Experimental evaluation reveals enhanced power output and efficiency in cut-corner prism energy harvesters, suggesting improved self-powered marine monitoring.
Self-powered sensors play a vital role in intelligent marine environmental monitoring, yet existing sensors suffer from low harvesting efficiency. To enhance harvesting efficiency, this study investigates the influence of cross-sectional shape and aspect ratio on the performance of energy harvesters. Specifically, the combined effects of windward side length ( WS ) and parallel side length ( PS ) are examined under two distinct aspect ratios, H * = 3.0 and H * = 5.33, where significant variations in amplitude response characteristics were previously identified by Wang and Yao (2024a). The results show that the maximum output power monotonically increases with both WS and PS when H * = 3.0, and reaches 1.45 mW at WS = 0.4 D and PS = 0.8 D , which is 2.2 times that of the square prism. When H * = 5.33, the PS variation corresponding to the maximum output power becomes non-monotonic and is affected by WS , and has the maximum output power at WS = 0.4 D and PS = 0.6 D , which is 3.43 mW, 3.3 times that of square prism. Furthermore, the wind energy conversion efficiency for H * = 3.0 is significantly higher than that for H * = 5.33 over the range of wind speeds, with up to 1.33% for H * = 3.0 and maximum 1.17% for H * = 5.33. Meanwhile, its frequency characteristics are analyzed, and the transition process of the prism from vortex-induced vibration (VIV) to galloping during the vibration is explained. Finally, to validate its practical applicability, the feasibility of using this cut-corner prism to supply power for thermohygrometers and LEDs was verified through wind tunnel experiments. In comparison with the square prism, the cut-corner prism achieves a significant improvement in the charging rate of capacitors. Therefore, the proposed C-PWEH offers a promising solution for such applications by converting persistent offshore wind energy into electricity to power distributed wireless sensor nodes.
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Wang et al. (2026) studied this question.
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