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At least 1,531 records · Page 85

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NASA NTRS2011

Fermi Gamma-Ray Space Telescope - Science Highlights for the First Two Years on Orbit

Fermi science objectives cover probably everything in high energy astrophysics: How do super massive black holes in Active Galactic Nuclei create powerful jets of material moving at nearly light speed? What are the jets made of? What are the mechanisms that produce Gamma-Ray Burst (GRB) explosions? What is the energy budget? How does the Sun generate high-energy gamma-rays in flares? How do the pulsars operate? How many of them are around and how different are they? What are the unidentified gamma-ray sources found by EGRET? What is the origin of the cosmic rays that pervade the Galaxy? What is the nature of dark matter? Fermi LAT successfully operates on the orbit for more than 2 years and demonstrates excellent performance, which is continuously monitored and calibrated. LAT collected> 100 billion on-orbit triggers

Moiseev, Alexander↗

NASA NTRS2005

Component-Based Visualization System

A software system has been developed that gives engineers and operations personnel with no "formal" programming expertise, but who are familiar with the Microsoft Windows operating system, the ability to create visualization displays to monitor the health and performance of aircraft/spacecraft. This software system is currently supporting the X38 V201 spacecraft component/system testing and is intended to give users the ability to create, test, deploy, and certify their subsystem displays in a fraction of the time that it would take to do so using previous software and programming methods. Within the visualization system there are three major components: the developer, the deployer, and the widget set. The developer is a blank canvas with widget menu items that give users the ability to easily create displays. The deployer is an application that allows for the deployment of the displays created using the developer application. The deployer has additional functionality that the developer does not have, such as printing of displays, screen captures to files, windowing of displays, and also serves as the interface into the documentation archive and help system. The third major component is the widget set. The widgets are the visual representation of the items that will make up the display (i.e., meters, dials, buttons, numerical indicators, string indicators, and the like). This software was developed using Visual C++ and uses COTS (commercial off-the-shelf) software where possible.

Delgado, Francisco↗

NASA NTRS2011

Overview of Pre-Flight Physical Training, In-Flight Exercise Countermeasures and the Post-Flight Reconditioning Program for International Space Station Astronauts

International Space Station (ISS) astronauts receive supervised physical training pre-flight, utilize exercise countermeasures in-flight, and participate in a structured reconditioning program post-flight. Despite recent advances in exercise hardware and prescribed exercise countermeasures, ISS crewmembers are still found to have variable levels of deconditioning post-flight. This presentation provides an overview of the astronaut medical certification requirements, pre-flight physical training, in-flight exercise countermeasures, and the post-flight reconditioning program. Astronauts must meet medical certification requirements on selection, annually, and prior to ISS missions. In addition, extensive physical fitness testing and standardized medical assessments are performed on long duration crewmembers pre-flight. Limited physical fitness assessments and medical examinations are performed in-flight to develop exercise countermeasure prescriptions, ensure that the crewmembers are physically capable of performing mission tasks, and monitor astronaut health. Upon mission completion, long duration astronauts must re-adapt to the 1 G environment, and be certified as fit to return to space flight training and active duty. A structured, supervised postflight reconditioning program has been developed to prevent injuries, facilitate re-adaptation to the 1 G environment, and subsequently return astronauts to training and space flight. The NASA reconditioning program is implemented by the Astronaut Strength, Conditioning, and Rehabilitation (ASCR) team and supervised by NASA flight surgeons. This program has evolved over the past 10 years of the International Space Station (ISS) program and has been successful in ensuring that long duration astronauts safely re-adapt to the 1 g environment and return to active duty. Lessons learned from this approach to managing deconditioning can be applied to terrestrial medicine and future exploration space flight missions.

