Predictions for isobaric collisions at s N N = 200 GeV from a multiphase transport model
Not Available
Deng, Wei-Tian↗
SEARCH · Engineering Papers
Results for “Multiphase”
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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Partitioning of rare earths in multiphase nuclear waste glass-ceramics
Not provided.
Materials Science↗
A proximity‐based image‐processing algorithm for colloid assignment in segmented multiphase flow datasets
Summary Colloidal transport and deposition are of both environmental and engineering importance. Easier access to x‐ray microtomography (XMT) coupled with improved imaging resolution has made XMT a unique and viable tool for visualizing and quantifying these processes. Currently, there is scant information in the literature addressing colloid segmentation and analysis in saturated and unsaturated porous media, in particular related to spatial partitioning of colloids. To support this need, an approach to assign segmented colloidal particles and aggregates to different partitioning classes based on their proximity to different phases is presented here. The method uses different markers for each attachment site (e.g. wetting‐nonwetting phase interfaces). An example XMT dataset from a drainage experiment is used to demonstrate the efficacy of the image processing algorithms. Flow conditions, and fluid and colloid properties, can thus be compared to the behaviour of colloids within the porous medium. This algorithm can help elucidate colloidal deposition mechanisms and the importance of different attachment sites, explore the importance of fluid properties, as well as the arrangement and shape of the colloids.
BRUECK, C. L.↗
Next-generation Multiphase flow solver for Fluidized bed Applications.
Abstract not provided.
Kotteda, V M Krushnarao↗
Practical aspects and uncertainty analysis of biological effective dose (BED) regarding its three-dimensional calculation in multiphase radiotherapy treatment plans
Purpose: There is a growing interest in the radiation oncology community to use the biological effective dose (BED) rather than the physical dose (PD) in treatment plan evaluation and optimization due to its stronger correlation with radiobiological effects. Radiotherapy patients may receive treatments involving a single only phase or multiple phases (e.g., primary and boost). Since most treatment planning systems cannot calculate the analytical BED distribution in multiphase treatments, an approximate multiphase BED expression, which is based on the total physical dose distribution, has been used. The purpose of this paper is to reveal the mathematical properties of the approximate BED formulation, relative to the true BED. Methods: The mathematical properties of the approximate multiphase BED equation are analyzed and evaluated. In order to better understand the accuracy of the approximate multiphase BED equation, the true multiphase BED equation was derived and the mathematical differences between the true and approximate multiphase BED equations were determined. The magnitude of its inaccuracies under common clinical circumstances was also studied. All calculations were performed on a voxel-by-voxel basis using the three-dimensional dose matrices. Results: Results showed that the approximate multiphase BED equation is accurate only when the dose-per-fractions (DPFs) in both the first and second phases are equal, which occur when the dose distribution does not significantly change between the phases. In the case of heterogeneous dose distributions, which significantly vary between the phases, there are fewer occurrences of equal DPFs and hence the inaccuracy of the approximate multiphase BED is greater. These characteristics are usually seen in the dose distributions being delivered to organs at risk rather than to targets. Conclusions: The finding of this study indicates that the true multiphase BED equation should be implemented in the treatment planning systems due to the inconsistent accuracy of the approximate multiphase BED equation in most of the clinical situations.
60 APPLIED LIFE SCIENCES↗
A consistent and conservative volume distribution algorithm and its applications to multiphase flows using Phase-Field models
In the present study, the multiphase volume distribution problem, where there can be an arbitrary number of phases, is addressed using a consistent and conservative volume distribution algorithm. The proposed algorithm satisfies the summation constraint, the conservation constraint, and the consistency of reduction. The first application of the volume distribution algorithm is to determine the Lagrange multipliers in multiphase Phase-Field models that enforce the mass conservation, and a multiphase conservative Allen-Cahn model that satisfies the consistency of reduction is developed. A corresponding consistent and conservative numerical scheme is developed for the model. The multiphase conservative Allen-Cahn model has a better ability than the multiphase Cahn-Hilliard model to preserve under-resolved structures. The second application is to develop a numerical procedure, called the boundedness mapping, to map the order parameters, obtained numerically from a multiphase model, into their physical interval, and at the same time to preserve the physical properties of the order parameters. Along with the consistent and conservative schemes for the multiphase Phase-Field models, the numerical solutions of the order parameters are reduction consistent, conservative, and bounded, which are theoretically analyzed and numerically validated. Then, the multiphase Phase-Field models are coupled with the momentum equation by satisfying the consistency of mass conservation and the consistency of mass and momentum transport, thanks to the consistent formulation. Finally, it is demonstrated that the proposed model and scheme converge to the sharp-interface solution and are capable of capturing the complicated multiphase dynamics even when there is a large density and/or viscosity ratio.
