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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

A Concept for Civil Space Traffic Management

As technology has improved, operators have sought to use cubesats, as well as smallsats more generally, to perform increasingly more ambitious and sophisticated functions. Despite this, practical concerns associated with cubesat infant mortality, conjunctions, limited maneuverability, and debris generation have been relatively muted because most cubesats have been launched to lower orbits that limit both their orbital lifetime and consequences should a collision occur. NASA ARC has developed a concept for a highly-automated and distributed space traffic management (STM) architecture, drawing on similar work done to provide traffic management for small unmanned aerial systems (UAS) operating at low altitudes. The system proposes a strategy to accommodate growing space traffic volume safely, as well as pave the way for a transition of civil STM authority to a civilian governmental entity. The architecture envisions an open-access software platform architecture of data and service suppliers, consumers, and regulators, connected via a set of application programming interfaces (APIs). The platform would build on, rather than replicate existing integration and coordination efforts within the space situational awareness ecosystem, using existing standards for data message formats from organizations like the Consultative Committee for Space Data Systems and wrapping, rather than replacing existing integrations. We will present an initial STM architecture in this presentation, with a few examples showing how stakeholders can interact structurally, but flexibly, within this architecture.

Space Situational Awareness↗
NASA NTRS2005

Tools for Basic Statistical Analysis

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

Luz, Paul L.↗
NASA NTRS2012

Acquisition of Long-Duration, Low-Gravity Slosh Data Utilizing Existing ISS Equipment (SPHERES) for Calibration of CFD Models of Coupled Fluid-Vehicle Behavior

Accurate prediction of coupled fluid slosh and launch vehicle or spacecraft dynamics (e.g., nutation/precessional movement about various axes, attitude changes, ect.) requires Computational Fluid Dynamics (CFD) models calibrated with low-gravity, long duration slosh data. Recently completed investigations of reduced gravity slosh behavior have demonstrated the limitations of utilizing parabolic flights on specialized aircraft with respect to the specific objectives of the experiments. Although valuable data was collected, the benefits of longer duration low-gravity environments were clearly established. The proposed research provides the first data set from long duration tests in zero gravity that can be directly used to benchmark CFD models, including the interaction between the sloshing fluid and the tank/vehicle dynamics. To explore the coupling of liquid slosh with the motion of an unconstrained tank in microgravity, NASA's Kennedy Space Center, Launch Services Program has teamed up with the Florida Institute of Technology (FIT), Massachusetts Institute of Technology (MIT) and the Office of the Chief Technologist (OCT) to perform a series of slosh dynamics experiments on the International Space Station using the SPHERES platform. The Synchronized Position Hold Engage Reorient Experimental Satellites (SPHERES) testbed provides a unique, free-floating instrumented platform on ISS that can be utilized in a manner that would solve many of the limitations of the current knowledge related to propellant slosh dynamics on launch vehicle and spacecraft fuel tanks. The six degree of freedom (6-DOF) motion of the SPHERES free-flyer is controlled by an array of cold-flow C02 thrusters, supplied from a built-in liquid C02 tank. These SPHERES can independently navigate and re-orient themselves within the ISS. The intent of this project is to design an externally mounted tank to be driven inside the ISS by a set of two SPHERES devices (Figure 1 ). The tank geometry simulates a launch vehicle upper stage propellant tank and the maneuvers replicate those of real vehicles. The design includes inertial sensors, data acquisition, image capture and data storage interfaces to the SPHERES VERTIGO computer system on board the flight article assembly. The design also includes mechanical and electronic interfaces to the existing SPHERES hardware, which include self-contained packages that can operate in conjunction with the existing SPHERES electronics.

