Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “material training”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Development of a hydraulic model of the human systemic circulation

Physical and numeric models of the human circulation are constructed for a number of objectives, including studies and training in physiologic control, interpretation of clinical observations, and testing of prosthetic cardiovascular devices. For many of these purposes it is important to quantitatively validate the dynamic response of the models in terms of the input impedance (Z = oscillatory pressure/oscillatory flow). To address this need, the authors developed an improved physical model. Using a computer study, the authors first identified the configuration of lumped parameter elements in a model of the systemic circulation; the result was a good match with human aortic input impedance with a minimum number of elements. Design, construction, and testing of a hydraulic model analogous to the computer model followed. Numeric results showed that a three element model with two resistors and one compliance produced reasonable matching without undue complication. The subsequent analogous hydraulic model included adjustable resistors incorporating a sliding plate to vary the flow area through a porous material and an adjustable compliance consisting of a variable-volume air chamber. The response of the hydraulic model compared favorably with other circulation models.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS1997

Understanding Skill in EVA Mass Handling: Theoretical and Operational Foundations - Volume 1

This report describes the theoretical and operational foundations for our analysis of skill in extravehicular mass handling. A review of our research on postural control, human-environment interactions, and exploratory behavior in skill acquisition is used to motivate our analysis. This scientific material is presented within the context of operationally valid issues concerning extravehicular mass handling. We describe the development of meaningful empirical measures that are relevant to a special class of nested control systems: manual interactions between an individual and the substantial environment. These measures are incorporated into a unique empirical protocol implemented on NASA's principal mass handling simulator, the precision air-bearing floor, in order to evaluate skill in extravehicular mass handling. We discuss the components of such skill with reference to the relationship between postural configuration and controllability of an orbital replacement unit, the relationship between orbital replacement unit control and postural stability, the relationship between antecedent and consequent movements of an orbital replacement unit, and the relationship between antecedent and consequent postural movements. Finally, we describe our expectations regarding the operational relevance of the empirical results as it pertains to extravehicular activity tools, training, monitoring, and planning.

Riccio, Gary↗
NASA NTRS1999

Boundary Conditions for the Paleoenvironment: Chemical and Physical Processes in Dense Interstellar Clouds: Summary of Research

The basic theme of this program was the study of molecular complexity and evolution for the biogenic elements and compounds in interstellar clouds and in primitive solar system objects. Research included the detection and study of new interstellar and cometary molecules and investigation of reaction pathways for astrochemistry from a comparison of theory and observed molecular abundances. The latter includes studies of cold, dark clouds in which ion-molecule chemistry should predominate, searches for the effects of interchange of material between the gas and solid phases in interstellar clouds, unbiased spectral surveys of particular sources, and systematic investigation of the interlinked chemistry and physics of dense interstellar clouds. In addition, the study of comets has allowed a comparison between the chemistry of such minimally thermally processed objects and that of interstellar clouds, shedding light on the evolution of the biogenic elements during the process of solar system formation. One PhD dissertation on this research was completed by a graduate student at the University of Massachusetts. An additional 4 graduate students at the University of Massachusetts and 5 graduate students from other institutions participated in research supported by this grant, with 6 of these thus far receiving PhD degrees from the University of Massachusetts or their home institutions. Four postdoctoral research associates at the University of Massachusetts also participated in research supported by this grant, receiving valuable training.

Irvine, William M.↗
NASA NTRS2007

The Road to Mach 10: A History of the X-43A Hypersonic Flight Test Program at NASA Dryden...Toward the Future

