A review of axial and radial ejectors: Geometric design, computational analysis, performance, and machine learning approaches

A review of axial and radial ejectors: Geometric design, computational analysis, performance, and machine learning approaches

This review examines the critical role of ejectors in refrigeration systems, emphasizing the need for a deeper understanding of their performance characteristics, particularly through a comparative analysis of axial and radial designs. Although previous research has explored ejector efficiency, significant knowledge gaps remain regarding the influence of geometric parameters under varying operational conditions. Key geometric factors, including primary nozzle position, area ratio, mixing chamber length, suction length, and convergence angle, are systematically analyzed for their impact on performance metrics such as entrainment ratio (ER), critical back pressure (BP), and overall efficiency. Furthermore, this review integrates advanced visualization techniques and machine learning (ML) applications, extending its scope to emerging fields such as organic Rankine cycles (ORC) and desalination. Furthermore, the study highlights advancements in ejector technology across diverse applications, demonstrating their potential to improve efficiency, reduce energy consumption, and enhance functionality in refrigeration, desalination, and ORC systems. The review also explores the role of non-equilibrium condensation in steam ejectors. Additionally, it synthesizes findings from experimental and computational studies, highlighting the trade-offs and synergies between these methodologies. Findings indicate that axial ejectors exhibit versatility and resilience, particularly in applications with surplus waste energy, achieving up to a 13% improvement in ER with optimized nozzle positioning. Conversely, radial ejectors excel in handling corrosive fluids and demonstrate enhanced performance with innovations like rotary flow designs. Ejector efficiency is significantly influenced by geometry, working fluids, and operating conditions, with isentropic efficiency typically ranging from 10% to 30% for steam ejectors and 20% to 40% for gas ejectors, and optimized designs achieving efficiencies exceeding 50% under specific conditions. Additionally, computational fluid dynamics (CFD) analyses reveal no notable differences between 2D and 3D turbulent models in supersonic ejector simulations. In summary, this review underscores the critical importance of optimizing geometric design, leveraging advanced CFD modeling, and employing visualization techniques to enhance ejector performance and broaden their applications across various industries.