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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Scalability of GlennICE in a Parallel Environment

GlennICE (Glenn Icing Computational Environment) is a comptational tool designed to calculate ice growth on complex three- dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for tractability in a practical engineering application. Although studies have demonstrated a reduction in the amount of work (memory footprint) required, research has yet to systematically investigate the effects of scaling GlennICE. This paper sets out to benchmark the scalability of GlennICE within a parallel environment and investigate if an increase in the number of processors result in a linear speed up.

Computational Icing↗
DOE OSTI2016

Comparisons of RELAP5-3D Analyses to Experimental Data from the Natural Convection Shutdown Heat Removal Test Facility

The Reactor Cavity Cooling System (RCCS) is an important passive safety system being incorporated into the overall safety strategy for high temperature advanced reactor concepts such as the High Temperature Gas- Cooled Reactors (HTGR). The Natural Convection Shutdown Heat Removal Test Facility (NSTF) at Argonne National Laboratory (Argonne) reflects a 1/2-scale model of the primary features of one conceptual air-cooled RCCS design. The project conducts ex-vessel, passive heat removal experiments in support of Department of Energy Office of Nuclear Energy’s Advanced Reactor Technology (ART) program, while also generating data for code validation purposes. While experiments are being conducted at the NSTF to evaluate the feasibility of the passive RCCS, parallel modeling and simulation efforts are ongoing to support the design, fabrication, and operation of these natural convection systems. Both system-level and high fidelity computational fluid dynamics (CFD) analyses were performed to gain a complete understanding of the complex flow and heat transfer phenomena in natural convection systems. This paper provides a summary of the RELAP5-3D NSTF model development efforts and provides comparisons between simulation results and experimental data from the NSTF. Overall, the simulation results compared favorably to the experimental data, however, further analyses need to be conducted to investigate any identified differences.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Thermophilic acetylxylan esterase genes and enzymes from alicyclobacillus acidocaldarius and related organisms and methods

A genetically modified organism comprising at least one nucleic acid sequence and/or at least one recombinant nucleic acid isolated from Alicyclobacillus acidocaldarius and encoding a polypeptide involved in at least partially degrading, cleaving, transporting, metabolizing, or removing polysaccharide, lignocellulose, hemicellulose, lignin, chitin, heteroxylan, and/or xylan-decorating group; and at least one nucleic acid sequence and/or at least one recombinant nucleic acid encoding a polypeptide involved in fermenting sugar molecules to a product. Additionally, enzymatic and/or proteinaceous extracts may be isolated from one or more genetically modified organisms. The extracts are utilized to convert biomass into a product. Further provided are methods of converting biomass into products comprising: placing the genetically modified organism and/or enzymatic extracts thereof in fluid contact with polysaccharides, cellulose, lignocellulose, hemicellulose, lignin, starch, sugars, sugar oligomers, carbohydrates, complex carbohydrates, chitin, heteroxylans, glycosides, and/or xylan-, glucan-, galactan-, or mannan-decorating groups.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

Thermal control for the 1990's

Current thermal distribution systems on large spacecraft, such as the Space Shuttle and Spacelab, use pumped fluid loops that circulate the coolant between a series of user stations and a single rejection point, involving complex plumbing and controls with a significant power penalty and limited reliability. In order to provide heat transport at near-isothermal conditions in future large spacecraft, two-phase flow systems will be implemented by taking advantage of the heat of vaporization and condensation of common working fluids at minimal expenditure of power and temperature variation. Such systems are considered for the cases of the thermal requirements of nearly 100 potential astrophysics and astronomy instruments. Data on temperature requirements, power dissipations, environmental fluxes, heat addition or rejection, and general description, are used to form conceptual designs for the thermal utility.

Ollendorf, S.↗
NASA NTRS1994

An analysis code for the Rapid Engineering Estimation of Momentum and Energy Losses (REMEL)

Nonideal behavior has traditionally been modeled by defining efficiency (a comparison between actual and isentropic processes), and subsequent specification by empirical or heuristic methods. With the increasing complexity of aeropropulsion system designs, the reliability of these more traditional methods is uncertain. Computational fluid dynamics (CFD) and experimental methods can provide this information but are expensive in terms of human resources, cost, and time. This report discusses an alternative to empirical and CFD methods by applying classical analytical techniques and a simplified flow model to provide rapid engineering estimates of these losses based on steady, quasi-one-dimensional governing equations including viscous and heat transfer terms (estimated by Reynold's analogy). A preliminary verification of REMEL has been compared with full Navier-Stokes (FNS) and CFD boundary layer computations for several high-speed inlet and forebody designs. Current methods compare quite well with more complex method results and solutions compare very well with simple degenerate and asymptotic results such as Fanno flow, isentropic variable area flow, and a newly developed, combined variable area duct with friction flow solution. These solution comparisons may offer an alternative to transitional and CFD-intense methods for the rapid estimation of viscous and heat transfer losses in aeropropulsion systems.

