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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Cell-cycle research with synchronous cultures: an evaluation

The baby-machine system, which produces new-born Escherichia coli cells from cultures immobilized on a membrane, was developed many years ago in an attempt to attain optimal synchrony with minimal disturbance of steady-state growth. In the present article, we put forward a model to describe the behaviour of cells produced by this method, and provide quantitative evaluation of the parameters involved, at each of four different growth rates. Considering the high level of selection achievable with this technique and the natural dispersion in interdivision times, we believe that the output of the baby machine is probably close to optimal in terms of both quality and persistence of synchrony. We show that considerable information on events in the cell cycle can be obtained from populations with age distributions very much broader than those achieved with the baby machine and differing only modestly from steady state. The data presented here, together with the long and fruitful history of findings employing the baby-machine technique, suggest that minimisation of stress on cells is the single most important factor for successful cell-cycle analysis.

Non-NASA Center↗
NASA NTRS2009

Columbia Crew Survival Investigation Report

NASA commissioned the Columbia Accident Investigation Board (CAIB) to conduct a thorough review of both the technical and the organizational causes of the loss of the Space Shuttle Columbia and her crew on February 1, 2003. The accident investigation that followed determined that a large piece of insulating foam from Columbia s external tank (ET) had come off during ascent and struck the leading edge of the left wing, causing critical damage. The damage was undetected during the mission. The CAIB's findings and recommendations were published in 2003 and are available on the web at http://caib.nasa.gov/. NASA responded to the CAIB findings and recommendations with the Space Shuttle Return to Flight Implementation Plan. Significant enhancements were made to NASA's organizational structure, technical rigor, and understanding of the flight environment. The ET was redesigned to reduce foam shedding and eliminate critical debris. In 2005, NASA succeeded in returning the space shuttle to flight. In 2010, the space shuttle will complete its mission of assembling the International Space Station and will be retired to make way for the next generation of human space flight vehicles: the Constellation Program. The Space Shuttle Program recognized the importance of capturing the lessons learned from the loss of Columbia and her crew to benefit future human exploration, particularly future vehicle design. The program commissioned the Spacecraft Crew Survival Integrated Investigation Team (SCSIIT). The SCSIIT was asked to perform a comprehensive analysis of the accident, focusing on factors and events affecting crew survival, and to develop recommendations for improving crew survival for all future human space flight vehicles. To do this, the SCSIIT investigated all elements of crew survival, including the design features, equipment, training, and procedures intended to protect the crew. This report documents the SCSIIT findings, conclusions, and recommendations.

Source record↗
NASA NTRS2010

Introduction of the Space Shuttle Columbia Accident, Investigation Details, Findings and Crew Survival Investigation Report

As the Space Shuttle Program comes to an end, it is important that the lessons learned from the Columbia accident be captured and understood by those who will be developing future aerospace programs and supporting current programs. Aeromedical lessons learned from the Accident were presented at AsMA in 2005. This Panel will update that information, closeout the lessons learned, provide additional information on the accident and provide suggestions for the future. To set the stage, an overview of the accident is required. The Space Shuttle Columbia was returning to Earth with a crew of seven astronauts on 1Feb, 2003. It disintegrated along a track extending from California to Louisiana and observers along part of the track filmed the breakup of Columbia. Debris was recovered from Littlefield, Texas to Fort Polk, Louisiana, along a 567 statute mile track; the largest ever recorded debris field. The Columbia Accident Investigation Board (CAIB) concluded its investigation in August 2003, and released their findings in a report published in February 2004. NASA recognized the importance of capturing the lessons learned from the loss of Columbia and her crew and the Space Shuttle Program managers commissioned the Spacecraft Crew Survival Integrated Investigation Team (SCSIIT) to accomplish this. Their task was to perform a comprehensive analysis of the accident, focusing on factors and events affecting crew survival, and to develop recommendations for improving crew survival, including the design features, equipment, training and procedures intended to protect the crew. NASA released the Columbia Crew Survival Investigation Report in December 2008. Key personnel have been assembled to give you an overview of the Space Shuttle Columbia accident, the medical response, the medico-legal issues, the SCSIIT findings and recommendations and future NASA flight surgeon spacecraft accident response training. Educational Objectives: Set the stage for the Panel to address the investigation, medico-legal issues, the Spacecraft Crew Survival Integrated Investigation Team report and training for accident response.