42 ENGINEERING↗
Multiphase flow and phase change in microgravity: Fundamental research and strategic research for exploration of space
NASA is preparing to undertake science-driven exploration missions. The NASA Exploration Team's vision is a cascade of stepping stones. The stepping-stone will build the technical capabilities needed for each step with multi-use technologies and capabilities. An Agency-wide technology investment and development program is necessary to implement the vision. The NASA Exploration Team has identified a number of areas where significant advances are needed to overcome all engineering and medical barriers to the expansion of human space exploration beyond low-Earth orbit. Closed-loop life support systems and advanced propulsion and power technologies are among the areas requiring significant advances from the current state-of-the-art. Studies conducted by the National Academy of Science's National Research Council and Workshops organized by NASA have shown that multiphase flow and phase change play a crucial role in many of these advanced technology concepts. Lack of understanding of multiphase flow, phase change, and interfacial phenomena in the microgravity environment has been a major hurdle. An understanding of multiphase flow and phase change in microgravity is, therefore, critical to advancing many technologies needed. Recognizing this, the Office of Biological and Physical Research (OBPR) has initiated a strategic research thrust to augment the ongoing fundamental research in fluid physics and transport phenomena discipline with research especially aimed at understanding key multiphase flow related issues in propulsion, power, thermal control, and closed-loop advanced life support systems. A plan for integrated theoretical and experimental research that has the highest probability of providing data, predictive tools, and models needed by the systems developers to incorporate highly promising multiphase-based technologies is currently in preparation. This plan is being developed with inputs from scientific community, NASA mission planners and industry personnel. The fundamental research in multiphase flow and phase change in microgravity is aimed at developing better mechanistic understanding of pool boiling and ascertaining the effects of gravity on heat transfer and the critical heat flux. Space flight experiments conducted in space have shown that nucleate pool boiling can be sustained under certain conditions in the microgravity environment. New space flight experiments are being developed to provide more quantitative information on pool boiling in microgravity. Ground-based investigations are also being conducted to develop mechanistic models for flow and pool boiling. An overview of the research plan and roadmap for the strategic research in multiphase flow and phase change as well as research findings from the ongoing program will be presented.
Singh, Bhim S.↗
Simulation of Multiphase Flow and Poromechanical Effects Around Injection Wells in CO 2 Storage Sites
In geological CO 2 storage operations, wellbore deformations and leakage pathways formations can occur around injection and abandoned wells subjected to high rates and long-term CO 2 injection. To guide engineering design and prevent CO 2 leakage risks, a full understanding of the underlying physics and robust numerical models is necessary to evaluate the response of underground formations in the near wellbore region and in the reservoir. In this study, a multi-scale and multi-physics open-source simulator (GEOS) is used to simulate multiphase flow and poromechanical deformations over time in three dimensions. The governing equations for mechanical deformations of the rock body and multiphase compositional fluid flow within the rock matrix are solved with a fully coupled finite element and finite volume approach. The Drucker–Prager model with friction hardening is applied to simulate elastoplastic deformation and a multiphase fluid model with power-law correlations for relative permeability is used to model the migration of CO 2 plume, which are coupled with numerical implicit scheme. Simulation results are verified against multiple analytical solutions for multiphase flow and wellbore problems, thus demonstrating the accuracy of this advanced simulator. In two engineering applications, here we highlight the impact of elastoplastic deformation and coupled modeling for assessing induced displacements and stress perturbations, which are more pronounced in the near wellbore regions. This work focuses on short-term processes in the vicinity of injection wells where stress evolutions, rock deformations and multiphase compositional flow and transport are simulated jointly to ensure wellbore stability and prevent damage. This fully coupled geomechanical model can simulate multiphase flow and any associated poromechanical effects within the CO 2 storage site and in the surrounding formations. Such a large-scale, long-term, multi-physics simulation model is useful in many ways: it can guide operational decisions for CO 2 injection, assess the containment potential and risks of a site, and analyze the wellbore stability and integrity during and after CO 2 injection.