Dechant, Lawrence J.↗
DOE OSTI2022

Fluid Dynamics of Axial Turbomachinery: Blade- and Stage-Level Simulations and Models

The current generation of axial turbomachines is the culmination of decades of experience, and detailed understanding of the underlying flow physics has been a key factor for achieving high efficiency and reliability. Driven by advances in numerical methods and relentless growth in computing power, computational fluid dynamics has increasingly provided insights into the rich fluid dynamics involved and how it relates to loss generation. This article presents some of the complex flow phenomena occurring in bladed components of gas turbines and illustrates how simulations have contributed to their understanding and the challenges they pose for modeling. The interaction of key aerodynamic features with deterministic unsteadiness, caused by multiple blade rows, and stochastic unsteadiness, i.e., turbulence, is discussed. High-fidelity simulations of increasingly realistic configurations and models improved with help of machine learning promise to further grow turbomachinery performance and reliability and, thus, help fluid mechanics research have a greater industrial impact.

Mechanics↗
DOE OSTI2014

Phase separation in solutions with specific and nonspecific interactions

Protein solutions, which tend to be thermodynamically stable under physiological conditions, can demix into protein-enriched and protein-depleted phases when stressed. Using a lattice-gas model of proteins with both isotropic and specific, directional interactions, we calculate the critical conditions for phase separation for model proteins with up to four patches via Monte Carlo simulations and statistical associating fluid theory. Given a fixed specific interaction strength, the critical value of the isotropic energy, which accounts for dispersion forces and nonspecific interactions, measures the stability of the solution with respect to nonspecific interactions. Phase separation is suppressed by the formation of protein complexes, which effectively passivate the strongly associating sites on the monomers. Nevertheless, we find that protein models with three or more patches can form extended aggregates that phase separate despite the assembly of passivated complexes, even in the absence of nonspecific interactions. We present a unified view of the critical behavior of model fluids with anisotropic interactions, and we discuss the implications of these results for the thermodynamic stability of protein solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

On the spatial distribution of magnetic fields on the solar surface

Recent measurements of solar surface magnetic fields suggest that the spatial distribution of these fields is fractal. In order to understand the physical basis for such geometric complexity, we study here the advection of magnetic flux tubes relatively simple random motions on the surface of a fluid and investigate the spatial statistics of the resulting surface field. While this study does not directly address the question of why solar surface fields have the observed spatial structure, it is designed to build our intuition about how surface flows lead to complex spatial structuring of magnetic fields. As part of our study, we discuss the various methods by which one can describe the spatial distribution of the surface magnetic flux and relate them mathematically; this turns out to be a crucial point of our work since, as we show, a number of previous analyses have misinterpreted the analysis procedures for determining fractal dimensions. Our principal result is the explicit demonstration that simple random flows lead to magnetic flux spatial distributions with a multifractal dimension spectrum. Furthermore, we demonstrate that this magnetic spatial structure is generic, i.e., is characteristic of a very large class of random flows.

Tao, L.↗
DOE OSTI2024

ExaWind: Open‐source CFD for hybrid‐RANS/LES geometry‐resolved wind turbine simulations in atmospheric flows

