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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Combustor-Turbine Interactions By Using the Open National Combustion Code (OpenNCC) and the Glenn-HT Code

We develop the methodology of coupling two different computational fluid dynamic (CFD) codes, OpenNCC and Glenn-HT, in order to investigate the unsteady flow fields inside the combustor and around the first-stage stator of a high-pressure turbine (HPT) from the energy efficient engine (E 3 ) program. In our coupling strategy, OpenNCC, a time accurate unstructured mesh multi-phase combustion CFD code, is applied to the combustor region and Glenn-HT, a structured mesh CFD code designed for turbine applications, is utilized inside the HPT region. As a proof of concept, we first simulate the three-dimensional airflow over the backward facing step and compared the predicted pressure coefficient against experimental data. We then considered a Jet-A/Air combustor with the NASA single learn direct injector (LDI) as a reacting flow test case. Here, Glenn-HT is used in the downstream of the combustor and assumes that the working fluid is a single gas (i.e., air) where the properties of the gas are taken from time- and area-averaged values at the combustor exit. A fully coupled combustor-turbine simulation using both OpenNCC and Glenn-HT was conducted on the E 3 combustor and a detailed analysis done pertaining to how a realistic combustor outflow affects migration of hot-streaks and its impact on the aerodynamic behavior inside the HPT. It is found that the combustion dynamics (i.e., the switching main and pilot flame strength) significantly alters the aerodynamic behavior inside the HPT including hot-streak migration. Variations of the temperature and the velocity magnitude in the passage could be up to ±75 and ±15. These large variations are an important part of the combustor-turbine interactions, which are overlooked by a single component simulation of the HPT while imposing the steady inflow boundary condition at the HPT inlet. Finally, it is observed the strong density gradient associated with the hot-streaks and the pressure gradient at the passage significantly enhances the baroclinic torque, affecting the vorticity field.

CFD hot-streaks↗
NASA NTRSDate not supplied

Combining Data with Physical Knowledge for Uncertainty Quantification in Certification and Reliability Analysis

Unifying empirical data with predictive models can enable engineering cost-savings through certification by analysis and reliability-based design. Both concepts require rigorous uncertainty quantification (UQ) and robust understanding and treatment of relevant physics. Combining sampling-based UQ algorithms with high-fidelity simulations creates a computational bottleneck that is often alleviated through the use of machine learning (ML). ML can be used to create computationally efficient surrogates for simulations of complex or high-dimensional physical interactions (e.g., multi-phase interactions associated with melt pools in laser powder bed fusion or spatially-dependent material properties in functionally graded materials). However, negative side effects of ML may include a lack of interpretability and negative correlation between event rarity and simulation accuracy due to a lack of training data. As such, it is important to infuse ML algorithms with physics-based guardrails to provide confidence in their predictions. This talk will provide a brief review of recent NASA research at this intersection of physics-based simulation, ML, and UQ with a focus on certification and reliability analysis.

uncertainty quantification↗
NASA NTRSDate not supplied

Developing New Tools for Modeling Rocket Plume-Surface Interactions

With NASA’s goal to land the next human on the lunar surface in the next few years, it has become vitally important that we have a better understanding of how future landing spacecraft will interact with the unique properties of regolith¬¬––the layer of loose, unconsolidated dust and rock on the lunar surface¬¬––which can cause hazards like visual obstructions, particulate clouds, and cratering of the landing zone. Researchers from the Fluid Dynamics Branch at NASA’s Marshall Space Flight Center are performing plume-surface interaction (PSI) simulations between lander engine plumes and unprepared regolith surfaces, and have developed new tools to provide predictive PSI environments for various NASA projects and missions, including the Human Lander System (HLS), Commercial Lunar Payload Services (CLPS), and future Mars landers. These tools allow the researchers to determine how to best meet the simulation and time requirements for each project by varying model fidelity. The highest fidelity tool is the Gas Granular Flow Solver (Loci/GGFS) that models gas-particle multi-phase interactions to predict regolith cratering and ejection of particles into the immediate surroundings of the lander. At its highest fidelity, it can model microscopic regolith particle interactions with a particle size/shape distribution that statistically replicates actual regolith, however, to be most effective with today’s computing resources, it is currently run using only one to three equivalent particle sizes/shapes. The team also incorporated engineering models into their software suite to create production-ready hybrid tools with reduced fidelity. At the lowest fidelity, the computational fluid dynamics (CFD) code Loci/CHEM+DIGGEM can predict crater depth over time by relating local CFD-predicted surface shear stresses to a model of erosion mass flux.

