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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Exploring Whether Subsurface Fluid Production Can Minimize Triggered Seismicity in Geothermal Fields

Fluid injection and production related to energy recovery and other industrial operations alter the pressure and stress state of subsurface reservoirs which can lead to induced seismicity. Here, the primary goal is to investigate the hypothesis that the modulation of stress state in subsurface reservoirs through fluid injection/production operations can reduce the likelihood of inducing seismicity. Validation of this mitigation strategy will provide an active operational method to control induced seismicity in subsurface reservoir exploitations such as geothermal energy recovery and carbon storage. In this project, we analyze the relationship between extensive fluid production and the paucity of aftershock activity at the Coso Geothermal plant (CGP) following the 2019 Ridgecrest earthquake sequence, where high rates of aftershock triggering were expected. We developed a high-fidelity multiphase coupled thermo-hydro-mechanical (THM) model to simulate fluid injection/production activities at the CGP between 1986 and 2020. THM results of surface subsidence due to high rates of fluid production agree well with field observations from global positioning system (GPS) and interferometric synthetic aperture radar (InSAR). Subsequently, the variations of pore pressure, temperature and stress state were used to drive numerical earthquake simulations of the aftershock response to the 2019 Ridgecrest earthquakes. The earthquake simulations show that seismic quiescence may occur following the Ridgecrest event, depending on the initial stress state at the time of the mainshock and at the initiation of geothermal energy production. Seismic quiescence occurs in 20% of the cases we explored, where rates are decreased by 50% of the background rate in the two years following the mainshock. In circumstances where aftershock rates increase near the CGP following Ridgecrest, the average rate change is a factor of two larger than background rates from simulations with no operations. These findings indicate that unlike many other operations that bring faults closer to failure, operations at the CGP are acting to stabilize faults such that triggering in the current stress state is minimal.

58 GEOSCIENCES↗
DOE OSTI2013

Liquid and liquid–gas flows at all speeds

All speed flows and in particular low Mach number flow algorithms are addressed for the numerical approximation of the Kapila et al. [1] multiphase flow model. This model is valid for fluid mixtures evolving in mechanical equilibrium but out of temperature equilibrium and is efficient for material interfaces computation separating miscible and non-miscible fluids. In this context, the interface is considered as a numerically diffused zone, captured as well as all present waves (shocks, expansion waves). The same flow model can be used to solve cavitating and boiling flows [2]. Many applications occurring with liquid–gas interfaces and cavitating flows involve a very wide range of Mach number, from 10{sup −3} to supersonic (and even hypersonic) conditions with respect to the mixture sound speed. It is thus important to address numerical methods free of restrictions regarding the Mach number. To do this, a preconditioned Riemann solver is built and embedded into the Godunov explicit scheme. It is shown that this method converges to exact solutions but needs too small time steps to be efficient. An implicit version is then derived, first in one dimension and second in the frame of 2D unstructured meshes. Two-phase flow preconditioning is then addressed in the frame of the Saurel et al. [3] algorithm. Modifications of the preconditioned Riemann solver are needed and detailed. Convergence of both single phase and two-phase numerical solutions are demonstrated with the help of single phase and two-phase steady nozzle flow solutions. Last, the method is illustrated by the computation of real cavitating flows in Venturi nozzles. Vapour pocket size and instability frequencies are reproduced by the model and method without using any adjustable parameter.

42 ENGINEERING↗
DOE OSTI2020

Multiphase Reacting Flow Simulations and Optimization of Commercial-Scale Aerobic Bioreactors

