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DOE OSTI2014

A New Analytic-Adaptive Model for EGS Assessment, Development and Management Support

To increase understanding of the energy extraction capacity of Enhanced Geothermal System(s) (EGS), a numerical model development and application project is completed. The general objective of the project is to develop and apply a new, data-coupled Thermal-Hydrological-Mechanical-Chemical (T-H-M-C) model in which the four internal components can be freely selected from existing simulation software without merging and cross-combining a diverse set of computational codes. Eight tasks are completed during the project period. The results are reported in five publications, an MS thesis, twelve quarterly, and two annual reports to DOE. Two US patents have also been issued during the project period, with one patent application originated prior to the start of the project. The “Multiphase Physical Transport Modeling Method and Modeling System” (U.S. Patent 8,396,693 B2, 2013), a key element in the GHE sub-model solution, is successfully used for EGS studies. The “Geothermal Energy Extraction System and Method" invention (U.S. Patent 8,430,166 B2, 2013) originates from the time of project performance, describing a new fluid flow control solution. The new, coupled T-H-M-C numerical model will help analyzing and designing new, efficient EGS systems.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

BHR equations re-derived with immiscible particle effects

Compressible and variable density turbulent flows with dispersed phase effects are found in many applications ranging from combustion to cloud formation. These types of flows are among the most challenging to simulate. While the exact equations governing a system of particles and fluid are known, computational resources limit the scale and detail that can be simulated in this type of problem. Therefore, a common method is to simulate averaged versions of the flow equations, which still capture salient physics and is relatively less computationally expensive. Besnard et al. [1] developed such a model for variable density miscible turbulence, where ensemble-averaging was applied to the flow equations to yield a set of filtered equations. Besnard et al. further derived transport equations for the Reynolds stresses, the turbulent mass flux, and the density-specific volume covariance, to help close the filtered momentum and continuity equations. We re-derive the exact BHR closure equations which include integral terms owing to immiscible effects. Physical interpretations of the additional terms are proposed along with simple models. The goal of this work is to extend the BHR model to allow for the simulation of turbulent flows where an immiscible dispersed phase is non-trivially coupled with the carrier phase.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Multiphase Modeling in a Parallel Plate Fluidized Bed Receiver for Concentrating Solar Power

A novel high temperature particle solar receiver is developed by using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a packed bed at the lower end, leaving the system from the bottom at a constant flow rate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built and a near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2K.

CSP↗

NASA NTRS1992

Potential pressurized payloads: Fluid and thermal experiments

Space Station Freedom (SSF) presents the opportunity to perform long term fluid and thermal experiments in a microgravity environment. This presentation provides perspective on the need for fluids/thermal experimentation in a microgravity environment, addresses previous efforts, identifies possible experiments, and discusses the capabilities of a proposed fluid physics/dynamics test facility. Numerous spacecraft systems use fluids for their operation. Thermal control, propulsion, waste management, and various operational processes are examples of such systems. However, effective ground testing is very difficult. This is because the effect of gravity induced phenomena, such as hydrostatic pressure, buoyant convection, and stratification, overcome such forces as surface tension, diffusion, electric potential, etc., which normally dominate in a microgravity environment. Hence, space experimentation is necessary to develop and validate a new fluid based technology. Two broad types of experiments may be performed on SSF: basic research and applied research. Basic research might include experiments focusing on capillary phenomena (with or without thermal and/or solutal gradients), thermal/solutal convection, phase transitions, and multiphase flow. Representative examples of applied research might include two-phase pressure drop, two-phase flow instabilities, heat transfer coefficients, fluid tank fill/drain, tank slosh dynamics, condensate removal enhancement, and void formation within thermal energy storage materials. In order to better support such fluid/thermal experiments on board SSF, OSSA has developed a conceptual design for a proposed Fluid Physics/Dynamics Facility (FP/DF). The proposed facility consists of one facility rack permanently located on SSF and one experimenter rack which is changed out as needed to support specific experiments. This approach will minimize the on-board integration/deintegration required for specific experiments. The FP/DF will have acceleration/vibration compensation, power and thermal interfaces, computer command/data collection, a video imaging system, and a portable glove box for operations. This facility will allow real-time astronaut interaction with the testing.