In terms of technology, the X-43A/Hyper-X represented a singular milestone. After nearly a half century of high hopes, studies, wind tunnel tests, proposals, and canceled projects, a scramjet-powered vehicle had flown. The performance of the engine qualified the scramjet design tools and scaling laws. In turn, the theoretical calculations and ground testing could be used to design more advanced engine concepts. Just as important, both the scramjet and vehicle systems had successfully operated in the variable temperatures and densities of the atmosphere. The X-43A systems were able to maintain the exact flight conditions necessary for the scramjet to operate properly. Control deflections to correct the engine-induced moments were close to pre-flight predictions. When the unexpected occurred, such as when the vehicle pitched up during the cowl opening on the second flight, the control system was sufficiently designed to correct the situation. The airframe and wing structure, the thermal protection material, and the internal conditions of the X-43A performed largely as predicted. The HXLV thermal anomaly during the ascent on the third flight and "the Mach 8 unpleasantness" during the descent indicated that the HXLV and X-43A were not as resilient to aerodynamic heating as expected. The X-43A 's airframe drag and lift both were slightly higher than predicted, but still within preflight uncertainty predictions. The stability and control were as predicted, as was the boundary layer transition. The biggest aerodynamic worry before the flight was the separation of the HXLV and the X- 43A. After all was said and done, this went exactly as predicted, proving that non-symmetrical/high-dynamic pressure stage separations could be performed. This in turn meant that two-stage-to-orbit vehicles employing this technology were feasible. The Hyper-X program also served as a training ground for a new generation of scramjet and hypersonic researchers. This included both NASA and contractor personnel, providing them with experience in ground testing and component development; vehicle design, construction, integration, system checkout, and, ultimately, flight testing and data analysis. Additionally, researchers learned the practical details of running a project within finite budget and time limits, about the ambiguousness of risk assessment, and about the need to spend a significant amount of time and effort dealing with engineering problems, such as those with the FAS, that have nothing to do with the project's research goals. Finally, all those who worked on the X-43A project now know what it is like to spend years transforming an idea into a functional vehicle, only for it to be lost in a matter of seconds. And then to go through years of work to correct the problems, to face the possibility that still more might exist, and finally to savor the triumph of two successful flights. For those who will work on the hypersonic projects that emerge in coming years, these experiences may prove to be the most valuable of all.

Peebles, Curtis↗
NASA NTRS2024

Synergistic Retrievals of Ice in High Clouds From Elastic Backscatter Lidar, Ku-band Radar and Submillimeter Wave Radiometer Observations

In this study, we investigate the synergy of elastic backscatter lidar, Ku-band radar, and sub-millimeter-wave radiometer measurements in the retrieval of ice from satellite observations. The synergy is analyzed through the generation of a large dataset of IceWater Content (IWC) profiles and simulated lidar, radar and radiometer observations. The characteristics of the instruments e.g. frequencies, sensitivities, etc. are set based on the expected characteristics of instruments of the Atmosphere Observing System (AOS) mission. A hold-out validation methodology is used to assess the accuracy of the IWC profiles retrieved from various combinations of observations from the three instruments. Specifically, the IWC and associated observations are randomly divided into two datasets, one for training and the other for evaluation. The training dataset is used to train the retrieval algorithm, while the evaluation dataset is used to assess the retrieval performance. The dataset of IWC profiles is derived from CloudSat reflectivity and CALIOP lidar observations. The retrieval of the ice water content IWC profiles from the computed observations is achieved in two steps. In the first step, a class, out of 18 potential classes characterized by different vertical distribution of IWC, is estimated from the observations. The 18 classes are predetermined based on the k-Means clustering algorithm. In the second step, the IWC profile is estimated using an Ensemble Kalman Smoother (EKS) algorithm that uses the estimated class as a priori information. The results of the study show that the synergy of lidar, radar, and radiometer observations is significant in the retrieval of the IWC profiles. Nevertheless, it should be mentioned that this synergy was found under idealized conditions, and additional work might be required to materialize it in practice. The inclusion of the lidar backscatter observations in the retrieval process has a larger impact on the retrieval performance than the inclusion of the radar observations. As ice clouds have a significant impact on atmospheric radiative processes, this work is relevant to ongoing efforts to reduce uncertainties in climate analyses and projections.

