scholarly journals Numerical Investigation of Scour Beneath Pipelines Subjected to an Oscillatory Flow Condition

2021 ◽  
Vol 9 (10) ◽  
pp. 1102
Author(s):  
Jun Huang ◽  
Guang Yin ◽  
Muk Chen Ong ◽  
Dag Myrhaug ◽  
Xu Jia
Keyword(s):  
Granular Flow ◽  
Flow Condition ◽  
Oscillatory Flow ◽  
Flow Patterns ◽  
Two Phase ◽  
Initial Development ◽  
Steady Streaming ◽  
Turbulence Flow ◽  
Binary Collisions ◽  
Rheology Model

The present study carries out two-dimensional numerical simulations to investigate scour beneath a single pipeline and piggyback pipelines subjected to an oscillatory flow condition at a Keulegan–Carpenter (KC) number of 11 using SedFoam (an open-source, multi-dimensional Eulerian two-phase solver for sediment transport based on OpenFOAM). The turbulence flow is resolved using the two-phase modified k−ω 2006 model. The particle stresses due to the binary collisions and enduring contacts among the sediments are modeled using the rheology model of granular flow. The present numerical model is validated for the scour beneath a single pipeline, and the simulated sediment profiles are compared with published experimental data and numerical simulation results. The scour process beneath three different piggyback pipelines under the same flow condition are also considered, and the scour development and surrounding flow patterns are discussed in detail. Typical steady-streaming structures around the pipeline due to the oscillatory flow condition are captured. The scour depth during the initial development of the scour process for the piggyback pipeline with the small pipeline placed above the large one is the largest among all the investigated configurations. The phase-averaged flow fields show that the flow patterns are influenced by the additional small pipeline.

Numerical Investigation of Scour Around Subsea Pipelines Near the Seabed

2019 ◽  
Author(s):  
Guang Yin ◽  
Zhen Cheng ◽  
Shengnan Liu ◽  
Muk Chen Ong
Keyword(s):  
Granular Flow ◽  
Present Model ◽  
Scour Depth ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Simulations ◽  
2D Simulation ◽  
Binary Collisions ◽  
Simulation Results ◽  
Subsea Pipelines

Abstract In the present study, two-phase flow simulations using SedFoam (an open-source multi-dimensional Eulerian two-phase solver based on OpenFOAM) are employed to investigate the scour phenomenon around pipelines in the vicinity of the seabed. A complete transport profile from the immobile bed, to slowly moving quasi-static bed and upper transport layers can be captured by the present model. The fluid Reynolds stress is modeled using the two-phase k-ε model. The particle stresses due to binary collisions and enduring contacts are modeled by kinetic theory for granular flow and a phenomenological frictional model, respectively. The model is first validated through a two-dimensional (2D) simulation of scour around a single pipeline near the seabed. The predicted time-dependent scour profiles as well as the scour depth are compared with the simulation results of Lee et al. (2016) and the experimental data reported by Mao (1986). A numerical experiment is then carried out to investigate the scour around the piggyback near the seabed. The effects of different locations of the small pipeline on the scour depth are studied.

Numerical Investigation of Scour Beneath a Subsea Piggyback Pipeline

2020 ◽  
Author(s):  
Jun Huang ◽  
Guang Yin ◽  
Muk Chen Ong ◽  
Xu Jia
Keyword(s):  
Boundary Layer ◽  
Flow Field ◽  
Kinetic Theory ◽  
Boundary Layer Flow ◽  
Granular Flow ◽  
Scour Depth ◽  
Two Dimensional ◽  
Two Phase ◽  
Binary Collisions ◽  
Layer Flow

Abstract In present study, two-dimensional numerical simulations have been carried out to investigate scour beneath a piggyback pipeline subjected to a subsea boundary layer flow using SedFoam (an open-source multi-dimensional Eulerian two-phase solver for sediment transport based on OpenFOAM). In the piggyback configuration, a small pipeline is attached on the upstream and downstream sides of a large pipeline. This form of piggyback can reduce the scour depth beneath the pipeline (Yang et al., 2019). In the solver, the turbulence Reynolds stress is resolved using a two-phase modified k-ε model. The particle stresses caused by the binary collisions and contacts are modeled by the kinetic theory for granular flow and a phenomenological frictional model, respectively. The effects of the locations of the small pipelines attached on the large pipeline on the scour and the surrounding flow field are discussed.

scholarly journals Pseudo Dynamic Visualization of Boiling Two-phase Flow under Oscillatory Flow Condition

2013 ◽  
Vol 43 ◽  
pp. 269-276 ◽  
Author(s):  
H. Umekawa ◽  
T. Ami ◽  
S. Fujiyoshi ◽  
Y. Saito
Keyword(s):  
Flow Condition ◽  
Oscillatory Flow ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Dynamic Visualization ◽  
Two Phase

scholarly journals Machine Learning Model of Dimensionless Numbers to Predict Flow Patterns and Droplet Characteristics for Two-Phase Digital Flows