Kerstman, Eric↗

NASA NTRS2012

Comparison of Ocular Outcomes in Two 14-Day Bed Rest Studies

Reports of astronauts' visual changes have raised concern about ocular health during long-duration spaceflight. Some of these findings include globe flattening with hyperopic shifts, choroidal folds, optic disc edema, retinal nerve fiber layer (RNFL) thickening, and cotton wool spots. While the etiology remains unknown, it is hypothesized that, in predisposed individuals, hypertension in the brain may follow cephalad fluid shifts during spaceflight. This possible mechanism of ocular changes may also apply to analogous cases of idiopathic intracranial hypertension (IIH) or pseudotumor cerebri on Earth patients. Head-down t ilt (HDT) bed rest is a spaceflight analog that induces cephalad fluid shifts. Previous studies of the HDT position demonstrated body fluid shifts associated with changes in intraocular pressure (IOP) but the conditions of bed rest varied among experiments, making it difficult to compare data and draw conclusions. For these reasons, vision evaluation of bed rest subjects was implemented for NASA bed rest studies since 2010, in an attempt to monitor vision health in subjects subjected to bed rest. Vision monitoring is thus currently performed in all NASA-conducted bed rest campaigns

Cromwell, Ronita L.↗

NASA NTRS2012

Scalable Integrated Multi-Mission Support System (SIMSS) Simulator Release 2.0 for GMSEC

Scalable Integrated Multi-Mission Support System (SIMSS) Simulator Release 2.0 software is designed to perform a variety of test activities related to spacecraft simulations and ground segment checks. This innovation uses the existing SIMSS framework, which interfaces with the GMSEC (Goddard Mission Services Evolution Center) Application Programming Interface (API) Version 3.0 message middleware, and allows SIMSS to accept GMSEC standard messages via the GMSEC message bus service. SIMSS is a distributed, component-based, plug-and-play client-server system that is useful for performing real-time monitoring and communications testing. SIMSS runs on one or more workstations, and is designed to be user-configurable, or to use predefined configurations for routine operations. SIMSS consists of more than 100 modules that can be configured to create, receive, process, and/or transmit data. The SIMSS/GMSEC innovation is intended to provide missions with a low-cost solution for implementing their ground systems, as well as to significantly reduce a mission s integration time and risk.

Kim, John↗

NASA NTRS2012

Scalable Integrated Multi-Mission Support System Simulator Release 3.0

The Scalable Integrated Multi-mission Support System (SIMSS) is a tool that performs a variety of test activities related to spacecraft simulations and ground segment checks. SIMSS is a distributed, component-based, plug-and-play client-server system useful for performing real-time monitoring and communications testing. SIMSS runs on one or more workstations and is designed to be user-configurable or to use predefined configurations for routine operations. SIMSS consists of more than 100 modules that can be configured to create, receive, process, and/or transmit data. The SIMSS/GMSEC innovation is intended to provide missions with a low-cost solution for implementing their ground systems, as well as significantly reducing a mission s integration time and risk.

Kim, John↗

NASA NTRS2013

Evidence for Smectite Clays from MSL SAM Analyses of Mudstone at Yellowknife Bay, Gale Crater, Mars

Drilled samples of mudstone from the Sheepbed unit at Yellowknife Bay were analyzed by MSL instruments including the Sample Analysis at Mars (SAM) and Chemistry and Mineralogy (CheMin) instruments in MSL's Analytical Laboratory. CheMin analyses revealed the first in situ X-ray diffraction based evidence of clay minerals on Mars, which are likely trioctahedral smectites (e.g., saponite) and comprise approx 20% of the mudstone sample (e.g., Bristow et al., this meeting). SAM analyses, which heated the mudstone samples to 1000 C and monitored volatiles evolved to perform in situ evolved gas analysis mass spectrometry (EGA-MS), resulted in a H2O trace exhibiting a wide evolution at temperatures < 500 C, and an evolution peak at higher temperatures near approx 750 C. The low temperature H2O evolution has many potential contributors, including adsorbed H2O, smectite interlayer H2O, and structural H2O/OH from bassanite and akaganeite (identified by CheMin) and H2O/OH from amorphous phases in the sample. The high temperature H2O is consistent with the evolution of H2O from the dehydroxylation of the smectite clay mineral. Comparison to EGA-MS data collected under SAM-like conditions on a variety of clay mineral reference materials indicate that a trioctahedral smectite, such as saponite, is most consistent with the high temperature H2O evolution observed. There may also be SAM EGA-MS evidence for a small high temperature H2O evolution from scoop samples from the Yellowknife Bay Rocknest sand shadow bedform. As in the mudstone samples, this evolution may indicate the detection of smectite clays, and the idea that minor clays may be present in Rocknest materials that could be expected to be at least partially derived from local sources is reasonable. But, because smectite clays were not definitively observed in CheMin analyses of Rocknest materials, they must be present at much lower abundances than the approx 20% observed in the mudstone samples. This potential detection underscores the complementary nature of the MSL CheMin and SAM instruments for investigations of martian sample mineralogy. Information on the nature of Yellowknife Bay clay minerals may also be available from the detection of H2 evolved during SAM EGA-MS at high temperature. A likely source of at least some of this H2 is H2O evolved from the smectite clays at high temperature, and it is possible these evolutions can be used in a similar fashion to high temperature H2O releases to provide constraints on the clay minerals in a sample. In addition, the D/H of this high temperature H2, as well as the H2O, can be derived from SAM MS and Tunable Laser Spectrometer (TLS) data, respectively. These D/H values may help to inform the provenance of high and low temperature water evolved from martian samples

