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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Processing Methodology for Double Sensor Probe in a Bubbly Flow

Bubbly flow phenomenon is the most common flow pattern in nuclear plant system. In this paper, according to Hibiki and Bartel, the experiment was designed to observe the fluid conditions surrounding nuclear rod. In recent years, double sensor probe is one of the measuring techniques for the bubbly flow. It can measure local void fraction and bubble velocity. After mathematical statistical calculation, interfacial area concentration is obtained by Kataoka. The double sensor probe method, with the advantage for measuring local interfacial area concentration, has become widely used in many measurement methods. The paper of Liu and Zhao were referred to establish the post-processing for the raw data obtained from measuring instrument. After drawing the signal of the probe, it is important to analyze the raw data for the elimination of unnecessary noise signal and highlight the characteristic signal. Based on the same experimental condition, the different filtering methods, Simple Moving Average (SMA) and Gaussian average, were compared and discussed by the double sensor probe.

42 ENGINEERING↗
DOE OSTI2017

Interface tracking simulations of bubbly flows in PWR relevant geometries

[en] Highlights: • Simulations were performed for turbulent bubbly flows in PWR subchannel geometry. • Liquid turbulence is fully resolved by direct numerical simulation approach. • Bubble behavior is captured using level-set interface tracking method. • Time-averaged single- and two-phase turbulent flow statistical quantities are obtained. - Abstract: The advances in high performance computing (HPC) have allowed direct numerical simulation (DNS) approach coupled with interface tracking methods (ITM) to perform high fidelity simulations of turbulent bubbly flows in various complex geometries. In this work, we have chosen the geometry of the pressurized water reactor (PWR) core subchannel to perform a set of interface tracking simulations (ITS) with fully resolved liquid turbulence. The presented research utilizes a massively parallel finite-element based code, PHASTA, for the subchannel geometry simulations of bubbly flow turbulence. The main objective for this research is to demonstrate the ITS capabilities in gaining new insight into bubble/turbulence interactions and assisting the development of improved closure laws for multiphase computational fluid dynamics (M-CFD). Both single- and two-phase turbulent flows were studied within a single PWR subchannel. The analysis of numerical results includes the mean gas and liquid velocity profiles, void fraction distribution and turbulent kinetic energy profiles. Two sets of flow rates and bubble sizes were used in the simulations. The chosen flow rates corresponded to the Reynolds numbers of 29,079 and 80,775 based on channel hydraulic diameter (D_h) and mean velocity. The finite element unstructured grids utilized for these simulations include 53.8 million and 1.11 billion elements, respectively. This has allowed to fully resolve all the turbulence scales and the deformable interfaces of individual bubbles. For the two-phase flow simulations, a 1% bubble volume fraction was used which resulted in 17 bubbles in the smaller case and 262 bubbles in the larger case. In the larger simulation case the size of the resolved bubbles is 0.65 mm in diameter, and the bulk mesh cell size is about 30 microns. Those large-scale simulations provide new level of details previously unavailable and were enabled by the excellent scaling performance of our two-phase flow solver and access to the state-of-the-art supercomputing resources. The presented simulations used up to 256 thousand processing threads on the IBM BG/Q supercomputer “Mira” (Argonne National Laboratory).

Nuclear Science & Technology↗
DOE OSTI2020

Uncertainty analysis of PIV measurements in bubbly flows considering sampling and bubble effects with ray optics modeling

In this report, a modeling-based approach is developed to investigate the external sources of uncertainty in particle image velocimetry (PIV) measurements for two-phase bubbly flows. Primarily relied on ray optics modeling, this study focuses on the uncertainty in PIV measurements due to bubble-induced light distortion. In addition, the uncertainty due to sampling is also considered through synthetic PIV images generated from Monte Carlo sampling. Based on a PIV-planar laser induced florescence (PLIF) measurement system, three case studies are performed and discussed, considering respectively the sampling effect, bubble effect, and the combination of these two effects. These case studies confirm the validity of the ray optics modeling in obtaining accurate particle images through a benchmark test. Furthermore, it is also found that the bubble effect could significantly influence the particle images. On the other hand, the result of the case study with synthetic PIV images indicates that the bubble effect on particle images can be minimized by removing “outliers” in the obtained velocity vector field through a multi-pass post-processing procedure. However, the uncertainty of the velocity measurements will still increase.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Eulerian-Eulerian large eddy simulation of two-phase dilute bubbly flows