Swanson, Theodore D.↗

DOE OSTI2016

Efficient implicit LES method for the simulation of turbulent cavitating flows

We present a numerical method for efficient large-eddy simulation of compressible liquid flows with cavitation based on an implicit subgrid-scale model. Phase change and subgrid-scale interface structures are modeled by a homogeneous mixture model that assumes local thermodynamic equilibrium. Unlike previous approaches, emphasis is placed on operating on a small stencil (at most four cells). The truncation error of the discretization is designed to function as a physically consistent subgrid-scale model for turbulence. We formulate a sensor functional that detects shock waves or pseudo-phase boundaries within the homogeneous mixture model for localizing numerical dissipation. In smooth regions of the flow field, a formally non-dissipative central discretization scheme is used in combination with a regularization term to model the effect of unresolved subgrid scales. The new method is validated by computing standard single- and two-phase test-cases. Comparison of results for a turbulent cavitating mixing layer obtained with the new method demonstrates its suitability for the target applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

The impact of capillary heterogeneity on CO 2 flow and trapping across scales

Capillary heterogeneity has been identified over the last decade as a key control on subsurface CO 2 flow behavior during geological CO 2 sequestration. These heterogeneities can be formed in all sedimentary rocks, ranging from slight variations in the sand grain sizes to extensive sequences of interbedded sands, shales, and limestones. Capillary heterogeneity has been largely, although not entirely, overlooked in subsurface flow modeling because it is assumed to only directly influence fluid redistribution over scales of centimeters to meters. However, even small-scale fluid movements can result in dramatic impacts on the mobility and trapping of the CO 2 over kilometers. Therefore, neglecting capillary heterogeneity at multiple scales could potentially lead to errors in modeling and predicting field-scale plume migration. In this review paper, we aim to provide a consistent overview to (1) establish that capillary heterogeneity can have a major impact on CO 2 plume migration, (2) establish the respective length scales at which capillary heterogeneity matters, and (3) provide guidance for numerical modeling. This review covers pertinent literature and extracts key observations from the core to the field scales. Experimental studies have shown that millimeter-decimeter scale capillary heterogeneity can cause the so-called capillary heterogeneity trapping in addition to pore-scale residual trapping. Even at such a small scale, capillary heterogeneity can already lead to complex upscaled constitutive relationships, such as flow-rate dependent and anisotropic relative permeability, which affects field-scale CO 2 migration even when field-scale heterogeneities are present. Under gravity-dominated flow regimes, centimeter-meter scale capillary heterogeneity can entrap a significant amount of CO 2 at field scale, not just after imbibition but also during drainage. In certain cases, the presence of capillary heterogeneity can even completely stop the vertical movement of the CO 2 plume, hence greatly reducing leakage risks. At meter-kilometer scale, the influence of capillary heterogeneity is more pronounced and can hinder or redirect CO 2 migration in both lateral and vertical directions. The impact of capillary heterogeneity across multiple spatial scales poses a great challenge in modeling CO 2 migration at field scale, because it is practically impossible to build a field-scale earth model with grid blocks at millimeter scale. We recommend a hierarchical modeling approach to address this challenge. At field scale, earth models are built to capture geological features and heterogeneities in high but still practical grid resolutions. For each facies or rock type of the field-scale model, high- resolution meter-scale “conceptual” models are built with millimeter-scale grid blocks to capture representative fine-scale bedding geometries and heterogeneities in various environments of deposition, bridging the gap from subcore scale to the size of a field-scale simulation grid block. Upscaling is then used to preserve the smaller-scale flow dynamics of various rock types in field-scale simulations. Here, future work is needed to (1) refine, improve, and validate the hierarchical modeling approach; (2) build libraries of fine-scale bedding models for facies in various environments of deposition; (3) quantify multiscale capillary heterogeneity effects under subsurface uncertainties; (4) gain learning from different storage formations; and (5) establish best practices that balance accuracy and computational speed.

Capillary heterogeneity↗

DOE OSTI2017

Verification of bubble tracking method and DNS examinations of single- and two-phase turbulent channel flows

