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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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DOE OSTI2020

High-Resolution Laser-Induced Graphene. Flexible Electronics beyond the Visible Limit

Laser-induced graphene (LIG) is a multifunctional graphene foam that is commonly direct-written with an infrared laser into a carbon-based precursor material. Here, a visible 405 nm laser is used to directly convert polyimide into LIG. This enabled the formation of LIG with a spatial resolution of ~12 μm and a thickness of <5 μm. The spatial resolution enabled by the relatively smaller focused spot size of the 405 nm laser represents a >60% reduction in LIG feature sizes reported in prior publications. This process occurs in situ in an SEM chamber, thus allowing direct observation of LIG formation. The reduced size of the LIG features enables the direct-write formation of flexible electronics that are not visible to the unaided eye. A humidity sensor is demonstrated which could detect human breath with a response time of 250 ms. With the growing interest in LIG for flexible electronics and sensors, finer features can greatly expand its utility.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Diverse ecophysiological adaptations of subsurface Thaumarchaeota in floodplain sediments revealed through genome-resolved metagenomics

Abstract The terrestrial subsurface microbiome contains vastly underexplored phylogenetic diversity and metabolic novelty, with critical implications for global biogeochemical cycling. Among the key microbial inhabitants of subsurface soils and sediments are Thaumarchaeota, an archaeal phylum that encompasses ammonia-oxidizing archaea (AOA) as well as non-ammonia-oxidizing basal lineages. Thaumarchaeal ecology in terrestrial systems has been extensively characterized, particularly in the case of AOA. However, there is little knowledge on the diversity and ecophysiology of Thaumarchaeota in deeper soils, as most lineages, particularly basal groups, remain uncultivated and underexplored. Here we use genome-resolved metagenomics to examine the phylogenetic and metabolic diversity of Thaumarchaeota along a 234 cm depth profile of hydrologically variable riparian floodplain sediments in the Wind River Basin near Riverton, Wyoming. Phylogenomic analysis of the metagenome-assembled genomes (MAGs) indicates a shift in AOA population structure from the dominance of the terrestrial Nitrososphaerales lineage in the well-drained top ~100 cm of the profile to the typically marine Nitrosopumilales in deeper, moister, more energy-limited sediment layers. We also describe two deeply rooting non-AOA MAGs with numerous unexpected metabolic features, including the reductive acetyl-CoA (Wood-Ljungdahl) pathway, tetrathionate respiration, a form III RuBisCO, and the potential for extracellular electron transfer. These MAGs also harbor tungsten-containing aldehyde:ferredoxin oxidoreductase, group 4f [NiFe]-hydrogenases and a canonical heme catalase, typically not found in Thaumarchaeota. Our results suggest that hydrological variables, particularly proximity to the water table, impart a strong control on the ecophysiology of Thaumarchaeota in alluvial sediments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Improving galaxy clustering measurements with deep learning: analysis of the DECaLS DR7 data

ABSTRACT Robust measurements of cosmological parameters from galaxy surveys rely on our understanding of systematic effects that impact the observed galaxy density field. In this paper, we present, validate, and implement the idea of adopting the systematics mitigation method of artificial neural networks for modelling the relationship between the target galaxy density field and various observational realities including but not limited to Galactic extinction, seeing, and stellar density. Our method by construction allows a wide class of models and alleviates overtraining by performing k-fold cross-validation and dimensionality reduction via backward feature elimination. By permuting the choice of the training, validation, and test sets, we construct a selection mask for the entire footprint. We apply our method on the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Emission Line Galaxies (ELGs) selection from the Dark Energy Camera Legacy Survey (DECaLS) Data Release 7 and show that the spurious large-scale contamination due to imaging systematics can be significantly reduced by up-weighting the observed galaxy density using the selection mask from the neural network and that our method is more effective than the conventional linear and quadratic polynomial functions. We perform extensive analyses on simulated mock data sets with and without systematic effects. Our analyses indicate that our methodology is more robust to overfitting compared to the conventional methods. This method can be utilized in the catalogue generation of future spectroscopic galaxy surveys such as eBOSS and Dark Energy Spectroscopic Instrument (DESI) to better mitigate observational systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Design Advancement of an Indoor Soil Deposition Chamber: A Road to Standardization

An indoor soil deposition chamber has been designed and constructed at the Arizona State University Photovoltaic Reliability Lab (ASU-PRL) to simulate photovoltaic (PV) module soiling in the field. This paper discusses the next set of revisions to the design, which are organized into three categories: design improvements, cost reduction, and new features. The design process was carried out with the intention of working toward the development of a national or international soiling standard. The improvements made to the chamber are described in detail to provide a guide for other laboratories or research facilities who wish to study photovoltaic (PV) soiling.

