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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.

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At least 379 records · Page 21

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NASA NTRS1986

Deformational sequence of a portion of the Michipicoten greenstone belt, Chabanel Township, Ontario

Detailed mapping at a scale of one inch = 400 feet is being carried out within a fume kill, having excellent exposure, located in the southwestern portion of the Michipicoten Greenstone Belt near Wawa, Ontario. The rocks are metasediments and metavolcanics of lower greenschist facies. U-Pb geochronology indicates that they are at least 2698 + or - 11 Ma old. The lithologic packages strike northeast to northwest, but the dominant strike is approximately east-west. Sedimentary structures and graded bedding are well preserved, aiding in the structural interpretation of this multiply deformed area. At least six phases of deformation within a relatively small area of the Michipicoten Greenstone Belt have been tentatively identified. These include the following structural features in approximate order of occurrence: (0) soft-sediment structures; (1) regionally overturned rocks, flattened pebbles, bedding parallel cleavage, and early, approximately bedding parallel faults; (2) northwest to north striking cleavage; (3) northeast striking cleavage and associated folds, and at least some late movement on approximately bedding parallel faults; (4) north-northwest and northeast trending faults; and (5) diabase dikes and associated fracture cleavages. Minor displacement of the diabase dikes occurs on faults that appear to be reactivated older structures.

Shrady, C. H.↗

NASA NTRS2010

Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.

Thipphavong, David↗

NASA NTRS2017

Orion Exploration Flight Test Post-Flight Inspection and Analysis

The multipurpose crew vehicle, Orion, is being designed and built for NASA to handle the rigors of crew launch, sustainment and return from scientific missions beyond Earth orbit. In this role, the Orion vehicle is meant to operate in the space environments like the naturally occurring meteoroid and the artificial orbital debris environments (MMOD) with successful atmospheric reentry at the conclusion of the flight. As a result, Orion's reentry module uses durable porous, ceramic tiles on almost thirty square meters of exposed surfaces to accomplish both of these functions. These durable, non-ablative surfaces maintain their surface profile through atmospheric reentry; thus, they preserve any surface imperfections that occur prior to atmospheric reentry. Furthermore, Orion's launch abort system includes a shroud that protects the thermal protection system while awaiting launch and during ascent. The combination of these design features and a careful pre-flight inspection to identify any manufacturing imperfections results in a high confidence that damage to the thermal protection system identified post-flight is due to the in-flight solid particle environments. These favorable design features of Orion along with the unique flight profile of the first exploration flight test of Orion (EFT-1) have yielded solid particle environment measurements that have never been obtained before this flight.

Miller, J. E.↗

NASA NTRS2018

Seeking the Signs of Life: Assessing the Presence of Biosignatures in the Returned Sample Suite

A biosignature (''definitive biosignature'' or DBS) is an object, substance and/or pattern whose origin specifically requires a biological agent. One category of DBS are complex organic molecules and/or structures whose formation and abundances relative to other compounds are virtually unachievable in the absence of life. A potential biosignature (PBS) is an object, substance and/or pattern that might have a biological origin and thus compels investigators to gather more data before reaching a conclusion as to the presence or absence of life. The usefulness of a PBS is determined not only by the probability that life created it but also by the improbability that nonbiological processes produced it. Because habitable planetary environments create nonbiological features that can mimic biosignatures, these environments must be characterized to the extent necessary to provide a context that is essential for confirming the presence of DBS. Environmental conditions also must have allowed biosignatures to be preserved and amenable to detection. Categories of biosignatures and their measurement requirements are indicated below.

