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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Optimizing green infrastructure placement under precipitation uncertainty

Increased urbanization, infrastructure degradation, and climate change threaten to overwhelm stormwater systems across the nation, rendering them ineffective. Green Infrastructure (GI) practices are low cost, low regret strategies that can contribute to urban runoff management. However, questions remain as to how to best distribute GI practices through urban watersheds given precipitation uncertainty and the variable hydrological responses to them. We develop stochastic programming models to determine the optimal placement of GI practices across a set of candidate locations in a watershed to minimize the total expected runoff under medium-term precipitation uncertainties. Specifically, we first develop a two-stage stochastic programming model. Next, we reformulate this model using perturbed parameters to reduce the requisite computational time and extend it to multi-stage. In addition, we introduce constraints that allow for incorporating sub-catchment-level runoff reduction considerations. Furthermore, we account for hydrological connectivity in the watershed using an underlying acyclic connectivity graph of sub-catchments and incorporate various practical considerations into the models. In addition, we develop a systemic approach to downscale the existing daily precipitation projections into hourly units and efficiently estimate the corresponding hydrological responses. These advancements are brought together in a case study for an urban watershed in a mid-sized city in the U.S., where we perform sensitivity analyses, evaluate the importance of the considered constraints, and provide insights.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

MSR Salt Spill Accident Testing Using Eutectic NaCl-UCl 3

Assessing the potential consequences of identified accident scenarios is an essential part of the licensing process for a new nuclear reactor and is achieved by using accident progression models. A likely accident scenario that will be evaluated by developers of molten salt reactors (MSRs) is a spill of radionuclide-bearing fuel salt onto the reactor containment floor (i.e., a salt spill accident). Models to determine the consequences of a molten salt spill accident need to be parameterized and validated using experimental data, but little experimental effort has been dedicated to fill these data gaps to date. Specifically, data is needed to enable model development for individual processes (e.g., spreading, heat transfer, corrosion, radionuclide vaporization, and aerosol generation) that quantifies the sensitivities towards the initial conditions of the spill, the ambient environment, and the features of the containment. In addition, integrated experiments that simulate salt spill accidents will need to be conducted to provide insight into coupled processes and data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1981

The use of frequency methods in rotorcraft system identification

A new approach to model structure determination is examined. Flight data from the Rotor Systems Research Aircraft (RSRA) are transformed into the frequency domain and truncated to provide band limiting. The stepwise regression technique is then used to identify a quasistatic state-space model from the transformed data. The data processing requirements for both time domain and frequency domain identification are discussed and the results of the two techniques are compared.

Duval, R. W.↗
DOE OSTI2022

Data-Driven Simulation-Based Planning for Electric Airport Shuttle Systems: A Real-World Case Study

Many airports are adopting battery electric buses in their shuttle fleets due to concerns over air quality and regulations. This study proposes a simulation-based optimization modeling framework to help airport shuttle operators effectively deploy electric buses. We evaluated a planned airport electric shuttle system with an event-driven simulator. Empirical data collected from existing systems were used to drive the simulations. We then proposed a simulation-based optimization model to determine the battery capacity, charging power, and number of chargers so that predefined objective(s) (e.g., minimizing total capital cost, minimizing emissions) are optimized. Compared to existing studies, the primary contribution of the proposed method is that it can model the real-world stochastic nature of operations in an electric bus system with much higher fidelity. To demonstrate the proposed modeling framework, we study a real-world shuttle system at the Dallas-Fort Worth International Airport, and present extensive numerical studies. When considering partial fleet electrification, the model can provide a set of Pareto optimal solutions. When considering full fleet electrification, the optimal solution requires a 50-kWh battery capacity and four 210-kW chargers, resulting in a total capital cost of $26,744,000. The results demonstrate that the proposed modeling framework can effectively optimize the planning of electric airport shuttle systems with partial or full fleet electrification.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

The profile algorithm for microwave delay estimation from water vapor radiometer data