Mircea Grecu↗
NASA NTRS2001

Emotional/Mental Challenges Pre-, In-, and Post-Flight

Dr. Voss has flown aboard the Space Shuttle five times. She knows well her inner concerns, emotions, and mental challenges attending such highly demanding and risky adventures. And she has shared those ideas with her colleagues. She notes that their busy training schedules and fully committed on orbit time allow little time for dwelling on most of these issues. However, they are nonetheless real and may not be ignored with impunity. She thinks that perhaps they are more striking for rookie space farers, but all spacecrew members share them and can profit by assuring proper support and unique solutions for their own specific situation, which could vary with the mission. In her own experience, she found notable benefit from sharing with close members of her family, both before flight and during. The latter has proved of great value to all crew persons in the form of their personal ground contact time with family and friends. In addition, how one arranges and what one provides in the on board personal space and time goes far toward keeping a confident and upbeat view of the big picture. The type and amount of off duty diversions (e.g., music, reading material) are important, as are how one participates in group time. And it is universally agreed that viewing time at the spacecraft windows offers great joy and calm. Dr. Voss conjectures that there could be a difference in how people deal with these matters on busy, short-duration (Shuttle type) missions versus those of longer ones, particularly out of low earth orbit, where the options in the advent of mishap are fewer. Her final opinion is one of optimism and assurance that the human person will do well in coping with this new environment.

Voss, Janice↗
NASA NTRS2010

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗
NASA NTRS2024

AC and DC Fault Management for Megawatt Electrified Aircraft Electrical Powertrains - Task 2: Power Quality Filtering Using Nanocrystalline Soft Magnetic Inductor

The NASA RTAPS program on AC and DC Fault Management for Megawatt Electrified Power Train is a multi-year joint project with Pratt & Whitney (P&W), Collins Aerospace (CA), and RTX Technology Research Center (RTRC). This research program focuses on the high-voltage distribution issues that present a significant technological obstacle in the adoption of Electrified Aviation Propulsion (EAP) systems. One challenge to the adoption of high-voltage distribution systems with power electronic converters is the need for filter elements to limit the generation and propagation of noise, protect the cable systems from premature aging and prevent against excessive heating within subcomponents due to high-frequency induced currents. While increased distribution voltages aide in reducing the cable mass for a fixed power system, the associated mass with the filtering elements for power electronic converter can grow with increasing distribution voltages – thereby mitigating any benefit associated with increasing the distribution system voltage. To enable high-voltage distribution systems with high system specific power densities, new magnetic materials must be developed. Therefore, the second task of the NASA RTAPS program is associated with the design and application of advanced soft magnetic components for Megawatt class electric propulsion systems, specifically the motor drive system. This report covers the collaborative work between NASA Glenn Research Center (GRC), RTRC, P&W and CA in the development of three types of magnetic components over the span of the three-year program. These critical magnetic components are the DC side EMI filter, which limits the propagation of harmful electromagnetic noise to the rise of the distribution system, and the AC side damping with the dv/dt filter, which limits the fast rise time of the power electronic converter output voltage to limit the degradation on the cable/motor insulation systems. Each of these components are investigated from component level design and are optimized at the system level with a combined modelling and testing effort. In the final experimental evaluation of the NASA developed soft magnetic material with a dv/dt filter, a commercial-off-the-shelf (COTS) magnetic core and the GRC magnetic core are optimized and loaded at 320Arms to evaluate their difference in performance. After a run time of 30 minutes in a MW-class motor driver at RTRC, the NASA GRC cores were found to not only offer a lower temperature rise of nearly 25°𝐶, but also a reduction in measured core loss of 25% (12.75W to 9.5W).

Elecrified Aircraft Propulsion↗
NASA NTRS2003

Solar Pumped Solid State Lasers for Space Solar Power: Experimental Path

We outline an experimentally based strategy designed to lead to solar pumped solid state laser oscillators useful for space solar power. Our method involves solar pumping a novel solid state gain element specifically designed to provide efficient conversion of sunlight in space to coherent laser light. Kilowatt and higher average power is sought from each gain element. Multiple such modular gain elements can be used to accumulate total average power of interest for power beaming in space, e.g., 100 kilowatts and more. Where desirable the high average power can also be produced as a train of pulses having high peak power (e.g., greater than 10(exp 10 watts). The modular nature of the basic gain element supports an experimental strategy in which the core technology can be validated by experiments on a single gain element. We propose to do this experimental validation both in terrestrial locations and also on a smaller scale in space. We describe a terrestrial experiment that includes diagnostics and the option of locating the laser beam path in vacuum environment. We describe a space based experiment designed to be compatible with the Japanese Experimental Module (JEM) on the International Space Station (ISS). We anticipate the gain elements will be based on low temperature (approx. 100 degrees Kelvin) operation of high thermal conductivity (k approx. 100 W/cm-K) diamond and sapphire (k approx. 4 W/cm-K). The basic gain element will be formed by sequences of thin alternating layers of diamond and Ti:sapphire with special attention given to the material interfaces. We anticipate this strategy will lead to a particularly simple, robust, and easily maintained low mass modelocked multi-element laser oscillator useful for space solar power.

