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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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Studies are reported of the long term responses of the model atmosphere to anomalies in snow cover and sea surface temperature. An abstract of a previously issued report on the computed response to surface anomalies in a global atmospheric model is presented, and the experiments on the effects of transient sea surface temperature on the Mintz-Arakawa atmospheric model are reported.
Abstract Quantitative predictions of natural and induced phenomena in fractured rock is one of the great challenges in the Earth and Energy Sciences with far‐reaching economic and environmental impacts. Fractures occupy a very small volume of a subsurface formation but often dominate fluid flow, solute transport and mechanical deformation behavior. They play a central role in CO 2 sequestration, nuclear waste disposal, hydrogen storage, geothermal energy production, nuclear nonproliferation, and hydrocarbon extraction. These applications require predictions of fracture‐dependent quantities of interest such as CO 2 leakage rate, hydrocarbon production, radionuclide plume migration, and seismicity; to be useful, these predictions must account for uncertainty inherent in subsurface systems. Here, we review recent advances in fractured rock research covering field‐ and laboratory‐scale experimentation, numerical simulations, and uncertainty quantification. We discuss how these have greatly improved the fundamental understanding of fractures and one's ability to predict flow and transport in fractured systems. Dedicated field sites provide quantitative measurements of fracture flow that can be used to identify dominant coupled processes and to validate models. Laboratory‐scale experiments fill critical knowledge gaps by providing direct observations and measurements of fracture geometry and flow under controlled conditions that cannot be obtained in the field. Physics‐based simulation of flow and transport provide a bridge in understanding between controlled simple laboratory experiments and the massively complex field‐scale fracture systems. Finally, we review the use of machine learning‐based emulators to rapidly investigate different fracture property scenarios and accelerate physics‐based models by orders of magnitude to enable uncertainty quantification and near real‐time analysis.
The feasibility of long-range weather prediction through the use of global general circulation models (GCMs) was investigated. A climate model was developed to simulate the monthly mean state of the atmosphere from real global initial data at the beginning of the month. The model contains the same dynamic and physical ingredients as most numerical weather prediction models and GCMs. The model generates a one-day global simulation on the 8 x 10 grid in four minutes (on an IBM 360/95 computer), so that a 30 day forecast can be executed in two hours. The high speed of the model is achieved mainly at the price of its coarse resolution, which requires certain parameterizations of surface boundary conditions, as well as inherent filtering of smaller-scale features of the initial state.
Two scaled models of the Aeroassist Flight Experiment (AFE) vehicle were tested in two air wind tunnels and one CF4 tunnel. The tests were to determine the static longitudinal aerodynamic characteristics, and shock shapes for the configuration in hypersonic continuum flow. The tests were conducted with a range of angle of attack to evaluate the effects of Mach number, Reynolds numbers, and normal shock density ratio.
The Scale Model Acoustic Test (SMAT) is a 5% scale test of the Space Launch System (SLS), which is currently being designed at Marshall Space Flight Center (MSFC). The purpose of this test is to characterize and understand a variety of acoustic phenomena that occur during the early portions of lift off, one being the overpressure environment that develops shortly after booster ignition. The SLS lift off configuration consists of four RS-25 liquid thrusters on the core stage, with two solid boosters connected to each side. Past experience with scale model testing at MSFC (in ER42), has shown that there is a delay in the ignition of the Rocket Assisted Take Off (RATO) motor, which is used as the 5% scale analog of the solid boosters, after the signal to ignite is given. This delay can range from 0 to 16.5ms. While this small of a delay maybe insignificant in the case of the full scale SLS, it can significantly alter the data obtained during the SMAT due to the much smaller geometry. The speed of sound of the air and combustion gas constituents is not scaled, and therefore the SMAT pressure waves propagate at approximately the same speed as occurs during full scale. However, the SMAT geometry is much smaller allowing the pressure waves to move down the exhaust duct, through the trench, and impact the vehicle model much faster than occurs at full scale. To better understand the effect of the RATO timing simultaneity on the SMAT IOP test data, a computational fluid dynamics (CFD) analysis was performed using the Loci/CHEM CFD software program. Five different timing offsets, based on RATO ignition delay statistics, were simulated. A variety of results and comparisons will be given, assessing the overall effect of RATO timing simultaneity on the SMAT overpressure environment.
The feasibility of extended and long-range weather prediction by means of global atmospheric models was studied. A number of computer experiments were conducted at GISS with the GISS global general circulation model. Topics discussed include atmospheric response to sea-surface temperature anomalies, and monthly mean forecast experiments with the global model.
Three numerical experiments that investigate the scaling of land-surface processes - either of the inputs or parameters - are reported, and the aggregated processes are compared to the spatially variable case. The first is the aggregation of the hydrologic response in a catchment due to rainfall during a storm event and due to evaporative demands during interstorm periods. The second is the spatial and temporal aggregation of latent heat fluxes, as calculated from SiB. The third is the aggregation of remotely sensed land vegetation and latent and sensible heat fluxes using TM data from the FIFE experiment of 1987 in Kansas. In all three experiments it was found that the surface fluxes and land characteristics can be scaled, and that macroscale models based on effective parameters are sufficient to account for the small-scale heterogeneities investigated.