Chandler, Michael↗
NASA NTRS2011

Parametric Modeling of the Safety Effects of NextGen Terminal Maneuvering Area Conflict Scenarios

The goal of this work was to analytically identify and quantify the issues, challenges, technical hurdles, and pilot-vehicle interface issues associated with conflict detection and resolution (CD&R)in emerging operational concepts for a NextGen terminal aneuvering area, including surface operations. To this end, the work entailed analytical and trade studies focused on modeling the achievable safety benefits of different CD&R strategies and concepts in the current and future airport environment. In addition, crew-vehicle interface and pilot performance enhancements and potential issues were analyzed based on review of envisioned NextGen operations, expected equipage advances, and human factors expertise. The results of perturbation analysis, which quantify the high-level performance impact of changes to key parameters such as median response time and surveillance position error, show that the analytical model developed could be useful in making technology investment decisions.

Rogers, William H.↗
NASA NTRS2010

Utilizing In Situ Directional Hyperspectral Measurements to Validate Bio-Indicator Simulations for a Corn Crop Canopy

Two radiative transfer canopy models, SAIL and the two-layer Markov-Chain Canopy Reflectance Model (MCRM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the photochemical reflectance index in a cornfield. In situ hyperspectral measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles (psi) at three different view zenith angles (Theta (sub v)), and later used to validate model outputs. Field observations of photochemical reflectance index (PRI) for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, as a function of both Theta (sub v) and psi . Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, the MCRM-simulated PRI values showed satisfactory correlation and RMSE, as compared to in situ values. However, the performance of the MCRM model was significantly improved after defining a lower canopy layer comprised of shaded leaves beneath the upper sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; but unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. Leaf area index (LAI) showed the most significant impact on MCRM-simulated PRI among the parameters studied. This research shows the importance of hyperspectral and narrow band sensor studies, and especially the necessity of including the green wavelengths (e.g., 531 nm) on satellites proposing to monitor carbon dynamics of terrestrial ecosystems.

Cheng, Yen-Ben↗
NASA NTRS2011

Quadrocopter Control Design and Flight Operation

A limiting factor in control system design and analysis for spacecraft is the inability to physically test new algorithms quickly and cheaply. Test flights of space vehicles are costly and take much preparation. As such, EV41 recently acquired a small research quadrocopter that has the ability to be a test bed for new control systems. This project focused on learning how to operate, fly, and maintain the quadrocopter, as well as developing and testing protocols for its use. In parallel to this effort, developing a model in Simulink facilitated the design and analysis of simple control systems for the quadrocopter. Software provided by the manufacturer enabled testing of the Simulink control system on the vehicle.

Karwoski, Katherine↗
NASA NTRS2004

Error Modeling of Multibaseline Optical Truss: Part 1: Modeling of System Level Performance

Global astrometry is the measurement of stellar positions and motions. These are typically characterized by five parameters, including two position parameters, two proper motion parameters, and parallax. The Space Interferometry Mission (SIM) will derive these parameters for a grid of approximately 1300 stars covering the celestial sphere to an accuracy of approximately 4uas, representing a two orders of magnitude improvement over the most precise current star catalogues. Narrow angle astrometry will be performed to a 1uas accuracy. A wealth of scientific information will be obtained from these accurate measurements encompassing many aspects of both galactic (and extragalactic science. SIM will be subject to a number of instrument errors that can potentially degrade performance. Many of these errors are systematic in that they are relatively static and repeatable with respect to the time frame and direction of the observation. This paper and its companion define the modeling of the, contributing factors to these errors and the analysis of how they impact SIM's ability to perform astrometric science.