Schallhorn, Paul↗
NASA NTRS2013

Acquisition of Long-Duration, Low-Gravity Slosh Data Utilizing Existing ISS Equipment (SPHERES) for Calibration of CFD Models of Coupled Fluid-Vehicle Behavior

Accurate prediction of coupled fluid slosh and launch vehicle or spacecraft dynamics (e.g., nutation/precessional movement about various axes, attitude changes, ect.) requires Computational Fluid Dynamics (CFD) models calibrated with low-gravity, long duration slosh data. Recently completed investigations of reduced gravity slosh behavior have demonstrated the limitations of utilizing parabolic flights on specialized aircraft with respect to the specific objectives of the experiments. Although valuable data was collected, the benefits of longer duration low-gravity environments were clearly established. The proposed research provides the first data set from long duration tests in zero gravity that can be directly used to benchmark CFD models, including the interaction between the sloshing fluid and the tank/vehicle dynamics. To explore the coupling of liquid slosh with the motion of an unconstrained tank in microgravity, NASA's Kennedy Space Center, Launch Services Program has teamed up with the Florida Institute of Technology (FIT), Massachusetts Institute of Technology (MIT) and the NASA Game Changing Development Program (GCD) to perform a series of slosh dynamics experiments on the International Space Station using the SPHERES platform. The Synchronized Position Hold Engage Reorient Experimental Satellites (SPHERES) testbed provides a unique, free-floating instrumented platform on ISS that can be utilized in a manner that would solve many of the limitations of the current knowledge related to propellant slosh dynamics on launch vehicle and spacecraft fuel tanks. The six degree of freedom (6-DOF) motion of the SPHERES free-flyer is controlled by an array of cold-flow C02 thrusters, supplied from a built-in liquid C02 tank. These SPHERES can independently navigate and re-orient themselves within the ISS. The intent of this project is to design an externally mounted tank to be driven inside the ISS by a set of two SPHERES devices (Figure 1). The tank geometry simulates a launch vehicle upper stage propellant tank and the maneuvers replicate those of real vehicles. The design includes inertial sensors, data acquisition, image capture and data storage interfaces to the SPHERES VERTIGO computer system on board the flight article assembly. The design also includes mechanical and electronic interfaces to the existing SPHERES hardware, which include self-contained packages that can operate in conjunction with the existing SPHERES electronics

Schallhorn, Paul↗
DOE OSTI2024

Increasing the Reproducibility and Replicability of Supervised AI/ML in the Earth Systems Science by Leveraging Social Science Methods

Artificial intelligence (AI) and machine learning (ML) pose a challenge for achieving science that is both reproducible and replicable. The challenge is compounded in supervised models that depend on manually labeled training data, as they introduce additional decision-making and processes that require thorough documentation and reporting. We address these limitations by providing an approach to hand labeling training data for supervised ML that integrates quantitative content analysis (QCA)—a method from social science research. The QCA approach provides a rigorous and well-documented hand labeling procedure to improve the replicability and reproducibility of supervised ML applications in Earth systems science (ESS), as well as the ability to evaluate them. Specifically, the approach requires (a) the articulation and documentation of the exact decision-making process used for assigning hand labels in a “codebook” and (b) an empirical evaluation of the reliability” of the hand labelers. In this paper, we outline the contributions of QCA to the field, along with an overview of the general approach. We then provide a case study to further demonstrate how this framework has and can be applied when developing supervised ML models for applications in ESS. With this approach, we provide an actionable path forward for addressing ethical considerations and goals outlined by recent AGU work on ML ethics in ESS.

58 GEOSCIENCES↗
DOE OSTI2024

Quantifying the Influence of Size, Shape, and Density of Microplastics on Their Transport Modes: A Modeling Approach

Microplastics (MPs) pose significant risks to marine ecosystems and human health, necessitating accurate predictions of their distributions in aquatic environments for effective risk mitigation. However, understanding MP transport dynamics is challenging because of the inadequate representation of MP characteristics such as size, shape, and density in numerical models. Further, the accuracy of the MP vertical profiles in existing models has not been thoroughly validated. Thus, we developed an MP transport model within the Finite Volume Community Ocean Model framework (FVCOM-MP) by integrating MP characteristics. We validated FVCOM-MP against experimental and analytical data, focusing on various MP transport modes and transitions. FVCOM-MP successfully replicates MP profiles in different transport modes, including the bedload, surface-load, suspended-load, and mixed-load modes. Additionally, we introduce phase diagrams for classifying MP transport modes based on particle characteristics, enhancing our understanding of MP dynamics in aquatic systems. The transport modes for a number of real-world MP particles, including fishing line, plastic bag/bottle fragments, synthetic fibers, tire wear particles, polyvinyl chloride and expanded polystyrene pellets, were analyzed with these phase diagrams.

