Search NASA⌕ Search

SEARCH · Search NASA

Results for “CFD modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

CFD modeling of turbulent air flow in self-heated gyroid TPMS structures: Thermal-hydraulic performance and validation

The application of mathematically derived geometries, such as triply periodic minimal surface (TPMS) lattices, has garnered significant interest across various fields, including the nuclear sector, due to their superior thermal-hydraulic characteristics for heat transfer compared to traditional plain or finned tubes. Here, this study validates a computational fluid dynamics (CFD) model, evaluates different turbulence models and CFD model settings, and performs uncertainty quantification to provide a comprehensive analysis. Despite extensive research on CFD modeling of TPMS lattices, such as gyroid and diamond geometries, there is a notable lack of publicly available literature providing comprehensive details on numerical analysis aspects, including convergence and methodological best practices. This study embarks on a benchmark analysis of a gyroid geometry to evaluate its thermal-hydraulic performance under turbulent flow conditions and scrutinize various CFD model configurations. The main contributions of this work include validating the CFD model, assessing and comparing different turbulence models, and enhancing pressure drop and temperature prediction capabilities. The results aim to support the development of methodologies needed to benchmark and enhance numerical analysis techniques for TPMS lattices. This work seeks to complement the existing body of knowledge, support the development of TPMS reactor concepts, and improve best practices for CFD modeling of TPMS lattices, ultimately advancing methodologies to support future applications in this domain.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Validation & Verification of CFD Models for Cryogenic Fluid Management of Propellant Tanks in Space

This article describes the need and the strategy for CFD model development, validation, and verification for Cryogenic Fluid Management (CFM) of Propellant Tanks in Space. It describes the type of CFD models that must be developed to address the future needs of Space CFM. It also discusses the two classes of experiments currently used to validate the fidelity of the CFD models. These two experiment classes are: (a) the small-scale simulant fluid science experiments that are equipped with scientific diagnostics to elucidate the underlying two-phase fluid physics of the CFM processes; and (b) the large-scale cryogenic experiments that assess the engineering performance of the propellant tank for storage and transfer. The current status of the CFD model development and validation is briefly assessed by presenting examples of segregated two-phase flow problems that have been successfully modeled. The future model development directions for CFM situations involving more complex interpenetrating phases are also defined.

Cryogenic Fluid Management↗

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for modeling two-phase flow, as well as interfacial heat, mass and momentum transfer between the liquid and vapor regions. The CFD model is validated against self-pressurization experiment performed using the K-site flightweight hydrogen storage tank at NASA Glenn Research Center 1 . Laminar and turbulent simulations are performed together with conjugate heat transfer analysis. Effects of turbulence, the value of accommodation coefficient used for predicting phase change rates, as well as tank wall geometry are presented and discussed. Predicted tank pressures, fluid and wall temperatures are compared with the experimental data at 49% fill level and two different heat loads for validating this CFD model.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for modeling two-phase flow, as well as interfacial heat, mass and momentum transfer between the liquid and the vapor regions. The CFD model is validated against self-pressurization experiment performed using the K-site flightweight hydrogen storage tank at NASA Glenn Research Center1. Laminar and turbulent simulations are performed together with conjugated heat transfer analysis. Effects of turbulence, the value of accommodation coefficient used for predicting phase change rates, as well as tank wall geometry are presented and discussed. Predicted tank pressures, fluid and wall temperatures are compared with the experimental data at 49% fill level and two different heat loads for validating this CFD model.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for representing the phase boundary and the associated interfacial heat, mass and momentum transfer between the liquid and the vapor regions. The CFD model is validated against self-pressurization experiment performed in the K-site flightweight hydrogen storage tank at NASA Glenn Research Center. Laminar and turbulent simulations together with conjugated heat transfer analysis are performed. Effects of turbulence, as well as tank wall conduction are presented and discussed. Predicted tank pressures and fluid temperatures are compared with the experimental data at two different heat loads for validating the CFD model.

phase change↗

CFD modeling of crystallization fouling with CO 2 desorption incorporated for a falling-film evaporator in thermal desalination