Source record↗

DOE OSTI2024

An asymptotic-preserving semi-Lagrangian algorithm for the anisotropic heat transport equation with arbitrary magnetic fields

Here, we extend the recently proposed semi-Lagrangian algorithm for the extremely anisotropic heat transport equation [Chacón et al., J. Comput. Phys ., 272 (2014)] to deal with arbitrary magnetic field topologies. The original scheme (which showed remarkable numerical properties) was valid for the so-called tokamak-ordering regime, in which the magnetic field magnitude was not allowed to vary much along field lines. The proposed extension maintains the attractive features of the original scheme (including the analytical Green's function, which is critical for tractability) with minor modifications, while allowing for completely general magnetic fields. The accuracy and generality of the approach are demonstrated by numerical experiment with an analytical manufactured solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems

Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.

Algorithms↗

NASA NTRS1995

Paleobiology of the Mesoproterozoic Billyakh Group, Anabar Uplift, northern Siberia

Silicified peritidal carbonates of the Mesoproterozoic Kotuikan and Yusmastakh Formations, Anabar Uplift, northeastern Siberia, contain exceptionally well-preserved microfossils. The assemblage is dominated by ellipsoidal akinetes of nostocalean cyanobacteria (Archaeoellipsoides) and problematic spheroidal unicells (Myxococcoides); both are allochthonous and presumably planktonic. The assemblage also includes distinctive mat-forming scytonematacean and entophysalidacean cyanobacteria, diverse short trichomes interpreted as cyanobacterial hormogonia or germinated akinetes, rare longer trichomes, and several types of colonial unicells. Although many taxa in the Kotuikan-Yusmastakh assemblage are long-ranging prokaryotes, the overall character of the assemblage is distinctly Mesoproterozoic, with its major features shared by broadly coeval floras from Canada, China, India, and elsewhere in Siberia. Microfossils also occur in middle to inner shelf shales of the Ust'-Il'ya and lower Kotuikan Formations. Leiosphaerid acritarchs (up to several hundred microns in diameter) characterize this facies. As in other Mesoproterozoic acritarch assemblages, acanthomorphic and other complex forms that typify Neoproterozoic assemblages are absent. The combination in Billyakh assemblages of exceptional preservation and low eukaryotic diversity supports the hypothesis that nucleated organisms diversified markedly near the Mesoproterozoic-Neoproterozoic boundary. The assemblages also demonstrate the antiquity of cyanobacteria capable of cell differentiation and suggest the importance of both changing peritidal substrates and evolving eukaryotes in determining stratigraphic patterns of Proterozoic prokaryotes. The permineralized assemblage contains 33 species belonging to 17 genera. Ten new species or new combinations are proposed: Archaeoellipsoides costatus n. sp., A. elongatus n. comb., A. dolichos n. comb., A. minor n. nom., A. crassus n. comb., A. major n. comb., A. bactroformis n. sp., Veteronostocale medium n. sp., Filiconstrictosus cephalon n. sp., and Partitiofilum yakschinii n. sp.

Non-NASA Center↗

DOE OSTI2021

RivGraph: Automatic extraction and analysis of river and delta channel network topology

River networks sustain life and landscapes by carrying and distributing water, sediment, and nutrients throughout ecosystems and communities. At the largest scale, river networks drain continents through tree-like tributary networks. At typically smaller scales, river deltas and braided rivers form loopy, complex distributary river networks via avulsions and bifurcations.In order to model flows through these networks or analyze network structure, the topology, or connectivity, of the network must be resolved. Additionally, morphologic properties of each river channel as well as the direction of flow through the channel inform how fluxes travel through the network’s channels. Riv Graphis a Python package that automates the extraction and characterization of river channel networks from a user-provided binary image, or mask, of a channel network (Fig. 1). Masks may be derived from (typically remotely-sensed) imagery, simulations, or even hand-drawn. RivGraph will create explicit representations of the channel network by resolving river centerlines as links, and junctions as nodes. Flow directions are solved for each link of the network without using auxiliary data, e.g., a digital elevation model (DEM). Morphologic properties are computed as well, including link lengths, widths, sinuosities, branching angles,and braiding indices. If provided,RivGraph will preserve georeferencing information of the mask and will export results as ESRI shapefiles, GeoJSONs, and GeoTIFFs for easy import into GIS software.RivGraph can also return extracted networks as networkx objects for convenient interfacing with the full-featured networkx package (Hagberg et al., 2008). Finally, RivGraph offers a suite of topologic metrics that were specifically designed for river channel network analysis (Tejedor et al., 2015b).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1986

