CFD research on the influence of geometry characteristic on flow pattern and the transition mechanism in Rushton turbine stirred vessels

In this paper, the transient MRF approach coupled with the standard k-ε and SST k-ω turbulence models was employed to study the effect of bottom shape, impeller diameter (D J) and bottom height (H 2) on critical impeller off-bottom clearance (C). It was found the bottom shape and bottom height (H 2) have obvious influence on the flow pattern transition from double-loop to single-loop of RT impeller. The flow pattern transition mechanism was inferred to relate to the relationship between the space required by the lower circulation zone and the actual space. The boundary conditions of critical C were further concluded to help distinguish the flow pattern and receive the expected one in the stirred vessel design.

Cost-based recurrence analysis of conductance time series for gas–liquid two-phase flow system

Gas–liquid two-phase flows are frequently encountered in chemical and nuclear industries. The study of gas–liquid flow structures is of great significance for understanding the mechanisms of the flow pattern transition. In this paper, a direct-image multi-electrode conductance sensor (DMCS) was used to detect the structure information of vertical gas–liquid flows. Recurrence plot (RP) and cost-based recurrence plot (CBRP) are validated using typical nonlinear systems, i.e. Lorenz system and Hénon map, and used to analyze the signals collected by the DMCS. The results indicate that the determinism (DET) derived from the CBRP is sensitive to flow pattern evolution, and can also demonstrate the internal differences in the same flow patterns.

Flow Pattern Transition in Pipes Using Data-Driven and Physics-Informed Machine Learning

Flow pattern is an important engineering design factor in two-phase flow in the chemical, nuclear and energy industries, given its effects on pressure drop, holdup, and heat and mass transfer. The prediction of two-phase flow patterns through phenomenological models is widely used in both industry and academy. In contrast, as more experimental data become available for gas-liquid flow in pipes, the use of data-driven models to predict flow-pattern transition, such as machine learning, has become more reliable. This type of heuristic modeling has a high demand for experimental data, which may not be available in some industrial applications. As a consequence, it may fail to deliver a sufficiently generalized transition prediction. Incorporation of physics in machine learning is being proposed as an alternative to improve prediction and also to reduce the demand for experimental data. This paper evaluates the use of hybrid-physics-data machine learning to predict gas-liquid flow-pattern transition in pipes. Random forest and artificial neural network are the chosen tools. A database of experiments available in the open literature was collected and is shared in this work. The performance of the proposed hybrid model is compared with phenomenological and data-driven machine learning models through confusion matrices and graphics. The results show improvement in prediction performance even with a low amount of data for training. The study also suggests that graphical comparison of flow-pttern transition boundaries provides better understanding of the performance of the models than the traditional metric

Flow Pattern Transition Criteria for Upward Two-Phase Flow in Annulus

Vertical upward two-phase flows in annulus are of great importance in many industrial fields due to the closely relationship between the flow patterns and the heat transfer characteristics. Common flow patterns in annulus are bubbly (B), slug (S), churn (C) and annular (A) flow, most of which are quite similar to those in tubes. However, due to the elliptic nose and asymmetric shape of the Taylor bubble in annulus, the slug to churn flow transition could be influenced by the channel geometry which was usually ignored in most of the previous researches. The flow pattern transition criteria for tubes are thus not applicable for annulus, especially for slug to churn flow transition, which should be separately studied. Therefore, in this paper, the basic characteristics of the flow pattern in annulus and their transition mechanism are analyzed. In addition, a set of semi-empirical transition criteria with higher accuracy are assessed and selected for annulus based on theoretical analysis and comparisons with experimental data.