An efficient mathematical model is presented for conducting large eddy simulation (LES) of turbulent bubbly flows at low gas hold-ups. The mathematical model is based on the filtered multi-fluid equations derived by application of the component-weighted volume-averaging process of each phase. A two-fluid model is applied to the filtered set of equations, yielding a more computationally tractable set of filtered equations. The filtered equations are formulated in generalized curvilinear coordinates to simulate turbulent gas-liquid bubbly flows in complex geometries. The Germano model is used to account for sub-grid turbulent stresses. The gas and liquid momentum equations are discretized with the hybrid staggered/non-staggered method. The performance of the developed mathematical model is demonstrated by simulating the benchmark test case of a turbulent gas-liquid bubbly flow in a rectangular bubble column. The accuracy of the proposed method is assessed via comparison with the experimental data and other numerical results in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Evaluation of interfacial area transport models for horizontal bubbly flow

This paper presents evaluation results of interfacial area transport equation (IATE) for horizontal air-water bubbly flow. The steady-state one-dimensional, one-group IATE for adiabatic air-water bubbly flow developed by Talley [1] is employed in the current evaluation study. The models evaluated include: (a) drift-flux-based closure relations for void-weighted bubble velocity and void fraction; (b) frictional pressure drop model based on the Lockhart-Martinelli approach; (c) bubble interaction mechanisms; and (d) covariance associated with asymmetric bubble distribution in horizontal two-phase flow. In order to evaluate the models, a local two-phase flow database obtained by the four-sensor conductivity probe in fourteen different test conditions is employed, which covers a wide range of flow conditions in horizontal bubbly flow regime, with superficial liquid and gas velocities ranging from 3.50-6.00 m/s and 0.09- 1.00 m/s, respectively. It is demonstrated that both the void weighted bubble velocity and void fraction are predicted well with an average percent difference of ±2.7%. The fictional pressure loss can be predicted with an average percent difference of ±1.12%. The covariance parameters calculated from the modeling approach generally compare well with those calculated from experimental data within ±20% difference. It is found that the IATE generally predicts the measured interfacial area concentration with an average percent difference of ±5.7%. Furthermore, the effect of liquid velocity on individual bubble interaction mechanisms is investigated. It is found that both the contributions of random collision and turbulent impact decrease as liquid velocity decreases. (authors)

42 ENGINEERING↗
DOE OSTI2014

Investigations of Bubbly Flows using Direct Numerical Simulations

Direct numerical simulations are used to examine the behavior of relatively high void fraction bubbly flows. The full Navier-Stokes equations are solved for both the bubbles and the ambient liquid and the flow near the moving and deforming phase boundaries is resolved fully. This yields detailed data for the evolution of the system that can be used to extract information about the basic bubble-bubble and bubble-flow interactions as well as about the averaged properties of the system. Such information are critical for the generation of averaged engineering models of industrial size systems as well as for novel applications of bubbly flows where experiments are difficult. The project has yielded detailed information about many aspects of bubbly flows. The results for flows in vertical channels are particularly significant and have yielded an essentially complete understanding of many aspects of the flows. The important insight is that the flow has a particularly simple structure, consisting of a homogeneous core in hydrostatic balance and a wall layer whose composition depends of whether the liquid is flowing upward or downward. These results hold for both laminar and turbulent flows and have allowed us to derive an analytical model to predict the flow. We have also shown that bubble deformability results in a completely different flow structure, but also giving rise to relatively simple predictive models. Preliminary studies of transient migration of a non-homogeneous bubble distribution and coalescence induced flow regime transitions in vertical channels were also done.

42 ENGINEERING↗
DOE OSTI2018

Interface Tracking Investigation of Geometric Effects on the Bubbly Flow in PWR Subchannels

