Seawater desalination is one of the most widely used technologies for freshwater production; however, its high energy consumption remains a pressing global challenge. Both the development and utilization of sustainable energy sources are anticipated to mitigate the energy shortages associated with seawater desalination while also effectively addressing the environmental issues linked to fossil fuel usage. This study provides a comprehensive overview of the classification and evolution of traditional desalination technologies, emphasizing the advancements, progress, and challenges associated with integrating various sustainable energy sources into the desalination process. Then, the cost, efficiency, and energy consumption of desalination systems driven by sustainable energy are discussed, and it is found that even the most widely used reverse osmosis (RO) technology driven by fossil fuels has CO₂ emissions of 0.3–1.7 kgCO₂/m³ and the lowest cost of desalinated water as high as 0.01 USD/m³, suggesting the necessity and urgency of applying sustainable energy. A comparison of different seawater desalination systems driven by different sustainable energy sources is also carried out. The results reveal that although the seawater desalination system driven by sustainable energy has a lower efficiency and a higher cost than the traditional system, it has more potential from the perspective of environmental protection and sustainable development. Furthermore, the efficiency and cost of desalination technology driven by a single sustainable energy source is lower than that driven by multi-sustainable energy sources, while the efficiency of desalination systems driven by multi-sustainable energy is lower than that driven by hybrid energy, and its cost is higher than that of desalination systems driven by hybrid energy. Considering factors such as cost, efficiency, consumption, economic scale, and environmental impact, the integration of various seawater desalination technologies and various energy sources is still the most effective strategy to solve water shortage, the energy crisis, and environmental pollution at present and in the future.

A multiphase mathematic model based on realizable k-ε turbulence model for subsonic flow was presented to investigate the mixing flow behaviors between gas and water in the gas-liquid ejector. The simulation was carried out to predict the pumping performance of the ejector by a commercial computational code ANSYS-FLUENT 15.0. General agreements between the predicted results and experimental data validated the present theoretical model. Using the present approach, the pressure, velocity, and turbulence intensity distribution along center-line and contours of gas and liquid volume fraction profiles were predicted. It is found that the mixing process between gas and water in ejector can be divided into three periods, co-axial flow, mixing shock flow, and bubble flow. The prediction results show that the mixing shock is a dominant position in affecting the mixing flow behavior in gas-liquid ejector and the ejector’s performances.

In the perception of unmanned systems, small object detection faces numerous challenges, including small size, low resolution, dense distribution, and occlusion, leading to suboptimal perception performance. To address these issues, we propose a specialized algorithm named Unmanned-system Small-object Detection-You Only Look Once (USD-YOLO). First, we designed an innovative module called the Anchor-Free Precision Enhancer to achieve more accurate bounding box overlap measurements and provide a smarter processing mechanism, thereby improving the localization accuracy of candidate boxes for small and densely distributed objects. Second, we introduced the Spatial and Channel Reconstruction Convolution module to reduce redundancy in spatial and channel features while extracting key features of small objects. Additionally, we designed a novel C2f-Global Attention Mechanism module to expand the receptive field and capture more contextual information, optimizing the detection head’s ability to handle small and low-resolution objects. We conducted extensive experimental comparisons with state-of-the-art models on three mainstream unmanned system datasets and a real unmanned ground vehicle. The experimental results demonstrate that USD-YOLO achieves higher detection precision and faster speed. On the Citypersons dataset, compared with the baseline, USD-YOLO improves mAP50-95, mAP50, and Recall by 8.5%, 5.9%, and 2.3%, respectively. Additionally, on the Flow-Img and DOTA-v1.0 datasets, USD-YOLO improves mAP50-95 by 2.5% and 2.5%, respectively.

Micro-cooling systems are compact refrigeration systems widely applicable in microchemical analysis, biomedicine, and microelectromechanical systems (MEMS). These systems rely on the use of micro-ejectors to achieve precise, fast, and reliable flow and temperature control. However, the efficiency of micro-cooling systems is hindered by spontaneous condensation occurring downstream of the nozzle throat and within the nozzle itself, impacting the performance of the micro-ejector. A micro-scale ejector mathematical model describing wet steam flow was simulated to investigate the steam condensation phenomenon and its influence on flow, incorporating equations for liquid phase mass fraction and droplet number density transfer. The simulation results of wet vapor flow and ideal gas flow were compared and analyzed. The findings revealed that the pressure at the micro-nozzle outlet exceeded predictions based on the ideal gas assumption, while the velocity fell below it. These discrepancies indicated that condensation of the working fluid reduces the pumping capacity and the efficiency of the micro-cooling system. Furthermore, simulations explored the impact of inlet pressure and temperature conditions on spontaneous condensation within the nozzle. The results demonstrated that the properties of the working fluid directly influence transonic flow condensation, underscoring the importance of selecting appropriate working fluid parameters for nozzle design to ensure nozzle stability and optimal micro-ejector operation.