14 SOLAR ENERGY↗

NASA NTRS1979

Preliminary QCGAT program test results

The paper presents the NASA Lewis program to demonstrate that large engine technology can be applied to general aviation engines to reduce noise, emissions, and fuel consumption. After a Phase I study, two contractors, Garrett AiResearch and AVCO-Lycoming, were selected to design, manufacture, assemble, test, and deliver their Quiet, Clean, General Aviation Turbofan (QCGAT) engines to NASA. Noise, emission, and performance goals and how well they were met are discussed. Noise goals involve take off noise 3.5 n. mi. from runway threshold, sideline noise at .25 n mi. and approach noise 1 n mi. from the runway at an altitude of 370 ft. The AiResearch engines power a stretched Learjet 35 and the Lycoming a specially conceived Beech executive jet, resulting in differing power goals. Thus the thrust goal for the Lycoming was 1622 lb. while the AiResearch goal was 3937 lb. Cruise thrust goals were 485 lb. at Mach 0.6 at 25,000 ft. and 903 lb. at Mach 0.8 at 40,000 ft. respectively. The design of both engines, based on existing cores, is studied, noting such special QCGAT features as new reduction gears, combustor and power turbine. Test results are given, indicating that while the goals for noise and thrust were met those for emissions were only partially met.

Koenig, R. W.↗

NASA NTRS1979

A small, passively operated hydrogen maser

The paper describes a compact passive hydrogen maser with unique features including a reduction in size. It uses a passive operation mode, permitting the use of a small microwave TE(011) cavity dielectrically loaded by a low loss alumina. The Teflon coated quartz bulb common in other masers has been replaced by a Teflon coating on the inside wall of the cavity producing a simpler designed and a more rugged H-maser package. The cavity and the attached endcaps comprise the vacuum envelope, allowing the use of a single vacuum system. The dimensional stability of the ceramic cavity under barometric changes is sufficiently within the range of the electronic cavity servo so that a second vacuum system is not required. For temperature control, a single oven is located in the magnetic shield nest.

Howe, D. A.↗

NASA NTRS1983

The properties of coronal voids

Skylab coronagraph observations of the outer solar corona have revealed dark, ray-like structures whose identification as a true coronal phenomenon rather than a subtle photographic effect is presently undertaken. Photometric analysis indicates that these features represent a reduction of 5% in coronal radiance, and the use of a previously developed model of the coronal electron component allows the specification of void electron densities over a 2.5-4.5 solar radius range. Projection of the phenomena onto synoptic surface maps indicates a close relationship with filaments and neutral lines, and a potentially significant temporal correlation between void formation and the formation of the underlying prominence is noted.

Macqueen, R. M.↗

NASA NTRS1986

Optical processing and Space Station automation

Optical information processing research aimed at Space Station automation applications is reviewed. The emphasis of the NASA Ames Research Center program is on intelligent optical pattern recognition and optical control processing. Attention is given to the primary functions of an overall scene understanding system: distortion-invariant optical feature generation, dimensionality reduction, object classification, and contextual information processing. A method of using synthetic discriminant functions to facilitate learning in a high-speed optical correlator is described. A discussion is presented of candidate analog and digital architectures for the optical implementation of state-estimation algorithms needed for the control of high-dimension dynamic systems. The multivariate system chosen for the optical control technology demonstration - a segmented, adaptive mirror and interferometrically based wavefront sensor - is also described.

