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

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
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 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 computational fluid dynamics (CFD) models with conjugate heat transfer that are 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, and wall temperature. 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.

Computational Fluid Dynamics↗
NASA NTRS2008

Computational Fluid Dynamics Analysis Success Stories of X-Plane Design to Flight Test

Examples of the design and flight test of three true X-planes are described, particularly X-plane design techniques that relied heavily on computational fluid dynamics(CFD) analysis. Three examples are presented: the X-36 Tailless Fighter Agility Research Aircraft, the X-45A Unmanned Combat Air Vehicle, and the X-48B Blended Wing Body Demonstrator Aircraft. An overview is presented of the uses of CFD analysis, comparison and contrast with wind tunnel testing, and information derived from CFD analysis that directly related to successful flight test. Lessons learned on the proper and improper application of CFD analysis are presented. Highlights of the flight-test results of the three example X-planes are presented. This report discusses developing an aircraft shape from early concept and three-dimensional modeling through CFD analysis, wind tunnel testing, further refined CFD analysis, and, finally, flight. An overview of the areas in which CFD analysis does and does not perform well during this process is presented. How wind tunnel testing complements, calibrates, and verifies CFD analysis is discussed. Lessons learned revealing circumstances under which CFD analysis results can be misleading are given. Strengths and weaknesses of the various flow solvers, including panel methods, Euler, and Navier-Stokes techniques, are discussed.

Cosentino, Gary B.↗
NASA NTRS2025

Physics-Based Modeling and Simulation of Self-Reacting Friction Stir Welding Using Computational Fluid Dynamics

A physics-based model was developed to simulate the behavior of material in a self-reacting friction stir welding (SR-FSW) process for the joining of metals. This steady-state model builds upon fundamental computational fluid dynamic (CFD) principles within Ansys Fluent to solve the discretized equations. The effective viscosity is calculated using a viscoplastic model using a Sheppard-Wright formulation of flow stress. Numerous advancements have been made in the incorporated physics including (1) temperature-dependent material properties; (2) locally adaptable flow and thermal boundary conditions; and (3) adapting material properties in nugget in response to microstructural changes. Simulation strategies to accelerate computation and improve numerical stability include adapting the mesh refinement and solver relaxation factors during simulation. The result is a highly robust and computationally efficient model capable of providing the material flow and temperature history across the domain. As material history determines the local microstructure and ultimately weld strength, an accurate and detailed physics-based model has the potential to accelerate SR-FSW process development. The model is highly adaptable to changes in process parameters, tool design, or alloy.

Process Modeling↗
DOE OSTI2021

Validation of Computational Fluid Dynamics Simulations for Biological Performance Assessment in Hydropower units (Final Report)

The biological performance assessment (BioPA) toolset developed by Pacific Northwest National Laboratory (PNNL) estimates the relative biological performance of fish passage at a hydroelectric power turbine unit. The tool is based on the use of computational fluid dynamics (CFD) and fish biological response relationships. The recent release, BioPA-v3, is based on directly computed trajectory and collision of material Lagrangian particles using CFD simulation codes rather than the prior version that relies on Tecplot to compute streamtrace trajectories. Before modifying the toolset, a series of validation tests were performed at the various steps of modification in the toolset. Validation is a critical step of any numerical investigation that reflects the accuracy and reliability of the predicted results. It raises the confidence level of the user to use the modified version of the BioPA toolset. Several test cases were simulated and compared, where available, to observed data. The trajectory and collision of the small spherical and cylindrical particles in a water flume were compared to in-house experiments. The CFD predicted collision rate and flow field compared well with experimental observation for vane array and large cylinder as target bodies. Next, the CFD-predicted flow field and hydraulic performance of a laboratory-scale model of a Francis turbine was also successfully validated. Note that the trajectory of the particles is significantly affected by the flow field in such extreme conditions. In addition to the particle trajectories and flow field, the collision detection method employed in the CFD simulations was also successfully validated. The CFD predicted impact velocity, collision time, velocity, and trajectory of a sphere excellently matched with analytical value for a bouncing ball in the elastic collision. A similar approach was also tested and successfully validated for a collision of sphere with a 45° inclined plane. After successfully validating different cases, the BioPA toolset was modified to use direct output of the CFD prediction and the new version can be used in evaluating biological performance at hydroelectric turbines.

13 HYDRO ENERGY↗
NASA NTRS1988

Computational Fluid Dynamics In Rotary-Wing Aerodynamics

Emerging techniques appear vital to progress in rotary-wing-airplane industry. Report reviews current trends in field of helicopter-rotor aerodynamics. Selected test cases used to demonstrate current research in computational fluid dynamics (CFD) vital to analysis and design of advanced rotor-craft.

Davis, Sanford S.↗
DOE OSTI2025

Computational Fluid Dynamics Analysis of the Molten Salt Tritium Transport Experiment Test Section

Tritium, a radionuclide produced through neutron capture by lithium and other elements (beryllium and fluoride) in molten salts, presents unique challenges to radionuclide release. This is true for both fusion energy breeder blankets and molten salt fission reactors. The fundamental understanding of tritium transport is crucial to the safe design and operation of these reactors. The Molten Salt Tritium Transport Experiment (MSTTE), currently under construction at Idaho National Laboratory, aims to investigate tritium transport phenomena using a forced-convection fluoride salt loop. This loop is designed to study various transport mechanisms, such as permeation through metals and gas-liquid interactions, and is intended to support future research on tritium extraction units. A critical aspect of the MSTTE loop design is ensuring a fully developed velocity profile before the fluid reaches the permeation test section where measurements are made. This study employs computational fluid dynamics to model the salt flow behavior within the MSTTE permeation test section. A realizable k-ε turbulent model with enhanced wall treatment is used to simulate the single-phase, vertical upward flow of molten salt FLiNaK under isothermal conditions. The simulation results indicated flow distortion and underdeveloped profiles at all planned flow rates within the test section due to the 85-deg sharp bend. To address this issue, a reduced diameter with a reducer and expander and a flow conditioner are investigated to achieve fully developed flow. The analysis showed that the flow conditioner successfully corrected the flow profile, achieving fully developed behavior at a flow rate of 50 liters per minute (LPM). In conclusion, this research enhances our understanding of flow dynamics in molten salt systems and contributes to optimizing tritium transport control technologies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Computational fluid dynamic analysis of a novel particle-to-air fluidized-bed heat exchanger for particle-based thermal energy storage applications

