Results for “FLUID DYNAMICS” — Page 7

NASA NTRSDate not supplied

Modeling of Particle Transport and Impact in Transient, Multiphase Oxidizer-Rich Environments Using Computational Fluid Dynamics and Lagrangian Particle Tracking

Particle impacts from foreign object debris (FOD) in an oxidizer-rich environment have been shown to be a credible and significant risk for ignition and failure of components and vehicles. The risk of particle ignition is dependent on many factors, including particle impact velocity/energy and fluid composition (i.e. fluid phase, species presence, and state). Prediction of particle transport and particle impacts in relevant environments, including transient, multiphase flows, is important for assessing the risk and avoiding repeated expensive system level tests. The capability to model both the fluid dynamics and particle transport in complex three-dimensional geometries and multiphase environments has been developed at Marshall Space Flight Center (MSFC) in the propulsion fluid dynamic branch (ER42) by utilizing computational fluid dynamics (CFD) simulations and Lagrangian particle tracking. Using CFD tools, including density-based Loci/CHEM with a cavitation model and pressure-based Loci/STREAM with a volume of fluids model, MSFC/ER42 has provided particle impact predictions to multiple projects for oxidizer compatibility assessments. Simulations of transient, multiphase environments such as liquid slugs flowing through tubing and cavitating flow in valves have been completed alongside one-way coupled Lagrangian particle tracking to predict particle impacts.

M.V. Fischels↗

NASA NTRS1989

Computational fluid dynamics at NASA Ames Research Center

Computational fluid dynamics (CFD) has made great strides in the detailed simulation of complex fluid flows, including the fluid physics of flows heretofore not understood. It is now being routinely applied to some rather complicated problems, and starting to impact the design cycle of aerospace flight vehicles and their components. In addition, it is being used to complement, and is being complemented by, experimental studies. In the present paper, some major elements of contemporary CFD research, such as code validation, turbulence physics, and hypersonic flows are discussed, along with a review of the principal pacing items that currently govern CFD. Several examples of pioneering CFD research are presented to illustrate the current state of the art. Finally, prospects for the future development and application of CFD are suggested.

Kutler, Paul↗

NASA NTRS2003

Overview of MSFC's Applied Fluid Dynamics Analysis Group Activities

TD64, the Applied Fluid Dynamics Analysis Group, is one of several groups with high-fidelity fluids design and analysis expertise in the Space Transportation Directorate at Marshall Space Flight Center (MSFC). TD64 assists personnel working on other programs. The group participates in projects in the following areas: turbomachinery activities, nozzle activities, combustion devices, and the Columbia accident investigation.

Garcia, Roberto↗

DOE OSTI2020

A space-time parallel algorithm with adaptive mesh refinement for computational fluid dynamics

This work describes a space-time parallel algorithm with space-time adaptive mesh refinement (AMR). AMR with subcycling is added to multigrid reduction-in-time (MGRIT) in order to provide solution efficient adaptive grids with a reduction in work performed on coarser grids. This algorithm is achieved by integrating two software libraries: XBraid (Parallel time integration with multigrid. https://computation.llnl.gov/projects/parallel-timeintegration-multigrid) and Chombo (Chombo software package for AMR applications—design document, 2014). The former is a parallel time integration library using multigrid and the latter is a massively parallel structured AMR library. Employing this adaptive space-time parallel algorithm is Chord (Comput Fluids 123:202–217, 2015), a computational fluid dynamics (CFD) application code for solving compressible fluid dynamics problems. For the same solution accuracy, speedups are demonstrated from the use of space-time parallelization over the time-sequential integration on Couette flow and Stokes’ second problem. On a transient Couette flow case, at least a 1.5× speedup is achieved, and with a time periodic problem, a speedup of up to 13.7× over the time-sequential case is obtained. In both cases, the speedup is achieved by adding processors and exploring additional parallelization in time. The numerical experiments show the algorithm is promising for CFD applications that can take advantage of the time parallelism. Future work will focus on improving the parallel performance and providing more tests with complex fluid dynamics to demonstrate the full potential of the algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Thermal Analysis of a Solid Particle Light-Trapping Planar Cavity Receiver Using Computational Fluid Dynamics