Fork, Richard L.↗
NASA NTRS2008

Effect of Upper-Cycle Temperature on the Load-Biased, Strain-Temperature Response of NiTi

Over the past decade, interest in shape memory alloy based actuators has increased as the primary benefits of these solid-state devices have become more apparent. However, much is still unknown about the characteristic behavior of these materials when used in actuator applications. Recently we have shown that the maximum temperature reached during thermal cycling under isobaric conditions could significantly affect the observed mechanical response of NiTi (55 wt% Ni), especially the amount of transformation strain available for actuation and thus work output. This investigation extends that original work to ascertain whether further increases in the upper-cycle temperature would produce additional improvement in the work output of the material, which has a stress-free Af of 113 oC, and to determine the optimum cyclic conditions. Thus, isobaric, thermal-cycle experiments were conducted in the aforementioned alloy at various stress levels from 50-300 MPa using upper-cycle temperatures of 165, 200, 230, 260, 290, 320 and 350 oC. The data indicated that the amount of applied stress influenced the transformation strain available in the system, as would be expected. However, the maximum temperature reached during the thermal excursion also plays a role in determining the transformation strain, with the maximum transformation strain being developed by thermal cycling to 290 oC. In situ, neutron diffraction showed that the differences in transformation strain were related to differences in martensite texture within the microstructure when cycling to different upper-cycle temperatures. Hence, understanding this effect is important to optimizing the operation of SMA-based actuators and could lead to new methods for processing and training shape memory alloys for optimal performance.

Padula, Santo, II↗
NASA NTRS2011

Effect of Upper-Cycle Temperature on the Load-Biased, Strain-Temperature Response of NiTi

Over the past decade, interest in shape memory alloy based actuators has increased as the primary benefits of these solid-state devices have become more apparent. However, much is still unknown about the characteristic behavior of these materials when used in actuator applications. Recently we have shown that the maximum temperature reached during thermal cycling under isobaric conditions could significantly affect the observed mechanical response of NiTi (55 wt% Ni), especially the amount of transformation strain available for actuation and thus work output. The investigation we report here extends that original work to ascertain whether further increases in the upper-cycle temperature would produce additional changes in the work output of the material, which has a stress-free austenite finish temperature of 113 C, and to determine the optimum cyclic conditions. Thus, isobaric, thermal-cycle experiments were conducted on the aforementioned alloy at various stresses from 50-300 MPa using upper-cycle temperatures of 165, 200, 230, 260, 290, 320 and 350 C. The data indicated that the amount of applied stress influenced the transformation strain, as would be expected. However, the maximum temperature reached during the thermal excursion also plays an equally significant role in determining the transformation strain, with the maximum transformation strain observed during thermal cycling to 290 C. In situ neutron diffraction at stress and temperature showed that the differences in transformation strain were mostly related to changes in martensite texture when cycling to different upper-cycle temperatures. Hence, understanding this effect is important to optimizing the operation of SMA-based actuators and could lead to new methods for processing and training shape memory alloys for optimal performance.