Seawater flowing around horizontal tubes in falling-film evaporators is a common configuration for thermal desalination. Heat is transferred from in-tube steam condensation to the shell-side seawater by conduction through the tube wall and scaling layer, and conduction and convection to the evaporating liquid film. CO 2 is simultaneously released from seawater and mixed with the produced vapor. Fouling coupled with CO 2 desorption has deleterious impacts on both evaporation and condensation. The evaluation of spatiotemporal dependent crystallization fouling and CO 2 desorption is vital to selecting optimal operating conditions. Here, in this work, a CO 2 desorption model is integrated into CFD modeling for predictions of coupled heat and mass transfer, to understand and predict scale formation and CO 2 desorption with local and transient profiles of temperature, carbonate species concentrations, pH, and total alkalinity. The porosity of the scale layer is experimentally determined as 67.7% and invoked in the calculation of effective thermal conductivity. The simulation results reveal that high steam temperatures increase seawater total alkalinity and accelerate scale formation. The scale thickness on the bottom tube reaches 0.30 μm and 5.24 μm for steam temperatures of 60 °C and 80 °C, respectively. High salinity leads to a large CO 2 desorption rates. The CO 2 desorption rate increases 43% when the seawater salinity increases from 35 to 55 g/kg. The effects of operating conditions on carbonate speciation and pH have been compared and analyzed. This model can serve as a comprehensive tool for the design of thermal desalination systems and optimal operation.

42 ENGINEERING↗

CFD Modeling of a Cryogenic Methane Drain Test with and without Induced Sloshing

Current planned NASA missions to the Moon and Mars involve the transfer of cryogenic propellants in orbit. These activities require large amounts of cryogenic propellant and the ability to transfer these fluids from one tank to another in an efficient manner. Predicting the pressurant required for the supply tank pressurization during the initial pressurization and expulsion process will be important to understand priori to reduce propellant margin.

Low Gravity Fluid Modeling↗

CFD modeling of high-flux plate-and-frame membrane modules for industrial carbon capture

In this work, we study the application of membrane-based separation systems for carbon capture, considering plate-and-frame membrane modules. The successful deployment of membrane CO2 capture system relies on high-performing membranes as well as effective membrane modules that can fully exploit the developed membranes. A plate-and-frame membrane module is especially attractive for CO2 capture from industrial flue gas due to its lower pressure drop compared to its counterparts such as spiral wound modules and hollow fiber modules. To design better plate-and-frame modules, we investigate their basic unit - a single membrane stack through a combination of computational modeling and experimental investigations. The modeling approach is based on Computational Fluid Dynamics (CFD) to represent a multiphysics problem, including the fluid flow and diffusion processes within a membrane module. We use experimental data collected under different operating conditions to validate the CFD model. Numerical results suggest a good agreement between experiments and model outputs for the CO2 recovery, CO2 mole fraction in the retentate and permeate, and stage-cut. The CFD model is able to predict accurately the flow behavior, providing valuable insights on the effects of fluid dynamics on mass transfer of CO2. We also carry out a sensitivity analysis to identify the effect of key parameters on the CO2 recovery and the CO2 purity of the outlet streams.

Dosso, Cheick↗

CFD Modeling of Tank Pressurization and Axial Jet Mixing Experiments with and without Non-Condensable Gas in the Ullage

A two-phase CFD model for tank pressurization and following jet mixing of a cryogenic storage tank is presented using VOF approach for representing the phase boundary and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. The CFD model was validated against pressurization and liquid jet mixing data for a 110-inch diameter tank provided by Bullard1. Cases with like-gas and non-condensable gas pressurization are studied. The results of the cases with like-gas pressurization and following mixing are presented first, focusing on the effects of turbulence at the vapor-liquid interface on the tank pressure and phase change rates predictions. The second part of this paper is devoted to testing and validating the CFD model against non-condensable gas pressurization and following mixing. Tank pressures predicted in both cases are compared with each other and with the experimental data.

Computational Fluid Dynamics↗

CFD Modeling of Tank Pressurization and Axial Jet Mixing Experiments with and without Non-Condensable Gas in the Ullage

A two-phase CFD model for tank pressurization and following jet mixing of a cryogenic storage tank is presented using VOF approach for representing the phase boundary and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. The CFD model was validated against pressurization and liquid jet mixing data for a 110-inch diameter tank provided by Bullard. Cases with like-gas and non-condensable gas pressurization are studied. The results of the cases with like-gas pressurization and following mixing are presented first, focusing on the effects of turbulence at the vapor-liquid interface on the tank pressure and phase change rates predictions. The second part of this paper is devoted to testing and validating the CFD model against non-condensable gas pressurization and following mixing. Tank pressures predicted in both cases are compared with each other and with the experimental data.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Autogenous Pressurization and Expulsion

