0-7844-8133-2

History

Published online: Apr 17, 2018
Published in print: Apr 17, 2018

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Authors

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Thomas F. Golecki, M.ASCE [email protected]
P.E., S.E.
Intelligent Infrastructure Systems, 1900 Market St., Suite 300, Philadelphia, PA 19103. E-mail: [email protected]
Jeffrey S. Weidner, Ph.D., M.ASCE [email protected]
Univ. of Texas at El Paso, 500 W. Univ. Ave, El Paso, TX 79968. E-mail: [email protected]

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