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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 NTRS2013

ISTP CDF Skeleton Editor

Basic Common Data Format (CDF) tools (e.g., cdfedit) provide no specific support for creating International Solar-Terrestrial Physics/Space Physics Data Facility (ISTP/SPDF) standard files. While it is possible for someone who is familiar with the ISTP/SPDF metadata guidelines to create compliant files using just the basic tools, the process is error-prone and unreasonable for someone without ISTP/SPDF expertise. The key problem is the lack of a tool with specific support for creating files that comply with the ISTP/SPDF guidelines. There are basic CDF tools such as cdfedit and skeletoncdf for creating CDF files, but these have no specific support for creating ISTP/ SPDF compliant files. The SPDF ISTP CDF skeleton editor is a cross-platform, Java-based GUI editor program that allows someone with only a basic understanding of the ISTP/SPDF guidelines to easily create compliant files. The editor is a simple graphical user interface (GUI) application for creating and editing ISTP/SPDF guideline-compliant skeleton CDF files. The SPDF ISTP CDF skeleton editor consists of the following components: A swing-based Java GUI program, JavaHelp-based manual/ tutorial, Image/Icon files, and HTML Web page for distribution. The editor is available as a traditional Java desktop application as well as a Java Network Launching Protocol (JNLP) application. Once started, it functions like a typical Java GUI file editor application for creating/editing application-unique files.

Chimiak, Reine↗

NASA NTRS2012

Life-Cycle Assessments of Selected NASA Ground-Based Test Facilities

In the past two years, two separate facility-specific life cycle assessments (LCAs) have been performed as summer student projects. The first project focused on 13 facilities managed by NASA s Aeronautics Test Program (ATP), an organization responsible for large, high-energy ground test facilities that accomplish the nation s most advanced aerospace research. A facility inventory was created for each facility, and the operational-phase carbon footprint and environmental impact were calculated. The largest impacts stemmed from electricity and natural gas used directly at the facility and to generate support processes such as compressed air and steam. However, in specialized facilities that use unique inputs like R-134a, R-14, jet fuels, or nitrogen gas, these sometimes had a considerable effect on the facility s overall environmental impact. The second LCA project was conducted on the NASA Ames Arc Jet Complex and also involved creating a facility inventory and calculating the carbon footprint and environmental impact. In addition, operational alternatives were analyzed for their effectiveness at reducing impact. Overall, the Arc Jet Complex impact is dominated by the natural-gas fired boiler producing steam on-site, but alternatives were provided that could reduce the impact of the boiler operation, some of which are already being implemented. The data and results provided by these LCA projects are beneficial to both the individual facilities and NASA as a whole; the results have already been used in a proposal to reduce carbon footprint at Ames Research Center. To help future life cycle projects, several lessons learned have been recommended as simple and effective infrastructure improvements to NASA, including better utility metering and data recording and standardization of modeling choices and methods. These studies also increased sensitivity to and appreciation for quantifying the impact of NASA s activities.

Sydnor, George Honeycutt↗

NASA NTRS2013

A Kinematic Calibration Process for Flight Robotic Arms

The Mars Science Laboratory (MSL) robotic arm is ten times more massive than any Mars robotic arm before it, yet with similar accuracy and repeatability positioning requirements. In order to assess and validate these requirements, a higher-fidelity model and calibration processes were needed. Kinematic calibration of robotic arms is a common and necessary process to ensure good positioning performance. Most methodologies assume a rigid arm, high-accuracy data collection, and some kind of optimization of kinematic parameters. A new detailed kinematic and deflection model of the MSL robotic arm was formulated in the design phase and used to update the initial positioning and orientation accuracy and repeatability requirements. This model included a higher-fidelity link stiffness matrix representation, as well as a link level thermal expansion model. In addition, it included an actuator backlash model. Analytical results highlighted the sensitivity of the arm accuracy to its joint initialization methodology. Because of this, a new technique for initializing the arm joint encoders through hardstop calibration was developed. This involved selecting arm configurations to use in Earth-based hardstop calibration that had corresponding configurations on Mars with the same joint torque to ensure repeatability in the different gravity environment. The process used to collect calibration data for the arm included the use of multiple weight stand-in turrets with enough metrology targets to reconstruct the full six-degree-of-freedom location of the rover and tool frames. The follow-on data processing of the metrology data utilized a standard differential formulation and linear parameter optimization technique.