Direct numerical simulation (DNS) has been regarded as a reliable data source for the development and validation of turbulence models along with experiments. The realization of DNS usually involves a very fine mesh that should be able to resolve all relevant turbulence scales down to Kolmogorov scale [1]. As the most computationally expensive approach compared to other CFD techniques, DNS applications used to be limited to flow studies at very low Reynolds numbers. Thanks to the tremendous growth of computing power over the past decades, the simulation capability of DNS has now started overlapping with some of the most challenging engineering problems. One of those examples in nuclear engineering is the turbulent coolant flow inside reactor cores. Coupled with interface tracking methods (ITM), the simulation capability of DNS can be extended to more complicated two-phase flow regimes. Departure from nucleate boiling (DNB) is the limiting critical heat flux phenomena for the majority of accidents that are postulated to occur in pressurized water reactors (PWR) [2]. As one of the major modeling and simulation (M&S) challenges pursued by CASL, the prediction capability is being developed for the onset of DNB utilizing multiphase-CFD (M-CFD) approach. DNS (coupled with ITM) can be employed to provide closure law information for the multiphase flow modeling at CFD scale. In the presented work, research groups at NCSU and UND will focus on applying different ITM to different geometries. Higher void fraction flow analysis at reactor prototypical conditions will be performed, and novel analysis methods will be developed, implemented and verified for the challenging flow conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

Artificial Neural Network Representation of Dynamic Criticality Excursion Experiment Data

This paper outlines time dependent considerations in applying the artificial neural network (ANN) paradigm to dynamic nuclear criticality excursion experiment data. The ANN amongst a variety of uses, can apply to function fitting of multiple input-multiple output data sets, pattern recognition, cluster analysis, and time series prediction. The ANN is a component of Machine Learning (ML) data analysis. The practical application of ML to criticality safety has been funded through the Y-12 Plant Directed Research and Demonstration (PDRD) program to support criticality safety and emergency planning efforts. The initial effort considered function fitting of criticality excursion data. Recent efforts successfully extended the ANN to criticality safety code validation. The initial ANN work applied to criticality excursions centered around multivariate function fitting of static (tabular) data taken from the French Consequences Radiologiques d'un Accident de Criticite (CRAC) and SILENE reactor campaigns. The former report (LeCorche) summarized important tabular data for the first 44 CRAC experiments. The initial ANN was trained to specific time-independent inputs, then applied to predict peak fission rate and total fissions for a wide variety of fissile solutions process conditions. This work extends that effort to apply the ANN paradigm to dynamic prediction of time-dependent criticality excursion experiment data. A dynamic criticality excursion in fissile solution represents a complex multiphysics phenomenon. Factors include among other things, coupled neutronic, multiphase fluid flow, temperature, pressure, acoustic shock, boiling heat transfer, reactivity feedback, and radiolytic gas considerations. There have been many efforts to model (over time) as coupled ordinary and (space) as partial differential equations (ODE, PDE). The ANN representation noted here does not rely on solving explicit ODE or PDEs. Rather the intent is to demonstrate that as a time series, the criticality excursion can be predicted by training specific ANN architectures to experimental input and output time series exclusively. The rationale for extending this work to the time-dependent regime is important in developing a 'criticality excursion emulator' solely on the basis of learning characteristics from experiment dynamic data. An emulator is different than a computer code simulator driven by the solution of ODEs and PDEs given select 'tuning parameters' that match outputs to experiments. A criticality excursion emulator, derived exclusively from an ANN or ML, could predict most likely excursion characteristics, trained from historic dynamic experiment data, presented with input values within the range of those experiments. The work noted shows that generic time-series ANN architectures can be satisfactorily applied to the prediction of dynamic, extremely chaotic criticality excursion power given an initial time dependent input series. In reality, an excursion emulator could be driven by user-supplied initial (t=0), time independent or constant values to generate time dependent outputs. Thus ongoing work includes developing a custom ANN such that initial dynamic conditions would be predicted. Those results then serve as inputs to a customized ANN architecture currently in development. (author)

42 ENGINEERING↗

DOE OSTI2017

Predictive Model for Particle Residence Time Distributions in Riser Reactors. Part 1: Model Development and Validation

Here in this computational study, we model the mixing of biomass pyrolysis vapor with solid catalyst in circulating riser reactors with a focus on the determination of solid catalyst residence time distributions (RTDs). A comprehensive set of 2D and 3D simulations were conducted for a pilot-scale riser using the Eulerian-Eulerian two-fluid modeling framework with and without sub-grid-scale models for the gas-solids interaction. A validation test case was also simulated and compared to experiments, showing agreement in the pressure gradient and RTD mean and spread. For simulation cases, it was found that for accurate RTD prediction, the Johnson and Jackson partial slip solids boundary condition was required for all models and a sub-grid model is useful so that ultra high resolutions grids that are very computationally intensive are not required. Finally, we discovered a 2/3 scaling relation for the RTD mean and spread when comparing resolved 2D simulations to validated unresolved 3D sub-grid-scale model simulations.