We report that absorbing heat from the fuel rod surface, water as coolant can undergo subcooled boiling within a pressurized water reactor (PWR) fuel rod bundle. Because of the buoyancy effect, the vapor bubbles generated will then rise along and interact with the subchannel geometries. Reliable prediction of bubble behavior is of immense importance to ensure safe and stable reactor operation. However, given a complex engineering system like a nuclear reactor, it is very challenging (if not impossible) to conduct high-resolution measurements to study bubbly flows under reactor operation conditions. The lack of a fundamental two-phase-flow database is hindering the development of accurate two-phase-flow models required in more advanced reactor designs. In response to this challenge, first-principles–based numerical simulations are emerging as an attractive alternative to produce a complementary data source along with experiments. Leveraged by the unprecedented computing power offered by state-of-the-art supercomputers, direct numerical simulation (DNS), coupled with interface tracking methods, is becoming a practical tool to investigate some of the most challenging engineering flow problems. In the presented research, turbulent bubbly flow is simulated via DNS in single PWR subchannel geometries with auxiliary structures (e.g., supporting spacer grid and mixing vanes). The geometric effects these structures exert on the bubbly flow are studied with both a conventional time-averaging approach and a novel dynamic bubble tracking method. Lastly, the new insights obtained will help inform better two-phase models that can contribute to safer and more efficient nuclear reactor systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Two-Phase Turbulent Kinetic Energy Budget Computation in Co-Current Taylor Bubble Flow

Simulation of two-phase flows is relevant for reactor design and safety at normal operation or during accident scenarios. Often, the two-phase flow is in a regime in which slugs are formed or where the flow stratifies. Modeling such situations using standard single-phase Reynolds-averaged Navier-Stokes (RANS) turbulence models fails due to an overestimation of the eddy viscosity at the resolved two-phase interface. To solve this, an ad hoc turbulence damping term has been proposed in the literature that reduces the turbulence production locally at a two-phase interface, analogously to turbulence wall functions. However, this approach must be tailored to the specific setting and does not consider physical contributions such as surface tension or flow topology. Therefore, the problem of two-phase interfacial turbulence must be studied more in-depth. In this work, we consider co-current turbulent Taylor bubble flow using high-fidelity numerical simulation. The Basilisk code is used to simulate a Taylor bubble rising in a vertical pipe. By simulating the bubble in a moving frame of reference, we may study the turbulent kinetic energy (TKE) budgets ahead of the bubble, in its wake, and across the interface. The implementation of the TKE budget computation and the underlying averaging techniques are validated for the single-phase region ahead of the Taylor bubble using reference direct numerical simulation data. The analysis of the TKE budgets in the setting of Taylor bubble flow allows for the study of how turbulence behaves due to the presence of a two-phase interface and, in turn, supports the improvement of two-phase RANS models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

Measurement of interfacial structures in horizontal air-water bubbly flows

In order to predict multi-dimensional phenomena in nuclear reactor systems, methods relying on computational fluid dynamics (CFD) codes are essential. However, to be applicable in assessing thermal-hydraulic safety, these codes must be able to accurately predict the development of two-phase flows. Therefore, before practical application these codes must be assessed using experimental databases that capture multi-dimensional phenomena. While a large database exists that can be employed to assess predictions in vertical flows, the available database for horizontal flows is significantly lacking. Therefore, the current work seeks to develop an additional database in air-water horizontal bubbly flow through a 38.1 mm ID test section with a total development length of approximately 250 diameters. The experimental conditions are chosen to cover a wide range of the bubbly flow regime based upon flow visualization using a high-speed video camera. A database of local time-averaged void fraction, bubble velocity, interfacial area concentration, and bubble Sauter mean diameter are acquired throughout the pipe cross-section using a four-sensor conductivity probe. To investigate the evolution of the flow, measurements are made at axial locations of 44, 116, and 244 diameters downstream of the inlet. In the current work, only measurements obtained at L/D = 244 are presented. It is found that increasing the liquid superficial velocity tends to reduce both the bubble size and the degree of bubble packing near the upper wall. However, it is observed that the position of the maximum void fraction value remains nearly constant and is located approximately one bubble diameter away from the upper wall. It is also found that the bubble velocity exhibits a power law behavior resembling a single phase liquid turbulent velocity profile. Moreover, the local bubble velocity tends to decrease as the local void fraction increases. Conversely, increasing the gas superficial velocity is found to have little effect on the bubble size or velocity, but increases the bubble packing near the upper pipe wall. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

DEMONSTRATION OF A DATA-DRIVEN PHYSICS-BASED APPROACH FOR COMPUTATIONALLY EFFICIENT CFD PREDICTION OF TWO-PHASE BUBBLY FLOW

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale physics-guided data-driven approach, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. By defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

42 ENGINEERING↗
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Surfactant stabilized bubbles flowing in a Newtonian fluid

