Modeling Traveling Waves Using Mode Superposition
Analysis of the data from two Vortex-Induced Vibration (VIV) experiments conducted in the Gulf Stream on a 500-foot-long, 1.43 inches diameter, flexible, tension dominated riser model revealed that the response is predominantly characterized by the presence of traveling waves. It was also observed t...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
American Society of Mechanical Engineers
2017
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| Online Access: | http://hdl.handle.net/1721.1/109293 https://orcid.org/0000-0002-9828-9484 https://orcid.org/0000-0002-6144-660X |
| Summary: | Analysis of the data from two Vortex-Induced Vibration (VIV) experiments conducted in the Gulf Stream on a 500-foot-long, 1.43 inches diameter, flexible, tension dominated riser model revealed that the response is predominantly characterized by the presence of traveling waves. It was also observed that the location of the VIV excitation region (power-in) affects the characteristics of the response. The conventional method of modeling the excitation force as a standing wave was found inadequate to predict the location of the peak measured response accurately, especially in the cases where the excitation region is close to a boundary (the ends of the riser model). A modified excitation force model consisting of a combination of standing and traveling wave excitation regions is demonstrated to predict the location of the peak response more accurately. This work presents the idea of modifying the VIV excitation model to include traveling wave characteristics and using mode superposition method for computing the response to this modified force. Examples of the implementation of this method are shown for the two distinct cases of the location of the power-in region — the power-in region adjacent to the boundary and the power-in region away from the boundary. Depending on the location of the power-in region, different proportions of standing and traveling wave excitations are used to yield predicted responses that match the measured response characteristics. |
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