Results for “Grid computing environments” — Page 16

NASA NTRSDate not supplied

An Updated Secondary Lunar Meteoroid Ejecta Model for Engineering Design

Introduction: The surface of the Moon is constantly being bombarded by a flux of meteoroids of various sizes. Impacts due to these meteoroids produce secondary ejecta material at much lower speeds but with a total mass larger than the original impactor. Details about the secondary ejecta are important for planning missions on the lunar surface. In this work, an updated ejecta model is presented called the Meteoroid Model of Secondary Ejecta (MeMoSeE), to re-place the Apollo-era ejecta model, NASA SP-8013 [1], in the SLS-SPEC 159 Design Specification for Natural Environments (DSNE) [2]. The model pro-duces secondary ejecta flux environments for a user-specified location on the lunar surface, and sorts the incoming secondary flux by angular direction and speed. Methods: MeMoSeE is separated into three parts: the inputs, the conversion step, and the integration of fluxes. Inputs to the model include the primary meteoroid fluxes and the primary near-Earth object (NEO) fluxes. Meteoroid fluxes, both asteroidal and cometary, are calculated using the Meteoroid Engineering Model (MEM3) [3] for different locations on the Moon. For each surface location, an ephemeris is generated using the JPL HORIZONS System [4] that feeds into MEM3. The NEO fluxes are approximated by the high-density population of MEM3 (i.e., only the directionality), where the speed distribution of the NEO fluxes is renormalized to match observations [5]. The regolith properties are used as defined in the DSNE [2]. The conversion step utilizes scaling laws given by Housen & Holsapple 2011 [6] to convert the primary impactor flux to the total mass of secondary ejecta. The ejecta distribution, at the point-of-impact (POI), is separated into a zenith angle and azimuthal angle distribution. The zenith angle distribution follows a beta distribution where the peak depends on the impact altitude angle and the impact azimuth [7]. We employ an ejecta azimuth distribution that is based on Rival & Mandeville 1999 [8] which focuses ejecta in the downstream direction for more oblique impacts. Finally, during the integration step, we sum secondary ejecta number fluxes at a particular region-of-interest (ROI) that originated from many POI locations over the entire surface of the Moon. We keep track of both altitude and azimuth angle bins as well as a range of speed bins, following the igloo gridding as done in MEM3 [9]. The ejecta particle size distribution and density is assumed to be the same as the lunar regolith [10, 2]. Results: The primary fluxes are computed for one Metonic cycle (19 years) for various locations over the lunar surface with a fixed orientation. Both the angular and speed distributions of the primary fluxes are dependent on the latitude and longitude. The over-all primary fluxes show a roughly 13% increase from the eastern limb to the western limb. In general, the speed distribution of the secondary fluxes span from a user-defined minimum speed to the escape speed of the Moon (2.38 km/s), roughly following a power-law relation [6]. Different parts of the speed distribution come from different primary impact locations on the Moon. The secondary ejecta is dominated by the slowest speeds, where these particles originate nearby the ROI. For speeds around 71% of the escape speed, the secondary ejecta originates from locations near the antipodal point. On the other hand, for secondary ejecta speeds that exceed roughly 90% the escape speed, the ejecta particles come from all over the lunar surface to the ROI. Comparing the secondary ejecta fluxes from MeMoSeE with NASA SP-8013 [1], there is a reduction by about 2-3 orders of magnitude for secondary ejecta particles greater than 1 µg. These estimates agree with recent findings from Bjorkman & Christiansen 2019 [11]. The secondary ejecta fluxes are also compared with the primary fluxes, where the ejecta fluxes are roughly an order of magnitude greater than the primary fluxes. References: [1] Cour-Palais, B. G., (1969) NASA SP-8013. [2] NASA SLS-SPEC-159 Rev. H (2020). [3] Moorhead, A. V., et al. (2019) JS&R, 1-17. [4] Giorgini, J. D., (2015) IAUGA, 29, 2256293. [5] Moorhead, A. V., (2020) Memo OSMA/MEO/Lunar-001. [6] Housen, K. R., and Holsapple, K. A., (2011) Icarus, 211(1), 856-875. [7] Gault, D. E., and Wedekind, J. A., (1978) L&PSCP, 9, 3843-3875. [8] Rival, M., and Mandeville, J., (1999) Space Debris, 1(1), 45-57. [9] Moorhead, A. V., (2019) MEM3 User Guide. [10] Carrier, W. D., (1973) The Moon, 6(3-4), 250-263. [11] Bjorkman, M. D. & Christiansen, E. L., (2019) ODC

impacts↗

NASA NTRS2014

Aerodynamic Effects of High Turbulence Intensity on a Variable-Speed Power-Turbine Blade With Large Incidence and Reynolds Number Variations