Solution of the symmetric eigenproblem AX=lambda BX by delayed division

Delayed division is an iterative method for solving the linear eigenvalue problem AX = lambda BX for a limited number of small eigenvalues and their corresponding eigenvectors. The distinctive feature of the method is the reduction of the problem to an approximate triangular form by systematically dropping quadratic terms in the eigenvalue lambda. The report describes the pivoting strategy in the reduction and the method for preserving symmetry in submatrices at each reduction step. Along with the approximate triangular reduction, the report extends some techniques used in the method of inverse subspace iteration. Examples are included for problems of varying complexity.

Thurston, G. A.↗

NASA NTRS1989

The NASA/OAST telerobot testbed architecture

Through a phased development such as a laboratory-based research testbed, the NASA/OAST Telerobot Testbed provides an environment for system test and demonstration of the technology which will usefully complement, significantly enhance, or even replace manned space activities. By integrating advanced sensing, robotic manipulation and intelligent control under human-interactive supervision, the Testbed will ultimately demonstrate execution of a variety of generic tasks suggestive of space assembly, maintenance, repair, and telescience. The Testbed system features a hierarchical layered control structure compatible with the incorporation of evolving technologies as they become available. The Testbed system is physically implemented in a computing architecture which allows for ease of integration of these technologies while preserving the flexibility for test of a variety of man-machine modes. The development currently in progress on the functional and implementation architectures of the NASA/OAST Testbed and capabilities planned for the coming years are presented.

Matijevic, J. R.↗

NASA NTRSDate not supplied

A Drilling Mission to Search for Biosignatures of Life on Mars Simulated in Atacama Chile

Missions to search for evidence of life on Mars, including Mars Science Laboratory(MSL)are using drilling systems to get beneath the high oxidized and radiated surface where biomolecules may be preserved. MSL drill holes show that even at shallow depth the subsurface is more reduced and therefor more likely to preserve biosignatures. Analysis of these reduced materials yielded the first detection of organic carbon compounds on Mars[1].While MSL was capable of drilling only 10 cm, the ExoMars mission now planned for a 2022 launch will feature a rover carrying a 2 m drill, motivated by desire to penetrate beneath the irradiated surface. The Atacama Rover Astrobiology Drilling Studies(ARADS)was a PSTAR project that used flight prototype technologies in a highly relevant Mars analog site, together with related scientific studies, to better understand how to best search for life on Mars. ARADS field work was performed in Atacama Chile and featured a rover-mounted 1.2m auguring drill to acquire subsurface samples that were analyzed with flight prototype instruments designed to search for chemical signatures of life.

C R Stoker↗

DOE OSTI2022

Conversion of Resonance Parameters Between Wigner-Eisenbud R-matrix and Transition Matrix Pole Representation

The goal of this research is to develop a numerical code for translation between the current standard, Wigner-Eisenbud R-matrix parameters and a novel pole-representation of cross sections. The method follows Ducru et al. and constructs the conversion between these parametric representations of the scattering and reaction data. This pole representation, which expresses cross sections as a sum of simple poles (and their attendant residues), is examined in the context of the advantages provided by this compact, computationally efficient representation. These advantages include the ability to doppler broaden cross sections on-the-fly as well as a lower memory footprint when generating cross sections, an attractive feature to those interested in parallel GPU based Monte Carlo. Some conversion methods between R-matrix parameters and S-matrix poles have relied on curve fitting techniques. It is unknown weather these numerical methods necessarily preserve certain underlying physics properties of the standard R-matrix cross section model (such as unitarity). The direct conversion studied here aim to preserve such properties. This knowledge is of interest for future work into the generation of resonance parameter sensitivities.

