A general super-resolution reconstruction strategy was proposed for turbulent velocity fields using a generative adversarial network-based artificial intelligence framework. Two advanced neural networks, i.e., super-resolution generative adversarial network (SRGAN) and enhanced-SRGAN (ESRGAN), were first applied in fluid mechanics to augment the spatial resolution of turbulent flow. As a validation, the flow around a single-cylinder and a more complicated wake flow behind two side-by-side cylinders were experimentally measured using particle image velocimetry. The spatial resolution of the coarse flow field can be successfully augmented by 4² and 8² times with remarkable accuracy. The reconstruction performances of SRGAN and ESRGAN were comprehensively investigated and compared, including an analysis of the recovered instantaneous flow field, statistical flow quantities, and spatial correlations. The results convincingly demonstrated that both models can reconstruct the high-spatial-resolution flow field accurately even in an intricate flow configuration, and ESRGAN can provide a better reconstruction result than SRGAN in the mean and fluctuation flow field.

This paper focuses on the time-resolved turbulent flow reconstruction from discrete point measurements and non-time-resolved (non-TR) particle image velocimetry (PIV) measurements using an artificial intelligence framework based on long short-term memory (LSTM). To this end, an LSTM-based proper orthogonal decomposition (POD) model is proposed to establish the relationship between velocity signals and time-varying POD coefficients obtained from non-TR-PIV measurements. An inverted flag flow at Re = 6200 was experimentally measured using TR-PIV at a sampling rate of 2000 Hz for the construction of training and testing datasets and for validation. Two different time-step configurations were employed to investigate the robustness and learning ability of the LSTM-based POD model: a single-time-step structure and a multi-time-step structure. The results demonstrate that the LSTM-based POD model has great potential for time-series reconstruction since it can successfully recover the temporal revolution of POD coefficients with remarkable accuracy, even in high-order POD modes. The time-resolved flow fields can be reconstructed well using coefficients obtained from the proposed model. In addition, a relative error reconstruction analysis was conducted to compare the performance of different time-step configurations further, and the results demonstrated that the POD model with multi-time-step structure provided better reconstruction of the flow fields.

A small-scale solar organic Rankine cycle (ORC) is a promising renewable energy-driven power generation technology that can be used in the rural areas of developing countries. A prototype was developed and tested for its performance characteristics under a range of solar source temperatures. The solar ORC system power output was calculated based on the thermal and solar collector efficiency. The maximum solar power output was observed in April. The solar ORC unit power output ranged from 0.4 kW to 1.38 kW during the year. The highest power output was obtained when the expander inlet pressure was 13 bar and the solar source temperature was 120 °C. The area of the collector for the investigation was calculated based on the meteorological conditions of Busan City (South Korea). In the second part, economic and thermoeconomic analyses were carried out to determine the cost of energy per kWh from the solar ORC. The selling price of electricity generation was found to be $0.68/kWh and $0.39/kWh for the prototype and low cost solar ORC, respectively. The sensitivity analysis was carried out in order to find the influencing economic parameters for the change in NPV. Finally, the sustainability index was calculated to assess the sustainable development of the solar ORC system.

A new type of horizontal axis wind turbine adopting the Archimedes spiral blade is introduced for urban-use. Based on the angular momentum conservation law, the design formula for the blade was derived using a variety of shape factors. The aerodynamic characteristics and performance of the designed Archimedes wind turbine were examined using computational fluid dynamics (CFD) simulations. The CFD simulations showed that the new type of wind turbine produced a power coefficient (C_p) of approximately 0.25, which is relatively high compared to other types of urban-usage wind turbines. To validate the CFD results, experimental studies were carried out using a scaled-down model. The instantaneous velocity fields were measured using the two-dimensional particle image velocimetry (PIV) method in the near field of the blade. The PIV measurements revealed the presence of dominant vortical structures downstream the hub and near the blade tip. The interaction between the wake flow at the rotor downstream and the induced velocity due to the tip vortices were strongly affected by the wind speed and resulting rotational speed of the blade. The mean velocity profiles were compared with those predicted by the steady state and unsteady state CFD simulations. The unsteady CFD simulation agreed better with those of the PIV experiments than the steady state CFD simulations.

This paper introduces the concept of installing a small-scale organic Rankine cycle system for the generation of electricity in remote areas of developing countries. The Organic Rankine Cycle Systems (ORC) system uses a commercial magnetically-coupled scroll expander, plate type heat exchangers and plunger type working fluid feed pump. The heat source for the ORC system can be solar energy. A series of laboratory tests were conducted to confirm the cycle efficiency and expander power output of the system. Using the actual system data, the exergy destruction on the system components and exergy efficiency were assessed. Furthermore, the results of the variations of system energy and exergy efficiencies with different operating parameters, such as the evaporating and condensing pressures, degree of superheating, dead state temperature, expander inlet temperature and pressure ratio were illustrated. The system exhibited acceptable operational characteristics with good performance under a wide range of conditions. A heat source temperature of 121 °C is expected to deliver a power output of approximately 1.4 kW. In addition, the system cost analysis and financing mechanisms for the installation of the ORC system were discussed.