Numerical and experimental study of the ocean thermal energy capture process utilizing metal foam-phase-change material (PCM) composites

Ocean thermal energy (OTE) is an ideal in-situ retrievable energy source for underwater profiling vehicles to maintain their long-term mission capacity. A potential method to capture OTE is to utilize the volume change in metal foam-phase-change material (PCM) composites. In this study, a numerical model for the phase change and energy conversion processes was established. The solidification and melting process were observed experimentally to validate the proposed model. Based on the numerical model, a parametric study was conducted to demonstrate the influence of the back pressure, metal foam, ambient temperature and chamber diameter on the phase change process. The results indicate that (i) increasing the back pressure reduces the temperature difference between the solid phase area and the environment, thus increasing the melting time; (ii) adding copper foam with low porosity in the phase-change chamber can effectively improve the net power density of an ocean thermal engine; (iii) the net power density is significantly affected by the hot end temperature; (iv) reducing the inner diameter of the phase-change chamber can reduce the phase transition time. However, to maximize the net power density, an appropriate inner diameter and back pressure must be selected; and (v) after optimization, the net power density is increased by 151.7 %, which reflects the value of the proposed numerical model in engineering applications.

Automated summary

In this study, a numerical model for the phase change and energy conversion processes in ocean thermal energy (OTE) devices was established and validated through experimental observations. A parametric study was conducted, and the results showed that increasing the back pressure, adding copper foam with low porosity, and optimizing the inner diameter and back pressure can effectively improve the net power density of OTE devices. The proposed numerical model demonstrated a significant increase of 151.7% in net power density after optimization, indicating its value in engineering applications.