CLUTCH↗

DOE OSTI2025

SCM overview & the EBR-II shutdown heat removal tests validation.

Pronghorn is an engineering-scale, coarse-mesh, thermal-hydraulics tool for supporting reactor-core simulations of advanced nuclear reactors. Most of the current efforts in Pronghorn have been devoted in developing porous finite-volume capabilities and adapting closure correlations for coarse-mesh thermal-hydraulics modeling. However, for liquid-metal reactors (LMRs) with wire-wrapped fuel pin assemblies, a pin-level thermal-hydraulic resolution is required for most safety case studies (pin rupture, channel blockage, etc.). For this purpose, a new Subchannel application is developed in MOOSE, which affords the required flow field resolution, while still preserving an engineering-scale approach. This new solver can be natively coupled to Pronghorn and other MOOSE objects to enable full-core, multi-physics, multi-scale engineering studies. This presentation presents the main features of the SCM code and demonstrates a validation case based on the EBR-II SHRT tests.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2022

Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest.We conduct the evaluations on two climate use cases – one targeting small-scale, node features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.

Gong, Qian↗

NASA NTRS1983

Structure and other properties of Jupiter's distant magnetotail

Analyses of data from Voyager 2 experiments provide evidence for, and characteristics of, a Jovian magnetotail extending at least to 9,000 Jovian radii from the planet. During approximately (25 day) periodic sightings of the tail, the magnetic field tended to point radially towards or away from Jupiter, indicating preservation to large distances of the bipolar, lobe like structure observed near the planet. This periodicity, along with various properties of the solar wind at this time, indicates that the tail is apparently influenced by recurrent solar wind features. Anomalous magnetic fields, not aligned with the nominal tail axis, also exist within the tail, especially in the low density, central (core) region, indicating some complexity of internal structure.

Lepping, R. P.↗

NASA NTRS1983

Structure and other properties of Jupiter's distant magnetotail

Lepping, R. P.↗

NASA NTRS1985

Scientific objectives for a 1996 Mars Sample Return Mission

The Mars Sample Return Mission, designed to return a variety of surface and subsurface samples as well as atmospheric samples, is described. Primary information about the planet is essential to understanding its place in the evolution of the solar system. The most accurate landing techniques will be used to place the lander near geologically interesting features. A capable rover will be an essential element of the sample collection strategy to maximize the diversity of the samples. The sample collection and return systems will keep the samples at Mars ambient conditions or colder to preserve the abundances and distribution of volatile components. Planetary quarantine is an important consideration for both the Mars lander and the earth return vehicle. Quarantine procedures must be consistent with the primary objectives of the mission and must not compromise the investigations of the returned samples.

Blanchard, D. P.↗

DOE OSTI2023

Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti’s Theorem for Markov Chains

Conformal prediction is a widely used method to quantify uncertainty in settings where the data is independent and identically distributed (IID), or more generally, exchangeable. Conformal prediction takes in a pre-trained classifier and a calibration dataset as inputs, and returns a function which maps feature vectors to subsets of classes. The output of the returned function for a new feature vector is guaranteed to contain the true class with a pre-specified confidence. Despite its success and usefulness in IID settings, extending conformal prediction to non-exchangeable (e.g., Markovian) data in a manner that provably preserves all desirable theoretical properties has largely remained an open problem. As a solution, we extend conformal prediction to the setting of a Hidden Markov Model (HMM) with unknown parameters. The key idea behind the proposed method is to partition the non-exchangeable Markovian data from the HMM into exchangeable blocks by exploiting the de Finetti’s Theorem for Markov Chains discovered by Diaconis and Freedman (1980). The permutations of the exchangeable blocks are then viewed as randomizations of the observed Markovian data from the HMM. The proposed method provably retains all desirable theoretical guarantees offered by the classical conformal prediction framework and is general enough to be useful in many sequential prediction problems.

Nettasinghe, Don Buddhika Wijayantha↗