Collins, Curtis L.↗

NASA NTRS2014

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.

Weather↗

NASA NTRS2017

Lighting Automation - Flying an Earthlike Habit Project

Our proposal will enable the development of automated spacecraft habitats for long duration missions. Majority of spacecraft lighting systems employ lamps or zone specific switches and dimmers. Automation is not in the "picture". If we are to build long duration environments, which provide earth-like habitats, minimize crew time, and optimize spacecraft power reserves, innovation in lighting automation is a must. To transform how spacecraft lighting environments are automated, we will provide performance data on a standard lighting communication protocol. We will investigate utilization and application of an industry accepted lighting control protocol, DMX512. We will demonstrate how lighting automation can conserve power, assist with lighting countermeasures, and utilize spatial body tracking. By using DMX512 we will prove the "wheel" does not need to be reinvented in terms of smart lighting and future spacecraft can use a standard lighting protocol to produce an effective, optimized and potentially earthlike habitat.

Falker, Jay↗

NASA NTRS2019

Citizen Science Twitter Data Management for Earth Science Applications

Social media data can provide useful real-time and historical information relating to the natural world, but managing this data poses challenges. Scientists at GES DISC are exploring the potential of Twitter data to augment precipitation data from the Global Precipitation Measurement (GPM) mission. However, the format of Twitter data is unconventional in the context of NASA data centers, resulting in frustration for scientists who need to work with the data. This study investigated procedures and standards needed to properly manage Twitter data to make them compatible with these data centers. After comparing databases, the study found that the MongoDB database was best suited for the storage of raw Twitter data due to its flexibility, ability to be accessed by multiple users, and querying functionality. The study used the Python package Zarr to transform processed Twitter data into a gridded format similar to that of satellite data. Each Tweet was mapped onto a time-space grid; each grid location contained information about Tweet attributes and precipitation. The study developed a pipeline for downloading, storing, and gridding Twitter data and transformed Twitter data into an understandable format for users of NASA satellite data.

Li, Rachel↗

NASA NTRS2020

The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere

We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is greatest where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data are available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small, as well as from a survey of kernels available in the literature that in general low-top radiative kernels underestimate the stratospheric temperature response. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).

radiative kernels↗

NASA NTRS2021

Evaluation of vicarious calibration for airborne sensors using RadCalNet

Vicarious calibration approaches using in-situ measurements are key techniques applied to on-orbit remote sensors. The in-situ measurements have advantages in terms of traceability and quantifiable accuracy that make them ideal for inter-consistency studies of on-orbit sensors. The Committee on Earth Observation Satellites Working Group on Calibration and Validation Infrared Visible Optical Sensors initiated the Radiometric Calibration Network (RadCalNet) to provide automated surface and top-of-atmosphere (TOA) reflectance data from multiple participating ground sites to the worldwide user community. RadCalNet standardizes protocols for collecting data, processes TOA reflectance, and provides International System of Units traceable uncertainty budgets for the five currently operating sites. RadCalNet data from the Railroad Valley Playa, Nevada, site was used to provide an SI-traceable, absolute radiometric calibration of the Enhanced MODIS Airborne Simulator as part of an overflight of opportunity during the FIREX-AQ campaign. The results shown here demonstrate the utility of RadCalNet data for absolute radiometric calibration of airborne imagers making flights of opportunity without the need for coordination with a field validation team.

Sensors↗

NASA NTRS2020

Dynamic Countermeasure Fabrics for Post-Spaceflight Orthostatic Intolerance

Aerospace orthostatic intolerance garments (OIG) have historically been pneumatic (e.g., NASA’s antigravity suit), an approach that inhibits mobility and requires connection to an air supply. Elastic compression garments, an alternative technology, are difficult to don/doff and cannot be worn in a noncompressive state, resulting in discomfort and usability challenges. This research evaluates a novel technology—contractile shape memory alloy (SMA) knitted actuators—that can enable low-profile, dynamic compression for an aerospace OIG. To characterize the functional capabilities of SMA knitted actuators, displacement control testing was conducted on 10 actuator samples with a range of geometric design parameters. Inactive (FI) and actuated forces (FA) were observed by repeatedly thermally cycling each sample at 0%, 15%, 30%, and 45% structural strain. Compression capabilities were approximated using medical compression hosiery standards and anthropometric data from a representative aerospace population (ANSUR 2012). Dynamic compression predictions reached 52 mmHg (single layer fabric) and 105 mmHg (double layer fabric) at the ankle. Low, inactive pressures (p, 20 mmHg) demonstrate that compression is controllable and can be dynamically increased upon actuation up to 33 mmHg in a single layer system and up to 67 mmHg in a double layer system. The results highlight the potential of SMA knitted actuators to enable low-profile, dynamic compression garments that can reach medically therapeutic pressures on an aerospace population to counteract OI symptoms. In addition to astronautic applications, this technology demonstrates widespread terrestrial medical and high-performance aircraft applicability.

