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At least 181 records · Page 10

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗

Detection of Moving Targets Using Soliton Resonance Effect

The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.

Kulikov, Igor K.↗

Machine learning of hidden variables in multiscale fluid simulation

Solving fluid dynamics equations often requires the use of closure relations that account for missing microphysics. For example, when solving equations related to fluid dynamics for systems with a large Reynolds number, sub-grid effects become important and a turbulence closure is required, and in systems with a large Knudsen number, kinetic effects become important and a kinetic closure is required. By adding an equation governing the growth and transport of the quantity requiring the closure relation, it becomes possible to capture microphysics through the introduction of ‘hidden variables’ that are non-local in space and time. The behavior of the ‘hidden variables’ in response to the fluid conditions can be learned from a higher fidelity or ab-initio model that contains all the microphysics. In our study, a partial differential equation simulator that is end-to-end differentiable is used to train judiciously placed neural networks against ground-truth simulations. We show that this method enables an Euler equation based approach to reproduce non-linear, large Knudsen number plasma physics that can otherwise only be modeled using Boltzmann-like equation simulators such as Vlasov or particle-in-cell modeling.

42 ENGINEERING↗

Detection of High-impedance Arcing Faults in Radial Distribution DC Systems

High voltage, low current arcing faults in DC power systems have been researched at the NASA Glenn Research Center in order to develop a method for detecting these 'hidden faults', in-situ, before damage to cables and components from localized heating can occur. A simple arc generator was built and high-speed and low-speed monitoring of the voltage and current waveforms, respectively, has shown that these high impedance faults produce a significant increase in high frequency content in the DC bus voltage and low frequency content in the DC system current. Based on these observations, an algorithm was developed using a high-speed data acquisition system that was able to accurately detect high impedance arcing events induced in a single-line system based on the frequency content of the DC bus voltage or the system current. Next, a multi-line, radial distribution system was researched to see if the arc location could be determined through the voltage information when multiple 'detectors' are present in the system. It was shown that a small, passive LC filter was sufficient to reliably isolate the fault to a single line in a multi-line distribution system. Of course, no modification is necessary if only the current information is used to locate the arc. However, data shows that it might be necessary to monitor both the system current and bus voltage to improve the chances of detecting and locating high impedance arcing faults

Gonzalez, Marcelo C.↗

Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states

Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.

42 ENGINEERING↗

Hidden magnetism uncovered in a charge ordered bilayer kagome material ScV 6 Sn 6

Charge ordered kagome lattices have been demonstrated to be intriguing platforms for studying the intertwining of topology, correlation, and magnetism. The recently discovered charge ordered kagome material ScV 6 Sn 6 does not feature a magnetic groundstate or excitations, thus it is often regarded as a conventional paramagnet. Here, using advanced muon-spin rotation spectroscopy, we uncover an unexpected hidden magnetism of the charge order. We observe an enhancement of the internal field width sensed by the muon ensemble, which takes place within the charge ordered state. More importantly, the muon spin relaxation rate below the charge ordering temperature is substantially enhanced by applying an external magnetic field. Taken together with the hidden magnetism found in AV 3 Sb 5 (A = K, Rb, Cs) and FeGe kagome systems, our results suggest ubiqitous time-reversal symmetry-breaking in charge ordered kagome lattices.

36 MATERIALS SCIENCE↗

Silent emergency alarm system for schools and the like

An emergency alert system is described. In a school each classroom (or other area) is instrumented with a hidden microphone and receiver tuned to a non-audible frequency. The receivers' outputs are connected to a central display unit in the school's administrative office. Each instructor is provided with a small concealable transmitter which, when hand activated by the instructor upon the occurrance of any emergency, generates a non-audible signal at the receiver's tuned frequency.

Read, W. S.↗

Dwarf spheroidal galaxies: Keystones of galaxy evolution

Dwarf spheroidal galaxies are the most insignificant extragalactic stellar systems in terms of their visibility, but potentially very significant in terms of their role in the formation and evolution of much more luminous galaxies. We discuss the present observational data and their implications for theories of the formation and evolution of both dwarf and giant galaxies. The putative dark-matter content of these low-surface-brightness systems is of particular interest, as is their chemical evolution. Surveys for new dwarf spheroidals hidden behind the stars of our Galaxy and those which are not bound to giant galaxies may give new clues as to the origins of this unique class of galaxy.

