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Tip clearance in pump induces tip leakage vortex (TLV), which interacts with the main flow and leads to instability of flow pattern and decrease of pump performance. In this work, the characteristics of TLV in a mixed-flow pump are investigated by the numerical simulation using shear stress transport (SST) k–ω turbulence model with experimental validation. The trajectory of the primary tip leakage vortex (PTLV) is determined, and a power function law is proposed to describe the intensity of the PTLV core along the trajectory. Spatial–temporal evolution of the TLV in an impeller revolution period T can be classified into three stages: splitting stage, developing stage, and merging stage. The TLV oscillation period TT is found as 19/160 T, corresponding to the frequency 8.4 fi (fi is impeller rotating frequency). Results reveal that the TLV oscillation is intensified by the sudden pressure variation at the junction of two adjacent blades. On analysis of the relative vorticity transport equation, it is revealed that the relative vortex stretching item in Z direction is the major source of the splitting and shedding of the PTLV. The dominant frequency of pressure and vorticity fluctuations on the PTLV trajectory is 8.4 fi, same as the TLV oscillation frequency. This result reveals that the flow instability in the PTLV trajectory is dominated by the oscillation of the TLV. The blade number has significant effect on pressure fluctuation in tip clearance and on blade pressure side, because the TLV oscillation period varies with the circumferential length of flow passage.

In the COVID-19 outbreak year 2020, a consensus was reached on the fact that SARS-CoV-2 spreads through aerosols. However, finding an efficient method to detect viruses in aerosols to monitor the risk of similar infections and enact effective control remains a great challenge. Our study aimed to build a swirling aerosol collection (SAC) device to collect viral particles in exhaled breath and subsequently detect SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR). Laboratory tests of the SAC device using aerosolized SARS-CoV-2 pseudovirus indicated that the SAC device can produce a positive result in only 10 s, with a collection distance to the source of 10 cm in a biosafety chamber, when the release rate of the pseudovirus source was 1,000,000 copies/h. Subsequent clinical trials of the device showed three positives and 14 negatives out of 27 patients in agreement with pharyngeal swabs, and 10 patients obtained opposite results, while no positive results were found in a healthy control group (n = 12). Based on standard curve calibration, several thousand viruses per minute were observed in the tested exhalations. Furthermore, referring to the average tidal volume data of adults, it was estimated that an exhaled SARS-CoV-2 concentration of approximately one copy/mL is detectable for COVID-19 patients. This study validates the original concept of breath detection of SARS-CoV-2 using SAC combined with RT-PCR.

Tip clearance results in the leakage flow from blade pressure side to suction side, which will further cause the tip leakage vortex (TLV). Moreover, the flow pattern in an impeller is seriously deteriorated due to the TLV and its interaction with the main stream. In this work, the TLV in a mixed flow pump is investigated by numerical simulation validated by experiment measurement. The primary tip leakage vortex (PTLV) trajectory is specially studied with consideration of the tip clearance size δ, the impeller blade number Zi, and the impeller rotational speed n. The results show that δ slightly shifts the separation point (SP) of the PTLV but rarely affects the separation angle α. The increase in Zi and the decrease in n both lead to the shift of the SP toward the blade trailing edge and the decrease in α. Furthermore, a theoretical prediction model is proposed to predict the PTLV trajectory, by which the axial position and radial position of PTLV trajectory versus the rotation angle can be predicted. The proposed model is verified to be accurate to predict the PTLV trajectory, especially for the PTLV trajectory in the main flow passage. The dynamic evolution of TLV under different tip clearance sizes can all be classified into the same three stages: splitting stage, developing stage, and merging stage. Meanwhile, the dynamic evolution frequency fe is the same as the impeller rotational frequency fi.

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Abstract:With help from horizontal wells and hydraulic fracturing, shale gas has made a significant contribution to the energy supply. However, due to complex fracture networks and complicated mechanisms such as gas desorption and gas slippage in shale, forecasting shale gas production is a challenging task. Despite the versatility of many simulation methods including analytical models, semi-analytical models, and numerical simulation, Decline Curve Analysis has the advantages of simplicity and efficiency for hydrocarbon production forecasting. In this article, the eight most popular deterministic decline curve methods are reviewed: Arps, Logistic Growth Model, Power Law Exponential Model, Stretched Exponential Model, Duong Model, Extended Exponential Decline Model, and Fractural Decline Curve model. This review article is dedicated to summarizing the origins, derivations, assumptions, and limitations of these eight decline curve models. This review article also describes the current status of decline curve analysis methods, which provides a comprehensive and up-to-date list of Decline Curve Analysis models for petroleum engineers in analysis of shale gas reservoirs. This work could serve as a guideline for petroleum engineers to determine which Decline Curve models should be applied to different shale gas fields and production periods.

Cavitation is a complicated phenomenon in the centrifugal pump. In this work, the improved unsteady calculation model based on bubble-rotation-based Zwart–Gerber–Belamri (BRZGB) cavitation model is used to investigate the cavitation-vortex-pressure fluctuation interaction in a centrifugal pump under partial load with experimental validation. Spatial–temporal evolution of cavitation can be classified into three stages: developing stage, shedding stage, and collapsing stage. The cavitation evolution period is found as 1/4T (T is impeller rotation period), corresponding to the frequency 4fi (fi is impeller rotation frequency). On the analysis of the relative vorticity transport equation, it is revealed that the cavity is stretched by the relative vortex stretching term (RVS) and developed by the relative vortex dilation term (RVD), and they have great influence on the cavity shedding. The peak value of pressure fluctuation intensity occurs near the vapor–liquid interface at cavity rear, and shifts downstream with the cavitation development. The hysteresis between the vapor volume fraction, vorticity, and pressure fluctuation is observed, and the variation of vapor volume fraction is the source of cavitation-vortex-pressure interaction.