Abstract Predictive high‐fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and operational phenomena such as blade erosion, pitch‐control, stall/vortex‐induced vibrations, and aftermarket add‐ons. The biggest challenge with high‐fidelity modeling is the realization of numerical algorithms that can capture the relevant physics in detail through effective use of high‐performance computing. For modern supercomputers, that means relying on GPUs for acceleration. In this paper, we present ExaWind, a GPU‐enabled open‐source incompressible‐flow hybrid‐computational fluid dynamics framework, comprising the near‐body unstructured grid solver Nalu‐Wind, and the off‐body block‐structured‐grid solver AMR‐Wind, which are coupled using the Topology Independent Overset Grid Assembler. Turbine simulations employ either a pure Reynolds‐averaged Navier–Stokes turbulence model or hybrid turbulence modeling wherein Reynolds‐averaged Navier–Stokes is used for near‐body flow and large eddy simulation is used for off‐body flow. Being two‐way coupled through overset grids, the two solvers enable simulation of flows across a huge range of length scales, for example, 10 orders of magnitude going from O(μm) boundary layers along the blades to O(10 km) across a wind farm. In this paper, we describe the numerical algorithms for geometry‐resolved turbine simulations in atmospheric boundary layers using ExaWind. We present verification studies using canonical flow problems. Validation studies are presented using megawatt‐scale turbines established in literature. Additionally presented are demonstration simulations of a small wind farm under atmospheric inflow with different stability states.

17 WIND ENERGY↗
NASA NTRS1999

Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

Schallhorn, Paul↗
DOE OSTI2013

3D characterization of the Astor Pass geothermal system, Nevada

The Astor Pass geothermal system resides in the northwestern part of the Pyramid Lake Paiute Reservation, on the margins of the Basin and Range and Walker Lane tectonic provinces in northwestern Nevada. Seismic reflection interpretation, detailed analysis of well cuttings, stress field analysis, and construction of a 3D geologic model have been used in the characterization of the stratigraphic and structural framework of the geothermal area. The area is primarily comprised of middle Miocene Pyramid sequence volcanic and sedimentary rocks, nonconformably overlying Mesozoic metamorphic and granitic rocks. Wells drilled at Astor Pass show a ~1 km thick section of highly transmissive Miocene volcanic reservoir with temperatures of ~95°C. Seismic reflection interpretation confirms a high fault density in the geothermal area, with many possible fluid pathways penetrating into the relatively impermeable Mesozoic basement. Stress field analysis using borehole breakout data reveals a complex transtensional faulting regime with a regionally consistent west-northwest-trending least principal stress direction. Considering possible strike-slip and normal stress regimes, the stress data were utilized in a slip and dilation tendency analysis of the fault model, which suggests two promising fault areas controlling upwelling geothermal fluids. Both of these fault intersection areas show positive attributes for controlling geothermal fluids, but hydrologic tests show the ~1 km thick volcanic section is highly transmissive. Thus, focused upwellings along discrete fault conduits may be confined to the Mesozoic basement before fluids diffuse into the Miocene volcanic reservoir above. This large diffuse reservoir in the faulted Miocene volcanic rocks is capable of sustaining high pump rates. Understanding this type of system may be helpful in examining large, permeable reservoirs in deep sedimentary basins of the eastern Basin and Range and the highly fractured volcanic geothermal reservoirs in the Snake River Plain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗
NASA NTRS2018

Gas-Granular Simulation Framework for Spacecraft Landing Plume-Surface Interaction and Debris Transport Analysis

The Gas-Granular Flow Solver (GGFS) multi-phase flow computational framework has been developed to enable simulations of particle flows complex extra-terrestrial regolith materials. Particle flows of interest include the damage of unprepared landing sites from rocket plume impingement on Moon, Mars, and asteroids. The flow solver implements an Eulerian-Eulerian two-fluid model with fluid representation of the gas phase and granular phase to avoid the need to model billions of particle interactions. The granular phase is modeled as an Eulerian fluid with constituent physics closure models derived from first-principle Discrete Element Model (DEM) particle interaction simulations that capture the complex, non-linear granular particle interaction effects. Granular phase constituent models have been developed and integrated that address the complex, non-linear granular material mechanics complexities resulting from both: the irregular, jagged particle shapes and poly-disperse mixture effects encountered in extra-terrestrial regolith, with lunar regolith as the extreme. The GGFS capabilities are being integrated into a proven NASA plume-surface interaction and debris transport simulation framework featuring the Loci/CHEM CFD program and Debris Transport Analysis (DTA) post-processing tools for applications in robotic and human Moon and Mars lander development. Integration of the three simulation tool components. Loci/CHEM, GGFS, and DTA, into a coordinated simulation framework will enable time-accurate spacecraft landing simulations that account for the alteration of the landing surface through plume-induced cratering and the resulting redirection of plume impingement flow and debris transport. Initial implementation of this simulation framework and application examples will be presented.

