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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Regression Analysis of Top of Descent Location for Idle-thrust Descents

In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. The independent variables cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also recorded or computed post-operations. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajec- tory parameters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowl- edge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace. In particular, a model for TOD location that is linear in the independent variables would enable decision support tool human-machine interfaces for which a kinetic approach would be computationally too slow.

trajectory prediction↗
NASA NTRS2015

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team

A team is defined as: "two or more individuals who interact socially and adaptively, have shared or common goals, and hold meaningful task interdependences; it is hierarchically structured and has a limited life span; in it expertise and roles are distributed; and it is embedded within an organization/environmental context that influences and is influenced by ongoing processes and performance outcomes" (Salas, Stagl, Burke, & Goodwin, 2007, p. 189). From the NASA perspective, a team is commonly understood to be a collection of individuals that is assigned to support and achieve a particular mission. Thus, depending on context, this definition can encompass both the spaceflight crew and the individuals and teams in the larger multi-team system who are assigned to support that crew during a mission. The Team Risk outcomes of interest are predominantly performance related, with a secondary emphasis on long-term health; this is somewhat unique in the NASA HRP in that most Risk areas are medically related and primarily focused on long-term health consequences. In many operational environments (e.g., aviation), performance is assessed as the avoidance of errors. However, the research on performance errors is ambiguous. It implies that actions may be dichotomized into "correct" or "incorrect" responses, where incorrect responses or errors are always undesirable. Researchers have argued that this dichotomy is a harmful oversimplification, and it would be more productive to focus on the variability of human performance and how organizations can manage that variability (Hollnagel, Woods, & Leveson, 2006) (Category III1). Two problems occur when focusing on performance errors: 1) the errors are infrequent and, therefore, difficult to observe and record; and 2) the errors do not directly correspond to failure. Research reveals that humans are fairly adept at correcting or compensating for performance errors before such errors result in recognizable or recordable failures. Astronauts are notably adept high performers. Most failures are recorded only when multiple, small errors occur and humans are unable to recognize and correct or compensate for these errors in time to prevent a failure (Dismukes, Berman, Loukopoulos, 2007) (Category III). More commonly, observers record variability in levels of performance. Some teams commit no observable errors but fail to achieve performance objectives or perform only adequately, while other teams commit some errors but perform spectacularly. Successful performance, therefore, cannot be viewed as simply the absence of errors or the avoidance of failure Johnson Space Center (JSC) Joint Leadership Team, 2008). While failure is commonly attributed to making a major error, focusing solely on the elimination of error(s) does not significantly reduce the risk of failure. Failure may also occur when performance is simply insufficient or an effort is incapable of adjusting sufficiently to a contextual change (e.g., changing levels of autonomy).

Landon, Lauren Blackwell↗
NASA NTRS2018

Satellite Remote Sensing: Ocean Color

Satellite ocean color instruments routinely provide global, synoptic views of the Earth's marine biosphere. These spaceborne radiometers measure light exiting the top of the atmosphere at discrete wavelengths in the ultraviolet to shortwave infrared region of the spectrum. This includes measurements of the color of the ocean - information used to infer the contents of the sunlit upper ocean, such as concentrations of phytoplankton, suspended sediments, and dissolved organic carbon. Continuous marine biological, ecological, and biogeochemical data records from satellite ocean color instruments now span over twenty years. This time-series not only supports Earth system and climate research, but also ecosystem and watershed management activities, including detection of nuisance and harmful algal blooms.