09 BIOMASS FUELS↗

NASA NTRS1996

Multiphase Flow: The Gravity of the Situation

A brief survey is presented of flow patterns in two-phase, gas-liquid flows at normal and microgravity, the differences between them being explored. It seems that the flow patterns in zero gravity are in general much simpler than those in normal gravity with only three main regimes (namely bubbly, slug and annular flows) being observed. Each of these three regimes is then reviewed, with particular reference to identification of areas of study where investigation of flows at microgravity might not only be interesting in themselves, but also throw light on mechanisms at normal earth gravity. In bubbly flow, the main area of interest seems to be that of bubble coalescence. In slug flow, the extension of simple displacement experiments to the zero gravity case would appear to be a useful option, supplemented by computational fluid dynamics (CFD) studies. For annular flow, the most interesting area appears to be the study of the mechanisms of disturbance waves; it should be possible to extend the region of investigation of the onset and behavior of these waves to much low gas velocities where measurements are clearly much easier.

Hewitt, Geoffrey F.↗

DOE OSTI2019

Simulation of Boiling Two-Phase Flow in a Helical Coil Steam Generator Using the Spectral Element Code Nek-2P

To enable the design of a light water small modular reactor, the boiling flow inside a helical coil steam generator has been simulated with the two-fluid model in Nek-2P. Nek-2P is the multiphase branch of the spectral element code Nek5000. Details of the implementation of the two-fluid model and the included closure models are discussed. The presented closure models include interactions for momentum, heat, and mass transfer between phases. Models for the drag, lift, and turbulent dispersion forces are included. The complete model is fully consistent in the limits of both phasic volume fractions approaching zero and is able to simulate flows of dispersed vapor, continuous liquid, dispersed liquid, continuous vapor, or any combination thereof. The closure models and their implementation in Nek-2P have been validated by comparing to experimental data for a boiling flow, demonstrating excellent agreement. Results from the simulation of the helical coil indicate strong phasic separation driven by the effects of buoyancy and inertia. Finally, significant differences were observed in the results compared to simulations performed using Star-CCM+, although these differences were somewhat expected.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

250 kWth Pilot Testing in Support of a 10 MWe Coal-Direct Chemical Looping Demonstration Feasibility Study

The Coal-Direct Chemical Looping (CDCL) process is emerging as a promising technology capable of high efficiency for producing electricity with low cost for carbon capture. In the CDCL process, coal is fully combusted to form carbon dioxide (CO2) and water via reaction with Fe2O3-based oxygen-carrier particles in a moving-bed reducer reactor. During reaction with coal, the Fe2O3 is reduced to form a mixture of Fe and FeO. The reduced particles are then transported to the combustor reactor where they are re-oxidized with air. The oxidation of the Fe and FeO mixture generates heat that can be used to produce steam for power generation. Once the particles are fully regenerated, they are pneumatically recycled to the reducer reactor where another reduction-oxidation (Redox) cycle begins. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been developing the CDCL technology based on iron-based metal oxide particles circulating in a moving-bed reducer coupled with an entrained-flow combustor. As part of a Phase I effort of a DOE-sponsored project, B&W identified scale-up technology gaps for the coal-direct chemical looping reactor process, most of which fall under the moving-bed reactor design and operation. However, after the Phase I research, B&W concluded that the CDCL technology has the potential of generating electricity while meeting the DOE goals of greater than 90% CO2 capture and less than 35% increase in levelized cost of electricity (LCOE). B&W then moved to a Phase II project to design, build and demonstrate the CDCL technology at a 250 kWth capacity. B&W finished the construction and commissioning of the pilot test facility in 2017. The approach used to design a 250 kWth pilot-scale CDCL facility to investigate the technology gaps is presented. Important lessons from the commissioning activities that would transfer to commercial plant start-up are also shared. The findings from the test program are being incorporated into a Pre-FEED study for a 10 MWe large pilot demonstration. Under a separately-funded heat integration project, B&W and OSU are developing a multiphase computational fluid dynamic model (MFIX) of the combustor to quantify heat transfer to embedded steam generation surface, utilizing pinch analysis (ASPEN Energy Analyzer) to identify potential improvements of the heat integration scheme, and developing an integrated dynamic model (ProTRAX) of the steam turbine coupled with the chemical looping process to identify potential start-up and transient operation issues. Under an advanced control system for optimizing operation, B&W is supporting OSU to install a rules-based optimizer (B&W’s FocalPoint) on their 25 kWt bench-scale facility on the OSU West Campus. Finally, B&W and OSU were recently selected to perform a Phase I Feasibility study to evaluate installation of the 10 MWe pilot at the Dover Power & Light Municipal Power Plant in Dover, Ohio. The feasibility study includes compiling an Environmental Information Volume and generating a cost estimate for the design, construction and commissioning of the plant as well as lining up commitments from potential project participants and funding contributors. Updates on each project will be presented. The status of the technology development will be discussed. We focus on the progress made to date towards closing the technology gaps under each project.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