A new algorithm has been developed for the estimation of tropospheric microwave path delays from water vapor radiometer (WVR) data, which does not require site and weather dependent empirical parameters to produce accuracy better than 0.3 cm of delay. Instead of taking the conventional linear approach, the new algorithm first uses the observables with an emission model to determine an approximate form of the vertical water vapor distribution, which is then explicitly integrated to estimate wet path delays in a second step. The intrinsic accuracy of this algorithm, excluding uncertainties caused by the radiometers and the emission model, has been examined for two channel WVR data using path delays and corresponding simulated observables computed from archived radiosonde data. It is found that annual rms errors for a wide range of sites average 0.18 cm in the absence of clouds, 0.22 cm in cloudy weather, and 0.19 cm overall. In clear weather, the new algorithm's accuracy is comparable to the best that can be obtained from conventional linear algorithms, while in cloudy weather it offers a 35 percent improvement.

Robinson, Steven E.↗
NASA NTRS1998

BATSE Observations and Orbit Determination of the Be/X-Ray Transient EXO 2030+375

The Be/X-ray binary transient pulsar EXO 2030+375 (P(sub s) approx equal 42 s) has been observed with the large area detectors (LADs) of the Burst and Transient Source Experiment (BATSE) on the Compton Gamma-Ray Observatory (CGRO). Beginning in May 1991, twenty-two outbursts were observed over four years. Thirteen outbursts between February 1992 and August 1993 occurred consecutively at intervals of approx equal 46 days, close to the orbital period determined by Parmar et al. (1989) using EXOSAT data. The pulse profiles from the BATSE data are double-peaked and show no significant energy or luminosity dependence, unlike the EXOSAT observations of May-August 1985. An exponential model was used to fit the observed hard X-ray energy spectra from the thirteen consecutive outbursts. When EXOSAT discovered this pulsar during a giant outburst in May 1985, the X-ray luminosity peaked at L(sub x) = 1.0 x 10(esp 38) erg/ s (1-20 keV), assuming a 5 kpc distance to the source. The BATSE outbursts are found to be weaker 0.3 x 10(exp 37) less than or equal to L(sub x)(I-20 keV) less than or equal to 3.0 x 10(exp 37) erg/ s after extrapolating the observed flux (20-50 keV) to the EXOSAT energy band. Pulse phases derived from the thirteen outbursts were fit to two different models to determine a binary orbit. The new orbit is used to estimate 95% confidence limits for the mean peak spin frequency change during the out- bursts observed with BATSE. This, and the mean peak flux, are compared to the spin-up rates and fluxes determined by EXOSAT from the 1985 giant outburst, where disk accretion was thought to have occurred. It is unclear if these normal outbursts were driven by wind or disk accretion.

Strollberg, Mark T.↗
NASA NTRS2019

Urban Air Mobility Network and Vehicle Type - Modeling and Assessment

This paper describes exploratory modeling of an on-demand urban air mobility (UAM) network and sizing of vehicles to operate within that network. UAM seeks to improve the movement of goods and people around a metropolitan area by utilizing the airspace for transport. Aircraft sizing and overall network performance results are presented that include comparisons of battery-electric and various hybrid-electric vehicles that are fueled with diesel, jet fuel, compressed natural gas, and liquefied natural gas (LNG). Hybrid-electric propulsion systems consisting of internal combustion engine-generators, turbine-generators, and solid oxide fuel cells are explored. Ultimately, the "performance" of the UAM network over a day for each of the different vehicle types, propulsion systems, and stored energy sources is described in four parameters: 1) the average cost per seat-kilometer, which considers the costs of the energy/fuel, vehicle acquisition, insurance, maintenance, pilot, and battery replacement costs, 2) carbon dioxide emission rates associated with vehicle operations, 3) the average passenger wait time, and 4) the average load factor, i.e., the total number of seats filled with paying passengers divided by the total number of available seats. Results indicate that the "dispatch model," which determines when and where aircraft are flown around the UAM network, is critical in determining the overall network performance. This is due to the often-conflicting desires to allow passengers to depart with minimal wait time while still maintaining a high load factor to reduce operating costs. Additionally, regardless of the dispatch model, hybrid-electric aircraft powered by internal combustion engines fueled with diesel or LNG are consistently the lowest cost per seat-kilometer. Battery-electric and future technology LNG/solid oxide fuel cell aircraft produce the lowest emissions (assuming the California grid) with LNG-fueled internal combustion engine-powered hybrids producing only slightly more carbon dioxide.