Orthostatic intolerance↗

NASA NTRSDate not supplied

Space-to-Ground Optical Interface Verification for the Orion Artemis II Optical (O2O) Communications Demonstration

The Orion Artemis II Optical Communications (O2O) system will demonstrate the operational utility of laser communications for the first crewed Artemis mission scheduled to launch next year. O2O will provide an optical link with data rates up to 260 Mbps return from the moon and up to 20 Mbps forward to the moon. The optical link employs a Serially Concatenated Pulse Position Modulation (SCPPM) communications signal, compliant with the Consultative Committee for Space Data Systems (CCSDS) standard, and a modulated uplink beacon for acquisition and collaborative tracking. O2O employs optical ground stations located at the White Sands Complex (WSC) and Table Mountain Facility (TMF) to support the Earth end of the link. We describe interface testing performed between the space and ground terminals to verify the physical layer communication and beacon signals.

optical↗

NASA NTRS2024

High-Rate Delay Tolerant Networking (HDTN) Software Requirements Analysis

This document serves as a detailed analysis of the main networking protocols implemented by HDTN. Sources of the protocol specifications include Internet Engineering Task Force (IETF) Request for Comments (RFC) and Consultative Committee for Space Data Systems (CCSDS) standards. The focus of this report is to derive software requirements suitable for NASA Procedural Requirements 7150.2D Class B compliance, including requirements traceability and software verification and validation, from the source specifications. This analysis will be incorporated into the finalized HDTN Software Requirements Specification (SRS) but does not encompass the full scope of the HDTN SRS. Requirements in this document are considered draft. The complete requirements will include bundle application requirements, interface requirements, computer resource requirements, software quality factors, and additional requirements as determined by the project. This document is publicly released to the greater community to receive feedback and foster collaboration opportunities.

Rachel Dudukovich↗

NASA NTRSDate not supplied

Sizing and Performance Analysis of a MW-Class Electrified Aircraft Propulsion (Eap) System for A Parallel Hybrid Turboprop Concept

Aircraft electrification has emerged as a pivotal research and development focus in the 21st century, gaining international momentum as a strategic approach to curtail fuel consumption and emissions in the civil aviation sector. Under the Electrified Powertrain Flight Demonstration (EPFD) project, NASA and industry partners are raising the technical readiness, addressing integration challenges and gathering data for future standards and regulations for demonstrate Megawatt (MW) class Electrified Aircraft Propulsion (EAP) systems which can be utilized on regional turboprop or single aisle transports. With the rapid emergence of novel EAP concepts, risk reduction efforts are focused on developing the capabilities to evaluate the impacts of electrification at the conceptual design level where high variability in the EAP system architecture must be accounted for. This paper details an integrated, approach to parametric sizing of multi-MW EAP systems with the primary goal of assessing vehicle-level performance sensitivities to variations in electrical system component-level performance metrics. The focus of this work is to investigate the degree to which EAP component parameters such as specific power, efficiency, and energy density impact range and overall fuel savings.

EAP↗

NASA NTRSDate not supplied

Sizing and Performance Analysis of a MegaWatt-Class Electrified Aircraft Propulsion (EAP) System for a Parallel Hybrid Turboprop Concept