Concentrated solar power (CSP) is one of the most effective ways of harnessing solar power to create efficient, durable, and resilient energy systems. This study entails thermal modeling and analysis of a novel central tower receiver configuration. This receiver uses solid particles as the heat transfer fluid (HTF), a promising option for third-generation CSP systems. The configuration considered here is the light-trapping planar cavity receiver (LTPCR) introduced by the National Renewable Energy Laboratory. While heat transfer studies of various LTPCR subsystems have been done, system-level thermal analysis of the LTPCR receiver has not been attempted. This study also presents important sensitivity analyses of the operating parameters of the CSP system, which can help guide the design of future central tower receivers. This study employs Ansys Fluent as a computational fluid dynamics (CFD) tool to model fluid dynamics and heat transfer in the receiver, intending to quantify its thermal performance. The model seamlessly integrates Monte Carlo ray tracing data, which generates absorbed solar flux profiles from the heliostat field design, with the heat transfer characteristics of the fluidized particle bed. This unified model is designed to accurately predict the thermal behavior of the LTPCR. Analysis of preliminary results reveals that the primary loss mechanisms are radiative and natural convective losses, in that order. Based on observations from a baseline case, several strategies are suggested and numerically tested. These solutions include selective cooling of high-temperature regions and manipulation of particle bed parameters. Selective cooling of high-temperature regions reduced the peak temperature by 151 degrees C and decreased thermal losses by 0.9%. Improving the particle-wall heat transfer coefficient (P-W HTC) of the particle bed decreased the thermal losses by 1.7% and decreased the peak temperatures by 57 degrees C. Decreasing the particle inlet temperature (PIT) also reduced thermal losses by 3.5% and decreased peak temperatures by 29 degrees C. Compounding these strategies improved the thermal losses of the receiver from 13.5% in the baseline case to 7.5%. Additionally, the study explores the variation in thermal performance across different locations of the receiver, where a variation of thermal losses from 12.9% to 17.3% is found. This allows a comprehensive evaluation of potential improvements in efficiency and temperature management.

computational fluid dynamics↗

NASA NTRS2004

Overview af MSFC's Applied Fluid Dynamics Analysis Group Activities

This paper presents viewgraphs on NASA Marshall Space Flight Center's Applied Fluid Dynamics Analysis Group Activities. The topics include: 1) Status of programs at MSFC; 2) Fluid Mechanics at MSFC; 3) Relevant Fluid Dynamics Activities at MSFC; and 4) Shuttle Return to Flight.

Garcia, Roberto↗

DOE OSTI2022

Numerical fluid dynamics for FRG flow equations: Zero-dimensional QFTs as numerical test cases. I. The O ( N ) model

The functional renormalization group (FRG) approach is a powerful tool for studies of a large variety of systems, ranging from statistical physics over the theory of the strong interaction to gravity. The practical application of this approach relies on the derivation of so-called flow equations, which describe the change of the quantum effective action under the variation of a coarse-graining parameter. In the present work, we discuss in detail a novel approach to solve such flow equations. This approach relies on the fact that RG equations can be rewritten such that they exhibit similarities with the conservation laws of fluid dynamics. This observation can be exploited in different ways. First of all, we show that this allows to employ powerful numerical techniques developed in the context of fluid dynamics to solve RG equations. In particular, it allows us to reliably treat the emergence of nonanalytic behavior in the RG flow of the effective action as it is expected to occur in studies of, e.g., spontaneous symmetry breaking. Second, the analogy between RG equations and fluid dynamics offers the opportunity to gain novel insights into RG flows and their interpretation in general, including the irreversibility of RG flows. Further, we work out this connection in practice by applying it to zero-dimensional quantum-field theoretical models. The generalization to higher-dimensional models is also discussed. Our findings are expected to help improving future FRG studies of quantum field theories in higher dimensions both on a qualitative and quantitative level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1988