Biosphere↗
NASA NTRSDate not supplied

CropManage Application for Vineyard Irrigation Decision-Support

CropManage is a free web-application developed by U.C. Cooperative Extension to support evapotranspiration based irrigation scheduling and nutrient management for major specialty crops. Prescribed phenology curves are used to develop daily estimates of canopy cover within a given field, based on days since planting (annual crops) or budbreak (trees, vines). These curves are modulated by a MaxCan parameter representing seasonal maximum canopy cover. Crop development observations can be used to adjust for such factors as weather anomalies or non-standard agronomic practice, as needed. Canopy cover is converted to crop coefficient and combined with reference evapotranspiration to derive daily water consumption. Guidance on crop water requirement is then conveyed to users in terms of system runtime issued on-demand for a given date, largely based on total evapotranspiration since last irrigation event. In this study, CropManage was adapted to vineyards by adding modules accounting for early-season soil moisture depletion and cover crop presence. A crop stress parameter was added to accommodate deficit irrigation practice, allowing the user to specify percentage departure from full water requirement along with start/stop dates. An initial verification exercise was performed on three winegrape vineyards located in California’s Central Coast (2020), North Coast (2020) and Central Valley (2019). Daily crop evapotranspiration was monitored by eddy-covariance fluxtowers. MaxCan was measured by ground and satellite observation. Stress regime was specified by grower practice where available, otherwise stress levels were inferred from applied water records. Mean absolute error and mean bias error of modeled cumulative evapotranspiration were computed with respect to the eddy covariance measurements collected throughout the growing season. Results indicate the modified CropManage water management module performs reasonably well for winegrape. Additional effort is planned to modify the nutrient module for vineyard use.

CropManage↗
NASA NTRS2003

NETMARK: A Schema-less Extension for Relational Databases for Managing Semi-structured Data Dynamically

Object-Relational database management system is an integrated hybrid cooperative approach to combine the best practices of both the relational model utilizing SQL queries and the object-oriented, semantic paradigm for supporting complex data creation. In this paper, a highly scalable, information on demand database framework, called NETMARK, is introduced. NETMARK takes advantages of the Oracle 8i object-relational database using physical addresses data types for very efficient keyword search of records spanning across both context and content. NETMARK was originally developed in early 2000 as a research and development prototype to solve the vast amounts of unstructured and semi-structured documents existing within NASA enterprises. Today, NETMARK is a flexible, high-throughput open database framework for managing, storing, and searching unstructured or semi-structured arbitrary hierarchal models, such as XML and HTML.

Maluf, David A.↗
NASA NTRS2002

Continuous Risk Management

Risk identification is an ongoing activity that takes place during the routine project work flow. Project activities such as programmatic and technical meetings, telecons, reviews, and other forms of communication often bring to light project risks. When this occurs, we record and analyze the risk on a Risk Information Sheet. This process helps the project team identify and cope with project risks throughout the life of the project.

Sabelhaus, Phil↗
NASA NTRSDate not supplied

Overview of Model-Based Systems Engineering Efforts to Evolve the Airspace Research Roadmap

NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject is conducting research that evolves UAM airspace towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution requires a plan to effectively organize, integrate, and communicate NASA’s research and development. The planning tool, called the UAM airspace research roadmap, or just roadmap, is key to the execution of NASA’s UAM airspace research over the next ten years. Implemented through Model-Based Systems Engineering (MBSE) methodology, the roadmap will help to prioritize and coordinate research efforts, and to integrate results that build towards NASA’s research goals of evolving UAM airspace for integration of UAM operations into the National Airspace System (NAS). This paper presents an overview of on-going MBSE efforts to meet these overarching goals. Note: Included mp4 video of presentation included in record, runtime 9 mins 57 secs.

Model-Based Systems Engineering↗
DOE OSTI2024

Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation

The widespread application of genetically modified microorganisms (GMMs) across diverse sectors underscores the pressing need for robust strategies to mitigate the risks associated with their potential uncontrolled escape. This study merges computational modeling with CRISPR interference (CRISPRi) to refine GMM metabolic robustness. Utilizing ensemble modeling, we achieved high-throughput in silico screening for enzymatic targets susceptible to expression alterations. Translating these insights, we developed functional CRISPRi, boosting fitness control via multiplexed gene knockdown. Our method, enhanced by an insulator-improved gRNA structure and an off-switch circuit controlling a compact Cas12m, resulted in rationally engineered strains with escape frequencies below National Institutes of Health standards. The effectiveness of this approach was confirmed under various conditions, showcasing its ability for secure GMM management. This research underscores the resilience of microbial metabolism, strategically modifying key nodes to halt growth without provoking significant resistance, thereby enabling more reliable and precise GMM control. A record of this paper's transparent peer review process is included in the supplemental information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Inertia Estimation Under High Penetration of Inverter-based Resources