Final Report: Optimal Model Complexity in Geological Carbon Sequestration: A Response Surface Uncertainty Analysis

The critical component of a risk assessment study in evaluating GCS is an analysis of uncertainty in CO2 modeling. In such analyses, direct numerical simulation of CO2 flow and leakage requires many time-consuming model runs. Alternatively, analytical methods have been developed which allow fast and efficient estimation of CO2 storage and leakage, although restrictive assumptions on formation rock and fluid properties are employed. In this study, an intermediate approach is proposed based on the Design of Experiment and Response Surface methodology, which consists of using a limited number of numerical simulations to estimate a prediction outcome as a combination of the most influential uncertain site properties. The methodology can be implemented within a Monte Carlo framework to efficiently assess parameter and prediction uncertainty while honoring the accuracy of numerical simulations. The choice of the uncertain properties is flexible and can include geologic parameters that influence reservoir heterogeneity, engineering parameters that influence gas trapping and migration, and reactive parameters that influence the extent of fluid/rock reactions. The method was tested and verified on modeling long-term CO2 flow, non-isothermal heat transport, and CO2 dissolution storage by coupling two-phase flow with explicit miscibility calculation using an accurate equation of state that gives rise to convective mixing of formation brine variably saturated with CO2. All simulations were performed using three-dimensional high-resolution models including a target deep saline aquifer, overlying caprock, and a shallow aquifer. To evaluate the uncertainty in representing reservoir permeability, sediment hierarchy of a heterogeneous digital stratigraphy was mapped to create multiple irregularly shape stratigraphic models of decreasing geologic resolutions: heterogeneous (reference), lithofacies, depositional environment, and a (homogeneous) geologic formation. To ensure model equivalency, all the stratigraphic models were successfully upscaled from the reference heterogeneous model for bulk flow and transport predictions (Zhang & Zhang, 2015). GCS simulation was then simulated with all models, yielding insights into the level of parameterization complexity that is needed for the accurate simulation of reservoir pore pressure, CO2 storage, leakage, footprint, and dissolution over both short (i.e., injection) and longer (monitoring) time scales. Important uncertainty parameters that impact these key performance metrics were identified for the stratigraphic models as well as for the heterogeneous model, leading to the development of reduced/simplified models at lower characterization cost that can be used for the reservoir uncertainty analysis. All the CO2 modeling was conducted using PFLOTRAN – a massively parallel, multiphase, multi-component, and reactive transport simulator developed by a multi-laboratory DOE/SciDAC (Scientific Discovery through Advanced Computing) project (Zhang et al., 2017, in review). Within the uncertainty analysis framework, increasing reservoir depth were investigated to explore its effect on the uncertainty outcomes and the potential for developing gravity-stable injection with increased storage security (Dai et al., 20126; Dai et al., 2017, in review). Finally, to accurately model CO2 fluid-rock reactions and resulting long-term storage as secondary carbonate minerals, a modified kinetic rate law for general mineral dissolution and precipitation was proposed and verified that is invariant to a scale transformation of the mineral formula weight. This new formulation will lead to more accurate assessment of mineral storage over geologic time scales (Lichtner, 2016).

58 GEOSCIENCES↗

DOE OSTI2023

A Conservative Finite-Volume Based Interface-Tracking Algorithm Using the Signed Distance Function

Methods for tracking an interface between two fluid phases are developed to ensure desired fluid properties, conservation, and stability are preserved in a finitevolume (FV) discretization. Here, the interface is tracked using a level set method where the signed distance function implicitly defines the interface. Marching methods are used to evaluate the value of the signed distance function, including a novel initialization method to initialize any implicit function to the signed distance function around sharp corners in the level set. Global conservation and consistency with a set of governing equations is enforced by a compression coefficient that measures the volumetric compression or expansion due to inaccuracies in the level set evaluation. A redistribution method is integrated into the volume correction to eliminate the small-cell instability while maintaining global conservation. This suite of methods is implemented and tested using static uniform velocity, and potential flow cases with multiple interface geometries. Results show these methods achieve up to second order accuracy, and are conservative. The application for these methods is intended to track the interface of a 3D printing filament in a finite-volume discretization of the all-speed Navier-Stokes equations.