Computational fluid dynamics in aerospace

The status of computational fluid dynamics (CFD) is addressed in terms of methods, examples of CFD solutions, and computer technology. The examples are divided into aerospace applications and fluid physics applications, with the aerospace applications section being further divided into internal and external flows. The role CFD is expected to play in supporting the goals set forth by the Aeronautical Policy Review Committee established by the Office of Science and Technology Policy is noted.

Kutler, Paul↗

NASA NTRS1991

Characterization of MOCVD fluid dynamics by laser velocimetry

Three-component laser velocimetry techniques are applied to characterize the fluid dynamics of an MOCVD reactor. These methods provide three-dimensional quantitative measurements of the gas velocities inside the reactor at typical growth temperatures. The effects of buoyancy-induced convection are examined by comparing data from the hot reactor with cold reactor results. It was found that thermal convection dominated the fluid dynamics of the reactor at growth temperatures. Cold reactor tests showed unstable flow patterns that were subject to fluidic switching effects.

Johnson, E. J.↗

NASA NTRS1994

Computational Fluid Dynamics at NASA Ames Research Center

Computational fluid dynamics (CFD) is beginning to play a major role in the aircraft industry of the United States because of the realization that CFD can be a new and effective design tool and thus could provide a company with a competitive advantage. It is also playing a significant role in research institutions, both governmental and academic, as a tool for researching new fluid physics, as well as supplementing and complementing experimental testing. In this presentation, some of the progress made to date in CFD at NASA Ames will be reviewed. The presentation addresses the status of CFD in terms of methods, examples of CFD solutions, and computer technology. In addition, the role CFD will play in supporting the revolutionary goals set forth by the Aeronautical Policy Review Committee established by the Office of Science and Technology Policy is noted. The need for validated CFD tools is also briefly discussed.

Kutler, Paul↗

DOE OSTI2021

A Scoping Study to Develop a Computational Fluid Dynamics Based Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building

The objective of this work is to perform computational fluid dynamics simulations of a ventilated radiological-material-package staging building to determine the effect of including or excluding a variety of physical effects and computational methods on both the predicted package temperatures and required computational resources. The generic building contains 640 drum-packages containing heat-generating, radiological material supported on four racks that are eight levels tall. Additionally, there is a forced ventilation system, lighting, and insulated walls. Computational models were constructed that included or excluded (a) shelving, (b) effects of unsteadiness, and (c) radiation heat transfer. Simulations with each drum modeled separately were compared to simpler simulations with sets of four drums represented by an equivalent box-package. These models employed between 106 to 107 elements. Steady state simulations predicted package temperatures that were within 0.1°C of simulations that included transient effects and required only one-eighth the computational resources. Calculations that excluded shelving predicted temperatures within 0.6°C of simulations that included shelving and required one-fourth the computational resources. Excluding radiation heat transfer systematically increased temperatures by around 1.5°C but reduced computational resources by a factor of four. The box-package model reduced the computational resources by a factor of 3, but systematically predicted higher temperatures by around 1.1°C. These results will be used to develop an efficient computational fluid dynamics model to assess the ability of different staging building designs to prevent the temperature of package components from exceeding specified limits.