The effects of high inlet turbulence intensity on the aerodynamic performance of a variable speed power turbine blade are examined over large incidence and Reynolds number ranges. These results are compared to previous measurements made in a low turbulence environment. Both high and low turbulence studies were conducted in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility. The purpose of the low inlet turbulence study was to examine the transitional flow effects that are anticipated at cruise Reynolds numbers. The current study extends this to LPT-relevant turbulence levels while perhaps sacrificing transitional flow effects. Assessing the effects of turbulence at these large incidence and Reynolds number variations complements the existing database. Downstream total pressure and exit angle data were acquired for 10 incidence angles ranging from +15.8deg to −51.0deg. For each incidence angle, data were obtained at five flow conditions with the exit Reynolds number ranging from 2.12×10(exp 5) to 2.12×10(exp 6) and at a design exit Mach number of 0.72. In order to achieve the lowest Reynolds number, the exit Mach number was reduced to 0.35 due to facility constraints. The inlet turbulence intensity, Tu, was measured using a single-wire hotwire located 0.415 axial-chord upstream of the blade row. The inlet turbulence levels ranged from 8 to 15 percent for the current study. Tu measurements were also made farther upstream so that turbulence decay rates could be calculated as needed for computational inlet boundary conditions. Downstream flow field measurements were obtained using a pneumatic five-hole pitch/yaw probe located in a survey plane 7 percent axial chord aft of the blade trailing edge and covering three blade passages. Blade and endwall static pressures were acquired for each flow condition as well. The blade loading data show that the suction surface separation that was evident at many of the low Tu conditions has been eliminated. At the extreme positive and negative incidence angles, the data show substantial differences in the exit flow field. These differences are attributable to both the higher inlet Tu directly and to the thinner inlet endwall boundary layer that the turbulence grid imposes.

Flegel, Ashlie B.↗

NASA NTRS2014

Aerodynamic Effects of High Turbulence Intensity on a Variable-Speed Power-Turbine Blade with Large Incidence and Reynolds Number Variations

The effects of high inlet turbulence intensity on the aerodynamic performance of a variable speed power turbine blade are examined over large incidence and Reynolds number ranges. These results are compared to previous measurements made in a low turbulence environment. Both high and low turbulence studies were conducted in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility. The purpose of the low inlet turbulence study was to examine the transitional flow effects that are anticipated at cruise Reynolds numbers. The current study extends this to LPT-relevant turbulence levels while perhaps sacrificing transitional flow effects. Assessing the effects of turbulence at these large incidence and Reynolds number variations complements the existing database. Downstream total pressure and exit angle data were acquired for 10 incidence angles ranging from +15.8deg to −51.0deg. For each incidence angle, data were obtained at five flow conditions with the exit Reynolds number ranging from 2.12×10(exp 5) to 2.12×10(exp 6) and at a design exit Mach number of 0.72. In order to achieve the lowest Reynolds number, the exit Mach number was reduced to 0.35 due to facility constraints. The inlet turbulence intensity, Tu, was measured using a single-wire hotwire located 0.415 axial-chord upstream of the blade row. The inlet turbulence levels ranged from 8 to 15 percent for the current study. Tu measurements were also made farther upstream so that turbulence decay rates could be calculated as needed for computational inlet boundary conditions. Downstream flow field measurements were obtained using a pneumatic five-hole pitch/yaw probe located in a survey plane 7 percent axial chord aft of the blade trailing edge and covering three blade passages. Blade and endwall static pressures were acquired for each flow condition as well. The blade loading data show that the suction surface separation that was evident at many of the low Tu conditions has been eliminated. At the extreme positive and negative incidence angles, the data show substantial differences in the exit flow field. These differences are attributable to both the higher inlet Tu directly and to the thinner inlet endwall boundary layer that the turbulence grid imposes.

Flegel, Ashlie B.↗

NASA NTRSDate not supplied

High-Order Methods in NASA’s Next Generation of Computational Fluid Dynamics Tools