58 GEOSCIENCES↗
A consistent and conservative Phase-Field method for multiphase incompressible flows
In the present study, a consistent and conservative Phase-Field method, including both the model and scheme, is developed for multiphase flows with an arbitrary number of immiscible and incompressible fluid phases. The consistency of mass conservation and the consistency of mass and momentum transport are implemented to address the issue of physically coupling the Phase-Field equation, which locates different phases, to the hydrodynamics. These two consistency conditions, as illustrated, provide the “optimal” coupling because (i) the new momentum equation resulting from them is Galilean invariant and implies the kinetic energy conservation, regardless of the details of the Phase-Field equation, and (ii) failures of satisfying the second law of thermodynamics or the consistency of reduction of the multiphase flow model only result from the same failures of the Phase-Field equation but are not due to the new momentum equation. Physical interpretation of the consistency conditions and their formulations are first provided, and general formulations that are obtained from the consistency conditions and independent of the interpretation of the velocity are summarized. Then, the present consistent and conservative multiphase flow model is completed by selecting a reduction consistent Phase-Field equation. Several novel techniques are developed to inherit the physical properties of the multiphase flows after discretization, including the gradient-based phase selection procedure, the momentum conservative method for the surface force, and the general theorems to preserve the consistency conditions on the discrete level. Equipped with those novel techniques, a consistent and conservative scheme for the present multiphase flow model is developed and analyzed. The scheme satisfies the consistency conditions, conserves the mass and momentum, and assures the summation of the volume fractions to be unity, on the fully discrete level and for an arbitrary number of phases. All those properties are numerically validated. Finally, numerical applications demonstrate that the present model and scheme are robust and effective in studying complicated multiphase dynamics, especially for those with large-density ratios.
97 MATHEMATICS AND COMPUTING↗
Investigation of multiphase fluid imbibition in shale through synchrotron-based dynamic micro-CT imaging
While substantial advances were made in pore system characterization in shale in the past decade, understanding of fundamentals of multiphase fluid flow in shale remains limited. The complexity of multiphase fluid flow in shale is related to many factors including nanoscale to submicron-scale pore systems, differences in mineralogy and associated surface wettability, heterogeneity of these properties at different scales, and possible existence of microfractures. Previous work related to fluid flow, such as permeability measurement, spontaneous imbibition, and wettability analysis, includes many simplified assumptions/hypotheses with limited consideration of small-scale details. In addition, these studies were mostly focused on single-phase phenomena. Direct observation of multiphase fluid flow in shale showing small-scale details is highly desired. In this study, dynamic imaging using synchrotron-based micro-CT (computed microtomography) was conducted on two shale samples to investigate multiphase (oil and water) spontaneous imbibition. Here, the results revealed many details of multiphase flow in shale, including pore connectivity, porosity and permeability layered distribution, and wettability of microfractures and pores. At the same time, results illustrate the complexity of multiphase flow in shale and gaps in understanding that need further investigation.
