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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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NASA NTRS1974

The development and diversification of Precambrian life

The temporal relationships among various prominent events occurring in the evolution of life are considered. It is seen that the Precambrian encompasses an enormous segment of geologic time and includes more than 80% of the history of life on this planet. As a result of the studies of the past decade it appears that living systems were probably extant as early as 3300 m.y. ago. Photoautotrophs, apparently including blue-green algae, originated earlier than 3000 m.y. ago. Blue-green algae were the dominant components of earth's biota for the period extending from about 3000 to 1000 m.y. ago. The nucleated, eukaryotic cell type had become established at least as early as 900, and possibly prior to 1300 m.y. ago.

Schopf, J. W.↗

NASA NTRS1985

Study of application of space telescope science operations software for SIRTF use

The design and development of the Space Telescope Science Operations Ground System (ST SOGS) was evaluated to compile a history of lessons learned that would benefit NASA's Space Infrared Telescope Facility (SIRTF). Forty-nine specific recommendations resulted and were categorized as follows: (1) requirements: a discussion of the content, timeliness and proper allocation of the system and segment requirements and the resulting impact on SOGS development; (2) science instruments: a consideration of the impact of the Science Instrument design and data streams on SOGS software; and (3) contract phasing: an analysis of the impact of beginning the various ST program segments at different times. Approximately half of the software design and source code might be useable for SIRTF. Transportability of this software requires, at minimum, a compatible DEC VAX-based architecture and VMS operating system, system support software similar to that developed for SOGS, and continued evolution of the SIRTF operations concept and requirements such that they remain compatible with ST SOGS operation.

Dignam, F.↗

NASA NTRS1986

Analytic method for calculating properties of random walks on networks

A method for calculating the properties of discrete random walks on networks is presented. The method divides complex networks into simpler units whose contribution to the mean first-passage time is calculated. The simplified network is then further iterated. The method is demonstrated by calculating mean first-passage times on a segment, a segment with a single dangling bond, a segment with many dangling bonds, and a looplike structure. The results are analyzed and related to the applicability of the Einstein relation between conductance and diffusion.

Goldhirsch, I.↗

NASA NTRS1992

Structural aspects of the Araguainha impact structure (Brazil)

The results of two months of field studies carried out in 1988 are presented. During that time the northeast segment was mapped and the structural setting of the central area was studied in detail. In addition, the structure of outer zones of the Araguainha Crater was investigated along three radial sections.

Bischoff, L.↗

NASA NTRS2004

NASA Tech Briefs, November 2004

Topics include: Multifunction Imaging and Spectroscopic Instrument; Position-Finding Instrument Built Around a Magnetometer; Improved Measurement of Dispersion in an Optical Fiber; Probe for Sampling of Interstitial Fluid From Bone; Neuropsychological Testing of Astronauts; Method of Calibration for a Large Cathetometer System; Four-Channel PC/104 MIL-STD-1553 Circuit Board; Improved Method of Locating Defects in Wiring Insulation; Strobe Traffic Lights Warn of Approaching Emergency Vehicles; Improved Timing Scheme for Spaceborne Precipitation Radar; Concept for Multiple-Access Free-Space Laser Communications; Variable Shadow Screens for Imaging Optical Devices; Verifying Diagnostic Software; Initial Processing of Infrared Spectral Data; Activity-Centric Approach to Distributed Programming; Controlling Distributed Planning; New Material for Surface-Enhanced Raman Spectroscopy; Treated Carbon Nanofibers for Storing Energy in Aqueous KOH; Advanced Infant Car Seat Would Increase Highway Safety; Development of Biomorphic Flyers; Second-Generation Six-Limbed Experimental Robot; Miniature Linear Actuator for Small Spacecraft; Process for Making Single-Domain Magnetite Crystals; A New Process for Fabricating Random Silicon Nanotips; Resin-Transfer-Molding of a Tool Face; Improved Phase-Mask Fabrication of Fiber Bragg Gratings; Tool for Insertion of a Fiber-Optic Terminus in a Connector; Nanofluidic Size-Exclusion Chromatograph; Lightweight, Low-CTE Tubes Made From Biaxially Oriented LCPs; Using Redundancy To Reduce Errors in Magnetometer Readings; Compact Instrument for Measuring Profile of a Light Beam; Multilayer Dielectric Transmissive Optical Phase Modulator; Second-Generation Multi-Angle Imaging Spectroradiometer; Real-Time Adaptive Color Segmentation by Neural Networks; Research and Development in Optical Communications; Tests of Multibeam Scintillation Mitigation on Laser Uplinks; and Spaceborne Infrared Atmospheric Sounder.