This paper presents a two-phase computational fluid dynamics (CFD) model for simulating autogenous pressurization and expulsion in a cryogenic liquid hydrogen storage tank, utilizing a volume-of-fluid (VOF) approach combined with the kinetics-based Schrage equation to accurately capture the phase boundary and interfacial heat, mass, and momentum transfer between liquid and vapor phases. The model is validated against experimental data from NASA's K-site tank facility, specifically experimental case 225, which involved pressurization and controlled expulsion of liquid hydrogen. Various turbulence models are evaluated to assess their influence on model accuracy. The CFD simulations successfully replicate key thermodynamic behaviors observed during the experiments, including pressure evolution, temperature profiles, and phase-change dynamics at the vapor-liquid interface. The predicted tank pressures, temperatures, and pressurant requirements agree with experimental data, with pressurant mass predictions within 16\% of observed values. This study highlights the importance of selecting appropriate turbulence models to accurately simulate complex flow and heat transfer phenomena during tank pressurization and expulsion. By enhancing the accuracy and reliability of CFD models for liquid hydrogen under cryogenic conditions, this research contributes to developing efficient cryogenic propellant management strategies for future space missions.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Autogenous Pressurization and Expulsion

This paper presents a two-phase computational fluid dynamics (CFD) model for simulating autogenous pressurization and expulsion in a cryogenic liquid hydrogen storage tank, utilizing a volume-of-fluid (VOF) approach combined with the kinetics-based Schrage equation to accurately capture the phase boundary and interfacial heat, mass, and momentum transfer between vapor and liquid phases. The model is validated against experimental data from NASA's K-site tank facility, specifically experimental case 225, which involved autogenous pressurization and controlled expulsion of liquid hydrogen. Various turbulence models are evaluated to assess their influence on model accuracy. The CFD simulations successfully replicate key thermodynamic behaviors observed during the experiments, including pressure evolution, temperature profiles, and phase-change dynamics at the vapor-liquid interface. The predicted tank pressures and temperatures agree well with experimental data, whereas the pressurant mass predictions are within 16% of observed values. This study emphasizes the importance of selecting appropriate turbulence models to accurately simulate the complex flow and heat transfer phenomena during tank autogenous pressurization and expulsion. By improving the accuracy and reliability of CFD models for these processes, this research contributes to developing efficient cryogenic propellant management strategies for future space missions.

Computational Fluid Dynamics↗

Coupled Microbial-Conversion and Computational-Fluid-Dynamics (CFD) Models for Butanediol Production in Micro-Aerated Reactors

Microbial conversion of substrates to macromolecules has been widely used in the synthesis of value-added products in pharmaceutical and biotechnology industries. These bioreactions are also being investigated in the production of low-value commodities such as biofuels [1]. Gas-liquid mass-transfer and transport-reaction coupling are important challenges when designing and scaling up these reactor systems. Experiments in wellmixed small-scale reactors have enabled characterization of microbial reactivity, while their coupling with macroscale transport remains relatively unexplored. In this work, we use a coupled metabolic-CFD model to study the action of a genetically engineered microbe Zymomonas mobilis [2] on sugars to produce 2,3-Butanediol (BDO). BDO is an important hydrocarbon intermediate that can be catalytically upgraded to several fuels and chemicals [3]. An important aspect to this particular microbial conversion is the need for micro-aerated environments as opposed to traditional aerobic fermentation. Slight variations in oxygen concentration can result in competing reaction pathways that disable BDO production. Hence, gas-liquid mass transfer and transport need to be optimized in large-scale reactors to maximize BDO production, for which CFD is a valuable tool. The aerobic-fermentation CFD model previously developed by the authors [5] for simulating bubble-column and airlift reactors at scale was used in this study. The Reynolds-averaged mass, momentum and energy transport equations for interpenetrating gas and liquid phase are solved in this model along with the transport and interphase mass transfer of oxygen. Our previous work used a phenomenological model for microbial oxygen uptake that neglected microbial growth and other reaction pathways. In this work, a detailed metabolic model enabled prediction of product formation and inhibition pathways. In order to manage computational cost, we used a subcycling technique [6] that takes advantage of the clear separation in transport (~ 200 sec) and reaction (~ 2-3 hours) timescales. The CFD model is first solved to steady state, after which the metabolic model is advanced at every cell in the computational domain using the local oxygen concentration. The CFD model is then run to achieve a new steady state that provides a new oxygen distribution for the metabolic model. This process, where reaction and fluid updates are interleaved together, is iterated until reactants are completely exhausted. This work will examine the performance of different reactor designs such as bubble column and airlift reactors at scale (250-500 m3). Oxygen mass-transfer coefficient and distribution are critically analyzed among reactors, and optimization studies pertaining to aeration is presented. Furthermore, it has been observed in experiments that high BDO production may be achieved by manipulating the aerobic environment over the course of reaction, such that oxygen concentration is high during the growth phase, and very low as sugar is depleted. This characteristic will be addressed by our simulations for which a timedependent scheduling strategy for aeration is presented that maximizes BDO production. [1] Humbird, D., Davis, R., and McMillan, J., Aeration costs in stirred-tank and bubble column bioreactors, Biochemical Engineering Journal, 127, 161—166, 2017 [2] Yang, S., Mohagheghi, A., Franden, M. A., Chou, Y.-C., Chen, X., Dowe, N., Himmel, M. E., and Zhang, M., Metabolic engineering of zymomonas mobilis for 2, 3-butanediol production from lignocellulosic biomass sugars. Biotechnology for biofuels, 9(1):189, 2016 [3] Kim, S. J., Sim, H. J., Kim, J. W., Lee, Y. G., Park, Y. C., and Seo, J. H., Enhanced production of 2,3-butanediol from xylose by combinatorial engineering of xylose metabolic pathway and cofactor regeneration in pyruvate decarboxylase-deficient Saccharomyces cerevisiae. Bioresource Technology, 245:1551–1557, 2017 [4] Weller, H., Tabor, G., Jasak, H. and Fureby, C., A tensorial approach to computational continuum mechanics using object-oriented techniques, Computers in physics, 12, 6, 620--631, 1998

