Published November 19, 2020 | Version Submitted
Discussion Paper Open

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.

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Submitted - 2011.09609.pdf

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Additional details

Identifiers

Eprint ID
109397
Resolver ID
CaltechAUTHORS:20210604-142548826

Funding

NSF
CBET-2019712
Center for Autonomous Systems and Technologies

Dates

Created
2021-06-07
Created from EPrint's datestamp field
Updated
2023-06-02
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Caltech Custom Metadata

Caltech groups
Astronomy Department, GALCIT, Center for Autonomous Systems and Technologies (CAST)