SEARCH · Engineering Papers

Results for “seismic methods”

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.

SourceResearch connectionFrom yearThrough year

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

129 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 19

The topics include: 1) The abundances of Iron-60 in Pyroxene Chondrules from Unequilibrated Ordinary Chondrites; 2) LL-Ordinary Chondrite Impact on the Moon: Results from the 3.9 Ga Impact Melt at the Landing Site of Appolo 17; 3) Evaluation of Chemical Methods for Projectile Identification in Terrestrial and Lunar Impactites; 4) Impact Cratering Experiments in Microgravity Environment; 5) New Achondrites with High-Calcium Pyroxene and Its implication for Igneous Differentiation of Asteroids; 6) Climate History of the Polar Regions of Mars Deduced form Geologic Mapping Results; 7) The crater Production Function for Mars: A-2 Cumulative Power-Law Slope for Pristine Craters Greater than 5 km in Diameter Based on Crater Distribution for Northern Plains Materials; 8) High Resolution Al-26 Chronology: Resolved Time Interval Between Rim and Interior of a Highly Fractionated Compact Type a CAI from Efremovka; 9) Assessing Aqueous Alteration on Mars Using Global Distributions of K and Th; 10) FeNi Metal Grains in LaPaz Mare Basalt Meteorites and Appolo 12 Basalts; 11) Unique Properties of Lunar Soil for In Situ Resource Utilization on the Moon; 12) U-Pb Systematics of Phosphates in Nakhlites; 13) Measurements of Sound Speed in Granular Materials Simulated Regolith; 14) The Effects of Oxygen, Sulphur and Silicon on the Dihedral Angles Between Fe-rich Liquid Metal and Olivine, Ringwoodite and Silicate Perovskite: Implications for Planetary Core Formation; 15) Seismic Shaking Removal of Craters 0.2-0.5 km in Diameter on Asteroid 433 Eros; 16) Focused Ion Beam Microscoopy of ALH84001 Carbonate Disks; 17) Simulating Micro-Gravity in the Laboratory; 18) Mars Atmospheric Sample Return Instrument Development; 19) Combined Remote LIBS and Raman Spectroscopy Measurements; 20) Unusual Radar Backscatter Properties Along the Northern Rim of Imbrium Basin; 21) The Mars Express/NASAS Project at JPL; 22) The Geology of the Viking 2 Lander Site Revisited; 23) An Impact Genesis for Loki Patera? 24) Mars Polar Cap Edges Tracked over 3 Full Mars Years; 25) Elemental Abundance in Presolar SiC: Comparing Grains Separated by Acid Residue and Gently Separation Procedures; 26) First Results from the Descent Imager/Spectral Radiometer (DISR) Experiment on the Huygens Entry Probe of Titan; 27) Minor Element Behavior of Pallasite Olivine: Understanding Pallasite Thermal History and Chronology; 28) Canonical Anorthite in a Grosnaja Forsterite-bearing CAI; 29) Experimental Evidence for Condensation of 'Astrophysical' Carbonate; 30) Distribution and Classification of Multiple Coronae on Venus; 31) Recognition of Rayed Craters on Mars in THEMIS Thermal Infrared Imagery: Implications for Martian Meteorite Source Regions; 32) Geochemical Modeling of Evaporites on Mars: Insight from Meridiani Planum; 33) Hadean Crustal Processes Revealed from Oxygen Isotopes and U-Th-Pb Depth Profiling of Pre-4.0 Ga Detrital Zircons from Western Australia; 34) On Modeling the Seepage of Water into the Martian Subsurface; 35) Martial Gullies and Groundwater: A Series of Unfortunate Exceptions; 36) Olivine and Carbonate Globules in ALH84001: A Terrestrial Analog, and Implications for Water on Mars; 37) A Reevaluation of Mass Movements Within the Valles Marineris Region of Mars Using MOLA and MOC Data; 38) Evidence of Hydrated 109P/Swift-Tuttle Meteoroids from Meteor Spectroscopy; 39) Cr-54 Anomalies in the Solar System: Their Extent and Origin; 40) Reevaluation of the Mn-53-Cr-53 Systematic in the Basaltic Achondrites; 41) Effective Liquid Metal-Silicate Mixing Upon Shock by Power-Law Droplet Size Scaling in Richtmyer-Meshkov Like Perturbations; 42) Post-Impact Deformation of Impact Craters: Towards a Better Understanding Through the Study of Mjolnir Crater; 43) Cutting Silica Aerogel for Particle Extraction; 44) Liquid Hydrocarbons on Titan's Surface? How Cassini ISS Observations Fit into the Story (So Far); and 45) Mesoscale Simulations of Polar Circulations: Late Spring to Late Summe

Source record↗

NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗

NASA NTRS2013

Differential Muon Tomography to Continuously Monitor Changes in the Composition of Subsurface Fluids

Muon tomography has been used to seek hidden chambers in Egyptian pyramids and image subsurface features in volcanoes. It seemed likely that it could be used to image injected, supercritical carbon dioxide as it is emplaced in porous geological structures being used for carbon sequestration, and also to check on subsequent leakage. It should work equally well in any other application where there are two fluids of different densities, such as water and oil, or carbon dioxide and heavy oil in oil reservoirs. Continuous monitoring of movement of oil and/or flood fluid during enhanced oil recovery activities for managing injection is important for economic reasons. Checking on leakage for geological carbon storage is essential both for safety and for economic purposes. Current technology (for example, repeat 3D seismic surveys) is expensive and episodic. Muons are generated by high- energy cosmic rays resulting from supernova explosions, and interact with gas molecules in the atmosphere. This innovation has produced a theoretical model of muon attenuation in the thickness of rock above and within a typical sandstone reservoir at a depth of between 1.00 and 1.25 km. Because this first simulation was focused on carbon sequestration, the innovators chose depths sufficient for the pressure there to ensure that the carbon dioxide would be supercritical. This innovation demonstrates for the first time the feasibility of using the natural cosmic-ray muon flux to generate continuous tomographic images of carbon dioxide in a storage site. The muon flux is attenuated to an extent dependent on, amongst other things, the density of the materials through which it passes. The density of supercritical carbon dioxide is only three quarters that of the brine in the reservoir that it displaces. The first realistic simulations indicate that changes as small as 0.4% in the storage site bulk density could be detected (equivalent to 7% of the porosity, in this specific case). The initial muon flux is effectively constant at the surface of the Earth. Sensitivity of the method would be decreased with increasing depth. However, sensitivity can be improved by emplacing a greater array of particle detectors at the base of the reservoir.

Coleman, Max↗