Liever, Peter A.↗
DOE OSTI2020

The Complexity of Nonlinear Flow and non-Fickian Transport in Fractures Driven by Three-Dimensional Recirculation Zones

Subsurface fluid flow and solute transport are typically described by first-order or linear rate laws. However, deviations from the first-order rate laws (or anomalous behavior) are typical and lead to nonlinear flow and non-Fickian transport phenomena. The shared underlying mechanisms for these “anomalous” flow and transport phenomena, which are actually typical of fractures, are seldom analyzed. We investigated the co-occurrence of nonlinear flow and non-Fickian transport through numerical simulation experiments of pore-scale flow and solute transport processes through three-dimensional natural fractures. In these fractures, 3-D recirculation zones (RZs) developed and grew with increasing flow rates. Flow nonlinearity resulted from the RZ development and growth, which shrank the main flow channel. Moreover, the same RZs also captured solutes from the main flow channel and released them back later. This retardation resulted in non-Fickian transport. Thus, nonlinear flow and non-Fickian transport are intertwined via their shared dependence on RZs.

58 GEOSCIENCES↗
DOE OSTI2020

Probing complex geophysical geometries with chattering dust

Abstract The modern energy economy and environmental infrastructure rely on the flow of fluids through fractures in rock. Yet this flow cannot be imaged directly because rocks are opaque to most probes. Here we apply chattering dust, or chemically reactive grains of sucrose containing pockets of pressurized carbon dioxide, to study rock fractures. As a dust grain dissolves, the pockets burst and emit acoustic signals that are detected by distributed sets of external ultrasonic sensors that track the dust movement through fracture systems. The dust particles travel through locally varying fracture apertures with varying speeds and provide information about internal fracture geometry, flow paths and bottlenecks. Chattering dust particles have an advantage over chemical sensors because they do not need to be collected, and over passive tracers because the chattering dust delineates the transport path. The current laboratory work has potential to scale up to near-borehole applications in the field.

58 GEOSCIENCES↗
NASA NTRS2012

Methods for Computationally Efficient Structured CFD Simulations of Complex Turbomachinery Flows

This research presents more efficient computational methods by which to perform multi-block structured Computational Fluid Dynamics (CFD) simulations of turbomachinery, thus facilitating higher-fidelity solutions of complicated geometries and their associated flows. This computational framework offers flexibility in allocating resources to balance process count and wall-clock computation time, while facilitating research interests of simulating axial compressor stall inception with more complete gridding of the flow passages and rotor tip clearance regions than is typically practiced with structured codes. The paradigm presented herein facilitates CFD simulation of previously impractical geometries and flows. These methods are validated and demonstrate improved computational efficiency when applied to complicated geometries and flows.

Herrick, Gregory P.↗
NASA NTRS2018

Validation of Heat Transfer Correlations in Line Chill-Down Tests of Cryogenic Fluid in SINDA/FLUINT

Line chill-down is an important process in cryogenic tank propellant management, storage, and usage Complex flow dynamics during these processes: boiling heat transfer (film, transition, and nucleate) Understanding boiling phenomena can lead to efficient line chill-down systems that use less propellant, propellant stored, reducing cost for space missions Line Chill-down heat transfer was modelled using SINDA/FLUINT version 5.8 (SF) Multiple chill-down tests were modelled using: heat transfer correlations readily available in SF using HTN/HTC TIES heat transfer empiricisms developed by the University of Florida (UF) based on a series of liquid nitrogen chill-down tests using SF HTU TIES Chill-down tests modelled: liquid nitrogen tests conducted by the University of Florida horizontal flow, upward flow, and downward flow (Reynolds Numbers ranging 850-231,000)liquid hydrogen tests conducted by NASA Glenn Research Center vertical upward flow (Reynolds Number range of 18,400 - 433,000)The flow rate was measured far downstream of the test section, near the system exit. Where to set the flow rate? SF was highly sensitive, and sometime unstable, setting the test flow rate downstream (the outlet) of the test section model and setting the test pressure upstream (the inlet) of the test section model higher flow rate oscillations at the entrance of the model's test section SF was more stable setting the test flow rate upstream (than the downstream flow rate set case)test pressure was used as an inlet (SF plenum) to set the thermodynamic state (temperature and quality) coming into the system setting the appropriate downstream pressure was the unknown. The pressure drops predicted by SF for the downstream set flow rate boundary condition were much smaller than test section measured pressure drops. The multiphase pressure drop correlations used internally in SF may need to be adjusted. Models with an upstream flow rate set assumed a pressure drop that was small

cryogenic modeling↗