Assessment↗
DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hanford Waste Treatment Plant Effluent Management Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The Hanford Tank Waste Treatment and Immobilization Plant Effluent Management Facility (EMF) stack monitor location was qualified using a combination of scale model stacks to mitigate the risk of identifying that the sampling location does not meet the qualification criteria on the full-scale stack. The LV-S1 scale model stack was used as a baseline, augmented by the LB-S1 and LV-S2 scale model stacks to address the Direct Feed Low Activity Waste Effluent Management Facility Vessel Vent Process (DVP) injection into the main Active Confinement Ventilation (ACV) system duct. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling locations were geometrically similar to the actual stack, and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. The LV-S1, LB-S1, and LV-S2 scale model stack tests have met the criteria of the ANSI/HPS N13.1-1999 standard to demonstrate the stack sampling locations are well mixed. Verification tests of the EMF stack were performed at normal operating conditions. The minimum 1/6 DV value and the maximum 6 DV value from the scale model testing determine the range of stack flow rates for which the full-scale stack may be operated while remaining in compliance with the stack verification criterion. A practical range for the full-scale stack qualification uses the average DV through 6 DV from the scale model tests to compute the corresponding flow rates. Table S1 lists the operating flow rate along with the average and maximum qualified stack flow rate based on the LV-S1 scale model DV values. The operating flow is below the maximum qualified stack flow, which means that the scale model test results are acceptable for stack qualification. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be ≤20°. Second, the velocity uniformity at the full-scale stack must be ≤20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack test at the EMF. Flow angle results were <5°; all flow angle results were within the ≤20° criterion. The velocity uniformity results for each test condition ranged between 2.2% COV and 4.3% COV, all of which were within the range of the target % COV values from the scale model tests on the LV-S1, LB-S1, and LV S2 scale models. Based on these stack verification test results, the EMF filtered exhaust stack sampling location meets the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all planned fan operating configurations. This includes each combination of ACV fans with DVP exhausters. Further changes to the system configuration or operating conditions that are outside the qualified flow rates described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Hanford Waste Treatment Plant LAB Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The Waste Treatment Plant laboratory (LAB) facility stack monitor locations were qualified using scale model stacks to mitigate the risk of identifying that sampling locations do not meet the qualification criteria on the full-scale stack. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling location were geometrically similar to the actual stack, and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the LAB stacks were performed at normal operating conditions. The minimum 1/6 DV value, along with the maximum 6 DV value from the scale model testing, determines the range of conditions for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. A practical range for the full-scale stack qualification uses the average DV through 6 DV from the scale model tests to compute the corresponding flow rates. Table S1 lists the operating flow rates along with the average and maximum qualified stack flow rates for each of the LAB facility stacks. For each stack, the operating flow is below the maximum qualified stack flow, which means that the scale model test results are acceptable for stack qualification. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be ≤20°. Second, the velocity uniformity at the full-scale stack must be ≤20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack tests at the LAB facility. Flow angle results were primarily less than 10°, except for the LB-C2 Fan A results, which were an average of 13.7°; all flow angle results were within the ≤20° criterion. The velocity uniformity results for each test condition averaged between 1.5 and 4.1% COV, which were all within the range of the target percent coefficient of variation values from the scale model tests. Based on these stack verification test results, the three LAB filtered exhaust stack sampling locations meet the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all fan operating configurations. This includes single-fan as well as dual-fan operations for LB-C2, each of the dual-fan operating conditions for LB-S1, and each single-fan operating condition for LB-S2. Further changes to the system configuration or operating conditions that are outside the bounds described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Hanford Waste Treatment Plant LAB Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The WTP LAB stack monitor locations were qualified using scale model stacks to mitigate the risk of identifying that sampling locations do not meet the qualification criteria on the full-scale stack. As required by the ANSI/HPS N13.1-1999 standard, the scale model and its sampling location were geometrically similar to the actual stack and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the DV of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. Verification tests of the LAB stacks were performed at normal operating conditions. The maximum 6 DV value from the scale model testing determines the maximum conditions for which the full-scale stack may be operated and remain in compliance with the stack verification criterion. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be = 20°. Second, the velocity uniformity at the full-scale stack must be = 20% COV. Finally, the velocity uniformity results for the actual and scale model stacks must agree within 5% COV. In general, these criteria were met through the full-scale stack tests at the LAB facility. Some specific items for each scale model and full-scale stack comparison should be noted in assessing the validity of the verification tests. The LB-C2 scale model stacks were performed with single fan operations at then-minimum flow conditions. These conditions resulted in DV values that were too low to meet the DV range criterion, and therefore are unable to be used in qualifying single fan operations on the full-scale stack. However, the single fan operations demonstrated COV values for velocity uniformity as well as flow angles that were comparable to the dual-fan operations at high flows. Overall, the test conditions and test results were within the range of acceptable values based on current design flow rates. Single fan operations are expected to only occur infrequently for maintenance needs and is therefore not a planned operating condition at this time. The LB-S1 scale model stacks were performed at three fan combinations, and in each combination, at least one test was performed at the then-minimum flow conditions as well as at then-maximum flow conditions. While the then-minimum flow conditions result in a DV range that is lower than the verification test DV value, and therefore does not meet the criterion, these tests are un-necessary for the verification test acceptance. The normal and maximum flow conditions from the scale model stack tests meet the DV range criterion, and the velocity uniformity test results compare favorably with the full-scale stack results. The LB-S2 scale model stacks were performed at nominally the same maximum flow condition; however, the 6 DV value for Fan A operation was slightly lower than the full-scale stack test DV. The COV values from the scale model stacks were comparable between the Fan A and Fan B results, and the overall test conditions are within the range of acceptable values. The stack verification is therefore considered acceptable for both Fan A and Fan B operations. The verification tests were performed at flows that were appreciably higher than the design conditions, and further elevated flow rates would be beyond the range of acceptable DV. Based on these stack verification test results, the three LAB filtered exhaust stacks meet the qualification criteria provided in the ANSI/HPS N13.1-1999 standard. Further changes to the system configuration or operating conditions that are outside the bounds described in this and the scale model test reports (Glissmeyer, Flaherty, and Piepel (2001), Glissmeyer and Geeting (2013)) may require additional tests and additional analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2011