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NASA NTRS2018

Subsetting Satellite Level 2 Data at NASA GES DISC

Working with Level 2 satellite swath data can prove challenging for many users. The variety of metadata, high resolution, and orbit-based nature of such data makes it difficult to acquire and manage. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has developed a general-purpose Level 2 Subsetting service that facilitates access to Level 2 data products. The Level 2 Subsetter enables users to sub-sample swath and gridded data in a variety of ways: by location (in a lat/lon box, within a circle of given radius, or at a specific point), by time (via swath segments or collections of granules), by any nonspatial dimension, or by selecting specific variables. The Level 2 Subsetting service also allows users to specify output data configuration and file format. In this presentation, we will detail and demonstrate the capabilities of this new service.

Huwe, Paul↗

NASA NTRS2020

Learning instrument invariant characteristics for generating high-resolution global coral reef maps

Coral reefs are one of the most biologically complex and diverse ecosystems within the shallow marine environment. Unfortunately, these underwater ecosystems are threatened by a number of anthropogenic challenges, including ocean acidification and warming, overfishing, and the continued increase of marine debris in oceans. This requires a comprehensive assessment of the world's coastal environments, including a quantitative analysis on the health and extent of coral reefs and other associated marine species, as a vital Earth Science measurement. However, limitations in observational and technological capabilities inhibit global sustained imaging of the marine environment. Harmonizing multimodal data sets acquired using different remote sensing instruments presents additional challenges, thereby limiting the availability of good quality labeled data for analysis. In this work, we develop a deep learning model for extracting domain invariant features from multimodal remote sensing imagery and creating high-resolution global maps of coral reefs by combining various sources of imagery and limited hand-labeled data available for certain regions. This framework allows us to generate, for the first time, coral reef segmentation maps at 2-meter resolution, which is a significant improvement over the kilometer-scale state-of-the-art maps. Additionally, this framework doubles accuracy and IoU metrics over baselines that do not account for domain invariance.

Domain Adaptation↗

NASA NTRS2018

Spacecraft Block Scheduling for NASA’s Deep Space Network

Currently, NASA’s Deep Space Network (DSN) is responsible for uplink to, downlink from, and/or tracking of dozens of missions for space agencies across the world. The DSN scheduling process starts about four months prior to the start of the schedule week, a process in which requirements are deﬁned and then the schedule is created, de-conﬂicted, and negotiated over the next 2–3 weeks with a team of mission representatives. Now scheduled for late 2019, Exploration Mission1 (EM-1) will deploy upwards of 12 SmallSat missions that will be served by the DSN. This will increase the DSN’s actively serviced spacecraft by up to 30%, further increasing the diﬃculty of meeting all mission needs via the over subscribed network. To mitigate their impact on DSN scheduling, a block scheduling process is proposed for scheduling the SmallSats. Block scheduling consists of aggregating spacecraft together into larger “pseudo-spacecraft” based on geometric alignment that then follow the same process as any other DSN mission to receive segments of track time. These tracks are then decomposed into tracks for individual users based on their speciﬁc requirements. This paper describes a full novel scheduling tool set for building candidate blocks, evaluating the eﬃcacy of these blocks, and optimal and suboptimal de-blocking schemes. To demonstrate these developed tools, results from three simulations are presented: a blocking example with lunar SmallSats, blocking potential in the greater DSN spacecraft catalog, and opportunistic multiple spacecraft per aperture potential for the DSN spacecraft catalog. Block scheduling has the potential to reduce overhead and scheduling resources for the EM-1 SmallSats while also providing them with a better means to meet their mission requirements.

