Biwei Fu

Geothermal energy, a renewable energy source with enormous reserves independent of the external environment, is essential for reducing carbon emissions. Spiral fin coaxial borehole heat exchanger (SFCBHE) is vital for geothermal energy extraction. Its heat extraction performance requires further improvements for efficient performance that consider the structural sizes and installation positions of the SFCBHE and the nonlinear coupling with respect to several factors. The heat extraction performance of SFCBHE is optimized using a combination of genetic algorithm–back-propagation neural network (GA–BPNN) and the Q-learning-based marine predator algorithm (QLMPA). This study analyzes and compares the effects of geothermal energy extraction of smooth pipe TY-1, structure before optimization TY-2, and optimized structure TY-3. Following optimization with GA–BPNN–QLMPA, the heat extraction performance of TY-3 is enhanced by 30.8% and 23.6%, respectively. The temperature of maximum extraction is improved by 26.8 K and 24.0 K, respectively. The power of maximum heat extraction is increased by 148.2% and 109.5%, respectively. The optimization method can quickly and accurately determine the heat extraction performance for different structural sizes and installation positions of the SFCBHE. These findings are crucial for developing high-performance SFCBHE and efficiently using geothermal energy.

Coaxial borehole heat exchangers provide a practical method for geothermal energy extraction, but heat transfer efficiency is low. In order to address this problem, three coaxial borehole heat exchangers with vortex generators, based on the enhanced heat transfer theory, are proposed in this paper. The author compared and analyzed the heat transfer performance of three coaxial borehole heat exchangers with vortex generators and those of traditional structures, which explains why the new heat exchanger’s heat transfer mechanism is enhanced. The results demonstrated that the vortex generator can enhance the fluid flow’s turbulent kinetic energy in the coaxial heat exchanger. This generator can also improve the mixing characteristics of the fluid flow and heat transfer. The resultant increase in the inlet flow velocity can decrease the friction coefficient f, increase the Nusselt number and strengthen the coaxial sleeve. As a result, the heat exchange performance of the tubular heat exchanger will also be improved. The thread vortex generator (TVG) heat exchanger outperforms the other three heat exchangers in terms of heat exchange performance, extraction temperature and heat extraction power. The results evidenced that the TVG heat exchanger is better than the smooth tube heat exchanger. The thermal performance coefficient PEC was improved by 1.1 times, and the extraction temperature and heating power were increased by 24.06% and 11.93%, respectively. A solid theoretical foundation is provided by the extracted outcomes for designing and selecting high-efficiency coaxial borehole heat exchangers suitable for geothermal energy extraction.

Self-excited oscillation pulse jet technology is widely used to clean sediment from oil storage tanks. Its successful application is dependent on jet performance. As the cleaning requirements of the oil industry increase, it is necessary to optimise the structure of self-excited oscillation pulsed jet nozzles (SOPJNs) to optimise cleaning and energy efficiencies. In this study, the jet performance of a SOPJN is modelled and analysed based on computational fluid dynamics with consideration of a large eddy simulation and homogeneous cavitation. The modelling results are highly consistent with experimental results. The effects of the SOPJN’s inlet diameter, cavity diameter, cavity length, wall reflection angle, and inlet pressure on the jet’s peak velocity, oscillation frequency, and cavitation number were analysed. The results show that the oscillation frequency decreases with the increase of the inlet diameter d₁, cavity diameter D, cavity length L and reflection angle of wall α. Optimisation of the SOPJN inlet diameter, cavity length, and wall reflection angle produced a jet with a high peak velocity and strong cavitation. The optimal nozzle cavity diameter strengthens cavitation, while the peak velocity fluctuates as the cavity diameter increases. The peak velocity increases with the inlet pressure, while the increasing rate of the peak velocity decreases. The results of this study can be used in the design and optimisation of similar nozzle structures for improved pulse jet cleaning.