Ennis, D. J.↗

DOE OSTI2025

Kernel Manifolds: Nonlinear‐Augmentation Dimensionality Reduction Using Reproducing Kernel Hilbert Spaces

This paper generalizes recent advances on quadratic manifold (QM) dimensionality reduction by developing kernel methods-based nonlinear-augmentation dimensionality reduction. QMs, and more generally feature map-based nonlinear corrections, augment linear dimensionality reduction with a nonlinear correction term in the reconstruction map to overcome approximation accuracy limitations of purely linear approaches. While feature map-based approaches typically learn a least squares optimal polynomial correction term, we generalize this approach by learning an optimal nonlinear correction from a user-defined reproducing kernel Hilbert space. Our approach allows one to impose arbitrary nonlinear structure on the correction term, including polynomial structure, and includes feature map and radial basis function-based corrections as special cases. Furthermore, our method has relatively low training cost and has monotonically decreasing error as the latent space dimension increases. In conclusion, we compare our approach to proper orthogonal decomposition and several recent QM approaches on data from several example problems.

kernel methods↗

DOE OSTI2025

Ranking Biological Features in Soil-Based Microbial Multi-Omics Data with Integration Modeling

Distinguishing the most important features (e.g. proteins, metabolites, etc.) per group (e.g. control and treatment) is a critical challenge in feature-rich multi-omics experiments, especially in soil data. Traditional feature identification and ranking approaches, such as differential expression, are based on single omics and thus not directly translatable to multi-omics experiments. Here, 5 multi-omics integration models (DIABLO, JACA, MOFA, MultiMLP, and SLIDE) that were not explicitly built for soil data applications were tested using a soil-based multi-omics experiment. The data were obtained from an experimental setup of an autoclaved soil system inoculated with 8 bacteria and using chitin as the carbon source and including samples collected at 0- (control), 4-, 8-, and 12-weeks post-inoculation. The omics data included metaproteomics, 16S rRNA sequencing, and LC-MS/MS metabolomics (in positive and negative mode). Each multi-omics integration model was implemented, and top features were compared to differential univariate statistics per omic type, demonstrating that integration approaches cut the potential number of top features from 2957 identified by differential statistics to 13-224 (a 99.6% to 92.4% reduction). Interestingly, most top features across integration models were not shared; though, scaling and averaging ranks across models shared similar patterns. This work highlights the usefulness of multi-omics integration models in soil-based microbial studies and the power of using multiple integration models together to interpret results.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Reliable vision-guided grasping

Automated assembly of truss structures in space requires vision-guided servoing for grasping a strut when its position and orientation are uncertain. This paper presents a methodology for efficient and robust vision-guided robot grasping alignment. The vision-guided grasping problem is related to vision-guided 'docking' problems. It differs from other hand-in-eye visual servoing problems, such as tracking, in that the distance from the target is a relevant servo parameter. The methodology described in this paper is hierarchy of levels in which the vision/robot interface is decreasingly 'intelligent,' and increasingly fast. Speed is achieved primarily by information reduction. This reduction exploits the use of region-of-interest windows in the image plane and feature motion prediction. These reductions invariably require stringent assumptions about the image. Therefore, at a higher level, these assumptions are verified using slower, more reliable methods. This hierarchy provides for robust error recovery in that when a lower-level routine fails, the next-higher routine will be called and so on. A working system is described which visually aligns a robot to grasp a cylindrical strut. The system uses a single camera mounted on the end effector of a robot and requires only crude calibration parameters. The grasping procedure is fast and reliable, with a multi-level error recovery system.

Nicewarner, Keith E.↗

NASA NTRS1992

Reliable vision-guided grasping

Automated assembly of truss structures in space requires vision-guided servoing for grasping a strut when its position and orientation are uncertain. This paper presents a methodology for efficient and robust vision-guided robot grasping alignment. The vision-guided grasping problem is related to vision-guided 'docking' problems. It differs from other hand-in-eye visual servoing problems such as tracking in that the distance from the target is a relevant servo parameter. The methodology described in this paper is a hierarchy of levels in which the vision/robot interface is decreasingly 'intelligent', and increasingly fast. Speed is achieved primarily by information reduction. This reduction exploits the use of region-of-interest windows in the image plane and feature motion prediction. These reductions invariably require stringent assumptions about the image. Therefore, at a higher level, these assumptions are verified using slower, more reliable methods. This hierarchy provides for robust error recovery in that when a lower-level routine fails, the next-higher routine will be called and so on. A working system is described which visually aligns a robot to grasp a cylindrical strut. The system uses a single camera mounted on the end effector of a robot and requires only crude calibration parameters. The grasping procedure is fast and reliable, with a multi-level error recovery system.