McAdam, Amy↗

NASA NTRS2011

Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials

Composite structures are gaining importance for use in the aerospace industry. Compared to metallic structures their behavior is less well understood. This lack of understanding may pose constraints on their use. One possible way to deal with some of the risks associated with potential failure is to perform in-situ monitoring to detect precursors of failures. Prognostic algorithms can be used to predict impending failures. They require large amounts of training data to build and tune damage model for making useful predictions. One of the key aspects is to get confirmatory feedback from data as damage progresses. These kinds of data are rarely available from actual systems. The next possible resource to collect such data is an accelerated aging platform. To that end this paper describes a fatigue cycling experiment with the goal to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis showed distinct differences in the signatures of growing failures between data collected at conditions. Periodic X-radiographs were taken to assess the damage ground truth. Results after signal processing showed clear trends of damage growth that were correlated to damage assessed from the X-ray images.

composites↗

NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗

NASA NTRS2015

International Space Station Major Constituent Analyzer On-Orbit Performance

The Major Constituent Analyzer is a mass spectrometer based system that measures the major atmospheric constituents on the International Space Station. A number of limited-life components require periodic change-out, including the ORU 02 analyzer and the ORU 08 Verification Gas Assembly. Improvements to ion pump operation and ion source tuning have improved lifetime performance of the current ORU 02 design. The most recent ORU 02 analyzer assemblies, as well as ORU 08, have operated nominally. For ORU 02, the ion source filaments and ion pump lifetime continue to be key determinants of MCA performance and logistical support. Monitoring several key parameters provides the capacity to monitor ORU health and properly anticipate end of life.

Gardner, Ben D.↗

NASA NTRS2018

Results from the Deep Convective Clouds-Based Response Versus Scan-Angle Characterization for the MODIS Reflective Solar Bands

The Terra and Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) scan mirror reflectance is a function of the angle of incidence (AOI) and was characterized prior to launch by the instrument vendor. The relative change of the prelaunch response versus scan angle (RVS) is tracked and linearly scaled on-orbit using observations at two AOIs of 11.2° and 50.2° corresponding to the moon view and solar diffuser, respectively. As the missions continue to operate well beyond their design life of six years, the assumption of linear scaling between the two AOIs is known to be inadequate in accurately characterizing the RVS, particularly at short wavelengths. Consequently, an enhanced approach of supplementing the on-board measurements with response trends from desert pseudoinvariant calibration sites (PICS) was formulated in MODIS Collection 6 (C6). An underlying assumption for the continued effectiveness of this approach is the long-term (multiyear) and short-term (month to month) stability of the PICS. Previous work has shown that the deep convective clouds (DCC) can also be used to monitor the onorbit RVS performance with less trend uncertainties compared with desert sites. In this paper, the raw sensor response to the DCC is used to characterize the on-orbit RVS on a band and mirror-side basis. These DCC-based RVS results are compared with those of C6 PICS-based RVS, showing an agreement within 2% observed in most cases. The pros and cons of using a DCC-based RVS approach are also discussed in this paper. Although this reaffirms the efficacy of the C6 PICS-based RVS, the DCC-based RVS approach presents itself as an effective alternative for future considerations. Potential applications of this approach to other instruments, such as Suomi National Polarorbiting Partnership, Joint Polar Satellite Systems, and Visible Infrared Imaging Radiometer Suite, are also discussed.

