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At least 163 records · Page 9

Visualization of fluid dynamics at NASA Ames

Some of the hardware and software tools and techniques in use at NASA's numerical aerodynamic simulation facility for the analysis of computational fluid dynamics are described. The visualization process can be illustrated by video tapes and stereo pictures. Although these visualization tools have dramatically improved the ability to conduct research in fluid dynamics, a comparison of the current environment for analysis with an 'ideal' environment illustrates that there are still major improvements that should be made. The most time-consuming task in future analyses of the increasingly complex computer simulations will be the extraction and clear display of the key features. In addition, the interface between the workstation and the scientist should be improved significantly. Current research on techniques for creating these improvements is described.

Watson, V.↗

Critical fluid dynamics in two and three dimensions

We describe a numerical method for simulating stochastic fluid dynamics near a critical point in the Ising universality class. This theory is known as model H, and is expected to govern the nonequilibrium dynamics of quantum chromodynamics (QCD) near a possible critical endpoint of the phase transition between a hadron liquid and the quark-gluon plasma. The numerical algorithm is based on a Metropolis scheme, and automatically ensures that the distribution function of the hydrodynamic variables in equilibrium is independent of the transport coefficients and only governed by the microscopic free energy. We verify dynamic scaling near the critical point of a two and three-dimensional fluid and extract the associated critical exponent z. Here, we find z≃3 in three dimensions, and z≃2 for a two-dimensional fluid. In a finite system, we observe a crossover between the mean field value z=4 and the true critical exponent z≃3 (z≃2 in d=2). This crossover is governed by the values of the correlation length and the renormalized shear viscosity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Computational fluid dynamics - The coming revolution

The development of aerodynamic theory is traced from the days of Aristotle to the present, with the next stage in computational fluid dynamics dependent on superspeed computers for flow calculations. Additional attention is given to the history of numerical methods inherent in writing computer codes applicable to viscous and inviscid analyses for complex configurations. The advent of the superconducting Josephson junction is noted to place configurational demands on computer design to avoid limitations imposed by the speed of light, and a Japanese projection of a computer capable of several hundred billion operations/sec is mentioned. The NASA Numerical Aerodynamic Simulator is described, showing capabilities of a billion operations/sec with a memory of 240 million words using existing technology. Near-term advances in fluid dynamics are discussed.

Graves, R. A., Jr.↗

Computational Fluid Dynamics Modeling to Simulate a Combined Reforming Process for Syngas and Hydrogen Production

An Oxygen Transport Membrane (OTM) combined reforming technology for producing syngas and hydrogen integrates the advantages of multiple processes—steam methane reforming (SMR), autothermal reforming (ATR), an air separation unit (ASU)—into a single integrated technology. The OTM consists of a primary reforming tube, in which desulfurized natural gas is partially reformed by steam at high pressure in the presence of a metal catalyst. This process is followed in series by a ceramic OTM with a secondary reformer, in which residual methane reforms and O 2 - ions react with a portion of the CO and H 2 fuel to provide the heat to support both primary and secondary reforming. Although the OTM combined reformer technology for syngas and H 2 production has been substantially developed in the last decade, several challenges that affect the overall production efficiency and reliability are yet to be fully understood, addressed, and resolved. Therefore, developing Computational Fluid Dynamics (CFD) models that incorporate fluid dynamics, mass transport, kinetics, heat transport, and structural mechanics is critical to understanding and minimizing the probability of tube failures during the startup and operation. In this report, an exhaustive literature review was performed to survey the current state of technology for producing syngas and H 2 using either conventional or renewable energy sources. The feedstocks reviewed include natural gas and coal for the conventional technologies, whereas biomass, solar, wind, and nuclear energy for the renewable technologies. The existing industry-grade COMSOL multiphysics models of OTM were upgraded for the latest software release. In addition, they were improved to help achieve grid and solver independence and were successfully ported on the ORNL high-performance computing clusters to speed up their run times. A 42% reduction in the simulation run time was achieved. A new higher-fidelity CFD model of an OTM tube was developed in the StarCCM+ simulation platform. This new model was designed to simulate various physics using first principles, e.g., turbulent flow, heat transfer, and chemical reactions while avoiding unnecessary simplifications. The resulting predictions were qualitatively assessed and provided useful insights into the multiphysics complexity of an OTM tube.