Aerobic bioreactors are widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries, wherein microbial bioreactions aid in the conversion of sugars to macromolecules. These reactors are also being actively investigated as a cost-effective pathway for the production of low-value commodities such as biofuels and animal feed. Reactor scale-up is one of the important challenges when designing these systems. Gas and liquid phase transport, mass-transfer, and mixing physics at large length scales can significantly affect microbial conversion rates, particularly when the microbial reaction requires a narrow set of conditions. These phenomena are difficult to study in small-scale bench-top reactors that are typically well-mixed. Predictive computational fluid dynamics (CFD) based simulations can therefore aid in the design and optimization of these reactors. This work presents multiphase Euler-Euler CFD simulations of commercial-scale (~ 500 m3) aerobic bioreactors. Our mathematical model treats the gas and liquid as interpenetrating phases. This approach reduces the computational complexity of tracking individual gas bubbles that are several orders of magnitude smaller than reactor dimensions. We solve the Reynolds averaged Navier-Stokes (RANS) multiphase equations that account for phase and chemical species transport, interphase mass and momentum transfer and uses a phenomenological model for oxygen uptake by microbes. We use a customized solver derived from open-source CFD toolbox, OpenFOAM, to perform these simulations, which has been validated against small-scale reactors in our previous work. This work examines the performance of three different reactor designs, viz. bubble column reactor, airlift reactor with an internal draft tube, and a stirred-tank reactor with Rushton impellers. Reactor oxygen mass-transfer coefficient, gas hold-up, and oxygen distribution are critically analyzed among reactors, and sensitivity studies pertaining to gas flow rates and reactor geometry will be presented.

09 BIOMASS FUELS↗
DOE OSTI2017

Constrained reduced-order models based on proper orthogonal decomposition

A novel approach is presented to constrain reduced-order models (ROM) based on proper orthogonal decomposition (POD). The Karush–Kuhn–Tucker (KKT) conditions were applied to the traditional reduced-order model to constrain the solution to user-defined bounds. The constrained reduced-order model (C-ROM) was applied and validated against the analytical solution to the first-order wave equation. C-ROM was also applied to the analysis of fluidized beds. Lastly, it was shown that the ROM and C-ROM produced accurate results and that C-ROM was less sensitive to error propagation through time than the ROM.

42 ENGINEERING↗
DOE OSTI2026

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗
DOE OSTI2020

High pressure/high temperature multiphase simulations of dodecane injection to nitrogen: Application on ECN Spray-A

The present work investigates the complex phenomena associated with pressure/high temperature dodecane injection for the Engine Combustion Network (ECN) Spray-A case, employing more elaborate thermodynamic closures, to avoid well known deficiencies concerning density and speed of sound prediction using traditional cubic models. A tabulated thermodynamic approach is proposed here, based on log 10 (p)-T tables, providing very high accuracy across a large range of pressures, spanning from 0 to 2500 bar, with only a small number of interpolation points. The tabulation approach is directly extensible to any thermodynamic model, existing or to be developed in the future. Here NIST REFPROP properties are used, combined with PC-SAFT Vapor-Liquid-Equilibrium to identify the liquid in mixtures penetration, hence avoiding the use of an arbitrary threshold for mass fraction. Identified liquid and vapour penetration are compared against experimental data from the ECN database showing a good agreement, within approximately 3–8% for axial penetration of liquid, 2% for vapor axial penetration and within experimental uncertainty for radial distribution of mass fraction. Analysis of the vortex evolution indicates that driving mechanisms behind the jet break-up are vortex tilting/stretching, then baroclinic torque, leading to Rayleigh-Taylor instabilities, closely followed by vortex dilation and finally viscous effects.

42 ENGINEERING↗
DOE OSTI2020

Two-Phase Fluid Flow Properties of Rough Fractures With Heterogeneous Wettability: Analysis With Lattice Boltzmann Simulations

