Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
In this thesis, a computational framework is proposed for optimizing the aerodynamic shape of bluff bodies used in galloping-based wind energy harvesters. The system targets low-wind speed environments, where normal wind turbines are not effective, offering a potential alternative to batteries used...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
AUC Knowledge Fountain
2026
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| Summary: | In this thesis, a computational framework is proposed for optimizing the aerodynamic shape of bluff bodies used in galloping-based wind energy harvesters. The system targets low-wind speed environments, where normal wind turbines are not effective, offering a potential alternative to batteries used for powering small electronic devices such as wireless sensors. The design relies on the galloping effect, where airflow around a bluff body induces transverse oscillations that drive an energy conversion mechanism. To generate efficient bluff body geometry, the Class-Shape Transformation (CST) method is used to define a wide range of candidate shapes with minimal design parameters. These shapes are evaluated using Direct Operating Points and Panel methods, simulations to analyze flow behavior and aerodynamic performance (lift and Drag). The synthesis of the bluff body geometry would start with CST functions which is a constructive method for building Bluff Bodies then a Genetic Algorithm (GA) is used to perform global shape optimization. This approach aims to enhance energy output by identifying bluff body shapes that promote favorable galloping behavior. Experimental runs would be run to compare the energy output of conventional bluff bodies to the CST defined ones on a piezoelectric energy harvester. |
|---|