Bilén, Sven G.↗

DOE OSTI2024

RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs

Abstract Flatbed scanners are commonly used for root analysis, but typical manual segmentation methods are time-consuming and prone to errors, especially in large-scale, multi-plant studies. Furthermore, the complex nature of root structures combined with noisy backgrounds in images complicates automated analysis. Addressing these challenges, this article introduces RhizoNet, a deep learning-based workflow to semantically segment plant root scans. Utilizing a sophisticated Residual U-Net architecture, RhizoNet enhances prediction accuracy and employs a convex hull operation for delineation of the primary root component. Its main objective is to accurately segment root biomass and monitor its growth over time. RhizoNet processes color scans of plants grown in a hydroponic system known as EcoFAB, subjected to specific nutritional treatments. The root detection model using RhizoNet demonstrates strong generalization in the validation tests of all experiments despite variable treatments. The main contributions are the standardization of root segmentation and phenotyping, systematic and accelerated analysis of thousands of images, significantly aiding in the precise assessment of root growth dynamics under varying plant conditions, and offering a path toward self-driving labs.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2021

The role of analysis error in the convergence of reanalysis production streams in MERRA-2

Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.

Amal El Akkraoui↗

NASA NTRS2001

Lidar Measurements of Wind, and Cloud & Aerosol Structures using HARLIE at the WVIOP, Sept/Oct 2000

The holographic scanning lidar HARLIE made continuous measurements of aerosol and cloud one-micron backscatter and derived the horizontal wind speed and direction at cloud height over the ARM (SGP) site during the water vapor campaign WVIOP, September 17 - October 6, 2000. Whenever possible, these measurements were compared with Loran-C winds as measured by the routine launches of Vaisala radiosonde balloons scheduled by the ARM project. Taken overall, the agreement between these two types of observation is excellent, which could be taken merely as a validation of the relatively new HARLIE technique. However, the detailed comparison for a given sonde launch clearly requires that, out of the HARLIE data which are taken all the time at all altitudes, one must select those segments that match the altitude-time trajectory of the sonde. Moreover, the conical HARLIE scan at a 45 deg. elevation angle covers a wide area that is more representative of the average wind conditions above the site than the isolated track of the sonde's ascent. We suggest that the HARLIE instrument offers a more general and improved representation of the horizontal wind profile whenever there is sufficient backscatter by clouds and aerosols for lidar operation. HARLIE is a rugged and compact lidar that operates from aircraft as well as from the ground and has been used in several meteorological campaigns. As a "direct detection" lidar, HARLIE does not require the complexity of a coherent detection system. The data reduction algorithms facilitate the rapid and accurate determination of wind speed and direction at all altitudes. Wind measurements and HARLIE performance data from WVIOP 2000 and other campaigns will be presented.

Schwemmer, Geary↗

NASA NTRS2014

A Concept of Operations for Far-Term Surface Trajectory-Based Operations (STBO)

The goal of this far-term STBO (Surface Trajectory-Based Operations) ConOps (Concept of Operations) is to increase the efficiency and predictability of airport surface operations, and reduce the environmental impact, by incorporating a time-based component to surface operations. In the far-term NextGen timeframe, airport surface operations will transition from current-day first-come, first-served operations, to strategically scheduled operations in which pilots are recruited as active participants in meeting the precise time-based goals of NextGen surface operations. The far-term STBO concept includes two-phases. Phase 1 introduces time-based traffic flow constraint points, which divide the taxi route into segments with an assigned Required Time of Arrival (RTA). This Phase 1 approach provides temporal certainty only near the traffic flow constraint points, but not in between. Minimal augmentations to the flight deck are required to support required time of arrival (RTA) management. Phase 2 further increases precision and efficiency by introducing full four-dimensional (4D) trajectories, with an x-y location for all times t. This phase assumes adoption of advanced flight deck equipage enabling higher temporal precision sufficient to support aircraft conformance to 4D trajectories. This allows more precision and less temporal uncertainty at all times along the route.

Surface Trajectory-Based Operations (STBO)↗

NASA NTRS1983

Flight assessment of a data-link-based navigation-guidance concept

With the proposed introduction of a data-link provision into the Air-Traffic-control (ATC) system, the capability will exist to supplement the ground-air, voice (radio) link with digital, data-link information. Additionally, ATC computers could provide, via the data link guidance and navigation information to the pilot which could then be presented in much the same manner as conventional navigation information. The primary objective of this study was to assess the feasibility and acceptability of using 4-sec and 12-sec information updating to drive conventional cockpit-navigation-instrument formats for path-tracking guidance. A flight test, consisting of 19 tracking tasks, was conducted and, through the use of pilot questionnaires and performance data, the following results were obtained. From a performance standpoint, the 4-sec and 12-sec updating led to a slight degradation in path-tracking performance, relative to continuous updating. From the pilot's viewpoint, the 12-sec data interval was suitable for long path segments (greater than 2 min of flight time), but it was difficult to use on shorter segments because of higher work load and insufficient stabilization time. Overall, it was determined that the utilization of noncontinuous data for navigation was both feasible and acceptable for the prescribed task.