42 ENGINEERING↗

DOE OSTI2023

Thermal photon production in Gubser inviscid relativistic fluid dynamics

The Gubser solution to inviscid relativistic fluid dynamics is used to examine the role of transverse expansion on the energy spectrum of photons radiated by quark-gluon plasma. Transverse flow is shown to be a modest effect on the energy spectrum of photons as a whole, despite its large effect on rare high-energy photons produced at low temperatures. An exact expression is derived for the volume of the plasma as a function of its temperature. Furthermore, a simple formula is obtained for the energy spectrum of high-energy thermal photons, which is used to relate the inverse slope T eff of the photon spectrum at energy E to the maximum temperature of the plasma T 0 , finding T eff ≈ T 0 / (1 + $\frac{5}{2}$ T 0 /E).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2018

Examination of Wave Speed in Rotating Detonation Engines Using Simplified Computational Fluid Dynamics

A simplified, two-dimensional, computational fluid dynamic (CFD) simulation, with a reactive Euler solver is used to examine possible causes for the low detonation wave propagation speeds that are consistently observed in air breathing rotating detonation engine (RDE) experiments. Intense, small-scale turbulence is proposed as the primary mechanism. While the solver cannot model this turbulence, it can be used to examine the most likely, and profound effect of turbulence. That is a substantial enlargement of the reaction zone, or equivalently, an effective reduction in the chemical reaction rate. It is demonstrated that in the unique flowfield of the RDE, a reduction in reaction rate leads to a reduction in the detonation speed. A subsequent test of reduced reaction rate in a purely one-dimensional pulsed detonation engine (PDE) flowfield yields no reduction in wave speed. The reasons for this are explained. The impact of reduced wave speed on RDE performance is then examined, and found to be minimal. Two other potential mechanisms are briefly examined. These are heat transfer, and reactive mixture non-uniformity. In the context of the simulation used for this study, both mechanisms are shown to have negligible effect on either wave speed or performance.

detonation↗

NASA NTRS2018

Examination of Wave Speed in Rotating Detonation Engines Using Simplified Computational Fluid Dynamics

A simplified, two-dimensional, computational fluid dynamic (CFD) simulation, with a reactive Euler solver is used to examine possible causes for the low detonation wave propagation speeds that are consistently observed in air breathing rotating detonation engine (RDE) experiments. Intense, small-scale turbulence is proposed as the primary mechanism. While the solver cannot model this turbulence, it can be used to examine the most likely, and profound effect of turbulence. That is a substantial enlargement of the reaction zone, or equivalently, an effective reduction in the chemical reaction rate. It is demonstrated that in the unique flowfield of the RDE, a reduction in reaction rate leads to a reduction in the detonation speed. A subsequent test of reduced reaction rate in a purely one-dimensional pulsed detonation engine (PDE) flowfield yields no reduction in wave speed. The reasons for this are explained. The impact of reduced wave speed on RDE performance is then examined, and found to be minimal. Two other potential mechanisms are briefly examined. These are heat transfer, and reactive mixture non-uniformity. In the context of the simulation used for this study, both mechanisms are shown to have negligible effect on either wave speed or performance.

combustion↗

NASA NTRSDate not supplied

Computational Fluid Dynamics Simulations of the Transonic Dynamics Tunnel Airstream Oscillator System

This paper presents a Computational Fluid Dynamics (CFD) model of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) with the Airstream Oscillator System (AOS) in operation. The TDT is a continuous-flow, closed circuit wind tunnel with a 16- by 16-foot slotted test section with cropped corners. The tunnel was originally built as the 19-ft Pressure Tunnel in 1938, but it was converted to the current transonic tunnel in the 1950s, with capabilities to use either air or heavy gas (R-134a) as the test medium. The TDT was also fitted with an AOS which can be used to create a gust field in the test section. To date, no computational analyses of the TDT involving the AOS have been performed. In this study, experimental data acquired of an oscillating airstream in the tunnel will be used to calibrate the computational analyses. A significant motivation of this work is to attempt to compare computational gust velocities to those recorded in the TDT literature. In addition to a validation of this model with experimental data, it may also be possible to supplement the experimental data with computational data. The experimental data is rather sparse and at only a few Mach numbers. Computational results may be able to expand the AOS data set. Another motivation for this work is that the Integrated Adaptive Wing Technology Maturation (IAWTM) semi-span model of the high-aspect-ratio CRM with 10 trailing edge control surfaces is currently being fabricated and will be delivered to the NASA Langley Transonic Dynamics Tunnel (TDT) for testing in late 2020. Among tests to be conducted, gust load alleviation (GLA) will be demonstrated at transonic conditions using the AOS.