42 ENGINEERING↗

DOE OSTI2018

Update on Design of 10 MWe Iron-Based Coal Direct Chemical Looping Demonstration Plant

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2018

A two-phase mixing layer between parallel gas and liquid streams: multiphase turbulence statistics and influence of interfacial instability

The two-phase mixing layer formed between parallel gas and liquid streams is an important fundamental problem in turbulent multiphase flows. The problem is relevant to many industrial applications and natural phenomena, such as air-blast atomizers in fuel injection systems and breaking waves in the ocean. The velocity difference between the gas and liquid streams triggers an interfacial instability which can be convective or absolute depending on the stream properties and injection parameters. In the present study, a direct numerical simulation of a two-phase gas–liquid mixing layer that lie in the absolute instability regime is conducted. A dominant frequency is observed in the simulation and the numerical result agrees well with the prediction from viscous stability theory. As the interfacial wave plays a critical role in turbulence transition and development, the temporal evolution of turbulent fluctuations (such as the enstrophy) also exhibits a similar frequency. To investigate the statistical response of the multiphase turbulence flow, the simulation has been run for a long physical time so that time-averaging can be performed to yield the statistically converged results for Reynolds stresses and the turbulent kinetic energy (TKE) budget. An extensive mesh refinement study using from 8 million to about 4 billions cells has been performed. The turbulent dissipation is shown to be highly demanding on mesh resolution compared with other terms in TKE budget. The results obtained with the finest mesh are shown to be close to converged results of turbulent dissipation which allow us to obtain estimations of the Kolmogorov and Hinze scales. The estimated Kolmogorov scale is found to be similar to the cell size of the finest mesh used here. The computed Hinze scale is significantly larger than the size of droplets observed and does not seem to be a relevant length scale to describe the smallest size of droplets formed in atomization.

Mechanics↗

DOE OSTI2014

Bayesian Treed Multivariate Gaussian Process with Adaptive Design: Application to a Carbon Capture Unit

Computer experiments (numerical simulations) are widely used in scientific research to study and predict the behavior of complex systems, which usually have responses consisting of a set of distinct outputs. The computational cost of the simulations at high resolution are often expensive and become impractical for parametric studies at different input values. To overcome these difficulties we develop a Bayesian treed multivariate Gaussian process (BTMGP) as an extension of the Bayesian treed Gaussian process (BTGP) in order to model and evaluate a multivariate process. A suitable choice of covariance function and the prior distributions facilitates the different Markov chain Monte Carlo (MCMC) movements. We utilize this model to sequentially sample the input space for the most informative values, taking into account model uncertainty and expertise gained. A simulation study demonstrates the use of the proposed method and compares it with alternative approaches. We apply the sequential sampling technique and BTMGP to model the multiphase flow in a full scale regenerator of a carbon capture unit. The application presented in this paper is an important tool for research into carbon dioxide emissions from thermal power plants.

Konomi, Bledar A.↗

DOE OSTI2019

Numerical Prediction of Oscillation Behaviors of a Multiphase Core–Shell Droplet During Interfacial Tension Measurement

Interfacial tension between molten high-temperature materials is to be measured using the electrostatic levitation furnace (ELF) and the electromagnetic levitator (ISS-EML) aboard the International Space Station. A levitated compound droplet of a concentric core–shell structure is excited either by an impulsive electromagnetic field or by a superimposed electrostatic field. The oscillation behavior of the compound droplet is analyzed to measure interfacial tension at the interface of the two phases. In support of the space experiments, a computational fluid dynamic model was developed to characterize the oscillation behavior of multiphase core–shell droplet. The developed model predicted the interfacial tension between molten copper-rich and cobalt-rich phases with a difference of 3.3 pct compared to the values reported in literature. The developed model is being utilized to investigate the influence of various test parameters on measured surface tension and also being extended for molten steel–molten slag systems.

36 MATERIALS SCIENCE↗