Abbott, T. S.↗

DOE OSTI2026

Correlating and Simulating Socio-Demographically Driven Residential End-Use Activity Schedules

Incorporating socio-demographic and behavioral considerations into decision-support tools is crucial for identifying gaps and addressing consumer needs to ensure reliable and affordable energy solutions. In energy simulation models, the correlation between socio-demographics and time-use behavior is not well-captured. Thus, we developed a large-scale simulation workflow to generate schedules for 10 residential activities across 24 population segments defined by age, income, and employment status. Using pre-pandemic 2015-2019 American Time Use Survey (ATUS) data, we used ANOVA to confirm the correlation between demographic factors and time use. We explored three k-modes clustering methods-backward, forward, and a new hybrid approach-to delineate the occupancy patterns based on demographics. Using the probability of cluster membership for each population segment and a time inhomogeneous Markov chain to generate activity transition probabilities for each cluster, we simulated 50,000 schedules per segment and validated them against the ATUS data. The hybrid method produced the most socio-demographically differentiated clusters while demonstrating comparable performance to other approaches, with an overall root mean square error of 0.12 for both weekday and weekend schedules. Thus, the hybrid method, where each cluster is dominated by certain demographic segments and occupancy patterns, offers more modeling versatility in terms of scenario analysis. The new workflow improves the socio demographic differentiation of energy consumption by considering differences in time use. This approach enables future research on demographically segmented time of use (TOU) energy consumption, including impacts of TOU utility bills and rate analysis, long-run marginal emissions, and energy retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1997

Bayesian Blocks: A New Method to Analyze Photon Counting Data

A Bayesian analysis of photon-counting data leads to a new time-domain algorithm for detecting localized structures (bursts), revealing pulse shapes, and generally characterizing intensity variations. The raw counting data -- time-tag events (TTE), time-to-spill (TTS) data, or binned counts -- is converted to a maximum likelihood segmentation of the observation into time intervals during which the photon arrival rate is perceptibly constant -- i.e. has a fixed intensity without statistically significant variations. The resulting structures, Bayesian Blocks, can be thought of as bins with arbitrary spacing determined by the data. The method itself sets no lower limit to the time scale on which variability can be detected. We have applied the method to RXTE data on Cyg X-1, yielding information on this source's short-time-scale variability.

Scargle, Jeffrey D.↗

NASA NTRS1998

Spaceflight reduces somatic embryogenesis in orchardgrass (Poaceae)

Somatic embryos initiate and develop from single mesophyll cells in in vitro cultured leaf segments of orchard-grass (Dactylis glomerata L.). Segments were plated at time periods ranging from 21 to 0.9 d (21 h) prior to launch on an 11 d spaceflight (STS-64). Using a paired t-test, there was no significant difference in embryogenesis from preplating periods of 14 d and 21 d. However, embryogenesis was reduced by 70% in segments plated 21 h before launch and this treatment was significant at P=0.0001. The initial cell divisions leading to embryo formation would be taking place during flight in this treatment. A higher ratio of anticlinal:periclinal first cell divisions observed in the flight compared to the control tissue suggests that microgravity affects axis determination and embryo polarity at a very early stage. A similar reduction in zygotic embryogenesis would reduce seed formation and have important implications for long-term space flight or colonization where seeds would be needed either for direct consumption or to grow another generation of plants.

NASA Discipline Plant Biology↗

NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: An Application to XCO2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics – amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (2009–2012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.74–0.77 ppm for every 10∘ of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a south–north seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (∼19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (−9 d per 10∘ latitude for fall segments and 10 d per 10∘ latitude for rise segments) and suggest that a specific latitude (∼2∘ N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development.

Calle, Leonardo↗

NASA NTRS2019

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: an Application to Xco2 to Estimate Benchmarks and Assess Model Bias

segmentation algorithm↗