EAP↗

DOE OSTI2023

A hybrid method to evaluate the life cycle climate performance of heat pumps

Heat pumps have a significant impact on the climate, and numerous studies exist discussing the environmental impact of heat pumps quantitatively. Life Cycle Climate Performance (LCCP) is a widely accepted metric and can evaluate the carbon footprint of heat pumps from cradle to grave. LCCP calculation typically requires inputs like annual energy consumption, the material used, refrigerant type, and charge level, which are usually the intermediate or final results from heat pump simulation tools. Thus, a platform linking the heat pump simulation software, local weather conditions, and LCCP evaluation tool can simplify the heat pump design process, especially for complicated systems. This paper presents an LCCP evaluation tool accessing the outputs from the DOE Heat Pump Design Model and the building loads and temperature bin data from AHRI standard 210/240. As for case studies, this paper investigates the LCCP values and life cycle electricity costs (LCEC) of a given cooling-based heat pump with R410A in five typical US cities. In conclusion, this cooling-based heat pump has the highest LCCP value at Chicago and lowest LCCP value at Seattle. In contrast, the heat pump has the highest LCEC at Seattle and the lowest LCEC at Miami. As a future work, a more comprehensive carbon emission and cost analysis of heat pump systems will be conducted through all major cities around the world.

Shen, Bo↗

DOE OSTI2024

BETTER Together

The Standard Energy Efficiency Data (SEED) and Building Efficiency Targeting Tool for Energy Retrofits (BETTER) platforms are both developed by the Department of Energy and work better together. SEED is a database to manage building characteristics and performance data from a variety of sources. BETTER provides simple energy efficiency measure analyses based on high level data about the building or portfolio of buildings. A demonstration of each platform and their integration will be provided. The inputs for BETTER are building type, floor area, location, utility data, and whether PV shall be included in the analysis. The BETTER analysis can be manually set up through the web application or data can be uploaded with a BuildingSync XML file either directly or through the API. SEED can be the source of this data and the data can be sent to BETTER through the SEED application after the BETTER API token has been entered. The benefit of utilizing SEED is that it has connections to many other sources of data such as ENERGY STAR Portfolio Manager, Audit Template, and Salesforce. Therefore, it is likely that a user of SEED will already have the required inputs for BETTER in SEED already and can create BETTER analyses across their whole portfolio in a couple mouse clicks. This is a major time savings and enables decision makers an easy path to identify buildings that should undergo more detailed audits or retrofit pathways.

ASHRAE↗

DOE OSTI2026

Creating a Training Dataset for Semantic Segmentation of Canal Networks for Irrigation Modernization

Canal infrastructure has provided critical irrigation water to the western United States for over a century. To continue providing vital water resources to the semi-arid West, irrigation systems must undergo maintenance and modernization. Many canal companies are resource-constrained, and because funding opportunities often require detailed knowledge of existing infrastructure, they can struggle to secure financial capital. We address this problem by creating training data for a semantic segmentation deep learning model to map canal networks throughout the western United States. To create a diverse and robust training dataset, we labelled 1-m NAIP imagery with the locations of no canals, wet canals, and dry/vegetated canals. Since creating these datasets is time consuming, we first developed a preprocessing methodology to identify canals within our four study areas. We used NAIP imagery and provided canal centerline data to buffer, standardize, and cluster the imagery, automating the labeling process as much as possible. However, this still required manual cleaning and manual classification of canal type. Challenges arose when canals were interrupted (e.g., road culverts or piped sections) or when nearby features shared similar characteristics (e.g., irrigated fields, trees, and shadows). Combining automated preprocessing with manual refinement produced four detailed canal masks to be used in the semantic segmentation model developed by Richard Tapia.

13 - HYDRO ENERGY↗

NASA NTRSDate not supplied

Open Science for Plants in Space: Improvements in NASA's Open Science Data Repository

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, elevated CO2, and many other abiotic stressors. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. Current OSDR standards include the ISA (Investigation-Study-Assay) experiment model, assay metadata configurations, and standardized terminology and ontologies. In 2024 OSDR will include a new suite of features for improved FAIR compliance including downloadable plant metadata templates, data submission tools and overall improved AI-readiness of plant datasets. AI/ML methods can be helpful tools to overcome the inherent challenges of space biology research (small sample size, sparse and heterogeneous data etc.). However these methods are built on an assumption of normalized and well-curated data. OSDR’s new curation tools will improve users ability to leverage ML and AI methods to model space biology data and better understand the complex effects of spaceflight on living systems across hierarchical biological levels. We look forward to sharing our advances with the spaceflight community.

FAIR↗

DOE OSTI2020

COVID-19 pandemic reveals the peril of ignoring metadata standards

Efficient response to the pandemic through the mobilization of the larger scientific community is challenged by the limited reusability of the available primary genomic data. Here, the Genomic Standards Consortium board highlights the essential need for contextual genomic data FAIRness, for empowering key data-driven biological questions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