The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets both include millions of measurement voxels and the comparisons highlight the complex 3D nature of the flow including strong vertical velocities in spanwise street canyons and flow acceleration in streamwise street canyons. The concentration fields are qualitatively similar albeit the LES shows larger dispersion. A quantitative analysis with performance measures compares the datasets pointwise and demonstrates that the two 3D datasets are similar with respect to many measures including a fractional bias of 0.02 (ideal=0.0), correlation coefficient of 0.87 (ideal = 1.0), and the fraction points within a factor of 2 is 0.98 (ideal = 1.0). Plume analysis compares the arrival and residence time of contaminant and is found to vary significantly with location within the urban environment with arrival times between 0 and 1.25 and differences within the contaminant cloud less than 10% at most locations.
Significant hardening effect due to Fe concentrations in Ni-based alloys with face-centered-cubic structure has been studied by using a combined experimental and atomistic-based computational approach via nanoindentation tests. The obtained experimental load–displacement data for the [0 0 1] crystal orientation reached a qualitative good agreement with molecular dynamics simulations results, leading to strong evidence that the main strengthening factors are associated to sluggish dislocation diffusion, reduced defect sizes and the nucleation of tetrahedral stacking faults. Here, interstitial type prismatic dislocation loops mainly formed by $\frac{1}{6}$$\langle$1 1 2$\rangle$ Shockley dislocations are nucleated during the loading process, where their interaction leads to the formation of pyramidal shaped stacking fault which are mainly created by $\frac{1}{3}$$\langle$1 0 0$\rangle$ Hirth dislocations lines. Observing both types of defects coexisting in the same plastic deformation zone by both approaches. Reported mechanical data, measured experimentally and interpreted numerically, are also in accordance with microstructural SEM and TEM investigations.
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Small scale model acoustic experiments were conducted to measure the noise produced in the flyover and sideline planes by an engine under the wing externally blown flap configuration in its approach attitude. Broadband low frequency noise reductions as large as 9 dB were produced by reducing the separation distance between the nozzle exhaust plane and the flaps. Experiments were also conducted to determine the noise suppression effectiveness in comparison with a reference configuration of three passive types of devices that were located on the jet impingement surfaces of the reference configuration. These devices produced noise reductions that varied up to 10 dB at reduced separation distances. In addition, a qualitative estimate of the noise suppression characteristics of the separate devices was made. Finally static aerodynamic performance data were obtained to evaluate the penalties incurred by these suppression devices. The test results suggest that further parametric studies are required in order to understand more fully the noise mechanisms that are affected by the suppression devices used.
A program of research has recently been initiated under the NASA Innovative Research Program to develop and test techniques for reconstructing the three-dimensional shapes of asteroids from ground-based radar observations. Presently, no methods exist to do this and the full scientific potential of current radar data sets lies untapped. The situation will become even more pronounced in approximately two years when the upgraded Arecibo radar system becomes capable of regularly producing asteroid data sets with very fine spatial resolution and high signal-to-noise ratios. If successful, the proposed research will significantly increase our knowledge of these objects. The potential and limitations of the techniques developed will be rigorously tested in a series of computer simulations and optical scattering experiments with scale models.
Assessing the quality of aleatoric uncertainty estimates from uncertainty quantification (UQ) deep learning methods is important in scientific contexts, where uncertainty is physically meaningful and important to characterize and interpret exactly. We systematically compare aleatoric uncertainty measured by two UQ techniques, Deep Ensembles (DE) and Deep Evidential Regression (DER). Our method focuses on both zero-dimensional (0D) and two-dimensional (2D) data, to explore how the UQ methods function for different data dimensionalities. We investigate uncertainty injected on the input and output variables and include a method to propagate uncertainty in the case of input uncertainty so that we can compare the predicted aleatoric uncertainty to the known values. We experiment with three levels of noise. The aleatoric uncertainty predicted across all models and experiments scales with the injected noise level. However, the predicted uncertainty is miscalibrated to $\rm{std}(\sigma_{\rm al})$ with the true uncertainty for half of the DE experiments and almost all of the DER experiments. The predicted uncertainty is the least accurate for both UQ methods for the 2D input uncertainty experiment and the high-noise level. While these results do not apply to more complex data, they highlight that further research on post-facto calibration for these methods would be beneficial, particularly for high-noise and high-dimensional settings.
This paper details the design and development of the Airborne Subscale Transport Aircraft Research (AirSTAR) test-bed at NASA Langley Research Center (LaRC). The aircraft is a 5.5% dynamically scaled, remotely piloted, twin-turbine, swept wing, Generic Transport Model (GTM) which will be used to provide an experimental flight test capability for research experiments pertaining to dynamics modeling and control beyond the normal flight envelope. The unique design challenges arising from the dimensional, weight, dynamic (inertial), and actuator scaling requirements necessitated by the research community are described along with the specific telemetry and control issues associated with a remotely piloted subscale research aircraft. Development of the necessary operational infrastructure, including operational and safety procedures, test site identification, and research pilots is also discussed. The GTM is a unique vehicle that provides significant research capacity due to its scaling, data gathering, and control characteristics. By combining data from this testbed with full-scale flight and accident data, wind tunnel data, and simulation results, NASA will advance and validate control upset prevention and recovery technologies for transport aircraft, thereby reducing vehicle loss-of-control accidents resulting from adverse and upset conditions.