Gallagher, John S., III↗

Cratering on Titan: A Pre-Cassini Perspective

The NASA-ESA Cassini mission, comprising a formidably instrumented orbiter and parachute-borne probe to be launched this October, promises to reveal a crater population on Titan that has been heretofore hidden by atmospheric haze. This population on the largest remaining unexplored surface in the solar system will be invaluable in comparative planetological studies, since it introduces evidence of the atmospheric effects of cratering on an icy satellite. Here, I highlight some impact features we may hope to find and could devote some modeling effort toward. Titan in a Nutshell: Radius= 2575 km. Density= 1880 kg/cubic m consistent with rock-ice composition. Surface pressure = 1.5 bar. Surface gravity = 1.35 m/square s Atmosphere -94% N2 6% CH, Surface temperature = 94K Tropopause temperature = 70K at 40 km alt. Probable liquid hydrocarbon deposits exist on or near the surface.Titan in a Nutshell: Radius= 2575 km. Density= 1880 kg/cubic m consistent with rock-ice composition. Surface pressure = 1.5 bar. Surface gravity = 1.35 m/square s; Atmosphere about 94% N2 6% CH, Surface temperature = 94K Tropopause temperature = 70K at 40 km alt. Probable liquid hydrocarbon deposits exist on or near the surface. Titan is comparable to Callisto and Ganymede for strength/gravity, Mars/Earth/Venus for atmospheric interaction, and Hyperion, Rhea, and Iapetus for impactor distribution. The leading/trailing asymmetry of crater density from heliocentric impactors is expected to be about 5-6, in the absence of resurfacing. Any Saturnocentric impactor population is likely to alter this. In particular the impact disruption of Hyperion is noted; because of the 3:4 orbital resonance with Titan, fragments from the proto-Hyperion breakup would have rapidly accreted onto Titan. Titan's resurfacing history is of course unknown. The disruption of impactors into fragments that individually create small craters is expected to occur. A crude estimate suggests a maximum separation of about 2 km (compared with 4 km on Venus, or 0.5 km on Earth). Crater chains are unlikely on Titan, since impactors must pass close enough to Saturn to be tidally disrupted; as a result, they would suffer aerodynamic disruption. Crater counting on adjacent satellites gives densities of about 200 per 10 (exp 6) square km for 20-km-diameter craters. However, the presence of a thick atmosphere leads to atmospheric shielding, depleting the relative abundance of small craters. This has been evaluated by models, and the relative abundance of small craters may be due to a diagnostic atmospheric collapse. A number of radar-dark "splotches" have been detected on Venus; these have been attributed to the interaction of the surface with the atmospheric shockwave produced by the Tunguska-like explosion of a bolide in the atmosphere. Simple analogy suggests that similar features might occur on Titan, but the shocked mass density (which controls the momentum coupling between the surface and the shockwave) of Titan's cold N2 atmosphere is about 20x smaller than that of Venus's hot CO2 atmosphere. Unless ice is much more easily turned to rubble than is rock, such features seem less probable on Titan. When the energy deposited by an impact forms a fireball with an equilibrate greater than one scale height, the fireball expands upward and can distribute ejecta. on ballistic exoatmospheric trajectories. On Venus this process is believed to be responsible for the parabolic features; the interaction of various-sized particles falling through the atmosphere with the zonal wind field winnows the particles to form a parabolic deposit. Although such a process is possible on Titan, the large scale height at higher altitudes would make it more difficult. Comparison with craters on other icy satellites suggests that craters on Titan will be fairly shallow (depth/diameter about 0.1) and craters greater than 10 km in diameter will have central peaks or domed bases, perhaps with central pits. The formation of ejecta. blankets may involve the atmosphere in a significant way, both by restraining the expansion of the ejecta cloud and by influencing the thermal history of the ejecta. Compared with Venus, Titan's atmosphere will chill an impact melt somewhat quickly, so the long ejecta flows seen on Venus seem less likely, detailed modeling needs to be performed to determine the impact melt production. Crater topography on Titan may be highlighted by the influence of liquids forming crater lakes. Craters with central peaks will typically form ring-shaped lakes, although horseshoe-shaped takes may be common; domed craters with central pits may even form bullseye lakes with islands with central ponds. If liquids have covered a substantial part of Titan's surface for a substantial period, hydroblemes and tsunami deposits may be common.

Lorenz, R. D.↗

Is the Martian Water Table Hidden from Radar View?

Mars may possess a global sub-surface groundwater table as an integral part of its current hydrological system, However, the Mars Advanced Radar for Subsurface and Ionospheric Sounding (MARSIS) onboard the 'Mars Express (MEx) spacecraft has yet to make a definitive detection of such a body of liquid water. In this work, we quantify. the conditions that would allow a detection of a deep aquifer and demonstrate that the lack of radar detection doses not uniquely role out the presence of such a body. Specifically, if the overlying crustal material has a conductivity above approximately 10(exp -5) S/m (equivalent to a loss tangent of 0.008), a radar echo frown an aquifer could be sufficiently attenuated by the intetvening medium to prevent its detection by MARSIS. As such, the lack of direct detection by MARSIS -- a "null result" does not rule out the possibility of the water table's existence.