Many types of renewable energy sources, especially solar and wind generation, are connected to the electric grid through power-electronic-based interfaces (inverters). These inverter-based resources (IBRs) are mechanically decoupled from the grid, which reduces system inertia and thus may compromise its stability and reliability. In this study, we examine the impact of high penetration of IBRs on the power grid’s inertia. To achieve this, we intentionally introduce disturbances into a simulation case study, such as a step load change, to observe and record the system’s frequency responses. This study offers a nuanced understanding of how the integration of IBRs affects grid stability, and it provides essential guidance for future grid management and resilience strategies.

Yadav, Ajay↗
NASA NTRS2001

Wireless Subsurface Microsensors for Health Monitoring of Thermal Protection Systems on Hypersonic Vehicles

Health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles in order to reduce life cycle costs, to increase safety margins, and to improve mission reliability. NASA Ames is leading the effort to develop inspection and health management technologies for thermal protection systems. This paper summarizes a joint project between NASA Ames and SRI International to develop 'SensorTags,' radio frequency identification devices coupled with event-recording sensors, that can be embedded in the thermal protection system to monitor temperature or other quantities of interest. Two prototype SensorTag designs containing thermal fuses to indicate a temperature overlimit are presented and discussed.

Milos, Frank S.↗
NASA NTRS2008

Dawn: Cooperation, not Control

On September 27, 2007, a Delta II rocket carrying the Dawn spacecraft lifted off from Kennedy Space Center. Part of NASAs Discovery program, the $370 million Dawn mission began its three-billion-mile voyage to the asteroid belt to study the asteroid Vesta and Ceres, a dwarf planet. The spacecraft is scheduled to reach Vesta in 2011. After spending nine months measuring the composition, shape, and topography of that body, it will travel a billion miles to carry out a similar analysis of Ceres in 2015. The Important Lessons: The demands of Dawn and other challenging missions have taught some important lessons for successful program and project management. These are the main ones: a) Program management, particularly of uncoupled and loosely coupled projects, should be more about enabling than controlling. You're working with motivated, high-performing teams and institutions with a track record of quality and success. Emphasize commander's intent over rudder control; let them know where you want to go and when you want to be there, then let them figure out how to get there. b) Open and honest discussion of issues is essential. People fill the void of the unknown with their worst fears. Get folks around the table and have open, honest, and frank dialogue. I've seldom seen this fail to get to the root of issues. c) You have to earn your seat at the table, proving that you are competent, trustworthy, and dedicated to the success of the mission. d) Know when to fold 'em. Your pride can get rolled up in making a milestone or launch date, but you have to make a judgment based on the realities of the situation and not wear down the team trying to meet an increasingly impossible deadline. e) The NASA governance model that gives a voice to the concerns of engineers and safety experts works-trust it and use it.

May, Todd↗
NASA NTRS2018

UTM UAS Serivce Supplier Development: Sprint 1 Toward Technical Capability Level 4