Computational Models of Exercise on the Advanced Resistance Exercise Device (ARED)

Muscle and bone loss remain a concern for crew returning from space flight. The advanced resistance exercise device (ARED) is used for on-orbit resistance exercise to help mitigate these losses. However, characterization of how the ARED loads the body in microgravity has yet to be determined. Computational models allow us to analyze ARED exercise in both 1G and 0G environments. To this end, biomechanical models of the squat, single-leg squat, and deadlift exercise on the ARED have been developed to further investigate bone and muscle forces resulting from the exercises.

Newby, Nate↗
DOE OSTI2020

Black-Box Optimization for Design of Concentrating Solar Power and Photovoltaic Hybrid Systems with Optimal Dispatch Decisions

The hybridization of concentrating solar power (CSP) and photovoltaics (PV) can enable dispatchable renewable electricity generation at a lower price than current stand-alone CSP systems. However, designing a CSP-PV hybrid system can be challenging because of the many degrees of freedom in design that affect the internal and external system interactions and trade-offs. We develop a methodology to determine optimal designs for CSP-PV hybrids by implementing NLopt's derivative-free, or “black-box,” algorithms around pre-existing CSP-PV hybrid simulation software that utilizes the National Renewable Energy Laboratory’s System Advisor Model (SAM); we then employ a dispatch optimization model to determine operational decisions that maximize a plant’s profits. We present optimal designs for CSP-PV hybrid systems dispatching against four time-of-delivery (ToD) pricing structures. NLopt’s algorithms can improve the base case design’s power purchase agreement (PPA) price by 15% to 21%, depending on the ToD pricing structure. In addition, we present the resulting optimal CSP-PV hybrid design’s annual performance metrics, which tend to have capacity factors between 50% and 62%, but are able to generate electricity during the year’s highest-valued periods about 90% of the time. Lastly, we investigate the trade-offs between capacity factor and PPA price using Pareto fronts and demonstrate that, for some ToD pricing structures, the system capacity factor can increase by 20% but at the expense of a 2% increase in PPA price.

black-box↗
DOE OSTI2020

Using Fourier-Plane Imaging Microscopy for Determining Transition-Dipole-Moment Orientations in Organic Light-Emitting Devices

Here, we use Fourier-plane imaging microscopy (FIM) to determine the transition-dipole-moment orientation in doped organic emissive thin films. The use of FIM enables precise, sensitive, and rapid measurement of dipole orientation in the emission layer of an organic light-emitting device (OLED). An optical model of a stratified birefringent multilayer is introduced for interpreting results obtained by FIM. Using the model, we determine the average orientation of transition-dipole-moment vectors of three phosphorescent dopant emitters. The dipole alignment measured by FIM quantitatively explains the difference in OLED efficiencies using these archetype dopant molecules. FIM provides a nondestructive tool to measure and ultimately improve the outcoupling efficiency of OLEDs and other light-emitting devices.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1976

Development of a solid propellant viscoelastic dynamic model

The results of a one year study to develop a dynamic response model for the Space Shuttle Solid Rocket Motor (SRM) propellant are presented. An extensive literature survey was conducted, from which it was concluded that the only significant variables affecting the dynamic response of the SRM propellant are temperature and frequency. Based on this study, and experimental data on propellants related to the SRM propellant, a dynamic constitutive model was developed in the form of a simple power law with temperature incorporated in the form of a modified power law. A computer program was generated which performs a least-squares curve-fit of laboratory data to determine the model parameters and it calculates dynamic moduli at any desired temperature and frequency. Additional studies investigated dynamic scaling laws and the extent of coupling between the SRM propellant and motor cases. It was found, in agreement with other investigations, that the propellant provides all of the mass and damping characteristics whereas the case provides all of the stiffness.

Hufferd, W. L.↗
NASA NTRS1990

Radiative flux measurements in the stratosphere

The objective is to determine how the stratospheric tropospheric exchange of water vapor is affected by the interaction of solar (visible) and planetary (infrared) radiation with tropical cumulonimbus anvils. This research involves field measurements from the ER-2 aircraft as well as radiative transfer modelling to determine heating and cooling rates and profiles that directly affect the exchange between the troposphere and the stratosphere.

Valero, Francisco P. J.↗
NASA NTRS1995

The NASA Ames Hypersonic Combustor-Model Inlet CFD Simulations and Experimental Comparisons

Computations have been performed on a three-dimensional inlet associated with the NASA Ames combustor model for the hypersonic propulsion experiment in the 16-inch shock tunnel. The 3-dimensional inlet was designed to have the combustor inlet flow nearly two-dimensional and of sufficient mass flow necessary for combustion. The 16-inch shock tunnel experiment is a short duration test with test time of the order of milliseconds. The flow through the inlet is in chemical non-equilibrium. Two test entries have been completed and limited experimental results for the inlet region of the combustor-model are available. A number of CFD simulations, with various levels of simplifications such as 2-D simulations, 3-D simulations with and without chemical reactions, simulations with and without turbulent conditions, etc., have been performed. These simulations have helped determine the model inlet flow characteristics and the important factors that affect the combustor inlet flow and the sensitivity of the flow field to these simplifications. In the proposed paper, CFD modeling of the hypersonic inlet, results from the simulations and comparison with available experimental results will be presented.

Venkatapathy, E.↗