High-pressure hydrogen storage is essential for maximizing hydrogen potential as a clean energy carrier. Achieving pressures up to 700 bar is necessary to increase its volumetric energy density and reciprocating compressors are favored for their ability to handle high flow rates. Furthermore, maintaining high purity of compressed gas necessitates the use of oil-free machines. Given the unique challenges posed by low molecular weight gas, high pressures, and the use of dry seals, accurately estimating leakage flows and piston ring wear in compressor cylinders is vital. This paper presents a gas flow network model aimed at predicting wear and leakage of dry-running piston seals for high-pressure hydrogen storage. The model accounts for the dynamics of the seals and the fluid dynamics of gas leaking through the narrow clearances between the moving piston and the cylinder liner, therefore considering the interaction between gas flow and seal displacement within piston grooves. Each volume of the network constitutes a 0-D system where mass and energy conservation equations are solved. Given the complexity of both physical phenomena and cavity geometry, the choice of 0-D systems represents a suitable trade-off between calculation speed and result accuracy. This paper proposes a numerical model designed to evaluate the thermodynamic properties of the volumes and to predict the pressure drop distribution across piston seals. It also assesses friction power generated by dry seals and identifies rings vulnerable to premature wear. Moreover, the model shows that optimizing the geometrical design of the seals minimizes the gas blow-by, enhancing compression efficiency and extending the machine lifespan.
A Gas Flow Network Model for Predicting Ring Dynamics and Leakage in Dry-Running Pistons Seals for High-Pressure Hydrogen Storage / Sassoli, Andrea; Raspanti, Sandro; Romani, Luca; Capanni, Alessio; Bassani, Simone; Ferrara, Giovanni; Balduzzi, Francesco. - ELETTRONICO. - 2:(2024), pp. 0-0. ( 69th ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, GT 2024 gbr 2024) [10.1115/gt2024-126694].
A Gas Flow Network Model for Predicting Ring Dynamics and Leakage in Dry-Running Pistons Seals for High-Pressure Hydrogen Storage
Sassoli, Andrea;Raspanti, Sandro;Romani, Luca;Ferrara, Giovanni;Balduzzi, Francesco
2024
Abstract
High-pressure hydrogen storage is essential for maximizing hydrogen potential as a clean energy carrier. Achieving pressures up to 700 bar is necessary to increase its volumetric energy density and reciprocating compressors are favored for their ability to handle high flow rates. Furthermore, maintaining high purity of compressed gas necessitates the use of oil-free machines. Given the unique challenges posed by low molecular weight gas, high pressures, and the use of dry seals, accurately estimating leakage flows and piston ring wear in compressor cylinders is vital. This paper presents a gas flow network model aimed at predicting wear and leakage of dry-running piston seals for high-pressure hydrogen storage. The model accounts for the dynamics of the seals and the fluid dynamics of gas leaking through the narrow clearances between the moving piston and the cylinder liner, therefore considering the interaction between gas flow and seal displacement within piston grooves. Each volume of the network constitutes a 0-D system where mass and energy conservation equations are solved. Given the complexity of both physical phenomena and cavity geometry, the choice of 0-D systems represents a suitable trade-off between calculation speed and result accuracy. This paper proposes a numerical model designed to evaluate the thermodynamic properties of the volumes and to predict the pressure drop distribution across piston seals. It also assesses friction power generated by dry seals and identifies rings vulnerable to premature wear. Moreover, the model shows that optimizing the geometrical design of the seals minimizes the gas blow-by, enhancing compression efficiency and extending the machine lifespan.| File | Dimensione | Formato | |
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