NASA's UAS Traffic Management (UTM) Project has been tasked with developing concepts and initial implementations for integrating and managing small unmanned aircraft systems (UAS) into the low altitude airspace. To accomplish this task, the Project planned a phased approach based on four Technical Capability Levels (TCLs). As of this writing, TCL4 is currently in development for a late Spring 2019 flight demonstration. This TCL is focused on operations in an urban environment and includes the handling of high density and large-scale off-nominal conditions, vehicle-to-vehicle communications, detect-and-avoid technologies, communication requirements, public safety operations, airspace restrictions, and other related goals. Through research and testing to date, NASA has developed an architecture for UTM that depends on commercial entities collaboratively providing services that are traditionally provided by the Air Navigation Service Provider(ANSP) in manned aviation. A key component of this architecture is the UAS Service Supplier (USS), which acts as a communications bridge between UAS operators and the ANSP when necessary. In addition, the collection of USSs form a USS Network to collaboratively manage the airspace through the sharing of data and the adherence to a standard or set of standards required to participate in this USS Network. This document provides a record of the first step in the development of interoperable USSs that will ultimately support TCL4 flight testing and formalization of the overall UTM concept. To develop these USSs and the underlying specifications for them, NASA has planned a series of "Sprints" to work with industry partners in implementing the features and proposed specifications for USSs to participate in TCL4. This report describes Sprint One. In this Sprint, the focus was on establishing a baseline for the Application Programming Interfaces (APIs) and their associated data models. In addition, the concept of UAS Volume Reservations (UVR) (areas that impose restrictions on sUAS that are allowed to operate) was tested. NASA provided the specifications and iterated on them with partners while implementers developed to those specifications. NASA then tested each partner's implementation to ensure compatibility with all other implementers. This process helped all stakeholders gain confidence that the foundation for future Sprints was solid.

UAS service supplier↗
NASA NTRS2018

UTM UAS Service Supplier Development: Sprint 2 Toward Technical Capability Level 4

NASA's UAS Traffic Management (UTM) Project has been tasked with developing concepts and initial implementations for integrating and managing small unmanned aircraft systems (UAS) into the low altitude airspace. To accomplish this task, the UTM Project planned a phased approach based on four Technical Capability Levels (TCLs). As of this writing, TCL4 is currently in development for a late Spring 2019 flight demonstration. This TCL is focused on operations in an urban environment and includes the handling of high density environments, large-scale off-nominal conditions, vehicle-to-vehicle communications, detect-and-avoid technologies, communication requirements, public safety operations, airspace restrictions, and other related goals. Through research and testing to date, NASA has developed an architecture for UTM that depends on commercial entities collaboratively providing services that are traditionally provided by the Air Navigation Service Provider (ANSP) in manned aviation. A key component of this architecture is the UAS Service Supplier (USS), which acts as a communications bridge between UAS operators and the ANSP when necessary. In addition, the collection of USSs form a USS Network to collaboratively manage the airspace through the sharing of data and the adherence to a standard or set of standards required to participate in this USS Network. This document provides a record of the second of four planned steps in the development of interoperable USSs that will ultimately support TCL4 flight testing and formalization of the overall UTM concept. To develop these USSs and their underlying specifications, NASA has planned a series of "Sprints" to work with industry partners in implementing the features and develop proposed specifications for USSs in order to to participate in TCL4. This report describes Sprint Two. In this Sprint, there was a major theme with four goals. The theme was the development and testing of a new USS discovery system, to better enable USSs to find and communicate with each other. The goals supporting this theme were: participants needed to implement and exercise the discovery service for USS-USS communications; USSs needed to demonstrate strategic deconfliction through operation sharing; the systems were to use discovery to aid in handling off-nominal operations; and finally, there was an investigation of an initial off-nominal reporting capability.

software engineering↗
DOE OSTI2025

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Spatialyze: A Geospatial Video Analytics System with Spatial-Aware Optimizations

Videos that are shot using commodity hardware such as phones and surveillance cameras record various metadata such as time and location. We encounter suchgeospatial videoson a daily basis and such videos have been growing in volume significantly. Yet, we do not have data management systems that allow users to interact with such data effectively. In this paper, we describe Spatialyze, a new framework for end-to-end querying of geospatial videos. Spatialyze comes with a domain-specific language where users can construct geospatial video analytic workflows using a 3-step, declarative,build-filter-observeparadigm. Internally, Spatialyze leverages the declarative nature of such workflows, the temporal-spatial metadata stored with videos, and physical behavior of real-world objects to optimize the execution of workflows. Our results using real-world videos and workflows show that Spatialyze can reduce execution time by up to 5.3×, while maintaining up to 97.1% accuracy compared to unoptimized execution.