Computational Fluid Dynamics↗

NASA NTRS2001

Overview of MSFC's Applied Fluid Dynamics Analysis Group Activities

This document is a presentation graphic which reviews the activities of the Applied Fluid Dynamics Analysis Group at Marshall Space Flight Center (i.e., Code TD64). The work of this group focused on supporting the space transportation programs. The work of the group is in Computational Fluid Dynamic tool development. This development is driven by hardware design needs. The major applications for the design and analysis tools are: turbines, pumps, propulsion-to-airframe integration, and combustion devices.

Garcia, Roberto↗

NASA NTRSDate not supplied

Liquid Hydrogen Tank Chill and No-Vent Fill Prediction using Computational Fluid Dynamics

Cryogenic tank chill and fill is an important cryogenic fluid management (CFM) technology that supports and enables many of NASA’s long-duration space missions. For no-vent fill, the receiver tank pressure remains below the supply tank pressure during the entire duration of the fill so that the tank does not require venting. This is especially advantageous for tank fill operations in low gravity where the position of the liquid is not always known and venting the tank may cause loss of propellant by venting liquid. In lieu of expensive tests conducted on-orbit, accurate computational models capable of predicting receiver tank pressure during cryogenic propellant tank fill may be used to reduce system and propellant mass as well as mission risk. However, these numerical models must be validated or anchored to test data. This study presents a computational fluid dynamics (CFD) model with conjugate heat transfer that is used to predict a liquid hydrogen tank chill and no-vent fill ground test conducted at Lewis Research Center (now Glenn Research Center) in 1991. The specific test case chosen for model validation implemented an upward-facing jet near the bottom of a cylindrical 34 liter tank. CFD predictions are compared to experimental measurements of tank pressure, fill level, fluid temperatures, and wall temperatures. The CFD results show reasonable agreement to the test data but overpredict the pressure collapse near the end of the fill despite the liquid jet penetrating the liquid-vapor interface. Several sensitivity studies are considered due to notable uncertainties in the experiment.

Computational Fluid Dynamics↗

NASA NTRSDate not supplied

Liquid Hydrogen Tank Chill and No-Vent Fill Prediction Using Computational Fluid Dynamics

Cryogenic tank chill and fill is an important cryogenic fluid management (CFM) technology that supports and enables many of NASA’s long-duration space missions. For no-vent fill, the receiver tank pressure remains below the supply tank pressure during the entire duration of the fill so that the tank does not require venting. This is especially advantageous for tank fill operations in low gravity where the position of the liquid is not always known and venting the tank may cause loss of propellant by venting liquid. In lieu of expensive tests conducted on-orbit, accurate computational models capable of predicting receiver tank pressure during cryogenic propellant tank fill may be used to reduce system and propellant mass as well as mission risk. However, these numerical models must be validated or anchored to test data. This study presents a computational fluid dynamics (CFD) model with conjugate heat transfer that is used to predict a liquid hydrogen tank chill and no-vent fill ground test conducted at Lewis Research Center (now Glenn Research Center) in 1991. The specific test case chosen for model validation implemented an upward-facing jet near the bottom of a cylindrical 34 liter tank. CFD predictions are compared to experimental measurements of tank pressure, fill level, fluid temperatures, and wall temperatures. The CFD results show reasonable agreement to the test data but overpredict the pressure collapse near the end of the fill despite the liquid jet penetrating the liquid-vapor interface. Several sensitivity studies are considered due to notable uncertainties in the experiment.

Computational Fluid Dynamics↗