Vibration energy harvesting (VeH) techniques by means of intentionally designed mechanisms have been used in the last decade for frequency bandwidth improvement under excitation for adequately high-vibration amplitudes. Oil, gas, and water are vital resources that are usually transported by extensive pipe networks. Therefore, wireless self-powered sensors are a sustainable choice to monitor in-pipe system applications. The mechanism, which is intended for water pipes with diameters of 2–5 inches, contains a piezoelectric beam assembled to the oscillating body. A novel U-shaped geometry of an underwater energy harvester has been designed and implemented. Then, the results have been compared with the traditional circular cylinder shape. At first, a numerical study has been carried at Reynolds numbers Re = 3000, 6000, 9000, and 12,000 in order to capture as much as kinetic energy from the water flow. Consequently, unsteady Reynolds Averaged Navier–Stokes (URANS)-based simulations are carried out to investigate the dynamic forces under different conditions. In addition, an Adaptive Differential Evolution (JADE) multivariable optimization algorithm has been implemented for the optimal design of the harvester and the maximization of the power extracted from it. The results show that the U-shaped geometry can extract more power from the kinetic energy of the fluid than the traditional circular cylinder harvester under the same conditions.
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Aramendia, I.; Saenz-Aguirre, A.; Boyano, A.; Fernandez-Gamiz, U.; Zulueta, E. Oscillating U-Shaped Body for Underwater Piezoelectric Energy Harvester Power Optimization. Micromachines2019, 10, 737.
Aramendia I, Saenz-Aguirre A, Boyano A, Fernandez-Gamiz U, Zulueta E. Oscillating U-Shaped Body for Underwater Piezoelectric Energy Harvester Power Optimization. Micromachines. 2019; 10(11):737.
Aramendia, Iñigo; Saenz-Aguirre, Aitor; Boyano, Ana; Fernandez-Gamiz, Unai; Zulueta, Ekaitz. 2019. "Oscillating U-Shaped Body for Underwater Piezoelectric Energy Harvester Power Optimization." Micromachines 10, no. 11: 737.