Fractures are conduits for fluid flow in low-permeability geological formations. Multiphase flow properties of fractures are important in natural processes and in engineering applications such as the evaluation of the sealing capacity of caprocks and productivity of hydrocarbon-bearing tight rocks. Investigations of flow and transport through fractures typically focus on the effects of fracture geometric and mechanical factors such as aperture, roughness, and compressibility. The wettability of the fracture surfaces and its influence on microscale interfacial phenomena and macroscale effective transport properties are seldom studied. In this study, we investigated the effect of heterogeneous wetting properties on the displacement of water by supercritical CO2 through a series of lattice Boltzmann method simulations. The results show the evolution of the CO2 plume within a fracture is controlled by both the roughness of the aperture field and the wetting distribution. We combined these factors into a capillary pressure map that can be related to the macroscopic flow behavior of the fracture. We observed that heterogeneous wetting distributions promote the residual trapping of water where lower capillary pressures allowed for isolated water pockets in higher capillary pressure zones. Analysis of fracture unsteady relative permeability shows the effect of wetting on permeability evolution and provides support for the viscous-coupling relative permeability model. Finally, analysis of the steady-state relative permeability and saturation demonstrates a strong correlation between permeability and the standard deviation of the capillary pressure field. Thus, characterizing the distribution of wetting properties of fractures is crucial to understanding multiphase fracture flow and transport properties.

58 GEOSCIENCES↗
DOE OSTI2020

A combined numerical and experimental study to elucidate primary breakup dynamics in liquid metal droplet-on-demand printing

Droplet-on-demand liquid metal jetting is emerging as a powerful technology for the additive manufacturing of metallic parts. The success of this method hinges on overcoming several technological challenges. Additionally, the principal one among these challenges is the controlled repeatable ejection of single uniform droplets. Due to the high density and surface tension of liquid metals, the droplet ejection process occurs near the minimal extremes of the printability phase diagram, defined by acceptable ranges for the Weber (We) and Ohnesorge (Oh) numbers. In this work, we experimentally demonstrate the satellite-free ejection of pneumatically actuated molten tin droplets in this extreme corner of printability and use a combination of high-speed video analysis and volume-of-fluid modeling to elucidate the droplet dynamics. While the simulations at low Oh and We can correctly describe several aspects of the breakup process, such as an increasing tail and pinch-point near the nozzle, no single parameter set can completely capture the droplet shape at breakup. Instead, the experimental droplet dynamics appear to include features from both high and low Oh breakup. This disagreement is ascribed to the incomplete description of the droplet ejection process including wetting and exit effects near the nozzle opening and surface effects such as transient cooling and oxide formation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Operator learning for predicting multiscale bubble growth dynamics

We report simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs). Herein, we develop a framework based on operator regression, the so-called deep operator network (DeepONet), with the long-term objective to simplify multiscale modeling by avoiding the fragile and time-consuming “hand-shaking” interface algorithms for stitching together heterogeneous descriptions of multiscale phenomena. To this end, as a first step, we investigate if a DeepONet can learn the dynamics of different scale regimes, one at the deterministic macroscale and the other at the stochastic microscale regime with inherent thermal fluctuations. Specifically, we test the effectiveness and accuracy of the DeepONet in predicting multirate bubble growth dynamics, which is described by a Rayleigh–Plesset (R–P) equation at the macroscale and modeled as a stochastic nucleation and cavitation process at the microscale by dissipative particle dynamics (DPD). First, we generate data using the R–P equation for multirate bubble growth dynamics caused by randomly time-varying liquid pressures drawn from Gaussian random fields (GRFs). Our results show that properly trained DeepONets can accurately predict the macroscale bubble growth dynamics and can outperform long short-term memory networks. We also demonstrate that the DeepONet can extrapolate accurately outside the input distribution using only very few new measurements. Subsequently, we train the DeepONet with DPD data corresponding to stochastic bubble growth dynamics. Although the DPD data are noisy and we only collect sparse data points on the trajectories, the trained DeepONet model is able to predict accurately the mean bubble dynamics for time-varying GRF pressures. Taken together, our findings demonstrate that DeepONets can be employed to unify the macroscale and microscale models of the multirate bubble growth problem, hence providing new insight into the role of operator regression via DNNs in tackling realistic multiscale problems and in simplifying modeling with heterogeneous descriptions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Impact of particle loading and phase coupling on gas–solid flow dynamics: A case study of a two-phase, gas–solid flow in an annular pipe