Padula, Santo, II↗
NASA NTRS2002

Superfinished Surfaces for Power Transfer Systems Improvement

The continuous demands for high performance and lightweight power train systems resulted in requirements for higher power density gearing systems. However, increasing the load bearing capacity of the gear teeth, without increasing size, places stringent requirements upon metallurgy, dimensional control, and surface finish of the final products. In order to operate the mating parts near the upper bounds of their theoretical design envelope, manufacturing processes are required that are capable of improving the fatigue life and load bearing capacity of precision parts, while producing the required geometric accuracy. Results of the recent experimental studies indicate that the super finishing process is able to achieve these goals. This paper will review the results of our continuing evaluation of the super finish process as applied to aerospace gearing. Two separate evaluations were performed on gears to examine the effects of super finishing on resistance to both pitting and contact fatigue. For the reported experiments, both conventional and super finished test gears were simultaneously manufactured using the same process and the same heat lot of materials. This paper will also provide a brief description of the manufacturing technology used to achieve the results and will compare the results with other published data. In addition, this paper presents a couple of off-the-shelf manufacturing technologies that have been successfully used to super finish test specimens and will provide a glimpse of other emerging super finishing technologies. This is a US Army Manufacturing Technology project. The project was sponsored by the Aviation and Missiles Command (AMCOM) and was being managed and conducted by IIT Research Institute.

Niskanen, Paul↗
NASA NTRSDate not supplied

Uncertainty Reduction With Multi-Model Monte Carlo for Crystal Plasticity Simulations of Additively Manufactured Metals

In this work, multi-model Monte Carlo estimators are developed to reduce uncertainty in quantities of interest (QoIs) extracted from crystal plasticity simulations of additively manufactured (AM) metals. A significant concern in AM parts is uncertainty in mechanical properties caused in part by complex microstructures that arise from the AM process. Quantifying uncertainty in microstructure-sensitive behavior using experiments alone is costly, especially when mechanical allowables must be established. Quantitative relationships among microstructure, micromechanical metrics like slip accumulation, crack initiation, and failure are also difficult to capture with limited experiments. Crystal plasticity material models instead enable computational prediction of micromechanical stress and strain fields given a discretized microstructure. However, high-fidelity finely discretized crystal plasticity simulations are computationally expensive, while lower-fidelity models are less accurate and generally biased, making uncertainty quantification and reduction computationally difficult as well. Multi-model Monte Carlo methods leverage correlations between high- and low-fidelity models to produce unbiased estimators for QoIs with reduced uncertainty relative to standard Monte Carlo. Crystal plasticity QoIs considered in this work include yield strength and the mean and extreme values of micromechanical fields that are relevant to crack initiation. Multi-model Monte Carlo estimators are developed for each individual QoI and several groups of QoIs. The results of this work establish relationships among model correlations, sample allocation, and uncertainty reduction for different combinations of QoIs and demonstrate a trend of less uncertainty reduction as QoIs become more sensitive to local microstructure. Limitations from using pilot samples to estimate model covariances and train low-fidelity models are also addressed. The uncertainty reduction achieved by multi-model Monte Carlo is an important step toward using computational mechanics models to predict microstructure-sensitive crack initiation and failure in AM parts.

uncertainty quantification↗
NASA NTRS2004

EVA Performance Prediction

Astronaut physical performance capabilities in micro gravity EV A or on planetary surfaces when encumbered by a life support suit and debilitated by a long exposure to micro gravity will be less than unencumbered pre flight capabilities. The big question addressed by human factors engineers is: what can the astronaut be expected to do on EVA or when we arrive at a planetary surface? A second question is: what aids to performance will be needed to enhance the human physical capability? These questions are important for a number of reasons. First it is necessary to carry out accurate planning of human physical demands to ensure that time and energy critical tasks can be carried out with confidence. Second it is important that the crew members (and their ground or planetary base monitors) have a realistic picture of their own capabilities, as excessive fatigue can lead to catastrophic failure. Third it is important to design appropriate equipment to enhance human sensory capabilities, locomotion, materials handling and manipulation. The evidence from physiological research points to musculoskeletal, cardiovascular and neurovestibular degradation during long duration exposure to micro gravity . The evidence from the biomechanics laboratory (and the Neutral Buoyancy Laboratory) points to a reduction in range of motion, strength and stamina when encumbered by a pressurized suit. The evidence from a long history of EVAs is that crewmembers are indeed restricted in their physical capabilities. There is a wealth of evidence in the literature on the causes and effects of degraded human performance in the laboratory, in sports and athletics, in industry and in other physically demanding jobs. One approach to this challenge is through biomechanical and performance modeling. Such models must be based on thorough task analysis, reliable human performance data from controlled studies, and functional extrapolations validated in analog contexts. The task analyses currently carried out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

