This study aims to investigate how high-temperature-induced changes in fluid properties affect the internal flow, energy dissipation and pressure pulsation in centrifugal pumps. It develops a temperature-density coupled correction model based on the Tammann equation of state to improve prediction accuracy under high-temperature conditions. The research systematically analyzes the resulting shifts in unsteady flow behavior, entropy production distribution and excitation mechanisms. The ultimate goal is to provide a theoretical foundation and engineering reference for enhancing the energy efficiency and vibration control of centrifugal pumps operating with high-temperature media.
This study employs a combined numerical and experimental approach. A temperature-density coupled correction model is developed based on the Tammann equation of state. Numerical simulations are conducted using the SST k-ω turbulence model on a validated mesh. An experimental test bench is built to validate the simulated pump performance. The analysis utilizes entropy production theory to quantify and localize energy losses and monitors pressure pulsations at specific points to investigate flow-induced excitation mechanisms under different operating conditions.
High-temperature, low-density media suppress large-scale flow separation within the impeller, significantly decreasing total entropy production and shifting energy dissipation from a concentrated to a distributed pattern. Flow stability improves as separation vortices are eliminated. The dominant pressure pulsation frequency shifts from a low-frequency axial mode to the blade passage frequency and its harmonics. Correspondingly, the primary excitation mechanism transitions from rotation-induced stall to dynamic-static interference and small-scale vortex shedding.
The study's limitations include the numerical model's omission of tip clearance, wall roughness, mechanical and volumetric losses, contributing to residual prediction errors. Experimental validation is based on a single pump handling a specific medium, limiting generalizability.
The study enables more accurate performance prediction for centrifugal pumps handling high-temperature media, directly aiding in optimized hydraulic design and reducing safety margins. It demonstrates that operating with high-temperature, low-density fluids inherently reduces large-scale flow instabilities and shifts energy loss patterns, guiding the selection of operating conditions for improved system efficiency. The identified shift in dominant pressure pulsation frequency and excitation mechanism provides critical insights for mitigating vibration and fatigue, informing the design of pump casings, support structures and connected piping in thermal systems for enhanced reliability in industries like chemical processing and power generation.
This research supports the global transition toward sustainable energy by enhancing the efficiency of critical thermal systems. Improving centrifugal pump performance reduces industrial energy consumption and associated carbon emissions. Increased operational reliability and safety in chemical plants and power stations contribute to environmental protection and public safety. By providing a pathway to design more robust and efficient industrial equipment, the study aids in reducing lifecycle costs and resource waste, ultimately supporting cleaner industrial processes and more stable energy infrastructure for society.
The study's originality lies in establishing a direct mechanistic link between high-temperature property changes and flow-energy-vibration coupling in centrifugal pumps, a gap in prior ambient-temperature research. It introduces a validated temperature-density coupled correction model based on the Tammann equation, moving beyond constant-property assumptions. Its value is providing a quantitative framework that explains how property shifts suppress large-scale separation, redistribute entropy production and fundamentally alter pressure pulsation dominance from stall to blade-frequency excitation. This enables accurate performance prediction and targeted design for efficiency and reliability in thermal systems.