Nicewarner, Keith E.↗

DOE OSTI2023

Advanced Modeling and Simulation to Characterize Advanced Boiling Water Reactor Source Terms to Support a Regulatory Approval Pathway for Right-Sized Emergency Planning Zone. Advanced Boiling Water Reactor (A-BWR) Project Phase 2

The United States Department of Energy (US DOE) is currently supporting the development of various small modular reactor (SMR), microreactor and advanced reactor designs. These reactors have improved safety features as compared to conventional Large Light Water Reactors (LLWRs), which include features that improve potential reduction of radiological source terms in the event of design and beyond-design basis accidents. Specifically, some reactors feature a relatively smaller containment volume with respect to the available surface area for fission product deposition; these include Integrated Pressurized Water Reactors (iPWRs), such as the NuScale SMR and SMR-type Boiling Water Reactors (BWRs) such as General Electric-Hitachi’s BWRX-300 design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1980

Propulsion Study for Small Transport Aircraft Technology (STAT)

Propulsion requirements were determined for 0.5 and 0.7 Mach aircraft. Sensitivity studies were conducted on both these aircraft to determine parametrically the influence of propulsion characteristics on aircraft size and direct operating cost (DOC). Candidate technology elements and design features were identified and parametric studies conducted to select the STAT advanced engine cycle. Trade off studies were conducted to determine those advanced technologies and design features that would offer a reduction in DOC for operation of the STAT engines. These features were incorporated in the two STAT engines. A benefit assessment was conducted comparing the STAT engines to current technology engines of the same power and to 1985 derivatives of the current technology engines. Research and development programs were recommended as part of an overall technology development plan to ensure that full commercial development of the STAT engines could be initiated in 1988.

Gill, J. C.↗

NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

Rotorcraft operating in high-threat environments fly close to the surface of the earth to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by the enemy. Two basic requirements for obstacle avoidance are detection and range estimation of the object from the current rotorcraft position. There are many approaches to the estimation of range using a sequence of images. The approach used in this analysis differes from previous methods in two significant ways: an attempt is not made to estimate the rotorcraft's motion from the images; and the interest lies in recursive algorithms. The rotorcraft parameters are assumed to be computed using an onboard inertial navigation system. Given a sequence of images, using image-object differential equations, a Kalman filter (Sridhar and Phatak, 1988) can be used to estimate both the relative coordinates and the earth coordinates of the objects on the ground. The Kalman filter can also be used in a predictive mode to track features in the images, leading to a significant reduction of search effort in the feature extraction step of the algorithm. The purpose is to summarize early results obtained in extending the Kalman filter for use with actual image sequences. The experience gained from the application of this algorithm to real images is very valuable and is a necessary step before proceeding to the estimation of range during low-altitude curvilinear flight. A simple recursive method is presented to estimate range to objects using a sequence of images. The method produces good range estimates using real images in a laboratory set up and needs to be evaluated further using several different image sequences to test its robustness. The feature generation part of the algorithm requires further refinement on the strategies to limit the number of features (Sridhar and Phatak, 1989). The extension of the work reported here to curvilinear flight may require the use of the extended Kalman filter.

Sridhar, Banavar↗

NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

The ability to detect and locate obstacles using on-board sensors and modify the nominal trajectory is necessary for safe landing of an autonomous lander on Mars. This paper examines some of the issues in the location of objects using a sequence of images from a passive sensor, and describes a Kalman filter approach to improve the range estimation to obstacles. The filter is also used to track features in the images leading to a significant reduction of search effort in the feature extraction step of the algorithm. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. An experiment is designed to acquire a sequence of images along with sensor motion parameters and the range estimation results using this imagery are presented.

Sridhar, B.↗

NASA NTRS1991

Passive range estimation for rotorcraft low-altitude flight

The automation of rotorcraft low-altitude flight presents challenging problems in control, computer vision and image understanding. A critical element in this problem is the ability to detect and locate obstacles, using on-board sensors, and modify the nominal trajectory. This requirement is also necessary for the safe landing of an autonomous lander on Mars. This paper examines some of the issues in the location of objects using a sequence of images from a passive sensor, and describes a Kalman filter approach to estimate the range to obstacles. The Kalman filter is also used to track features in the images leading to a significant reduction of search effort in the feature extraction step of the algorithm. The method can compute range for both straight line and curvilinear motion of the sensor. A laboratory experiment was designed to acquire a sequence of images along with sensor motion parameters under conditions similar to helicopter flight. Range estimation results using this imagery are presented.

Sridhar, B.↗

NASA NTRS1993

Passive range estimation for rotorcraft low-altitude flight

Sridhar, B.↗