plume surface interaction↗
NASA NTRSDate not supplied

Validation of Thermodynamic Behavior of Liquid Propellants under Sloshing and Draining

In recent years, considerable effort has been devoted to studying the future use of liquid methane (LCH4) in land, air, and space vehicle applications because of its high density and handling characteristics. This work presents a validation of computational tools for the thermodynamics characterization of a propellant tank undergoing sloshing and draining-induced thermal destratification as part of our continuous effort to improve simulation capabilities for support of NASA’s current and future flight programs. A multi-phase computational fluid dynamics (CFD) code developed at NASA MSFC, Loci/STREAM-VOF, is applied to predict gaseous pressurant requirements during the ramping, holding, and draining phases of operation with liquid methane. The experimental work conducted at the NASA K-site facility is used for validation. The effort showed that Loci/STREAM-VOF is capable of capturing the important findings from the previous experiments: (1) the pressurant mass required increases with the expulsion time due to longer mass transfer time at the interface; and (2) the pressurant mass required decreases with the increase in inlet temperature. Comparison with experimental data shows consistent good agreement at different expulsion times and different inlet gas temperatures.

H. Q. Yang↗
NASA NTRSDate not supplied

Development Efforts and Status of Plume-Surface Interaction Capabilities for Propulsive Landing Systems

Rocket plume-surface interaction is a multi-phase problem characterized by plume flow physics, erosion physics, and ejecta dynamics. All propulsive landers will experience plume-surface interaction. The risks posed by such effects can vary greatly as a function of the local environment, lander concept of operations, configuration, and physical scale. Prior Lunar and Martian landers have overcome challenges posed by these environments, on the basis of scaled ground testing and subsequent flight experience, but the landing systems for present and future missions are planning to operate increasingly outside of NASA's current experience with plume-surface interaction. This presentation discusses the current efforts and status of activities within NASA to progress understanding of fundamental plume-surface interaction physics, the capability to predict resulting environments and effects, and the definition of implications for current and future Lunar and planetary landing systems.

Landing↗
NASA NTRSDate not supplied

Validation of Thermodynamic Behavior of Liquid Propellants under Sloshing and Draining

In recent years, considerable effort has been devoted to studying the future use of liquid methane (LCH4) in land, air, and space vehicle applications because of its high density and handling characteristics. This work presents a validation of computational tools for the thermodynamics characterization of a propellant tank undergoing sloshing and draining-induced thermal destratification as part of our continuous effort to improve simulation capabilities for support of NASA’s current and future flight programs. A multi-phase computational fluid dynamics (CFD) code developed at NASA MSFC, Loci/STREAM-VOF, is applied to predict gaseous pressurant requirements during the ramping, holding, and draining phases of operation with liquid methane. The experimental work conducted at the NASA K-site facility is used for validation. The effort showed that Loci/STREAM-VOF is capable of capturing the important findings from the previous experiments: (1) the pressurant mass required increases with the expulsion time due to longer mass transfer time at the interface; and (2) the pressurant mass required decreases with the increase in inlet temperature. Comparison with experimental data shows consistent good agreement at different expulsion times and different inlet gas temperatures.

CFD↗
NASA NTRS2026

Influence of Processing Parameters on the Mechanical Properties of 3D Printed Borosilicate Particulate Reinforced Polymer Composites