The present study is devoted to a two-phase, gas–solid flow in an annular pipe (hollow cylinder) at an elevated pressure of 15 bars and moderate Reynolds number of circa 6000. The influence of the particle loading, the interaction between the phases, and turbulence dispersion on the flow dynamics is systematically studied by means of computational fluid dynamics simulations, employing the Ansys FLUENT commercial package. The cases with a particle volumetric fraction of 1.2% are referred to as “high particle loading,” and those with 0.13% are denoted as “low particle loading.” The following cases are investigated: (1) pure gas flow; (2) low particle loading two-phase flow with one-way coupling and with turbulence dispersion; (3) low particle loading two-phase flow with two-way coupling but without turbulence dispersion; (4) low particle loading two-phase flow with two-way coupling and with turbulence dispersion; (5) high particle loading two-phase flow with one-way coupling and with turbulence dispersion; (6) high particle loading two-phase flow with two-way coupling but without turbulence dispersion; and (7) high particle loading two-phase flow with two-way coupling and with turbulence dispersion. Additionally, the boundary layer is found to grow without fluctuations of the turbulent kinetic energy (TKE) for cases 1, 2, and 5. For case 4, the TKE fluctuations have been identified, although they appear to be less substantial than those in cases 6 and 7. The authors attribute the semi-chaotic nature of the TKE fluctuations to the particle loading and two-way coupling. In addition, the onset and development of the flow instability have been observed at a random axial distance in cases 4, 6, and 7. Such instability is also attributed to the two-way coupling with turbulence dispersion in the flow. It is concluded that the particle loading, one-way, or two-way coupling between the phases, and the turbulence dispersion models significantly influence the development of the flow dynamics with the same inlet and boundary conditions. Consequently, it is not a trivial question, which result a user should trust. The present computational results inspire to perform verification as well as experimental validation of the simulations, so the simulation results can subsequently be used with confidence for design analysis.

42 ENGINEERING↗
DOE OSTI2022

Modeling of shock-induced force on an isolated particle in water and air

The prediction of force on an isolated particle, while a shock is passing over it, is an important problem in many natural and industrial applications. Although the flow monotonically changes from the pre-shock to the post-shock state, the particle's force has been observed to behave nonmonotonically with a sharp peak when the shock is located halfway across the particle. This nonmonotonic behavior is due to the unsteady nature of the compression and rarefaction waves that radiate as the shock diffracts around the particle and, therefore, cannot be predicted by a quasi-steady model. An accurate force model must account for the unsteady nature of the flow and the sharp discontinues in the flow properties across the shock. In this work, we test four different inviscid models and observe that the compressible Maxey–Riley–Gatignol (C-MRG) model is the most accurate based on comparison with results from particle-resolved inviscid simulations at two different Mach numbers for both water and air as the medium. The C-MRG model is first demonstrated to predict the force on a stationary particle accurately and then extended to capture the force on a moving particle. Numerical complexities regarding the implementation of the C-MRG model are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Machine learning accelerated turbulence modeling of transient flashing jets

We report modeling the sudden depressurization of superheated liquids through nozzles is a challenge because the pressure drop causes rapid flash boiling of the liquid. The resulting jet usually demonstrates a wide range of structures, including ligaments and droplets, due to both mechanical and thermodynamic effects. As the simulation comprises increasingly numerous phenomena, the computational cost begins to increase. One way to moderate the additional cost is to use machine learning surrogacy for specific elements of the calculation. This study presents a machine learning-assisted computational fluid dynamics approach for simulating the atomization of flashing liquids accounting for distinct stages, from primary atomization to secondary breakup to small droplets using the Σ - Y model coupled with the homogeneous relaxation model. Notably, the models for thermodynamic non-equilibrium (HRM) and Σ - Y are coupled, for the first time, with a deep neural network that simulates the turbulence quantities, which are then used in the prediction of superheated liquid jet atomization. The data-driven component of this method is used for turbulence modeling, avoiding the solution of the two-equation turbulence model typically used for Reynolds-averaged Navier-Stokes simulations for these problems. Both the accuracy and speed of the hybrid approach are evaluated, demonstrating adequate accuracy and at least 25% faster computational fluid dynamics simulations than the traditional approach. This acceleration suggests that perhaps additional components of the calculation could be replaced for even further benefit. Published under an exclusive license by AIP Publishing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Supo Thermal Model Development II

