arXiv subjects

Zhuoran Dang

Publications and source records attributed to Zhuoran Dang.

5 recordsLinked to original sources

arXiv2021

Two-phase interfacial structure of bubbly-to-slug transition flows in a 12.7 mm ID vertical tube

This experimental study focuses on the characteristics of air-water two-phase interfacial structure. Interfacial parameters including void fraction, interfacial area concentration, and bubble interfacial velocity are measured using four-sensor electrical conductivity probe on a 12.7 mm ID vertical tube. The tube size is approximately equal to the maximum distorted bubble size. Therefore, the bubbly-to-slug transition characteristics can be different from in other sizes of tubes. Comparing with previous studies, this study provides an experimental database with a wide range on the bubbly-to-slug transition flows, with 4 different superficial liquid velocities (0.3, 0.5, 1.0, and 2.0 m/s) and void fraction ranging from 0.07 to 0.66. Experimental results show that the wall-peak void distribution does not appear in a small diameter tube under the bubbly-to-slug flow transition flow. The distribution is related with both void fraction and the relative bubble size to the tube size. In this sense, a new correlation of distribution parameter in the Drift Flux model is proposed based on the previous studies by Ishii and Hibiki et al. This experimental study can be a good reference for the model development of flow regime transition and the Interfacial Area Transport Equation.

physics.flu-dyn↗

arXiv2021

Interfacial area transport for bubbly-to-slug transition flows in small diameter pipes

This study aims to experimentally investigate the two-group interfacial area transport in small diameter pipes. Experimental data focusing on the bubbly to slug transition regime, namely one-group to two-group transport region, are collected in a 12.7 mm vertical pipe under adiabatic, air-water conditions. The result shows the intergroup transfer in the small diameter pipe can be drastic, especially under low superficial liquid velocities. The cause of this phenomenon is mainly due to the large relative bubble size comparing to the pipe cross-sectional area. The wake entrainment effect could be enhanced by the small spherical bubbles that are acting like cap or slug bubbles in a medium-size pipe. Based on the experimental observation, a throughout analysis of the dependence of the drastic intergroup transfer is provided in this study. The models predicting the initiation of drastic intergroup transfer in small diameter pipes in terms of the bubble diameter and the void fraction are developed. These models are compared with the two-phase data among the different pipe sizes and the results show a good agreement. These newly developed models are applied to the IATE wake entrainment model by developing a transition function analogous to the sigmoid function. With the transition function, the revised IATE model is given the new ability on predicting the drastic intergroup transfer phenomenon.

physics.flu-dyn↗

arXiv2020

A physics-informed reinforcement learning approach for the interfacial area transport in two-phase flow

The prediction of interfacial structure in two-phase flow systems is difficult and challenging. In this paper, a novel physics-informed reinforcement learning-aided framework (PIRLF) for the interfacial area transport is proposed. A Markov Decision Process that describes the bubble transport is established by assuming that the development of two-phase flow is a stochastic process with Markov property. The framework aims to capture the complexity of two-phase flow using the advantage of reinforcement learning (RL) in discovering complex patterns with the help of the physical model (Interfacial Area Transport Equation) as reference. The details of the framework design are described including the design of the environment and the algorithm used in solving the RL problem. The performance of the PIRLF is tested through experiments using the experimental database for vertical upward bubbly air-water flows. The result shows a good performance of PIRLF with rRMSE of 6.556%. The case studies on the PIRLF performance also show that the type of reward function that is related to the physical model can affect the framework performance. Based on the study, the optimal reward function is established. The approaches to extending the capability of PIRLF are discussed, which can be a reference for the further development of this methodology.

physics.comp-ph↗

arXiv2020

A new approach on estimating the fluid temperature in a multiphase flow system using particle filter method

Fluid temperature is important for the analysis of the heat transfers in thermal hydraulics. An accurate measurement or estimation of the fluid temperature in multiphase flows is challenging. This is due to that the thermocouple signal that mixes with temperature signals for each phase and non-negligible noises. This study provides a new approach to estimate the local fluid temperature in multiphase flows using experimental time-series temperature signal. The thermocouple signal is considered to be a sequence with Markov property and the particle filter method is utilized in the new method to extract the fluid temperature. A complete description of the new method is presented in this article.

physics.data-an↗

arXiv2019

Two-phase flow regime prediction using LSTM based deep recurrent neural network

Long short-term memory (LSTM) and recurrent neural network (RNN) has achieved great successes on time-series prediction. In this paper, a methodology of using LSTM-based deep-RNN for two-phase flow regime prediction is proposed, motivated by previous research on constructing deep RNN. The method is featured with fast response and accuracy. The built RNN networks are trained and tested with time-series void fraction data collected using impedance void meter. The result shows that the prediction accuracy depends on the depth of network and the number of layer cells. However, deeper and larger network consumes more time in predicting.

cs.CV↗