Emerging composite materials are expanding the potential of additive manufacturing and enabling applications previously restricted by traditional manufacturing methods. The multi-phase nature of these composite materials combined with the complex in-ternal geometry of additively manufactured parts have enabled unique behavior, and potentially new applications. Additionally, these materials can be pyrolyzed to create dense metal, ceramic, and glass parts with geometries typically not achievable by tra-ditional processes. Additive manufacturing of borosilicate glass-based systems can open new applications in nuclear engineering, astronomy, and bone regrowth therapy. To elucidate the process-parameter relationship of borosilicate-polylactic acid (PLA) composites, mechanical testing was conducted and compared with a pure polylactic acid polymer baseline. Test specimens were fabricated by fused-filament fabrication with minimal post-processing. Yield strength, ultimate strength, and elastic modulus were calculated from stress-strain curves. Optical and scanning electron microscopy were conducted to observe the specimen microstructure before and after testing. The highest compressive yield strength for the composite was 28.22 MPa, and the highest compressive yield strength for PLA was 49.30 MPa. Print orientation was found to benefit the composite material but have a detrimental effect on the pure matrix material. An elastic modulus of 2.66 GPa was recorded for the borosilicate-PLA composite at 100% infill, 1 shell wall, and layer lines parallel to compression axis. Microscopy revealed that lower modulus composite specimens had the particulates re-distributed within the matrix. Tensile testing was done according to a polymer testing standard, which caused difficulties obtaining consistent fracture within the gauge length.

mechanical testing↗
NASA NTRS2022

An Investigation Into Some Important Aspects of Droplet Breakup/Vaporization Behavior Caused By a Gas Flow (Both Nonreacting & Detonative Combustion) in a Shock Tube

As a part of the rotating detonation engine (RDE) technology enablement project at NASA Glenn Research Center (GRC), an effort was undertaken to extend our current computational capabilities of OpenNCC in some important ways with the implementation of a modeling approach to account for the droplet breakup caused by a shock-induced gas motion, & a vaporization model valid over a wide range of pressure conditions encountered in multiphase detonation. With the modified code, a study was undertaken to investigate the individual droplet behavior followed by the passage of a shock front. The study is carried out by tracking a sparse group of droplets to gain some understanding of shock induced droplet behavior under various shock strengths & fuel injector conditions. The study also looks into the effect of randomization involved in determining the droplet breakup outcomes. Over a wide range of sub-critical conditions examined, larger droplets are observed to undergo significant changes in droplet behavior following their breakup. However, smaller droplets (10 µm or less ) remain unaffected by any shock induced breakup. In a follow-on work, we investigated the impact of shock and droplet interaction in a detonation study involving both gaseous as well as gas/liquid (droplet clouds) fuel/air stoichiometric mixtures in a simple 3D shock-tube configuration. The droplet clouds are made up of different initial droplet sizes of either 6, 10, or 30 µm. We also investigated the individual droplet behavior followed by the passage of a detonation front. The results represent conditions that lead to both overdriven and C-J (ChapmanJouguet) detonations. Under both test conditions, most of the droplet vaporization is completed within a short distance (duration) behind the detonation front & well within the region of complete combustion observed in a corresponding equivalent gas-phase fuel/air mixture. The impact of the shock-induced droplet breakup is found to be significant in the calculations involving the 30-µm droplets. Subsequent to the breakup, the drop sizes vary from 1 to 10 µm. Another factor that contributed to the observed rapid vaporization is the result of vaporization taking place under supercritical conditions. The overall detonation properties of various droplet clouds (made up of different initial sizes) are similar to those observed in a corresponding gaseous fuel/air mixture. In the calculation involving a gaseous fuel, the calculated C-J detonation velocity is 1822 m/s involving Jet-A/air and φ = 1. In the overdriven detonation, it is 2044 m/s. In the calculations involving droplet clouds, the corresponding detonation velocities are lower. The impact of increased droplet size is primarily seen in a higher reduction in the detonation velocity.

shock/droplet interaction↗
NASA NTRSDate not supplied

Modeling Autogenous Pressurization and Draining of a Cryogenic Storage Tank in Normal Gravity