This report describes the continuation of the Computational Fluid Dynamics (CFD) model of the Supo cooling system described in the report, Supo Thermal Model Development1, by Cynthia Buechler. The goal for this report is to estimate the natural convection heat transfer coefficient (HTC) of the system using the CFD results and to compare those results to remaining past operational data. Also, the correlation for determining radiolytic gas bubble size is reevaluated using the larger simulation sample size. The background, solution vessel geometry, mesh, material properties, and boundary conditions are developed in the same manner as the previous report. Although, the material properties and boundary conditions are determined using the appropriate experiment results for each individual power level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

CFD Modeling of Cryogenic Chilldown in a Complex Channel under Normal and Low Gravity Conditions

Future NASA architectures have baselined cryogenic propulsion systems as well as cryogenic fluid management to support lunar missions and ultimately to support future missions to Mars. These missions will require chilling hardware down prior to engine restart as well as chilling lines and tanks prior to transferring and refueling these propulsion elements in orbit. In lieu of expensive tests conducted on-orbit, accurate predictive computational models of these chilldown processes can be used to reduce system and propellant mass as well as mission risk. To gain confidence in these computational models, appropriate anchoring and validation to experimental data in a relevant environment needs to be performed. Recent ground and sub-orbital flight experiments conducted by the Japan Aerospace Exploration Agency (JAXA) investigated chilldown of a complex channel resembling a turbopump bearing cavity at low flow rates. This work presents Computational Fluid Dynamics (CFD) model development of the chilldown experiment employing two-phase flow boiling models available in commercial CFD software STAR-CCM+ using Volume of Fluid (VOF) and the traditional Euler-Euler multiphase flow solvers. Comparisons of the numerical and experimental results under normal and low-gravity conditions are presented. An assessment of solid wall temperatures and phase distribution yielded important insights into multiphase solver choice, dependence on gravity environment, and challenges associated with cryogenic flow boiling prediction and validation.

CFD↗
DOE OSTI2018

Multiphase Large Eddy Simulation of a Pulsed Sieve-Plate Extraction Column - 18125

Presented here is research resulting from a framework of single-phase and multiphase modelling trials. These are intended to accurately simulate the internal flow phenomena arising in pulsed sieve-plate extraction columns representative of those found in industry. Three-dimensional unsteady flow calculations using large eddy simulation coupled with dynamic sub-grid scale modelling have been used to capture the transient effects of sinusoidal flow conditions using the open source CFD code OpenFOAM{sup R}. Multiphase interface interactions are modelled using the volume of fluid method with appropriate heavy and light phase fluidic properties capturing surface tension, density and viscous effects. The system studied consists of a 150 mm diameter column with two perforated plates with a fractional free area of 25 %, operational under 1 Hz pulsing frequency at a 50 mm amplitude and plate spacing of 300 mm. The materials simulated include water (single-phase) and 3 M nitric acid and dodecane / tributyl phosphate mixture at 30 vol% (multiphase). Results are compared with appropriate correlations from literature. The dispersive mixing efficiency of the system was also evaluated via a mixing index value which allows quantification of the ratio of rotational and irrotational flow components. This study has found that the predictive methods employed are effective at capturing the different scales of turbulence present within pulsed sieve-plate extraction columns, and its influence on their operation. As such, the work highlights the ability of large eddy simulation-based modelling to predict the complex flows in such column geometries. Furthermore, the techniques employed provide valuable insight into the hydrodynamic flow characteristics and mixing mechanisms arising within pulsed sieve-plate extraction columns. (authors)

42 ENGINEERING↗