Microplastic transport, Settling velocity, Rising ↗
NASA NTRS2004

Hubble Space Telescope Degradation Data Used for Ground-Based Durability Projection of Insulation on the International Space Station

Ground-based environmental durability tests have indicated that exposing materials in accelerated tests to known spacecraft mission degradation sources predicted by an environmental model does not simulate the extent of damage that occurs in the space environment. The reasons for this may include the complex nature of the space environment, which is not simulated completely in any ground-based facility, the extreme differences in exposure rates in space and in ground tests, and inaccuracies in environmental models. One approach to overcoming the difficulties in simulating the space environment using ground-based testing is to calibrate the facility using data from actual space-exposed materials to determine exposure levels required to replicate degraded properties observed in space. Research was conducted at the NASA Glenn Research Center to develop a ground-to-space correlation method that determines the durability of Teflon-based insulation for the International Space Station (ISS) by using data obtained in a ground facility and degraded Teflon thermal insulation retrieved from the Hubble Space Telescope.

deGroh, Kim K.↗
DOE OSTI2024

Evaluation and Intercomparison of Small Uncrewed Aircraft Systems Used for Atmospheric Research

Abstract Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Advanced wind turbine control development using field test analysis for generator overspeed mitigation

Abstract Turbulent and gusty wind conditions can cause generator overspeed peaks to exceed a threshold that then lead to wind turbine shutdowns, which then decrease the energy production of the wind turbines. We derive so‐called “gust measures” that predict when generator overspeed peaks may occur. These gust measures are then used to develop advanced controllers to mitigate generator overspeed peaks so that wind turbines can operate more robustly in difficult wind conditions without exceeding generator overspeed thresholds that would lead to turbine shutdown events. The advanced controllers are demonstrated in nonlinear aeroelastic simulations using the open‐source wind turbine simulation tool OpenFAST. To increase the realism of the simulations, they are run using field‐replicated wind conditions and a wind turbine model based on data from an experimental field campaign on a downscaled demonstrator of a novel extreme‐scale, two‐bladed, downwind rotor design.

17 WIND ENERGY↗
DOE OSTI2021

Small Animal IMRT Using 3D-Printed Compensators

Preclinical radiation replicating clinical intensity modulated radiation therapy (IMRT) techniques can provide data translatable to clinical practice. For this work, treatment plans were created for oxygen-guided dose-painting in small animals using inverse-planned IMRT. Spatially varying beam intensities were achieved using 3-dimensional (3D)-printed compensators.

3D PRINTING↗
DOE OSTI2024

Analytical noise bias correction for precise weak lensing shear inference

Noise bias is a significant source of systematic error in weak gravitational lensing measurements that must be corrected to satisfy the stringent standards of modern imaging surveys in the era of precision cosmology. This paper reviews the analytical noise bias correction method and provides analytical derivations demonstrating that we can recover shear to its second order using the ‘renoising’ noise bias correction approach introduced by METACALIBRATION. We implement this analytical noise bias correction within the AnaCal shear estimation framework and propose several enhancements to the noise bias correction algorithm. We evaluate the improved AnaCal using simulations designed to replicate Rubin Legacy Survey of Space and Time (LSST) imaging data. These simulations feature semi-realistic galaxies and stars, complete with representative distributions of magnitudes and Galactic spatial density. We conduct tests under various observational challenges, including cosmic rays, defective CCD columns, bright star saturation, bleed trails, and spatially variable point spread functions. Our results indicate a multiplicative bias in weak lensing shear recovery of less than a few tenths of a per cent, meeting LSST Dark Energy Science Collaboration requirements without requiring calibration from external image simulations. Additionally, our algorithm achieves rapid processing, handling one galaxy in less than a millisecond.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Novel Data Driven Noise Emulation Framework using Deep Neural Network for Generating Synthetic PMU Measurements

