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27 records · Page 2

Challenges in Predicting Planetary Granular Mechanics

Through the course of human history, our needs in agriculture, habitat construction, and resource extraction have driven us to gain more experience working with the granular materials of planet Earth than with any other type of substance in nature, with the possible exception being water. Furthermore, throughout the past two centuries we have seen a dramatic and ever growing interest among scientists and engineers to understand and predict both its static and rheological properties. Ironically, however, despite this wealth of experience we still do not have a fundamental understanding of the complex physical phenomena that emerge even as just ordinary sand is shaken, squeezed or poured. As humanity is now reaching outward through the solar system, not only robotic ally but also with our immediate human presence, the need to understand and predict granular mechanics has taken on a new dimension. We must learn to farm, build and mine the regoliths of other planets where the environmental conditions are different than on Earth, and we are rapidly discovering that the effects of these environmental conditions are not trivial. Some of the relevant environmental features include the regolith formation processes throughout a planet's geologic and hydrologic history, the unknown mixtures of volatiles residing within the soil, the relative strength of gravitation, ~d the atm9spheric pressure and its seasonal variations. The need to work with soils outside our terrestrial experience base provides us with both a challenge and an opportunity. The challenge is to learn how to extrapolate our experience into these new planetary conditions, enabling the engineering decisions that are needed right now as we take the next few steps in solar system exploration. The opportunity is to use these new planetary environments as laboratories that will help us to see granular mechanics in new ways, to challenge our assumptions, and to help us finally unravel the elusive physics that lie behind complex granular phenomena. Toward these goals, a workshop was held recently at NASA's John F. Kennedy Space Center, attracting over a hundred scientists and engineers from around the world and from a broad crosssection of scientific and engineering disciplines. This talk will provide an out-briefing from that workshop, communicating some of its early findings in regard to lunar and Martian exploration: (1) the requirements for working with granular materials, (2) the challenges that granular materials will pose, (3) the environmental conditions that affect granular mechanics, (4) instruments and measurements that are needed on the Moon and Mars to support granular material research, and (5) some of the possible research avenues that should be pursued.

Metzger, Philip T.↗

Air Quality Over the Canadian Oil Sands: A First Assessment Using Satellite Observations

Results from the first assessment of air quality over the Canadian oil sands -- one ofthe largest industrial undertakings in human history -- using satellite remote sensing observations of two pollutants, nitrogen dioxide (N0O) and sulfur dioxide (SO2), are presented. High-resolution maps were created that revealed distinct enhancements in both species over an area (roughly 30 km x 50 km) of intensive surface mining at scales of a few kilometers. The magnitude of these enhancements, quantified in terms of total mass, are comparable to the largest seen in Canada from individual sources. The rate of increase in NO2 between 2005 and 2010 was assessed at 10.4 +/- 3.5%/year and resulted from increases both in local values as well as the spatial extent of the enhancement. This is broadly consistent with both surface-measurement trends and increases in annual bitumen production. An increase in SO2 was also found, but given larger uncertainties, it is not statistically significant.

McLinden, C. A.↗

Design and Specifications for the Highland Regolith Prototype Simulants NU-LHT-1M and -2M

The first two prototype lunar regolith simulants were to replicate characteristics of the lunar highlands. A major change from initial plans was to use an estimate of typical Apollo 16 highland material rather than a specific core. This change was compatible with project objectives and necessitated by the lack of adequate data from a single core. To make the initial simulant, a crystalline component and a glass component were deemed necessary. Lithic feedstocks were obtained with the assistance of the Stillwater Mining Company. The mixing of the rock constituents was done based on normative mineralogy rather than modal mineralogy. This was done to simplify development. A major design decision was not to attempt simulation of the range of glass chemistries observed in Apollo samples. A single glass was assumed to be adequate for engineering purposes for which the simulant would be used. Glass was made in a process developed at Zybek Advanced Products of Boulder, Colorado. Mill sand was used as the feedstock for this process. A second generation of the simulant was made that incorporated the additional minerals apatite, synthetic whitlockite, and pyrite. The olivine source was changed to the commercially produced Twin Sisters Dunite, and a pseudo-agglutinate product was invented and added to the -2M product. The pseudo-agglutinate captures all of the lunar agglutinate features but does not attempt to incorporate nanophase Fe.