Computer Science↗
NASA NTRS1998

The Coupling of Solution Chemistry to Plant Nutrient Demand in an on Demand Nutrient Delivery System

The goal of the proposal will be to determine the suitability of the DASI instrument in providing a signal that can be recognized and be utilized as an indicator of plant stress. The method to be utilized for evaluating stress is the presentation of an every increasing level of nutrient deficiency and salinity stress (addition of salt (NACl) or increasing concentration of balanced nutrient) while simultaneously recording spectral reflectance using the DASI instrument and monitoring the traditional processes of gas exchange and nutrient uptake parameters. In this manner, we will be able to directly compare the DASI measurements with known stresses as determined by the traditional gas exchange and nutrient uptake measures of stress. We anticipate that the DASI will provide a sensitive identifier of plant stress; recording signals of the resulting changes in plant metabolism in real time, far before any visible effects of stress could be observed. Thus, there is a potential for very early management intervention to correct a stress condition before damage could develop. The present response time for the observation of visual symptoms of plant stress is considerable and only provides an indication that a stress is present after it has been present for an extended period of time. Thus, the impact of a plant-based life support function will have already been significant. An additional benefit of this research to regenerative life support will be the characterization of a potential recovery scenario from various degrees of stress. The experimental approach to be employed includes the removal of the stress at various points in the stress gradient and the characterization of plant performance and reflectance spectra during recovery from various degrees of stress. Spectral reflectance imaging techniques have been developed and used to measure the biochemical composition of plants and relate these characteristics to the fluxes of biochemical elements within the ecosystem.

Savage, Wayne↗
NASA NTRS2021

Southern Idaho Health & Air Quality: Monitoring Atmospheric Mixing Heights Post-Wildfire Through the Use of NASA Earth Observations

Wildfire smoke has long-lasting impacts on public and environmental health. Currently, agencies that monitor smoke base their decisions on an analysis of how fires burn, the direction the smoke moves from the fire source, and unverified estimates of mixing height. Mixing heights describe the maximum altitude to which a smoke plume rises. Satellite imagery provides more continuous and accurate coverage of mixing heights than current in situ methods. Thus, the team developed a software tool that processes and extracts mixing height observations from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Vertical Feature Mask granules. The team partnered with the National Oceanic and Atmospheric Administration’s National Weather Service, the Bureau of Land Management’s National Interagency Fire Center, and the National Park Service’s Fire Management Program Center to analyze historic fire events in southern Idaho. To do so, they used Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to verify where a CALIPSO pass intersects thermal anomalies and smoke plumes. The software extracts features of relevance from the hdf file of each CALIPSO transect to locate layers of continuous aerosols. The maximum altitude at which the aerosol ends is recorded as the mixing height, along with a matching latitude and longitude. The satellite-derived values can be used to validate past mixing height predictions and evaluate the accuracy and systematic bias of different estimation methods. These results may allow agencies to make better comparisons and subsequent smoke pollution management, prevention, and public health decisions if the spatial and temporal differences between predictions and observations can be resolved.

DEVELOP Project Summary↗
NASA NTRS1982

District wide water resources investigation and management using LANDSAT data. Phase 1: Lake volume

A technique for estimating available water storage volume using LANDSAT data was developed and applied to Lake Washington and Lake Harris in central Florida. The technique can be applied two ways. First, where the historical stage records are available, the historical LANDSAT data can be used to establish the relationship between lake volume and lake stage. In the second case, where the historical stage records are not available, the historical LANDSAT data can be used to estimate the historical lake stage after the lake volume and stage information become available in the future.

Shih, S. F.↗