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The recommended impact site for LCROSS is Shoemaker crater, centered at 88.1 S, 45 E. This 51-km diameter crater is in permanent shadow. However, more than half of its floor has been imaged by Earth-base radar. This degree of target knowledge will strongly constrain impact models and significantly increase the confidence of data interpretation.
Water droplet impingement data were obtained at the NASA Glenn Icing Research Tunnel (IRT) for four wings and one wing with two simulated ice shapes. The wings tested include three 36-in. chord wings (MS(1)-317, GLC-305, and a NACA 652-415) and a 57-in. chord Twin Otter horizontal tail section. The simulated ice shapes were 22.5- and 45-min glaze ice shapes for the Twin Otter horizontal tail section generated using the LEWICE 2.2 ice accretion program. The impingement experiments were performed with spray clouds having median volumetric diameters of 11, 21, 79, 137, and 168 mm. Comparisons to the experimental data were generated which showed good agreement for the clean wings and ice shapes at lower drop sizes. For larger drop sizes LEWICE 2.2 over predicted the collection efficiencies due to droplet splashing effects which were not modeled in the program. Also for the more complex glaze ice shapes interpolation errors resulted in the over prediction of collection efficiencies in cove and shadow regions of ice shapes.
Water droplet impingement data were obtained at the NASA Glenn Icing Research Tunnel (IRT) for a 36-in. chord NACA 23012 airfoil with and without simulated ice using a dye-tracer method. The simulated ice shapes were defined with the NASA Glenn LEWICE 2.2 ice accretion program and including one rime, four mixed and five glaze ice shapes. The impingement experiments were performed with spray clouds having median volumetric diameters of 20, 52, 111, 154, and 236 micron. Comparisons to the experimental data were generated which showed good agreement for the rime and mixed shapes at lower drop sizes. For larger drops sizes LEWICE 2.2 over predicted the collection efficiencies due to droplet splashing effects which were not modeled in the program. Also for the more complex glaze ice shapes interpolation errors resulted in the over prediction of collection efficiencies in cove or shadow regions of ice shapes.
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Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.
An attempt is made to relate the reflection from a broken cloud field to that from a plane parallel cloud of the same optical properties by using Monte Carlo simulations for a very simple model of an array of regularly spaced, infinitely long bar clouds. Reflection from the array is represented by an effective cloud fraction, and it is shown that for many cases this may be obtained by treating the cloud elements to be noninteracting azimuthally symmetric reflectors. The effective cloud fraction is a function of solar zenith angle, the aspect ratio of the individual cloud elements, and the normal or zenith cloud fraction of the array. Model computations for reflection from an array of randomly distributed identical cylinders are also presented as an example of a possible application of this technique.
In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s)range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant.
Spectral albedo measurements from the Landsat-4/5 Thematic Mapper require that spacecraft upwelling radiances be corrected for atmospheric absorption and scattering and for local surface illumination. A two-stream model is developed, with a lower boundary condition that varies with incidence angle. TM data must be registered to digital terrain data. Reflectance from points in shadows can be used to estimate optical depth. The primary application here is determination of the spectral albedo of snow. The TM is better-suited for this purpose than the MSS because of its larger dynamic range.
This paper presents the mechanical design and analysis work completed on the Lunar Orbiter Laser Altimeter (LOLA). LOLA is one of six instruments on the Lunar Reconnaissance Orbiter (LRO), scheduled to launch in 2008. LOLA's main objective is to produce a high-resolution global lunar topographic model to aid in safe landings and enhance surface mobility in future exploration missions. LOLA will also look for evidence of ice water in the permanently shadowed regions around the lunar poles. Beryllium was chosen as the primary material for the LOLA Optical Transmitter Assembly to take advantage of the material's low mass density for light weight optical instrument design and for CTE matching of the refractive optical components. In addition, the thermal conductivity and specific heat of beryllium minimizes thermal gradients and thermal excursions. Special consideration must be made for the planning and preparation to fabricate beryllium components, as well as the preparation and cleaning of the components for gold plating. Assembly challenges include handling, precision cleaning and integration and testing. Structural analysis considerations include following General Environmental Verification Specification (GEVS) guidelines for GSFC payloads. The GEVS random environment for LOLA has an acceptance level of 10.0 Grms, which was analyzed for higher frequency transients. The low frequency transients were analyzed using a Mass Acceleration Curve to obtain an equivalent static loading. In addition, Structural-Thermal-Optical analysis, commonly referred to as STOP analysis, was completed to predict optical performance under the instrument's operational thermal environment. This included stress and distortion analysis on the receiver telescope lens.