08 HYDROGEN↗

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets

Packed columns are commonly used in post-combustion processes to capture CO 2 emissions by providing enhanced contact area between a CO 2 -laden gas and CO 2 -absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs), computational fluid dynamics (CFD) can be used to model the liquid–gas countercurrent flow hydrodynamics in these columns and derive key determinants of CO 2 -capture efficiency. However, the large design space of these systems hinders the application of CFD for design optimization due to its high computational cost. In contrast, data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. We build our surrogates using MeshGraphNets (MGN), a graph neural network framework that efficiently learns and produces mesh-based simulations. We apply MGN to a random packed column modeled with over 160K graph nodes and a design space consisting of three key input parameters: solvent surface tension, inlet velocity, and contact angle. Our models can adapt to a wide range of these parameters and accurately predict the complex interactions within the system at rates over 1700 times faster than CFD, affirming its practicality in downstream design optimization tasks. This underscores the robustness and versatility of MGN in modeling complex fluid dynamics for large-scale CCS analyses.

97 MATHEMATICS AND COMPUTING↗

Computational Fluid Dynamics In Aerospace

Report reviews recent progress in computational fluid dynamics (CFD). Addresses state of art in terms of methods, examples of solutions, and computer technology. Provides examples of CFD solutions of aerospace and fluid-physics problems to illustrate recent progress. Aerospace solutions include rotor/stator velocity vectors from three-dimensional Navier-Stokes code for turbomachinery, pressure distributions from simulation of aeroelasticity of wing surface-pressure contours on four-bladed helicopter rotor in forward flight, and particle traces about several aerospace vehicles. Computer technology covers supercomputers, scientific work stations, local supercomputing networks, and remote access to supercomputers.

Kutler, Paul↗

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↗

Validation of a Multiphase Computational Fluid Dynamics Model for Vapor Pull-Through in Normal and Low Gravity

On-orbit fluid transfer such as refueling of propellant tanks and life-support systems can enable long-duration space missions. For safe and efficient liquid transfer operations, prior knowledge of liquid positioning and liquid-vapor interface behavior while draining in a low-gravity environment is required. Numerical models capable of predicting vapor ingestion (or vapor pull-through) can be used to design liquid transfer operations while reducing liquid residuals, mission risk and settling thrust required to prevent vapor ingestion. An experimental program conducted in the 2.2 Second Drop Tower facility at NASA Glenn Research Center investigated the vapor ingestion phenomenon for a range of outflow rates and tank sizes providing a database for validation. This study presents a Computational Fluid Dynamics model capable of accurately predicting the vapor ingestion using the Volume-of-Fluid multiphase solver in commercial code STAR-CCM+. A description of the experimental setup and general trends from similar studies are presented. Comparisons of the numerical prediction and test data in normal and low gravity show good agreement and give confidence in pursuing design of full-scale propellant transfer systems.

Computational Fluid Dynamics↗

Validation of a Multiphase Computational Fluid Dynamics Model for Vapor Pull-Through in Normal and Low Gravity

On-orbit fluid transfer such as refueling of propellant tanks and life-support systems can enable long-duration space missions. For safe and efficient liquid transfer operations, prior knowledge of liquid positioning and liquid-vapor interface behavior while draining in a reduced-gravity environment is required. Numerical models capable of predicting vapor ingestion (or vapor pull-through) can be used to design liquid transfer operations while reducing liquid residuals, mission risk and settling thrust required to prevent vapor ingestion. An experimental program conducted in the 2.2 Second Drop Tower facility at NASA Lewis Research Center in 1969 investigated the vapor ingestion phenomenon for a range of outflow rates and tank sizes providing a database for validation. This study presents a Computational Fluid Dynamics model capable of accurately predicting the vapor ingestion using the Volume-of-Fluid multiphase solver in commercial code STAR-CCM+. A description of the experimental setup and general trends from similar studies are presented. Comparisons of the numerical prediction and test data in normal and low gravity show good agreement and give confidence in pursuing design of full-scale propellant transfer systems.

Computational Fluid Dynamics↗

Validation of A Multiphase Computational Fluid Dynamics Model for Vapor Pull-Through in Normal and Low Gravity

On-orbit fluid transfer such as refueling of propellant tanks and life-support systems can enable long-duration space missions. For safe and efficient liquid transfer operations, prior knowledge of liquid positioning and liquid-vapor interface behavior while draining in a reduced-gravity environment is required. Numerical models capable of predicting vapor ingestion (or vapor pull-through) can be used to design liquid transfer operations while reducing liquid residuals, mission risk and settling thrust required to prevent vapor ingestion. An experimental program conducted in the 2.2 Second Drop Tower facility at NASA Lewis Research Center in 1969 investigated the vapor ingestion phenomenon for a range of outflow rates and tank sizes providing a database for validation. This study presents a Computational Fluid Dynamics model capable of accurately predicting the vapor ingestion using the Volume-of-Fluid multiphase solver in commercial code STAR-CCM+. A description of the experimental setup and general trends from similar studies are presented. Comparisons of the numerical prediction and test data in normal and low gravity show good agreement and give confidence in pursuing design of full-scale propellant transfer systems.

