Design of Experiments Study to Obtain a Robust 3D Computational Bridge Model
Ambient traffic vibration tests for the three continuous span bridge were conducted to investigate the dynamic response of the bridge in order to identify the natural frequencies and the mode shapes. Understanding the dynamic response of the bridge in its existing, unretrofitted condition is the starting point for developing confidence in the computer model because the same model will evolve from the existing bridge to the retrofitted bridge. A robust 3D computational model is developed using design of experiments (DOE) techniques. Extensive full factorial experiments are carried out to determine simultaneously the individual and interactive effects of many factors such as concrete density, concrete modulus of elasticity and steel modulus of elasticity that could affect the natural frequencies of the bridge. Data is processed to derive natural frequencies and modes shapes, which are remarkably consistent over the range of experiment conditions. ANSYS is used to complete the finite element model and analysis. In the DOE each factor is given two values. The set of allowable model factors which causes the model to match the tested natural frequencies and mode shapes are presented in this paper.
Keywords3D bridge model Robust bridge modeling Design of experiment Orthogonal arrays Bridge vibration modeling Computer aided experimental design Bridge dynamic analysis
The authors wish to thank all colleagues at AECOM including Mr. Dennis Miller and Dr. Jeremy Isenberg for their valuable comments on the paper and Mr. Bernie Hertlien and Mr. Dominik Duschlbauer whose expertise in data acquisition and processing was essential to the project.
- 1.Hedayat AS, Sloane NJA, Stufken J (1999) Orthogonal arrays: theory and applications. Springer, New YorkGoogle Scholar
- 2.Goodwin GC, Payne RL (1977) Dynamic system identification: experiment design and data analysis. Academic, New YorkGoogle Scholar
- 3.Rains EM, Sloane NJA, Stufken J (2000) The lattice of N-run orthogonal arrays. Journal of Statistical Planning and Inference, 102 (2002): 477–500Google Scholar
- 4.Boddy R, Smith G (2010) Effective experimentation for scientists and technologists. Wiley, New YorkGoogle Scholar
- 5.Lorenzen TJ, Anderson VL (1993) Design of experiments: a no-name approach. CRC Press, New YorkGoogle Scholar
- 6.Dorf R (1996) Engineering handbook. CRC Press, New YorkGoogle Scholar
- 7.Montgomery DC (2001) Design and analysis of experiments. Wiley, New YorkGoogle Scholar