Sensors play a critical role in supporting day-to-day grid operations and they are essential to operator’s decision-making process. Furthermore, sensors and sensor behaviors need to be emulated with grid simulations to perform modeling studies and to design cutting edge power systems applications. Ensuring the accurate behavior of these applications requires accurate emulation of sensors and pertinent signals. However, most grid simulators and modeling tools assume either zero error scenarios or simplistic noise models that may not always correlate to real-world sensors. To address the above issue, this work presents an initial study on the noise characteristics of phasor measurement units (PMUs), along with models for recreating their unique noise signatures. The proposed methods (both analytical and machine-learning-based) provide a substantial increase in a sensor’s model fidelity, a feature that can be leveraged by an end-user application to yield more accurate system representations. The proposed methods were then applied to micro PMU data from the EPFL microgrid campus to extract sensor noise profiles. This data was used to train a deep learning model, which was tested to emulate the noise characteristics present in actual signals. Based on the observed results and the employed data-driven methodology, the proposed methods may be adapted to replicate the behavior of other grid sensors and power new applications capable of detecting sensor degradation and eventual device failures in near real-time.

PMU, noise emulation, synthetic measurements, deep↗
DOE OSTI2022

Defective Interfering Viral Particle Treatment Reduces Clinical Signs and Protects Hamsters from Lethal Nipah Virus Disease

Defective interfering particles (DIs) contain a considerably smaller genome than the parental virus but retain replication competency. As DIs can directly or indirectly alter propagation kinetics of the parental virus, they offer a novel approach to antiviral therapy, capitalizing on knowledge from natural infection. However, efforts to translate in vitro inhibition to in vivo screening models remain limited. We investigated the efficacy of virus-like particles containing DI genomes (therapeutic infectious particles [TIPs]) in the Syrian hamster model of lethal Nipah virus (NiV) disease. We found that coadministering a high dose of TIPs intraperitoneally with virus challenge improved clinical course and reduced lethality. To mimic natural exposure, we also evaluated lower-dose TIP delivery and virus challenge intranasally, finding equally efficacious reduction in disease severity and overall lethality. Eliminating TIP replicative capacity decreased efficacy, suggesting protection via direct inhibition. These data provide evidence that TIP-mediated treatment can confer protection against disease and lethal outcome in a robust animal NiV model, supporting further development of TIP treatment for NiV and other high-consequence pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Human Liver Epithelial Cells (HuH7) Response to HCoV-229E Infection Epigenomics (ATAC-Seq) (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-299E) infection alters chromatin accessibility in infected cells. Sample data was obtained from mock-infected cells, UV-inactivated virus treated cells, and replication competent HCoV-229E infected immortalized human liver cells (HuH7) at 24 hours post infection. Samples were processed using ATAC-seq methods for reported bar coded libraries. Sample data was acquired using an Illumina Hi-Seq 2500 sequencer system and further processed for ATAC-Seq expression analysis.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

Persistent Seroconversion after Accidental Eye Exposure to Calcifying Nanoparticles

Biosafety of nanomaterials has attracted much attention recently. We report here a case where accidental human eye exposure to biogenic nanosized calcium phosphate in the form of calcifying nanoparticles (CNP) raised a strong IgG immune response against proteins carried by CNP. The antibody titer has persisted over ten years at the high level. The IgG was detected by ELISA using CNPs propagated in media containing bovine and human serum as antigen. The exposure incident occurred to a woman scientist (WS) at a research laboratory in Finland at 1993. CNP, also termed "nanobacteria", is a unique self-replicating agent that has not been fully characterized and no data on biohazards were available at that time. Before the accident, her serum samples were negative for both CNP antigen and anti-CNP antibody using specific ELISA tests (Nanobac Oy, Kuopio, Finland). The accident occurred while WS was harvesting CNP cultures. Due to a high pressure in pipetting, CNP pellet splashed into her right eye. Both eyes were immediately washed with water and saline. The following days there was irritation and redness in the right eye. These symptoms disappeared within two weeks without any treatment. Three months after the accident, blood and urine samples of WS were tested for CNP cultures (2), CNP-specific ELISA tests, and blood cell counts. Blood cell counts were normal, CNP antigen and culture tests were negative. A high IgG anti-CNP antibody titer was detected (see Figure). The antibodies of this person have been used thereafter as positive control and standard in ELISA manufacturing (Nano-Sero IgG ELISA, Nanobac Oy, Kuopio, Finland).