Propellant Transfer↗

Application of wave mechanics theory to fluid dynamics problems: Fundamentals

The application of the basic formalistic elements of wave mechanics theory is discussed. The theory is used to describe the physical phenomena on the microscopic level, the fluid dynamics of gases and liquids, and the analysis of physical phenomena on the macroscopic (visually observable) level. The practical advantages of relating the two fields of wave mechanics and fluid mechanics through the use of the Schroedinger equation constitute the approach to this relationship. Some of the subjects include: (1) fundamental aspects of wave mechanics theory, (2) laminarity of flow, (3) velocity potential, (4) disturbances in fluids, (5) introductory elements of the bifurcation theory, and (6) physiological aspects in fluid dynamics.

Krzywoblocki, M. Z. V.↗

Summary Report Of The FY25 Computational Fluid Dynamics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Verification and Validation (V&V) of numerical tools is critical for ensuring reasonable predictions during design, safety analysis, and licensing. Recent work in the Advanced Reactor Technologies - Gas-cooled Reactor (ART-GCR) program has focused on V&V of common Computational Fluid Dynamics (CFD) tools that are used within the Untied States. This report presents an update on these CFD V&V activities. These Generation IV Forum (GIF) Very High Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) is an international organization dedicated to the verification and validation of High Temperature Gas-Cooled Reactor (HTGR) simulation tools. Participation in the CMVB provides additional value to the V&V activities, as it allows for access to a wider range of data, and provides valuable benchmarking exercises. Three HTGR phenomena are targeted: Reactor Cavity Cooling System (RCCS) performance, core bypass flow, and lower plenum mixing. Simulations of the University of Wisconsin-Madison (UW-Madison) RCCS facilities are performed with Reynolds Averaged Navier-Stokes (RANS) in StarCCM+. Results are compared for both forced and natural convection conditions, with both exhibiting good agreement with experimental measurements. The Idaho National Laboratory (INL) matched index of refraction (MIR) and Korean Atomic Energy Research Institute (KAERI) bypass flow expeirments are used to validation CFD predictions of bypass flow. Simulations are performed with RANS in StarCCM+ and with Large Eddy Simulation (LES) in NekRS. Finally, preliminary simulations of the Institute of Nuclear and New Energy Technology (INET) lower plenum mixing facilities are presented. Initial work has developed models with LES, RANS, and porous media models. These preliminary models are presented and compared to each other to gauge differences in predictions with each of the three methods.

and Benchmarking (CMVB)↗

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fluid dynamic mathematical aspects of supernova remnants

Supernovae—explosions of stars—are a central problem in astrophysics since they contain information on the entire process of stellar evolution and nucleosynthesis. Rayleigh–Taylor (RT) and Richtmyer–Meshkov (RM) instabilities, developing during the supernova blast, lead to intense interfacial RT/RM mixing of the star's materials and couple astrophysical to atomic scales. This work analyzes some fluid dynamic mathematical aspects of the titanic task of supernova's blast. We handle mathematical challenges of RT/RM dynamics in supernova relevant conditions by directly linking the conservation laws governing RT/RM dynamics to symmetry-based momentum model, by exactly deriving the model parameters in the scale-dependent and scale-invariant regimes, and by exploring the special self-similar class for RT/RM interfacial mixing with variable accelerations. Here we reveal that RT/RM dynamics is strongly influenced by deterministic (the initial and the flow) conditions in the scale-dependent linear and nonlinear regimes and in the self-similar mixing regime. The theory outcomes are consistent with the observations of supernova remnants, explain the results of the scaled laboratory experiments in high energy density plasmas, and yield the design of future experiments for the accurate quantification of RT/RM dynamics in supernova relevant conditions. We find that from fluid dynamic mathematical perspectives, supernovae can be regarded as an astrophysical initial value problem. Along with the guidance of what explodes at microscopic scales, supernova remnants encapsulate information on the explosion hydrodynamics and the associated deterministic conditions at macroscopic scales. We urge such effects be considered in interpretations of the observational data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The fluid dynamic and shear environment in the NASA/JSC rotating-wall perfused-vessel bioreactor

The rotating-wall perfused-vessel (RWPV) bioreactor, used for both microgravity and Earth-based cell science experiments, is characterized in terms of the fluid dynamic and fluid shear stress environment. A numerical model of the flow field is developed and verified with laser Doppler velocimeter measurements. The effects of changes in operating conditions, including rotation rates and fluid perfusion rates, are investigated with the numerical model. The operating conditions typically used for ground-based experiments (equal rotation of the inner and outer cylinders) leads to flow patterns with relatively poor mass distribution characteristics. Approximately 50% of the inlet-perfused fluid bypasses the bulk of the fluid volume and flows to the perfusion exit. For operating conditions typical in microgravity, small differential rotation rates between the inner and outer cylinders lead to greatly improved flow distribution patterns and very low fluid shear stress levels over a large percentage of the fluid volume. Differences in flow patterns for the different operating conditions are explored. Large differences in the hydrodynamic environments for operating conditions typical of true microgravity and ground-based "microgravity simulations" are demonstrated.