58 GEOSCIENCES↗
Multiphase Simulations of the SLS Launch Environment
NASA’s Space Launch System (SLS), which will send astronauts back to the Moon in the next few years, is powered by four RS-25 engines and two RSRMV solid rocket boosters (SRBs). During launch the SLS propulsion system generates intense acoustics and other powerful waves, such as ignition overpressure (IOP) which, if unmitigated, have the potential to damage the vehicle and possibly cause loss of mission or crew. To protect the vehicle from these powerful waves, the SLS launch pad design includes an ignition overpressure/sound suppression (IOP/SS) system which sprays 270,000 gallons per minute of water very close to the SRB and RS-25 nozzles. The SRB and RS-25 engine plumes, and the proximity of the IOP/SS water, create a complex multiphase (gas and liquid) environment during the SLS ignition sequence. The interplay among these systems creates challenges related to water spray into/onto engine nozzles, potential debris transport, and additional transient loads due to strong plume-water interactions - all of which the SLS vehicle must be able to withstand. Prior to the Artemis I launch, the SLS multiphase liftoff environment was largely unknown due to differences from the Space Shuttle and other programs. Some data was available from tests of individual systems, but no integrated testing or analysis was available. Even post-launch analysis of Artemis I cannot provide a full understanding of the complex physics involved due to limited (or obstructed) camera views and instrumentation. Computational fluid dynamics (CFD) is being used to investigate the details of the multiphase environment which could not be measured, help comprehend the data gathered from the launch, and ultimately identify phenomena that are a concern for future flights. Project Details Engineers at NASA’s Marshall Space Flight Center (MSFC) have executed simulations using the Loci/STREAM-Volume of Fluid (VoF) multiphase CFD solver to understand this environment. Initial efforts successfully validated the CFD solver on various tests, giving confidence to simulate the SLS multiphase liftoff environment prior to the Artemis I launch. The CFD simulation of the SLS ignition sequence was conducted in three phases. First the IOP/SS water system was simulated for approximately 6 seconds to reach a quasi-steady state. Next, the RS-25 engine plumes were activated and held at full power for 1 second. Lastly, the SRB booster was activated and the simulation was carried out until just prior to vehicle motion. This simulation process mimics the conditions that exist at launch. Results and Impact The SLS ignition sequence simulation results provide deep understanding of the underlying physics occuring during launch. Observations from the simulation include reduction of water splashing into/onto the engine nozzles, change in angling of the dense water sheets, and the origin of the powerful ignition overpressure (IOP) wave. These observations directly inform the SLS program on subjects including plume-water induced side loads, debris transport, and the acoustic launch environment. Additionally, with post launch comparison of CFD observations to flight data, these tools can be applied to launch vehicles and environments other than SLS with confidence. Why HPC Matters The SLS ignition sequence CFD simulations are conducted on meshes up to hundreds of millions of cells on thousands of processors for weeks at a time. These simulations generate terabytes of data that must also be stored and archived for future use on HPC systems. Simply put, the CFD simulations would not be possible without NASA HPC resources. What’s Next Comparisons between the Artemis I flight data and the CFD simulations will be continued to both improve confidence in the CFD results and provide deeper understanding into the SLS multiphase launch environment. This will be used to provide insight for decision making for the first manned SLS flight, Artemis II. Future simulations will target new configurations of the SLS IOP/SS water required to support the more powerful variants of the SLS vehicle, such as Block 1B. Additionally, this capability provides NASA the ability to investigate launch environments for vehicles other than SLS to support other missions.
