An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks

Author

Lee, Sang-Youl

Source

Mathematical Problems in Engineering

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-09-15

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Civil Engineering

Abstract EN

This study deals with an inverse method to identify moving loads on bridge decks using the finite element method (FEM) and a coupled genetic algorithm (c-GA).

We developed the inverse technique using a coupled genetic algorithm that can make global solution searches possible as opposed to classical gradient-based optimization techniques.

The technique described in this paper allows us to not only detect the weight of moving vehicles but also find their moving velocities.

To demonstrate the feasibility of the method, the algorithm is applied to a bridge deck model with beam elements.

In addition, 1D and 3D finite element models are simulated to study the influence of measurement errors and model uncertainty between numerical and real structures.

The results demonstrate the excellence of the method from the standpoints of computation efficiency and avoidance of premature convergence.

American Psychological Association (APA)

Lee, Sang-Youl. 2014. An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1044280

Modern Language Association (MLA)

Lee, Sang-Youl. An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks. Mathematical Problems in Engineering No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1044280

American Medical Association (AMA)

Lee, Sang-Youl. An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1044280

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1044280