Peacock, Brian↗
NASA NTRS1994

A quick look method of detecting water of hydration in small solar system bodies

The action of aqueous alteration of the near-subsurface material on asteroids and probably some satellites in the Solar System constitutes part of the formation history of the Solar System. The C-class asteroids (and subclasses B, G, and F) were initially believed to have undergone aqueous alteration based on their low albedos and neutral broadband visible and near-infrared colors. These spectra exhibit a sharp drop at wavelengths shorter than 0.55 microns due to a strong ferric oxide intervalence change transfer transition. This IVCT comprises multiple absorptions that are not uniquely indicative of phyllosilicates, but rather are present in the spectrum of any object containing Fe(2+) and Fe(3+) in its surface material. A definitive indication of aqueous alteration came when the broad IR absorption feature having a minimum near 3.0 microns indicative of structural hydroxyl (OH) and interlayer and and absorbed water in phyllosilicates was identified in the IR photometry of many C-class asteroids. Additional mineralogical compositional evidence of aqueously-altered asteroids has come as the result of high SNR narrowband spectrophotometry in the visible and near-infrared spectral regions taken using a CCD/spectrograph combination. An absorption feature centered at 0.7 microns indicative of an Fe(2+) - Fe(3+) charge transfer transition in oxidized iron in phyllosilicates in spectra of some low-albedo asteroids, especially C and G class, and CM2 carbonaceous chondrite meteorites was identified in the CCD spectra. The correlation and covariance of the 0.7-micron and 3.0-micron features were examined by comparing observations of asteroids common to both the CCD reflectance spectra and the 3.0-micron multicolor photometry data sets. Thirty-one pairs of observations were included in this training group. The results of the statistical study indicate that with a 95% confidence level, 84% of the objects observed either having or not having the 0.7-micron feature will correspondingly have the 3.0-micron water of hydration feature.

Vilas, F.↗
NASA NTRS2020

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

radiative transfer↗
NASA NTRS1998

Teaching Soil Science in Primary and Secondary Schools

Earth's thin layer of soil is a fragile resource, made up of minerals, organic materials, air, water, and billions of living organisms. Soils plays a variety of critical roles that sustain life on Earth. If we think about soil, we tend to see it first as the source of most of the food we eat and the fibers we use, such as wood and cotton. Few students realize that soils also provide the key ingredients to many of the medicines (including antibiotics), cosmetics, and dyes that we use. Fewer still understand the importance of soils in integrating, controlling, and regulating the movement of air, water, materials, and energy between the hydrosphere, lithosphere, atmosphere, and biosphere. Because soil sustains life, it offers both a context and a natural laboratory for investigating these interactions. The enclosed poster, which integrates soil profiles with typical landscapes in which soils form, can also help students explore the interrelationships of Earth systems and gain an understanding of our soil resources. The poster, produced jointly by the American Geological Institute and the Soil Science Society of America, aims to increase awareness of the importance of soil, as does the GLOBE (Global Learning and Observations To Benefit the Environment) Program. Vice President Al Gore instituted the GLOBE Program on Earth Day of 1993 to increase environmental awareness of individuals throughout the world, contribute to a better scientific understanding of the Earth, and help all students reach higher levels of achievement in science and mathematics. GLOBE functions as a partnership between scientists, students, and teachers in which scientists design protocols for specific measurements they need for their research that can be performed by K-12 students. Teachers are trained in the GLOBE protocols and teach them to their students. Students make the measurements, enter data via the Internet to a central data archive, and the data becomes available to scientists and the general community. Students benefit by having a "hands-on"experience in science, math, and technology, using their local environment as a learning laboratory, as well as contact with scientists and other students around the world. Soil investigations have become an essential component of GLOBE. The protocols that have been developed so far within the GLOBE program include GPS Location, Atmosphere/Climate, Soil Characterization, Soil Moisture and Temperature, Land Cover/Biometry, Hydrology, and Satellite Image Classification. For the GLOBE Soil Characterization Protocol, students explore the physical. chemical, and morphological properties of the soil at their study site. They are asked to dig a pit or use an auger to about 1 meter at at least 2 sites.

Levine, Elissa R.↗
NASA NTRSDate not supplied

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