Bioreactors↗

Computational Fluid Dynamics (CFD) Analysis Of Optical Payload For Lasercomm Science (OPALS) sealed enclosure module

Computational Fluid Dynamics (CFD) using the commercial CFD package CFDesign has been performed at NASA Jet Propulsion Laboratory (JPL) California Institute of Technology (Caltech) in support of the Phaeton Early Career Hire Program's Optical Payload for Lasercomm Science (OPALS) mission. The OPALS project is one which involves an International Space Station payload that will be using forced convection cooling in a hermetically sealed enclosure at 1 atm of air to cool "off-the-shelf" vendor electronics. The CFD analysis was used to characterize the thermal and fluid flow environment within a complicated labyrinth of electronics boards, fans, instrumentation, harnessing, ductwork and heat exchanger fins. The paradigm of iteratively using CAD/CAE tools and CFD was followed in order to determine the optimum flow geometry and heat sink configuration to yield operational convective film coefficients and temperature survivability limits for the electronics payload. Results from this current CFD analysis and correlation of the CFD model against thermal test data will be presented. Lessons learned and coupled thermal / flow modeling strategies will be shared in this paper.

Computational Fluid Dynamics (CFD)↗

Time-Accurate Computational Fluid Dynamics Analysis of a Supersonic Turbine to Assess Structural Mode Excitation

Gas turbines can experience significant unsteady loading during operation which can cause damage such as blade cracking or bearing wear. While computational fluid dynamics (CFD) modeling of full three-dimensional gas turbine flow to verify meanline design performance is standard practice within the industry, the use of time-accurate CFD makes it possible to assess the unsteady loading which can be especially problematic at operating conditions where unsteady fluid loading aligns with structural modes. The Fluid Dynamics branch (ER42) at NASA Marshall Space Flight Center has developed a time-accurate CFD analysis methodology using the unstructured, density-based, Loci-CHEM solver which is capable of simulating the relative motion required for turbomachinery applications through sliding interface meshes. The highly-parallel unstructured solver allows for full three-dimensional, time-accurate simulation of turbines including upstream and downstream components such as manifolds, nozzles, and stators, any of which could excite a turbine structural mode. Recently, Loci-CHEM was used to analyze the FASTRAC supersonic turbine to assess the loading on the rotor. Overall performance and time-averaged loading on the rotor was computed, including the axial force over the entire rotor disk which is required for force balance calculations on the turbopump. The FASTRAC turbine has supersonic nozzles upstream of the rotor that result in significant unsteady loading on the rotor blades at multiples of the nozzle pass frequency. The unsteady blade pressure loading was decomposed into the frequency domain for direct use in structural forced response analysis. Utilizing this type of CFD analysis coupled with structural analysis has proven to be a valuable tool in identifying structural modes that are being excited by unsteady fluid loading.

M.V. Fischels↗

Time-Accurate Computational Fluid Dynamics Analysis of a Supersonic Turbine to Assess Structural Mode Excitation

Gas turbines can experience significant unsteady loading during operation which can cause damage such as blade cracking or bearing wear. While computational fluid dynamics (CFD) modeling of full three-dimensional gas turbine flow to verify meanline design performance is standard practice within the industry, the use of time-accurate CFD makes it possible to assess the unsteady loading which can be especially problematic at operating conditions where unsteady fluid loading aligns with structural modes. The Fluid Dynamics branch (ER42) at NASA Marshall Space Flight Center has developed a time-accurate CFD analysis methodology using the unstructured, density-based, Loci-CHEM solver which is capable of simulating the relative motion required for turbomachinery applications through sliding interface meshes. The highly-parallel unstructured solver allows for full three-dimensional, time-accurate simulation of turbines including upstream and downstream components such as manifolds, nozzles, and stators, any of which could excite a turbine structural mode. Recently, Loci-CHEM was used to analyze the FASTRAC supersonic turbine to assess the loading on the rotor. Overall performance and time-averaged loading on the rotor was computed, including the axial force over the entire rotor disk which is required for force balance calculations on the turbopump. The FASTRAC turbine has supersonic nozzles upstream of the rotor that result in significant unsteady loading on the rotor blades at multiples of the nozzle pass frequency. The unsteady blade pressure loading was decomposed into the frequency domain for direct use in structural forced response analysis. Utilizing this type of CFD analysis coupled with structural analysis has proven to be a valuable tool in identifying structural modes that are being excited by unsteady fluid loading.

M V Fischels↗