Numerical Research About the Internal Flow of Steam-jet Vacuum Pump: Evaluation of Turbulence Models and Determination of the Shock-mixing Layer

AbstractSteam-jet vacuum pump is widely used in a range of applications. This paper evaluated the performance of four well-known turbulence models for predicting and understanding the internal flow of a steam-jet vacuum pump first. With the help of a commercial computational fluid dynamics (CFD) code ANSYS-Fluent 6.3, the simulation results obtained from the concerned turbulence models were compared with experimental values, the k-omega-SST model was chosen as a tool model for carrying out numerical simulations. Then, based on the simulation results obtained from specific operating conditions, a method for locating the shock-mixing layer was put forward. The shape of the shock-mixing layer shows that the secondary steam does not mix with the primary steam immediately after being induced into the mixing chamber of the pump; actually, they maintain their independence till the shocking position instead. After the shock happens, the shock-mixing layer disappear, the two fluid in the pump begin to mix with each other and discharge to the next stage with almost the same state. Based on the shape of the shock-mixing layer and the supersonic region of the secondary steam, a detailed analysis for the flow duct of the secondary steam was carried out. It is found that the throat of the secondary steam flow duct plays a crucial role in maintaining a stable operating state and the length of the throat reflects the back pressure endurance for the pump

Distributed Semi-Supervised Sparse Statistical Inference

This paper is devoted to studying the semi-supervised sparse statistical inference in a distributed setup. An efficient multi-round distributed debiased estimator, which integrates both labeled and unlabelled data, is developed. We will show that the additional unlabeled data helps to improve the statistical rate of each round of iteration. Our approach offers tailored debiasing methods for $M$-estimation and generalized linear model according to the specific form of the loss function. Our method also applies to a non-smooth loss like absolute deviation loss. Furthermore, our algorithm is computationally efficient since it requires only one estimation of a high-dimensional inverse covariance matrix. We demonstrate the effectiveness of our method by presenting simulation studies and real data applications that highlight the benefits of incorporating unlabeled data.Comment: 41 pages, 4 figure

Numerical modelling of micron particle inhalation in a realistic nasal airway with pediatric adenoid hypertrophy: A virtual comparison between pre- and postoperative models

Adenoid hypertrophy (AH) is an obstructive condition due to enlarged adenoids, causing mouth breathing, nasal blockage, snoring and/or restless sleep. While reliable diagnostic techniques, such as lateral soft tissue x-ray imaging or flexible nasopharyngoscopy, have been widely adopted in general practice, the actual impact of airway obstruction on nasal airflow and inhalation exposure to drug aerosols remains largely unknown. In this study, the effects of adenoid hypertrophy on airflow and micron particle inhalation exposure characteristics were analysed by virtually comparing pre- and postoperative models based on a realistic 3-year-old nasal airway with AH. More specifically, detailed comparison focused on anatomical shape variations, overall airflow and olfactory ventilation, associated particle deposition in overall and local regions were conducted. Our results indicate that the enlarged adenoid tissue can significantly alter the airflow fields. By virtually removing the enlarged tissue and restoring the airway, peak velocity and wall shear stress were restored, and olfactory ventilation was considerably improved (with a 16∼63% improvement in terms of local ventilation speed). Furthermore, particle deposition results revealed that nasal airway with AH exhibits higher particle filtration tendency with densely packed deposition hot spots being observed along the floor region and enlarged adenoid tissue area. While for the postoperative model, the deposition curve was shifted to the right. The local deposition efficiency results demonstrated that more particles with larger inertia can be delivered to the targeted affected area following Adenoidectomy (Adenoid Removal). Research findings are expected to provide scientific evidence for adenoidectomy planning and aerosol therapy following Adenoidectomy, which can substantially improve present clinical treatment outcomes.</p

Assessment of Effect of Bubble Departure Frequency in Forced Convective Subcooled Boiling

Bubble departure frequency is one of the important parameters for the prediction of subcooled flow boiling. This present work aims at an assessment of bubble departure frequency by investigating the physical mechanisms of three-dimensional two-fluid model coupled with the population balance equation. The CFX MUltiple-SIze-Group (MUSIG) model is used to predict bubbly flows with the presence of heat and mass transfer processes, particularly in subcooled boiling flows at low pressures. The assessment is carried out for these three models/correlations. The test shows that Podowski et al.'s model, with reasonable physical characteristics, is more realistic than the other two models when compared with the experimental data. The numerical results indicate that the higher the departure frequency, the lower the wall temperature and so the nucleation site density. In addition it is found that for both the axial and radial cases the curves of the void fraction tend to decrease with increase in departure frequency. The benchmark of the current numerical simulation with experimental data in both axial and radial profiles achieves successful agreement