A two-phase CFD model for autogenous pressurization and draining of a cryogenic storage tank is presented using both the Sharp Interface and Volume-Of-Fluid (VOF) approaches for capturing the front and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. Both models are validated against data provided by the Cryogenic Propellant Storage and Transfer (CPST) Engineering Development Unit (EDU) experiment. The results of the autogenous pressurization are presented first, focusing on the phase change and turbulence effects on the tank pressure and temperature predictions. Both the Sharp Interface (SI-CFD) and VOF (VOF-CFD) multiphase models predict tank pressure during pressurization within 3% of the measured values. The sensitivity of key physical and numerical parameters of the problem are tested using the Sharp Interface model. Effects of the accommodation coefficient (AC), and the computational grid structure are studied. The second part of this paper is devoted to validating the SI-VOF model, with an enhanced capability of moving the liquid-vapor interface, against the draining segment of the EDU experiment. The VOF-CFD model was also used to simulate tank draining and its results were compared with the results of the Sharp Interface model with the moving interface. Both models predict tank pressure during draining within 3.5% of the measured values. Pressure decrease rate is underpredicted by both models during the first 100 seconds of draining but matches the experimental rate for the rest of the simulation.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Modeling Autogenous Pressurization and Draining of a Cryogenic Storage Tank in Normal Gravity

A two-phase CFD model for autogenous pressurization and draining of a cryogenic storage tank is presented using both the Sharp Interface and Volume-Of-Fluid (VOF) approaches for capturing the front and the associated interfacial heat, mass and momentum transfer between the liquid and vapor regions. Both models are validated against data provided by the Cryogenic Propellant Storage and Transfer (CPST) Engineering Development Unit (EDU) experiment1. The results of the autogenous pressurization are presented first, focusing on the phase change and turbulence effects on the tank pressure and temperature predictions. Both the Sharp Interface (SI-CFD) and VOF (VOF-CFD) multiphase models predict tank pressure during pressurization within 3% of the measured values. The sensitivity of key physical and numerical parameters of the problem are tested using the Sharp Interface model. Effects of the accommodation coefficient (AC), and the computational grid structure are studied. The second part of this paper is devoted to validating the SI-VOF model, with an enhanced capability of moving the liquid-vapor interface, against the draining segment of the EDU experiment. The VOF-CFD model was also used to simulate tank draining and its results were compared with the results of the Sharp Interface model with the moving interface. Both models predict tank pressure during draining within 3.5% of the measured values. Pressure decrease rate is underpredicted by both models during the first 100 seconds of draining but matches the experimental rate for the rest of the simulation.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the Volume of Fluid (VOF) and Sharp Interface multiphase 2D axisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. Turbulence modeling; turbulence damping at the interface; and using constant vs. temperature dependent fluid properties were shown to have the most profound influence on predicted tank pressures and temperatures. Current study indicates that including phase change at the interface into the computational model is crucial for accurate prediction of the tank self-pressurization process. The effect of accommodation coefficient was also studied. Tank pressure values predicted by the VOF, and Sharp Interface models are within 4% of the experimental ones.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

CFD Model Development of a Cryogenic Storage Tank Self-Pressurization in Normal Gravity and Validation against SHIIVER Experiment

Two-Phase flow and heat transfer simulations with interfacial phase change of the Structural Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) self-pressurization experiment were conducted using storage tank CFD model in the framework of the ANSYS Fluent CFD code. The simulations were performed for the 70% fill level case with MLI on domes and no vapor cooling. All the phase change calculations in these simulations were generated by in-house Schrage-based evaporation-condensation model. The calculations were performed using both the VOF and Sharp Interface multiphase 2Daxisymmetric models. A number of parametric and sensitivity studies were performed to check the various aspects of the CFD model. These studies helped to understand the effects of varying several parameters on the tank pressure and temperature during self-pressurization. These parameters include: the effect of turbulence modeling and turbulence damping at the interface; the effect of constant vs. temperature dependent fluid properties; the effect of accommodation coefficient; the effect of modeling phase change at the interface and the effect of the fill level.

Computational Fluid Dynamics↗
NASA NTRSDate not supplied

Development and Validation of Two-Phase CFD Models for Key Elements of Propellant Tank CFM Operations in 1G and Microgravity –An Overview

This paper presents an overview of the state-of-the-art two-phase CFD models that have been developed for various propellant tank storage and transfer operations in 1g, partial gravity, and microgravity. The models are developed in the framework of the industry standard ANSYS/Fluent CFD code, the capabilities of which have been significantly enhanced and customized through the incorporation of unique submodels via User Defined Functions (UDF)s to satisfy the requirements of its intended variable gravity Cryogenic Fluid Management (CFM) applications. These models/submodels have been validated against experimental data that cross spatial scales, fluid types, and gravity levels in order to properly anchor the models’ physical and numerical fidelity. The CFM application/processes that have been modeled include tank self-pressurization, tank autogenous pressurization, tank pressure control using both subcooled jet mixing and droplet spray injection mechanisms, tank chilldown/filling, tank drainage, tank slosh for both volatile and non-volatile fluids. The strength and shortcomings of the two-phase models for each application are highlighted and discussed briefly.