Travis Rivord↗
Experimental determination of the speciation, partitioning, and release of perrhenate as a chemical surrogate for pertechnetate from a sodalite-bearing multiphase ceramic waste form
A key component to closing the nuclear fuel cycle is the storage and disposition of nuclear waste in geologic systems. Multiphase ceramic waste forms have been studied extensively as a potential host matrix for nuclear waste. Understanding the speciation, partitioning, and release behavior of radionuclides immobilized in multiphase ceramic waste forms is a critical aspect of developing the scientific and technical basis for nuclear waste management. In this study, we evaluated a sodalite-bearing multiphase ceramic waste form (i.e., fluidized-bed steam reform sodium aluminosilicate [FBSR NAS] product) as a potential host matrix for long-lived radionuclides, such as technetium (99Tc). The FBSR NAS material consists primarily of nepheline (ideally NaAlSiO4), anion-bearing sodalites (ideally M8[Al6Si6O24]X2, where M refers to alkali and alkaline earth cations and X refers to monovalent anions), and nosean (ideally Na8[AlSiO4]6SO4). Bulk X-ray absorption fine structure analysis of the multiphase ceramic waste form, suggest rhenium (Re) is in the Re(VII) oxidation state and has partitioned to a Re-bearing sodalite phase (most likely a perrhenate sodalite Na8[Al6Si6O24](ReO4)2). Rhenium was added as a chemical surrogate for 99Tc during the FBSR NAS synthesis process. The weathering behavior of the FBSR NAS material was evaluated under hydraulically unsaturated conditions with deionized water at 90 ?C. The steady-state Al, Na, and Si concentrations suggests the weathering mechanisms are consistent with what has been observed for other aluminosilicate minerals and include a combination of ion exchange, network hydrolysis, and the formation of an enriched-silica surface layer or phase. The steady-state S and Re concentrations are within an order of magnitude of the nosean and perrhenate sodalite solubility, respectively. The order of magnitude difference between the observed and predicted concentration for Re and S may be associated with the fact that the anion-bearing sodalites contained in the multiphase ceramic matrix are present as mixed-anion sodalite phases. These results suggest the multiphase FBSR NAS material may be a viable host matrix for long-lived, highly mobilie radionuclides which is a critical aspect in the management of nuclear waste.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Semi-implicit method to solve compressible multiphase fluid flows without acoustic time step restrictions
A new 3D multiphase numerical capability is presented here for simulating multiphase flow regimes at all Mach numbers (M). The new method is a semi-implicit extension of the finite volume discrete equation method (DEM) of Chinnaya et al. (2004), which originally used explicit time-stepping. The capability is also developed to work with another extension of the DEM to moving grids for arbitrary Lagrangian-Eularian (ALE) methods detailed in Dunn (2011). Rather than solving all phase equations simultaneously, the DEM reduces the equations to a system of single-phase Riemann solves, where each phase has its own velocity and thermodynamic state. Exchanges between the phases are modeled through source terms accounting for the phase interactions. Furthermore, since the original multiphase scheme uses an explicit time-advancement scheme, it has time step restrictions dictated by the speed of sound, which limits the model's ability to simulate weakly compressible flows which typically need to be integrated for longer time periods. Here, we extend the current multiphase formulation by implementing a pressure-correcting step to enable implicit calculations and remove acoustic time step limitations. The new semi-implicit algorithm allows use of relatively large time steps compared to an explicit method. Validation and benefits of the new implicit time-step method are illustrated using several examples including weakly compressible flows and strong shock waves. The scheme presented here is general and may be used for a variety of applications which require capabilities for handling multiphase flow at a wide range of Mach numbers. However, the goal of this research is to simulate all stages of high energy explosions, including the shock formation (high Mach numbers) and evolution of the buoyant cloud (low Mach numbers).
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
A Scalable Multigrid Reduction Framework for Multiphase Poromechanics of Heterogeneous Media
Simulation of multiphase poromechanics involves solving a multiphysics problem in which multiphase flow and transport are tightly coupled with the porous medium deformation. To capture this dynamic interplay, fully implicit methods, also known as monolithic approaches, are usually preferred. The main bottleneck of a monolithic approach is that it requires solution of large linear systems that result from the discretization and linearization of the governing balance equations. Because such systems are nonsymmetric, indefinite, and highly ill-conditioned, preconditioning is critical for fast convergence. Recently, most efforts in designing efficient preconditioners for multiphase poromechanics have been dominated by physics-based strategies. Current state-of-the-art “black-box” solvers such as algebraic multigrid (AMG) are ineffective because they cannot effectively capture the strong coupling between the mechanics and the flow subproblems, as well as the coupling inherent in the multiphase flow and transport process. In this work, we develop an algebraic framework based on multigrid reduction (MGR) that is suited for tightly coupled systems of PDEs. Using this framework, the decoupling between the equations is done algebraically through defining appropriate interpolation and restriction operators. One can then employ existing solvers for each of the decoupled blocks or design a new solver based on knowledge of the physics. We demonstrate the applicability of our framework when used as a “black-box” solver for multiphase poromechanics. Here, we show that the framework is flexible to accommodate a wide range of scenarios, as well as efficient and scalable for large problems.