Ciftcioglu, Neva↗
NASA NTRS2021

Northern Great Plains Disasters: Using Earth Observations to Enhance Flood Monitoring on Tribal Lands in the Northern Great Plains

In 2019, the Great Plains experienced unprecedented catastrophic flooding. Large flood events are predicted to increase in frequency and severity, posing risks to communities in this region, particularly Tribal Nations. We used data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), imagery from the Sentinel-2 MultiSpectral Instrument (MSI), and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) within Google Earth Engine to map historical floods in the region beginning in 2014 with particular attention to the Rosebud Sioux Reservation and the tribal lands of other Great Plains Tribal Water Alliance members. This historical mapping used C-SAR for a combined method approach with a Z-score algorithm in addition to an index for flooded short vegetation. We also developed a flood risk map by weighting different flood predictor variables according to flood risk literature. These variables included soil drainage from the Soil Survey Geographic Database (SSURGO); elevation, slope, and Topographic Wetness Index (TWI) derived from digital elevation models; precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS); land cover from the National Land Cover Database (NLDC); and Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 Operational Land Imager (OLI). From the flood extent and risk maps, we identified widespread flooding in short vegetation (including cropland) and noted flood susceptibility in regions exhibiting high social vulnerability and low community resilience (FEMA indices). We created an ArcGIS Online StoryMap to share project background, results, and data. Additionally, we provided a written tutorial so partners may replicate the flood mapping for future flood events.

Anna Ballasiotes↗
NASA NTRS2022

Maldives Climate: Monitoring Shoreline Changes and Island Loss in Response to Climate Change

Global sea level rise as a result of climate change continues to pose a critical threat to coastal ecosystems and populations. The archipelagic country of the Maldives is of critical concern due to being one of the lowest lying areas in the world. The development of reclaimed land in the Maldives by sand dredging has been a frequent response to both increasing sea levels and population increase. Such disturbance can lead to increased sedimentation off the coast and negatively impact coastal environments. Remote sensing tools such as satellite imagery have proved to be an effective tool in observing coastal changes in response to climate change and development. NASA DEVELOP created a methodology to analyze both water quality and shoreline erosion in the Maldives utilizing satellite imagery. Methods relied on open-source software such as QGIS and Google Earth Engine (GEE) and Satellite Imagery from PlanetScope, Landsat 8 Operational Land Instrument (OLI), Sentinel-2 Multi Spectral Instrument (MSI), and Aqua & Terra Moderate Resolution Imaging Radiospectrometer (MODIS) to analyze the changes in shorelines and assess water quality of select atolls within the Maldives. Findings show less shoreline change in developed parts of the island and more shoreline change in natural parts of the island. Additionally, water quality varies throughout the year and our data did not indicate seasonal trends. The methodology will be replicated to continue to monitor island erosion and water quality with the Maldives and will be applicable to other island and coastal systems.

remote sensing↗
DOE OSTI2022

Challenges and Lessons Learned from an Analysis of Three Zero Energy Buildings

Zero energy buildings, or zero energy ready buildings, which are designed and operated by public or private commercial property owners can play an important role in reducing carbon emissions. This paper discusses lessons learned and key takeaways from an in-depth analysis of three zero energy buildings that took an integrated design and construction approach to significantly reduce energy use. Two of these projects are new construction and one is a retrofit to zero energy. Findings are based on project literature review, data analysis, and in-depth interviews with the building design teams and staff who were involved during the design, construction, and operation of the buildings. The paper addresses value proposition and cost data in such a way that other building owners can replicate the strategies and technology solutions in response to regulatory mandates or organizational goals. It also provides details on operational improvements taken at each zero energy building to enhance energy performance and increase the potential for load flexibility, and discusses challenges and lessons gleaned from design teams and building staff. The findings serve as a reference for building owners, designers, engineers, contractors, or others interested in, or involved with, the design, construction, or use of new or existing buildings. The paper also includes recommended pathways for widespread adoption of zero energy strategies that can be applied in various locations.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