The missions of the National Aeronautics and Space Administration (NASA) routinely produce unique requirements and challenges for development and application of Computational Fluid Dynamics (CFD) methods. NASA presently embodies four distinct Mission Directorates: Aeronautics Research, Exploration Systems, Science, and Space Operations. These missions generate requirements for systems that operate in a wide variety of environments. They range from the high-speed flight of aerodynamically optimized vehicles operating in the earth’s atmosphere to spacecraft designed for missions that don’t favor aerodynamic optimization, some operating in the atmosphere of planets and planetary moons such as Mars and Venus or Saturn’s moon Titan. Systems supporting these vehicles, such as rocket and jet propulsion, reaction control systems, fluid and thermal transfer systems, etc. can also generate their own unique set of flow phenomena that challenge today’s CFD methodology. Through the NASA Engineering and Safety Center (NESC), NASA annually conducts state-of-the-discipline assessments in fifteen distinct engineering disciplines. These assessments are performed by the NASA Technical Fellows that lead Technical Discipline Teams (TDT) of recognized experts in these fifteen areas. In the Aerosciences discipline, three topics have been identified as the top challenges for the discipline: aero-plume interaction prediction, unsteady separated flows, and aerothermodynamic prediction. These challenge areas are defined by the Agency’s high-risk projects and problems on which the NESC is requested to perform independent testing, analysis, and assessments. When viewed as a whole, these tests, analyses, and assessments provide a clear view of the recurring technical challenges facing Agency engineers and researchers and can be used to guide future research and technology development. The present state-of-the-art in the application of CFD at NASA is the use of Reynolds-Averaged Navier- Stokes (RANS) solvers, primarily executed in a steady-state mode of operation. In isolated cases, Unsteady RANS (URANS) solvers have been employed when steady RANS solutions produce poorly converging or oscillating results or in cases, such as aeroelastic analysis, which require unsteady aerodynamic simulation. For most traditional external and internal aerodynamic flows, structured overset grids or unstructured grids are employed to minimize geometric modeling and grid generation times. Grid adaptation, primarily as a series of coarse-grain intermediate processing steps is also seeing use on particularly complex flow problems and configurations. In the case of aerothermodynamic flows, engineers have been forced to continue to employ structured grid techniques as the present unstructured grid methodology has proven inadequate in the prediction of surface heating. In the area of aero-plume interaction modeling, two-gas, frozen chemistry simulation is generally the state-of-the- art, with some production solvers capable of predicting flows with only a single gas component. Prediction of flows falling into the afore-mentioned top Aerosciences technical challenges have severely stressed the present state-of-the-art in CFD prediction and for some problems, such as unsteady separated flows and aero-plume interaction cases, engineers have begun employing Large Eddy Simulation (LES) and Hybrid RANS/LES techniques. In some isolated aero-propulsion interaction cases, chemically reacting flow simulations have been applied. These methods are highly evolutionary and engineers have little experience in their application, so they cannot be heavily relied upon in today’s application environment. Therefore, this leads one to muse over which numerical technologies will be included in the CFD tools that will be employed 30 years in the future. This presentation will describe specific technical problems that have stressed NASA’s traditional CFD methods to their breaking point and will link these issues to the Agency’s top Aerosciences technical challenges. The discussion will then shift to the characteristics of future CFD solvers that will be required to attack these challenges and how these characteristics differ from the present state-of-the- art. High-order methods certainly appear to have a place in the development of future CFD tools and some of the physical characteristics of our most challenging problems suggest that high-order methods are the only way to effectively solve them. But there are some relatively severe implementation issues that face these methods, particularly in the area of general applicability and robust operation as an engineering tool. Desired characteristics of next-generation CFD solvers will be discussed and the author’s view of which emerging numerical technologies might be employed to address these attributes will also be presented

David M Schuster↗

NASA NTRS2017

Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The PALS soil moisture was also compared to SMAP and in situ soil moisture at the 36-km scale, which is the SMAP grid size for the standard product. PALS and SMAP soil moistures were found to be very similar owing to the close match of the brightness temperature measurements and the use of a common soil moisture retrieval algorithm. Spatial heterogeneity, which was identified using the high-resolution PALS soil moisture and the intensive ground sampling, also contributed to differences between the soil moisture estimates. In general, discrepancies found between the L-band soil moisture estimates and the 5-cm depth in situ measurements require methodologies to mitigate the impact on their interpretations in soil moisture validation and algorithm development. Specifically, the metrics computed for the SMAP radiometer-based soil moisture product over WGEW will include errors resulting from rainfall, particularly during the monsoon season when the spatial distribution of soil moisture is especially heterogeneous.

SMAPVEX15↗

NASA NTRS1995

Numerical simulation of the general circulation of the atmosphere of Titan

The atmospheric circulation of Titan is investigated with a general circulation model. The representation of the large-scale dynamics is based on a grid point model developed and used at Laboratoire de Meteorologie Dynamique for climate studies. The code also includes an accurate representation of radiative heating and cooling by molecular gases and haze as well as a parametrization of the vertical turbulent mixing of momentum and potential temperature. Long-term simulations of the atmospheric circulation are presented. Starting from a state of rest, the model spontaneously produces a strong superrotation with prograde equatorial winds (i.e., in the same sense as the assumed rotation of the solid body) increasing from the surface to reach 100 m sec-1 near the 1-mbar pressure level. Those equatorial winds are in very good agreement with some indirect observations, especially those of the 1989 occultation of Star 28-Sgr by Titan. On the other hand, the model simulates latitudinal temperature contrasts in the stratosphere that are significantly weaker than those observed by Voyager 1 which, we suggest, may be partly due to the nonrepresentation of the spatial and temporal variations of the abundances of molecular species and haze. We present diagnostics of the simulated atmospheric circulation underlying the importance of the seasonal cycle and a tentative explanation for the creation and maintenance of the atmospheric superrotation based on a careful angular momentum budget.

NASA Discipline Exobiology↗