97 MATHEMATICS AND COMPUTING↗
A large deformation multiphase continuum mechanics model for shock loading of soft porous materials
A large deformation, coupled finite-element (FE) model is developed to simulate the multiphase response of soft porous materials subjected to high strain-rate loading. The approach is based on the theory of porous media (TPM) at large deformations. Simplifications to the one-dimensional regime studied in the numerical simulations follow. An overview of several different time integration schemes is presented for the purpose of solving the nonlinear dynamic coupled balance of momenta (mixture and fluid) and balance of mass of the mixture equations. Numerical examples are presented for (i) verification against closed-form analytical solutions assuming small loads, (ii) demonstrating large deformation effects at high strain-rate, and (iii) showing differences in deformations between a single-phase elastodynamics model with occluded compressible pore fluid and a multiphase poroelastodynamics model at high strain-rate. The multiphase model shows that the relative motion of the pore fluid significantly dampens the deformation response of the solid skeleton as compared to the single-phase model, and makes it possible to extract quantitative values for the stresses of the different constituents, thereby allowing one to form preliminary conclusions about the onset of damage in the solid skeleton. The novelty of the current work is developing a multiphase, large deformation, mixture theory numerical model for high strain-rate loading of soft porous materials. It was discovered that explicit, adaptive time-stepping Runge–Kutta schemes offer high accuracy at relatively low cost when compared to traditional implicit or explicit central difference time-stepping schemes for shock-like loadings. Here, shock viscosity is added to the mixture momentum balance equation to regularize the shock front, and a stabilization term is added to the mixture mass balance equation to stabilize equal order interpolation finite elements for the coupled finite element solution of multiphase materials.
Engineering↗
Asymmetric oligomerization state and sequence patterning can tune multiphase condensate miscibility
Endogenous biomolecular condensates, composed of a multitude of proteins and RNAs, can organize into multiphasic structures with compositionally distinct phases. This multiphasic organization is generally understood to be critical for facilitating their proper biological function. However, the biophysical principles driving multiphase formation are not completely understood. Here we use in vivo condensate reconstitution experiments and coarse-grained molecular simulations to investigate how oligomerization and sequence interactions modulate multiphase organization in biomolecular condensates. We demonstrate that increasing the oligomerization state of an intrinsically disordered protein results in enhanced immiscibility and multiphase formation. Interestingly, we find that oligomerization tunes the miscibility of intrinsically disordered proteins in an asymmetric manner, with the effect being more pronounced when the intrinsically disordered protein, exhibiting stronger homotypic interactions, is oligomerized. Our findings suggest that oligomerization is a flexible biophysical mechanism that cells can exploit to tune the internal organization of biomolecular condensates and their associated biological functions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Differentiable multiphase flow model for physics-informed machine learning in reservoir pressure management
Accurate subsurface reservoir pressure control is extremely challenging due to geological heterogeneity and multiphase fluid-flow dynamics. Predicting behavior in this setting relies on high-fidelity physics-based simulations that are computationally expensive. Yet, the uncertain, heterogeneous properties that control these flows make it necessary to perform many of these expensive simulations, which is often prohibitive. To address these challenges, we introduce a physics-informed machine learning workflow that couples a fully differentiable multiphase flow simulator, which is implemented in the DPFEHM framework with a convolutional neural network (CNN). The CNN learns to predict fluid extraction rates from heterogeneous permeability fields to enforce pressure limits at critical reservoir locations. By incorporating transient multiphase flow physics into the training process, our method enables more practical and accurate predictions for realistic injection-extraction scenarios compared to previous works. To speed up training, we pretrain the model on single-phase, steady-state simulations and then finetune it on full multiphase scenarios, which dramatically reduces the computational cost. We demonstrate that high-accuracy training can be achieved with fewer than three thousand full-physics multiphase flow simulations – compared to previous estimates requiring up to ten million. This drastic reduction in the number of simulations is achieved by leveraging transfer learning from much less expensive single phase simulations.
25 ENERGY STORAGE↗