Stoeser, D.↗

Evaluation of ERTS-1 data applications to geologic mapping, structural analysis and mineral resource inventory of South America with special emphasis on the Andes Mountain region

The author has identified the following significant results. Segerstrom delineated many grabens (down-faulted blocks) not shown on published maps of Argentina nor of South America. The faults that border the grabens are better appreciated in ERTS-1 imagery than on air photos or on the ground because of the masking affect of alluvial fill deposits. In frame no. 1188-13545 a change in local prevailing wind direction from east to southeast is noted in sand streams. In frame no. 1188-13551 it was surprising to see that Solar del Hombre Muerto was covered with water. In November 1971 the investigator has driven across the salt pan several times without wetting his wheels. It was also possible to differentiate the following rock and soil classes: Granites, metamorphic, volcanic rocks, Tertiary and Quaternary clastic deposits and salt pans. Portions of railroads and highways as well as small towns were identified. In frame no. 1188-13551 the Incahuasi Gold Mine and the Tincalayu Borax Mine were located.

Carter, W. D.↗

Mineralogical, optical, geochemical, and particle size properties of four sediment samples for optical physics research

X-ray diffraction and spectroscopy were used to investigate the mineralogical and chemical properties of the Calvert, Ball Old Mine, Ball Martin, and Jordan Sediments. The particle size distribution and index of refraction of each sample were determined. The samples are composed primarily of quartz, kaolinite, and illite. The clay minerals are most abundant in the finer particle size fractions. The chemical properties of the four samples are similar. The Calvert sample is most notably different in that it contains a relatively high amount of iron. The dominant particle size fraction in each sample is silt, with lesser amounts of clay and sand. The indices of refraction of the sediments are the same with the exception of the Calvert sample which has a slightly higher value.

Bice, K.↗

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

surface concentration↗

Appropriate Simulants are a Requirement for Mars Surface Systems Technology Development

To date, there are two simulants for martian regolith: JSC Mars-1A, produced from palagonitic (weathered) basaltic tephra mined from the Pu'u Nene cinder cone in Hawaii [1] by commercial company Orbitec, and Mojave Mars Simulant (MMS), produced from Saddleback Basalt in the western Mojave desert by the Jet Propulsion Laboratory [2]. Until numerous recent orbiters, rovers, and landers were sent to Mars, weathered basalt was surmised to cover every inch of the martian landscape. All missions since Viking have disproven that the entire martian surface is weathered basalt. In fact, the outcrops, features, and surfaces that are significantly different from weathered basalt are too numerous to realistically count. There are gullies, evaporites, sand dunes, lake deposits, hydrothermal deposits, alluvium, etc. that indicate sedimentary and chemical processes. There is no one size fits all simulant. Each unique area requires its own simulant in order to test technologies and hardware, thereby reducing risk.

Edmunson, Jennifer E.↗

Utilization of Unsupervised Anomalies Detector as a Tool for Managing the TDRS Constellation at GSFC

NASA’s Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The mission of the TDRS constellation is to provide relay communications from low-earth orbiting spacecraft to the primary ground station at the White Sands Complex in Las Cruces, New Mexico. Major customers include the International Space Station and Hubble Space Telescope. The NASA Space Network project office at GSFC manages the constellation of spacecraft. The constellation is over 30 years old, and a wide range of technologies and manufacturing techniques are represented on-orbit. Since 1983, the TDRS constellation has recorded thousands of gigabytes of telemetry data. Spacecraft telemetry data has changed throughout the three generations of TDRS spacecraft, however each spacecraft has the same basic functions with some generational enhancements. The constellation includes several spacecraft that have significantly outlived the manufacturer's projected lifetime. This has provided NASA with a significant benefit in terms of return on investment, however it places a burden on efficient management of the assets for maximum life without permitting a TDRS spacecraft to become stranded in its geosynchronous orbital slot. Consequently, the highest level of attention is paid to systems whose failure could strand a TDRS spacecraft in orbit. In this paper, we proposed two stages of analyzing spacecraft anomalies using data mining (DM) to enhance on-going predictions of spacecraft life, subsystem performance, and analysis of subsystem anomalies. The first stage conducts the unsupervised anomaly detector to detect potential anomalies in real-time telemetry data. The second stage introduced telemetry weight (TW) to each telemetry parameter to determine which parameter caused the strongest anomaly. We will present case studies of some of these analyses and how the data can impact decisions on the management of the constellation.

Ma, Kenneth Y.↗

Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation

National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.

Machine Learning (ML)↗