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Validation of a Two-Phase CFD Model for Autogenous Pressurization and Expulsion

This paper presents a two-phase CFD model for tank pressurization and expulsion in a liquid hydrogen cryogenic storage tank. The model uses a Volume-of-Fluid approach combined with the Kinetics-based Schrage equation to capture the phase boundary and the associated interfacial heat, mass, and momentum transfer between the liquid and vapor regions. The CFD model is validated against expulsion data from the NASA K-Site tank experiment. Predicted tank pressures, temperatures, and pressurant requirements are compared with the experimental data to demonstrate the model’s accuracy.

Autogenous Pressurization↗

Atmospheric Boundary-Layer and Flutter Computations Using CFD Model of the Transonic Dynamics Tunnel

This paper presents two Computational Fluid Dynamics (CFD) models of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT). 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 as the test medium. The first computational model describes the generation of an atmospheric-boundary-layer (ABL) profile inside the tunnel. An ABL, which includes both a wind profile and turbulence content, is one of the aerodynamic characteristics affecting the occurrence of wind-induced oscillations for a launch vehicle sitting on a pad. The challenging part of this analysis was modeling the turbulent flow inside the tunnel. This is due to the special ABL-generating hardware that was installed at the entrance of the TDT test section in order to change the downstream velocity profile and to introduce velocity fluctuations into the flow. The second CFD model builds on the computational aeroelastic results that were generated in support of the second Aeroelastic Prediction Workshop (AePW) for the NASA Benchmark Supercritical Wing (BSCW) configuration. During the AePW, the wing-only configuration (classical free-air model) was analyzed. In the current study, the flutter computations were conducted on the configuration as it was mounted in the TDT during the experiment. This includes the wing attached to the splitter plate that was attached to the wind-tunnel walls. The preliminary results show that the wind-tunnel walls marginally affect flutter prediction.

Pawel Chwalowski↗

CFD Modeling Activities at the NASA Stennis Space Center

A viewgraph presentation on NASA Stennis Space Center's Computational Fluid Dynamics (CFD) Modeling activities is shown. The topics include: 1) Overview of NASA Stennis Space Center; 2) Role of Computational Modeling at NASA-SSC; 3) Computational Modeling Tools and Resources; and 4) CFD Modeling Applications.

Allgood, Daniel↗

Validated CFD Model for Multimode Gasoline Compression Ignition Engine

A validated CFD model for the multimode combustion engine developed under the DOE funded project DE-EE0008478 (Co-optimized Mixed-Mode Engine and Fuel Demonstrator for Improved Fuel Economy while Meeting Emissions Requirements). It incorporates advanced physics-based fuel surrogate models for thermophysical properties and reaction kinetics. The combustion modes include spark ignition (SI), low temperature combustion (LTC), and compression ignition (CI). The real fuel model was validated for RON60, RON70, RON80, RON90, and two biofuel blends. The validation cases can be found in https://doi.org/10.2172/1887341.

02 PETROLEUM↗

CFD Model Of The Transonic Dynamics Tunnel With Applications

This paper presents the Computational Fluid Dynamics (CFD) model of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) with some recent applications. The TDT is a continuous-flow, closed circuit, slotted-test-section wind tunnel with a 16- by 16-foot 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 at pressures from atmosphere down to near vacuum. In this study, experimental data acquired in the empty tunnel using R-134a as the test medium was used to calibrate the computational data. Experimental data from a recent TDT test of a full-span fighter configuration in air was then selected for comparison with the numerical data. During this test, the configuration experienced a flutter event in the transonic flow regime. Numerically, the flutter event is simulated both inside the CFD model of the TDT and in a classical free-air model. The preliminary results show that the wind-tunnel walls do not affect flutter prediction.

Chwalowski, Pawel↗