Long-duration energy storage technologies are being targeted to enable cost-effective, decarbonized energy systems. Particle-based thermal energy storage systems are one promising technology by storing excess electricity or heat as sensible thermal energy in inexpensive, solid, inert particles. These systems are only possible if an effective and economical particle-to-working fluid heat exchanger exists. This study predicts the performance of a proposed, direct-contact, particle-to-air, pressurized fluidized-bed heat exchanger using computational fluid dynamics. The common Eulerian-Eulerian framework for modeling fluidized beds is first benchmarked to experimental results at a previously untested operating condition and application. Then, the benchmarked model evaluates the performance of a proposed design for a commercial-scale version of the novel particle-to-air heat exchanger. The results show pressure drop and gas-phase approach temperatures are advantageous compared to other proposed designs for particle-to-air heat exchangers in the literature; approach temperatures were less than 5 °C and gas-phase pressure drop across the fluidized bed was 32 kPa. The model also highlights the importance of gas distributor design and representation in the Eulerian-Eulerian framework to control fluidization behavior. In conclusion, the model built and benchmarked in this study can be leveraged to advance the design and analysis of these heat exchangers critical to the deployment of a promising long-duration energy storage technology.

25 ENERGY STORAGE↗
DOE OSTI2021

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗
NASA NTRS2004

Automated Static Culture System Cell Module Mixing Protocol and Computational Fluid Dynamics Analysis

This report is a documentation of a fluid dynamic analysis of the proposed Automated Static Culture System (ASCS) cell module mixing protocol. The report consists of a review of some basic fluid dynamics principles appropriate for the mixing of a patch of high oxygen content media into the surrounding media which is initially depleted of oxygen, followed by a computational fluid dynamics (CFD) study of this process for the proposed protocol over a range of the governing parameters. The time histories of oxygen concentration distributions and mechanical shear levels generated are used to characterize the mixing process for different parameter values.

Kleis, Stanley J.↗
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↗
DOE OSTI2021

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗
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↗
NASA NTRS2018

Computational Fluid Dynamics Analysis of the Stall Characteristics of a Wing Design Based on Prandtl's Minimum Induced Drag

Stall characteristics of a wing whose design was based on Prandtl’s minimum induced drag analysis is presented. Flow field is resolved using RANS CFD (Computational Fluid Dynamics) solver OVERFLOW-2. Both in freestream and in ground effect are analyzed. In addition, effect of low-Mach preconditioner on the stall characteristic is presented. Results show that simulations that lack preconditioner predicts higher stall angle as well as much more benign behavior near the stall angle. Stall analysis in freestream show that flow begins to separate at the inboard region. The flow at the tip remains attached until approximately 19.0 degrees angle of attack.

PRANDTL↗
DOE OSTI2020

HYDRODYNAMIC ANALYSIS OF MACROALGAE LOCAL MODEL USING COMPUTATIONAL FLUID DYNAMICS

In this article, a local scale, fully nonlinear coupled fluid-structural interaction (FSI) sugar kelp model has been developed using a computational fluid dynamics (CFD) method. In this model, to be consistent with available experimental data, the sugar kelp is approximated as elongated rectangles with smoothed isosceles triangles at the ends and a single kelp model with one end fixed in a channel with constant current model is developed. Several different current speeds are simulated, and the resulting drag forces and calculated drag coefficients are validated by comparison with experimental data from the literature. In a previous study, a global scale model was developed using a computational structural dynamics (CSD) method to simulate macroalgae farming system and guide the system configuration design. In the global scale model, the hydrodynamic forces are calculated using Morison’s equation and the kinematics and dynamics of the sugar kelp are simplified and the group of kelps attached to the long line is modeled as a slender structure with the same length and an effective diameter such that the volumes are consistent with the real physical system. This simplified model matches the weight and buoyancy but adjusting the hydrodynamic properties when the general hydrodynamic coefficients are employed. Therefore, optimal hydrodynamic coefficients used in global scale model were determined to obtain the hydrodynamic force more accurately. The validated local scale model is then be applied to determine the hydrodynamic coefficients of the simplified sugar kelp model for global dynamic analysis.

hydrodynamic modeling, macroalgae, CFD model↗
NASA NTRS1999

Large-Scale Distributed Computational Fluid Dynamics on the Information Power Grid Using Globus

This paper describes an experiment in which a large-scale scientific application development for tightly-coupled parallel machines is adapted to the distributed execution environment of the Information Power Grid (IPG). A brief overview of the IPG and a description of the computational fluid dynamics (CFD) algorithm are given. The Globus metacomputing toolkit is used as the enabling device for the geographically-distributed computation. Modifications related to latency hiding and Load balancing were required for an efficient implementation of the CFD application in the IPG environment. Performance results on a pair of SGI Origin 2000 machines indicate that real scientific applications can be effectively implemented on the IPG; however, a significant amount of continued effort is required to make such an environment useful and accessible to scientists and engineers.

Barnard, Stephen↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