Angal, Amit↗

NASA NTRSDate not supplied

Achieving Resilient In-Flight Performance for Advanced Air Mobility through Simplified Vehicle Operations

A research and development (R&D) approach is proposed for developing and validating concepts and technologies to achieve vehicle autonomy goals of Advanced Air Mobility (AAM) through Simplified Vehicle Operations (SVO). The approach applies resilience-engineering and human-automation teaming (HAT) principles to a framework for defining vehicle-based functions for the management of missions and flight trajectories, focusing initially on the en route flight domain. To achieve the SVO goal of reducing pilot training requirements and thereby increasing the pilot pool for AAM, while at the same time promoting ever-safer operations, a framework for identifying essential functions is proposed. In this framework, functions are first categorized by high-level functional purpose (mission management, flightpath management, tactical operations, and vehicle control) and then subcategorized by attributes of resilient-performing systems (abilities to monitor, respond, learn, and anticipate). The categorization by functional purpose provides structure within which HAT designs can be holistically explored and total levels of human vs. automation responsibility can be varied. The subcategorization by resilient-system attributes provides a mechanism for capturing safety-critical functions that may not be codified in current operational procedures and training curricula, particularly those where humans proactively enhance safety in currently undocumented ways. An R&D approach consisting of seven strategies is proposed in which automation engineering and human-factors communities can collaborate in the research, development, and design of an SVO roadmap to enable the ambitious objectives of AAM.

AAM↗

NASA NTRSDate not supplied

Conjunction Assessment(CA) Support Overview for the EOS Satellites

When a satellite is placed into its desired orbit, to achieve its designed mission objectives, it is imperative to maintain orbit requirements as well as the overall health and safety of the vehicle. One integral part of this process is ensuring that the satellite does not collide with any other vehicle or object in space, which can cause a detrimental consequence to the mission as well as to other satellites within the same orbit regime. To prevent such an occurrence, a thorough collision avoidance process must be followed. This process includes constantly monitoring potential conjunctions and performing collision avoidance maneuvers when necessary, while remaining within the limitations of the mission’s orbit maintenance requirements. This presentation will describe the Earth Observing System (EOS) Aqua, Aura and Terra satellite’s operational collision a! voidance process. It will highlight the routine conjunction assessment screening and data evaluation process performed by the NASA/GSFC EOS Collision Avoidance Engineers. The presentation will include background information, a summary of operational activities and duties, internal tools used for support, EOS High Interest Event statistics, and potential challenges expected in the future.

Syed Hasan↗

NASA NTRSDate not supplied

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become imperative across various sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot is constructed, utilizing natural language processing (NLP) techniques, to facilitate the deployment of these ML models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.

Development↗

NASA NTRSDate not supplied

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

Development↗

NASA NTRSDate not supplied

Machine Learning Application in Aircraft Engine Conceptual Design

In the current competitive environment, the successful creation and application of machine learning (ML) technologies have become crucial across multiple industries. This study outlines the process of creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models use supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. Key focus areas include crucial engine parameters such as thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While developing ML models is fundamental, ensuring their seamless deployment is equally important. To address this, a conversational AI chatbot is constructed using natural language processing (NLP) techniques to facilitate the deployment of these ML models. The comprehensive workflow includes several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine conceptual design.

Aircraft Engine↗

NASA NTRS2024

The Development and Deployment of Machine Learning Models for Aircraft Engine Concept Assessment

In today's competitive landscape, the effective development and utilization of machine-learning (ML) applications have become crucial across diverse economic sectors. This study presents an outline of the procedure involved in creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models leverage supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. The main areas of focus encompass crucial engine parameters like thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While the creation of ML models is fundamental for their utilization, ensuring their seamless deployment holds equal significance. To address this aspect, a conversational AI chatbot that specifically focuses on propulsion has been developed. Leveraging natural language processing (NLP) techniques, this chatbot simplifies the deployment of machine learning (ML) models. The comprehensive workflow encompasses several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine assessment.

AI Chatbot↗

DOE OSTI2014

Fermentation process using specific oxygen uptake rates as a process control

Specific oxygen uptake (OUR) is used as a process control parameter in fermentation processes. OUR is determined during at least the production phase of a fermentation process, and process parameters are adjusted to maintain the OUR within desired ranges. The invention is particularly applicable when the fermentation is conducted using a microorganism having a natural PDC pathway that has been disrupted so that it no longer functions. Microorganisms of this sort often produce poorly under strictly anaerobic conditions. Microaeration controlled by monitoring OUR allows the performance of the microorganism to be optimized.

59 BASIC BIOLOGICAL SCIENCES↗