Farrell, W. M.↗

Exposing Hidden Parts of the SE Process: MBSE Patterns and Tools for Tracking and Traceability

An interesting benefit of applying Model-Based Systems Engineering (MBSE) is that the rigor and coordination intrinsic to MBSE forces us to apply Systems Engineering to our own traditional activities, processes, and products, which results in richer, more expressive models, more powerful reasoning, and a clearer and more effective Systems Engineering (SE) process. Our MBSE frameworks and languages contain semantic richness sufficient to describe our systems at any particular point in time, often with an emphasis on the description of the system at major milestones. This is unarguably a real asset. However, when we apply MBSE in service of missions that are in development, rapidly evolving, of a larger scale, and where interpersonal communication is a critical part of the design process, we discover that our frameworks and languages are still not quite rich enough to enable us to ask the kinds of questions and get the kinds of answers we want in order to address the concerns of day to day work. This paper will discuss some patterns and tools we have developed to help address some of the not-always-explicit SE concerns that we have identified through our MBSE work. Particularly, this paper will discuss flexible yet practical methods for defining and capturing maturity, workflow, and agreement traceability within our system models, extensible ways to perform and track model audits, and ways to report and interact with this knowledge in the context of MBSE applied to support NASA’s Europa Project.

Jackson, Maddalena↗

Exposing Hidden Parts of the SE Process: MBSE Patterns and Tools for Tracking and Traceability

An interesting benefit of applying Model-Based Systems Engineering (MBSE) is that the rigor and coordination intrinsic to MBSE forces us to apply Systems Engineering to our own traditional activities, processes, and products, which results in richer, more expressive models, more powerful reasoning, and a clearer and more effective Systems Engineering (SE) process. Our MBSE frameworks and languages contain semantic richness sufficient to describe our systems at any particular point in time, often with an emphasis on the description of the system at major milestones. This is unarguably a real asset. However, when we apply MBSE in service of missions that are in development, rapidly evolving, of a larger scale, and where interpersonal communication is a critical part of the design process, we discover that our frameworks and languages are still not quite rich enough to enable us to ask the kinds of questions and get the kinds of answers we want in order to address the concerns of day to day work. This paper will discuss some patterns and tools we have developed to help address some of the not-always-explicit SE concerns that we have identified through our MBSE work. Particularly, this paper will discuss flexible yet practical methods for defining and capturing maturity, workflow, and agreement traceability within our system models, extensible ways to perform and track model audits, and ways to report and interact with this knowledge in the context of MBSE applied to support NASA’s Europa Project

Jackson, Maddalena↗

Far-field speckle correlations as a function of object position for microscopically distinguishing objects hidden in a randomly scattering medium

Super-resolution optical sensing is of critical importance in science and technology and has required prior information about an imaging system or obtrusive near-field probing. Additionally, coherent imaging and sensing in heavily scattering media such as biological tissue has been challenging, and practical approaches have either been restricted to measuring the field transmission of a single point source, or to where the medium is thin. We present the concept of far-subwavelength spatial sensing with relative object motion in speckle as a means to coherently sense through heavy scatter. Experimental results demonstrate the ability to distinguish nominally identical objects with nanometer-scale translation while hidden in randomly scattering media, without the need for precise or known location and with imprecise replacement. The theory and supportive illustrations presented provide the basis for super-resolution sensing and the possibility of virtually unlimited spatial resolution, including through thick, heavily scattering media with relative motion of an object in a structured field. This work provides enabling opportunities for material inspection, security, and biological sensing.

Hastings, Ryan L. (ORCID:0009000095977807)↗

Measuring Weld Profiles By Computer Tomography

Noncontacting, nondestructive computer tomography system determines internal and external contours of welded objects. System makes it unnecessary to take metallurgical sections (destructive technique) or to take silicone impressions of hidden surfaces (technique that contaminates) to inspect them. Measurements of contours via tomography performed 10 times as fast as measurements via impression molds, and tomography does not contaminate inspected parts.

Pascua, Antonio G.↗

Certification of COTS Software in NASA Human Rated Flight Systems

Adoption of commercial off-the-shelf (COTS) products in safety critical systems has been seen as a promising acquisition strategy to improve mission affordability and, yet, has come with significant barriers and challenges. Attempts to integrate COTS software components into NASA human rated flight systems have been, for the most part, complicated by verification and validation (V&V) requirements necessary for flight certification per NASA s own standards. For software that is from COTS sources, and, in general from 3rd party sources, either commercial, government, modified or open source, the expectation is that it meets the same certification criteria as those used for in-house and that it does so as if it were built in-house. The latter is a critical and hidden issue. This paper examines the longstanding barriers and challenges in the use of 3rd party software in safety critical systems and cover recent efforts to use COTS software in NASA s Multi-Purpose Crew Vehicle (MPCV) project. It identifies some core artifacts that without them, the use of COTS and 3rd party software is, for all practical purposes, a nonstarter for affordable and timely insertion into flight critical systems. The paper covers the first use in a flight critical system by NASA of COTS software that has prior FAA certification heritage, which was shown to meet the RTCA-DO-178B standard, and how this certification may, in some cases, be leveraged to allow the use of analysis in lieu of testing. Finally, the paper proposes the establishment of an open source forum for development of safety critical 3rd party software.

Goforth, Andre↗

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