Bubbles suspended in a fluid cause the suspension to have different rheological properties than the base fluid. In general, the viscosity of the suspension increases as the volume fraction of the bubbles is increased. A current application, and motivation for this study, is in wellbore cements used for hydrocarbon extraction and carbon sequestration. In these settings, the gas bubbles are dispersed into the cement to reduce the density as well as improve the properties for specific conditions or wellbore issues. In this paper, we use Stokesian dynamics to numerically simulate the behavior of a large number of bubbles suspended in a Newtonian fluid. Going beyond prior work on simulating particles in suspension, we account for the nature of bubbles by allowing for slip on the bubble surface, the deflection on the bubble surface, and a bubble–bubble pairwise interaction that represents the surfactant physics; we do not account for bubble compressibility. We incorporate these interactions and simulate bubble suspensions of monodisperse size at several volume fractions. We find that the bubbles remain better dispersed compared with hard spherical particles that show a greater tendency to structure or cluster.

Rosenbaum, Eilis↗
DOE OSTI2021

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗
NASA NTRS2023

Hydrodynamics of bubble flow through a porous medium with applications to packed bed reactors

Gas-liquid flows through packed bed reactors (PBRs) are challenging to predict due to the tortuous flow paths that fluid interfaces must traverse. Experiments at the International Space Station showed that bubble and pulse flows are predominately observed under microgravity conditions, while the trickle and spray flows observed under terrestrial conditions are not present in microgravity. To understand the physics behind the former experiments, we simulate bubble flow through a PBR for different packing-particle-diameter-based Weber numbers and under different gravity conditions. We demonstrate different pore-scale mechanisms, such as capillary entrapment, buoyancy entrapment, and inertia-induced bubble displacement. Then, we perform a quantitative analysis by introducing new dynamic scales, dependent upon the evolving gas-liquid interfacial area, to understand the dynamic trade-offs between the inertia, capillary, and buoyancy forces on a bubble passing through a PBR. This analysis leads us to define new dimensionless Weber-like numbers that delineate bubble entrapment from bubble displacement.

Pranay P Nagrani↗
NASA NTRS1992

Helium bubble flow visualization of the spanwise separation on a NACA 0012 with simulated glaze ice

Research was performed to experimentally visualize and document the flow separation due to simulated glaze ice accretion on a NACA 0012 semispan with 30 deg sweep using helium bubbles as flow tracers. Results are compared to Navier-Stokes computational simulations for different angles of attack. Prior to acquiring data for the semispan model, a two dimensional experiment was conducted to determine the accuracy of using the helium bubbles as flow tracers. Results from the three dimensional experiment compare well to the computational simulations.

Kerho, M.↗
NASA NTRS1992

Helium bubble flow visualization of the spanwise separation on a NACA 0012 with simulated glaze ice

Research has been performed to experimentally visualize and document the flow separation due to simulated glaze ice accretion on a NACA 0012 semispan with 30-deg sweep using helium bubbles as flow tracers. Results are compared to Navier-Stokes computational simulations for different angles of attack. Prior to acquiring data for the semispan model, a two-dimensional experiment was conducted to determine the accuracy of using the helium bubbles as flow tracers. Results from the 3D experiment compare well to the computational simulations.

Kerho, M.↗
NASA NTRS1978

Bubbly flow model for the dynamic characteristics of cavitating pumps

The recent experimental transfer matrices obtained by Ng and Brennen (1978) for some axial flow pumps revealed some dynamic characteristics which were unaccounted for by any existing theoretical analysis; their visual observations suggested that the bubbly cavitating flow in the blade passages could be responsible for these effects. A theoretical model of the dynamic response of this bubbly blade-passage flow is described in the present paper. Void-fraction fluctuations in this flow result not only from pressure fluctuations but also because the fluctuating angle of attack causes fluctuations in the rate of production of bubbles near the leading edge. The latter causes kinematic waves which interact through the boundary conditions with the dynamic waves caused by pressure fluctuation. The resulting theoretical transfer functions which results are in good qualitative agreement with the experiments; with appropriate choices of two parameters good quantitative agreement is also obtained. The theoretical model also provides one possible explanation of the observation that the pump changes from an essentially passive dynamic element in the absence of cavitation to a progressively more active element as the extent of cavitation increases.

Brennen, C.↗