A fast lumped parameter approach for the prediction of both aeration and cavitation in Gerotor pumps

Air Release and Cavitation Modeling with a Lumped Parameter Approach Based on the Rayleigh–Plesset Equation: The Case of an External Gear Pump

“…Dependence on Reynolds number is also incorporated as described in Blackburn et al [15] and McCloy et al [17], to extend the use of the orifice Equation (Equation (2)) to the case of transitional or laminar flow. In past work by Shah et al [13], the conventional orifice equation was modified to account for the compressibility effects through the orifice and is described in detail in Section 3.2.…”

“…Dynamic lumped parameter cavitation modeling techniques developed in the past are described in Refs. [11][12][13]24]. The reader can refer to the past works for additional details regarding the modeling approach.…”

“…Motivated by the Full Cavitation Model introduced by Singhal et al [7] and Zhou et al [11,12] developed a dynamic cavitation model that accounted for the instantaneous variation in both gas and vapor phases. The model was further extended to include compressibility effects in hydraulic connections and a more accurate form of the transport equation by Shah et al [13] and implemented in the simulation of a gerotor unit. In the simulations performed by Zhou et al [11] as well as Shah et al [13], the dynamic cavitation model predicts cavitation based on empirically defined relaxation parameters that specify the time scales of the phase change process.…”

“…The model was further extended to include compressibility effects in hydraulic connections and a more accurate form of the transport equation by Shah et al [13] and implemented in the simulation of a gerotor unit. In the simulations performed by Zhou et al [11] as well as Shah et al [13], the dynamic cavitation model predicts cavitation based on empirically defined relaxation parameters that specify the time scales of the phase change process. In Shah et al [13], the choice of relaxation parameters was dictated by iterative optimization of simulation results for a reference operating condition; however, the chosen parameters lack a clear physical interpretation and their choice remains arbitrary for a general case.…”

“…In the simulations performed by Zhou et al [11] as well as Shah et al [13], the dynamic cavitation model predicts cavitation based on empirically defined relaxation parameters that specify the time scales of the phase change process. In Shah et al [13], the choice of relaxation parameters was dictated by iterative optimization of simulation results for a reference operating condition; however, the chosen parameters lack a clear physical interpretation and their choice remains arbitrary for a general case. Moreover, specific choices of the relaxation parameters may lead to correct time scales in a given set of operating conditions; however, they may deviate from the physical time scales in other operating conditions.…”