We present Gemini Planet Imager polarized intensity imagery of HD 100453 in Y, J, and K1 bands that reveals an inner gap (9-18 au), an outer disk (18-39 au) with two prominent spiral arms, and two azimuthally localized dark features that are also present in Spectro-Polarimetric High-contrast Exoplanet REsearch (SPHERE) total intensity images. Spectral energy distribution fitting further suggests that the radial gap extends to 1 au. The narrow, wedge-like shape of the dark features appears similar to predictions of shadows cast by an inner disk that is misaligned with respect to the outer disk. Using the Monte Carlo radiative transfer code HOCHUNCK3D, we construct a model of the disk that allows us to determine its physical properties in more detail. From the angular separation of the features, we measure the difference in inclination between the disks (45deg) and their major axes, PA = 140deg east of north for the outer disk, and 100deg for the inner disk. We find an outer-disk inclination of 25deg +/- 10deg from face-on, in broad agreement with the Wagner et al. measurement of 34deg. SPHERE data in J and H bands indicate a reddish disk, which indicates that HD 100453 is evolving into a young debris disk.
Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.
Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.
Direct upward remote sensing of the moon’s exosphere from a surface vantage can address production of water-related lunar volatiles as well as their exospheric loss, ballistic transport, and ultimate adsorption in permanently shadowed regions (PSRs). Far UV (FUV) dayside measurements of atomic oxygen, liberated from regolith by energetic solar protons and micrometeorite impact, can provide critical insight into the endogenic lunar water cycle by constraining total column density [O] at site of production. A notional Lunar-surface UV Photometric Investigation of Exospheres (LUPINE) instrument is designed to exploit solar-pumped atomic oxygen fluorescence at 130.4-nm, in a manner similar to the Apollo 17 UV Spectrometer (UVS) experiment [Fastie 1973; Feldman and Morrison, 1991] and the LRO Lyman-alpha Mapping Project (LAMP) spectrograph [Cook et al., 2013], by implementing a zenith-directed FUV photometer from the lunar surface at low (± 10°) selenographic latitude during the lunar day. Atomic oxygen production from solar energetic particle impact sources is thought to maximize in near solar noon [Sarantos et al., 2012], and the lander-embedded zenith-directed LUPINE photometer, in contrast to UVS and LAMP twilight measurements from orbit, can potentially capture the full column abundance of lunar regolith liberated oxygen. Herein we describe adaptation of FUV reflective optics, pulse-counting electronics, and scattered-light-suppression technologies developed for LEO FUV photometry for the challenging thermal environment of the daylit lunar surface. Preliminary thermal modeling and TVAC measurements of heritage FUV photometer components suggests that, if allowed to shed ~8W of waste heat into the bus of a reference Commercial Lunar Payload Services (CLPS) lander, the LUPINE photometer will be kept sufficiently cool to limit dark current to less than 20 counts/s. This level of dark signal enables an OI 130.4-nm 3-sigma detection threshold of ~1 mR for assumed 2-hour integrations.
There are numerous examples of cases where the human operator is confronted with several tasks occurring simultaneously and continuously in time. The current study is an investigation into the nature of attention sharing between two continuous tasks with independent input-output modes. Eleven subjects were tested using a zero order compensatory control task with three levels of difficulty (input bandwidth) for each subject. As a secondary task on half of the trials, the subjects were also required to verbally shadow a random auditory input. Results from an extensive time and frequency domain analysis of the data are presented and discussed. The evidence supports a single channel model for continuous dual-task control.
The author has identified the following significant results. Shadow enhancement of topographic linears in photographic or scanner images is a valuable tool for interpretation of geologic structures. Whether linears will be enhanced or subdued depends on sun angle and azimuth. The relationship of the sun's attitude to topographic slopes determines which trends are available for interpretation in existing imagery, and it can be used to select the time of day, surface properties, and film and filter characteristics in planning aircraft flights or satellite orbital passes. The technique of selective shadow enhancement can be applied to all photographic or imaging experiments, but its best for snow-covered scenes, side-looking radar images, and painted relief models.
Shadow enhancement of topographic linears in photographic or scanner images is a valuable tool for interpretation of geologic structures. Whether linears will be enhanced or subdued depends on sun angle and azimuth. The relationship of the sun's attitude to topographic slopes determines which trends are available for interpretation in existing imagery, and it can be used to select the time of day, surface properties, and film and filter characteristics in planning aircraft flights or satellite orbital passes. The technique of selective shadow enhancement can be applied to all photographic or imaging experiments, but is best for snow-covered scenes, side-looking radar images, and painted relief models.
Spectral albedo measurements from the LANDSAT-4/5 thematic mappers require that spacecraft upwelling radiances be corrected for atmospheric absorption and scattering and for local surface illumination. A two-stream model is developed, with a lower boundary condition that varies with incidence angle. The TM data must be registered to digital terrain data. Reflectance from points in shadows can be used to estimate optical depth. The primary application is determination of the spectral albedo of snow. The TM is better-suited for this purpose than the MSS because of its larger dynamic range.