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 NTRSDate not supplied

Modeling of Cryogenic Heated-Tube Flow Boiling Experiments of Hydrogen and Helium With GFSSP

Accurate modeling of cryogenic boiling heat transfer is vital for the development of extended-duration space missions. Such missions may require the transfer of cryogenic propellants from in-space storage depots or the cooling of nuclear reactors. Purdue University in collaboration with NASA has assembled a database of cryogenic flow boiling data points from heated-tube experiments dating back to 1959, which has been used to develop new flow boiling correlations specifically for cryogens. Computational models of several of these experiments have been constructed in the Generalized Fluid System Simulation Program (GFSSP), a network flow code developed at NASA’s Marshall Space Flight Center. The new Purdue-developed correlations cover the full boiling curve: onset of nucleate boiling, nucleate boiling, critical heat flux, and film boiling. These correlations have been coded into GFSSP user subroutines. The fluids modeled are hydrogen and helium. Predictions of wall temperature, heat transfer coefficient, and pressure drop are presented and compared to the test data.

multi-phase flow↗
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 NTRSDate not supplied

Modeling of Cryogenic Heated-Tube Flow Boiling Experiments of Nitrogen and Methane with the Generalized Fluid System Simulation Program

Accurate modeling of cryogenic boiling heat transfer is vital for the development of extended-duration space missions. Such missions may require the transfer of cryogenic propellants from in-space storage depots or the cooling of nuclear reactors. Purdue University in collaboration with NASA has assembled a database of cryogenic flow boiling data points from heated-tube experiments dating back to 1959, which has been used to develop new flow boiling correlations specifically for cryogens. Computational models of several of these experiments have been constructed in the Generalized Fluid System Simulation Program (GFSSP), a network flow code developed at NASA’s Marshall Space Flight Center. The new Purdue-developed correlations cover the full boiling curve: onset of nucleate boiling, nucleate boiling, critical heat flux, and film boiling. These correlations have been coded into GFSSP user subroutines. The fluids modeled are methane and nitrogen. Predictions of wall temperature and heat transfer coefficient are presented and compared to the test data.

Multi-Phase Flow↗
NASA NTRSDate not supplied

Critical Heat Flux of Liquid Hydrogen, Liquid Methane, and Liquid Oxygen: A Review of Available Data and Predictive Tools

Available experimental data dealing with critical heat flux (CHF) of liquid hydrogen (LH 2 ), liquid methane (LCH 4 ), and liquid oxygen (LO 2 ) in pool and flow boiling are compiled. The compiled data are compared with widely used correlations. Experimental pool boiling CHF data for the aforementioned cryogens are scarce. Based on only 25 data points found in five independent sources, the correlation of Sun and Lienhard (1970) is recommended for predicting the pool CHF of LH 2 . Only two experiments with useful CHF data for the pool boiling of LCH 4 could be found. Four different correlations including the correlation of Lurie and Noyes (1964) can predict the pool boiling CHF of LCH 4 within a factor of two for more than 70% of the data. Furthermore, based on the 19 data points taken from only two available sources, the correlation of Sun and Lienhard (1970) is recommended for the prediction of pool CHF of LO 2 . Flow boiling CHF data for LH 2 could be found in seven experimental studies, five of them from the same source. Based on the 91 data points, it is suggested that the correlation of Katto and Ohno (1984) be used to predict the flow CHF of LH 2 . No useful data could be found for flow boiling CHF of LCH 4 or LO 2 . The available databases for flow boiling of LCH 4 and LO 2 are generally deficient in all boiling regimes. This deficiency is particularly serious with respect to flow boiling.

Multi-Phase Flow↗