2021 ◽  
Vol 11 (9) ◽  
pp. 4251
Author(s):  
Jinsong Zhang ◽  
Shuai Zhang ◽  
Jianhua Zhang ◽  
Zhiliang Wang
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Digital Microfluidics ◽  
Flow Patterns ◽  
Machine Learning Algorithms ◽  
Dimensionless Numbers ◽  
Two Phase ◽  
The Difference ◽  
Input Variables ◽  
Digital Microfluidic

In the digital microfluidic experiments, the droplet characteristics and flow patterns are generally identified and predicted by the empirical methods, which are difficult to process a large amount of data mining. In addition, due to the existence of inevitable human invention, the inconsistent judgment standards make the comparison between different experiments cumbersome and almost impossible. In this paper, we tried to use machine learning to build algorithms that could automatically identify, judge, and predict flow patterns and droplet characteristics, so that the empirical judgment was transferred to be an intelligent process. The difference on the usual machine learning algorithms, a generalized variable system was introduced to describe the different geometry configurations of the digital microfluidics. Specifically, Buckingham’s theorem had been adopted to obtain multiple groups of dimensionless numbers as the input variables of machine learning algorithms. Through the verification of the algorithms, the SVM and BPNN algorithms had classified and predicted the different flow patterns and droplet characteristics (the length and frequency) successfully. By comparing with the primitive parameters system, the dimensionless numbers system was superior in the predictive capability. The traditional dimensionless numbers selected for the machine learning algorithms should have physical meanings strongly rather than mathematical meanings. The machine learning algorithms applying the dimensionless numbers had declined the dimensionality of the system and the amount of computation and not lose the information of primitive parameters.

scholarly journals Two-Phase Flow Mass Transfer Analysis of Airlift Pump for Aquaculture Applications

Fluids ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 226
Author(s):  
Rashal Abed ◽  
Mohamed M. Hussein ◽  
Wael H. Ahmed ◽  
Sherif Abdou
Keyword(s):  
Mass Transfer ◽  
Oxygen Transfer ◽  
Transfer Rate ◽  
Two Phase Flow ◽  
Oxygen Transfer Rate ◽  
Flow Patterns ◽  
Oxygen Mass Transfer ◽  
Phase Flow ◽  
Two Phase ◽  
Airlift Pump

Airlift pumps can be used in the aquaculture industry to provide aeration while concurrently moving water utilizing the dynamics of two-phase flow in the pump riser. The oxygen mass transfer that occurs from the injected compressed air to the water in the aquaculture systems can be experimentally investigated to determine the pump aeration capabilities. The objective of this study is to evaluate the effects of various airflow rates as well as the injection methods on the oxygen transfer rate within a dual injector airlift pump system. Experiments were conducted using an airlift pump connected to a vertical pump riser within a recirculating system. Both two-phase flow patterns and the void fraction measurements were used to evaluate the dissolved oxygen mass transfer mechanism through the airlift pump. A dissolved oxygen (DO) sensor was used to determine the DO levels within the airlift pumping system at different operating conditions required by the pump. Flow visualization imaging and particle image velocimetry (PIV) measurements were performed in order to better understand the effects of the two-phase flow patterns on the aeration performance. It was found that the radial injection method reached the saturation point faster at lower airflow rates, whereas the axial method performed better as the airflow rates were increased. The standard oxygen transfer rate (SOTR) and standard aeration efficiency (SAE) were calculated and were found to strongly depend on the injection method as well as the two-phase flow patterns in the pump riser.

Two-Phase Flow and Heat Transfer in Rectangular Micro-Channels

2003 ◽  
Author(s):  
Weilin Qu ◽  
Seok-Mann Yoon ◽  
Issam Mudawar
Keyword(s):  
Heat Transfer ◽  
Pressure Drop ◽  
Flow Pattern ◽  
Two Phase Flow ◽  
Flow Patterns ◽  
Heat Sinks ◽  
Phase Flow ◽  
Micro Channel ◽  
Two Phase ◽  
Micro Channels

Knowledge of flow pattern and flow pattern transitions is essential to the development of reliable predictive tools for pressure drop and heat transfer in two-phase micro-channel heat sinks. In the present study, experiments were conducted with adiabatic nitrogen-water two-phase flow in a rectangular micro-channel having a 0.406 × 2.032 mm cross-section. Superficial velocities of nitrogen and water ranged from 0.08 to 81.92 m/s and 0.04 to 10.24 m/s, respectively. Flow patterns were first identified using high-speed video imaging, and still photos were then taken for representative patterns. Results reveal that the dominant flow patterns are slug and annular, with bubbly flow occurring only occasionally; stratified and churn flow were never observed. A flow pattern map was constructed and compared with previous maps and predictions of flow pattern transition models. Annual flow is identified as the dominant flow pattern for conditions relevant to two-phase micro-channel heat sinks, and forms the basis for development of a theoretical model for both pressure drop and heat transfer in micro-channels. Features unique to two-phase micro-channel flow, such as laminar liquid and gas flows, smooth liquid-gas interface, and strong entrainment and deposition effects are incorporated into the model. The model shows good agreement with experimental data for water-cooled heat sinks.

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