Wind speed inference from environmental flow-structure interactions
Abstract
This study aims to leverage the relationship between fluid dynamic loading and resulting structural deformation to infer the incident flow speed from measurements of time-dependent structure kinematics. Wind tunnel studies are performed on cantilevered cylinders and trees. Tip deflections of the wind-loaded structures are captured in time series data, and a physical model of the relationship between force and deflection is applied to calculate the instantaneous wind speed normalized with respect to a known reference wind speed. Wind speeds inferred from visual measurements showed consistent agreement with ground truth anemometer measurements for different cylinder and tree configurations. These results suggest an approach for non-intrusive, quantitative flow velocimetry that eliminates the need to directly visualize or instrument the flow itself.
Additional Information
The authors would like to thank Peter Gunnarson, Berthy Feng, and Emily de Jong for their assistance in running wind tunnel experiments, and Matthew Fu for his thoughtful comments and discussion. This work was supported by the National Science Foundation (grant CBET-2019712), and by the Center for Autonomous Systems and Technologies at Caltech. The authors report no conflict of interest. Data Availability Statement. The data discussed in this work will be made available at the Stanford Digital Repository at https://purl.stanford.edu/tp480sx4819. Author Contributions. Conceptualization: JLC; KLB; JOD. Methodology: JLC; JOD. Investigation: JLC. Software: JLC. Data analysis: JLC; JOD. Funding acquisition: KLB; JOD. Supplementary Material. Additional information can be found in the supplementary material.Attached Files
Submitted - 2011.09609.pdf
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Additional details
- Eprint ID
- 109397
- Resolver ID
- CaltechAUTHORS:20210604-142548826
- NSF
- CBET-2019712
- Center for Autonomous Systems and Technologies
- Created
-
2021-06-07Created from EPrint's datestamp field
- Updated
-
2023-06-02Created from EPrint's last_modified field
- Caltech groups
- Astronomy Department, GALCIT, Center for Autonomous Systems and Technologies (CAST)