meterology modeling↗
NASA NTRS2013

Geometric Effects on the Amplification of First Mode Instability Waves

The effects of geometric changes on the amplification of first mode instability waves in an external supersonic boundary layer were investigated using numerical techniques. Boundary layer stability was analyzed at Mach 6 conditions similar to freestream conditions obtained in quiet ground test facilities so that results obtained in this study may be applied to future test article design to measure first mode instability waves. The DAKOTA optimization software package was used to optimize an axisymmetric geometry to maximize the amplification of the waves at first mode frequencies as computed by the 2D STABL hypersonic boundary layer stability analysis tool. First, geometric parameters such as nose radius, cone half angle, vehicle length, and surface curvature were examined separately to determine the individual effects on the first mode amplification. Finally, all geometric parameters were allowed to vary to produce a shape optimized to maximize the amplification of first mode instability waves while minimizing the amplification of second mode instability waves. Since first mode waves are known to be most unstable in the form of oblique wave, the geometries were optimized using a broad range of wave frequencies as well as a wide range of oblique wave angles to determine the geometry that most amplifies the first mode waves. Since first mode waves are seen most often in flows with low Mach numbers at the edge of the boundary layer, the edge Mach number for each geometry was recorded to determine any relationship between edge Mach number and the stability of first mode waves. Results indicate that an axisymmetric cone with a sharp nose and a slight flare at the aft end under the Mach 6 freestream conditions used here will lower the Mach number at the edge of the boundary layer to less than 4, and the corresponding stability analysis showed maximum first mode N factors of 3.

Kirk, Lindsay C.↗
NASA NTRS2012

JUNO Photovoltaic Power at Jupiter

This paper summarizes the Juno modeling team work on predicting the Juno solar array performance at critical mission points including Juno Orbit Insertion (JOI) and End of Mission (EOM). This report consists of background on Juno solar array design, a summary of power estimates, an explanation of the modeling approach used by Aerospace, a detailed discussion of loss factors and performance predictions, a thermal analysis, and a review of risks to solar array performance

solar powered mission↗
NASA NTRS2012

Cognitive Systems Engineering: The Next 30 Years

This presentation is part of panel discussion on Cognitive Systems Engineering. The purpose of this panel is to discuss the challenges and future directions of Cognitive Systems Engineering for the next 30 years. I intended to present the work we have been doing with the Aviation Safety program and Space Human Factors Engineering project on Work Domain Analysis and some areas of Research Focus. Specifically, I intend to focus on the shift on the need to understand and model attention in mixed-initiative systems, the need for methods which can generate results to be used in trade-off decisions, and the need to account for a range of human behavior in the design.

Feary, Michael↗
NASA NTRS2016

SUPIN: A Computational Tool for Supersonic Inlet Design

A computational tool named SUPIN is being developed to design and analyze the aerodynamic performance of supersonic inlets. The inlet types available include the axisymmetric pitot, three-dimensional pitot, axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flow-field is divided into parts to provide a framework for the geometry and aerodynamic modeling. Each part of the inlet is defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick design and analysis. SUPIN provides inlet geometry in the form of coordinates, surface angles, and cross-sectional areas. SUPIN can generate inlet surface grids and three-dimensional, structured volume grids for use with higher-fidelity computational fluid dynamics (CFD) analysis. Capabilities highlighted in this paper include the design and analysis of streamline-traced external-compression inlets, modeling of porous bleed, and the design and analysis of mixed-compression inlets. CFD analyses are used to verify the SUPIN results.

computational fluid dynamics↗
NASA NTRS2016

The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type

As atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-View Sensor (SeaWiFS) algorithm atmospheric correction with approximately 13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD(sub 440)) is overestimated for AOD below approximately 0.1-0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value less than approximately 0.96.AOD(sub 440) and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.

single scattering albedo↗
NASA NTRS2016

Evaluation of Different MODIS AOD Retrieval Algorithms for PM (sub 2.5) Estimation in the Western, Midwestern and Southeastern United States with Implications for Public Health

This study was part of the research activities of the Center for Applied Atmospheric Research and Education (CAARE) funded by the NASA MUREP (Minority University Research and Education Project) Institutional Research Opportunity (MIRO) Program. Satellite measurements of Aerosol Optical Depth (AOD) have been shown to be correlated with ground measurements of fine particulate matter less than 2.5 microns PM (sub 2.5), which in turn has been linked to respiratory and heart diseases. The strength of the correlation between AOD and PM (sub 2.5) varies for different AOD retrieval algorithms and geographic regions. We evaluated several Moderate Resolution Imaging Spectrometer (MODIS) AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target versus Deep Blue), Collections (5.1 versus 6) and spatial resolutions (10-kilometers versus 3-kilometers) for cities in the Western, Midwestern and Southeastern U.S. We developed and validated PM (sub 2.5) prediction models using remotely-sensed AOD data, which were improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind speed, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the predictive power of all the PM (sub 2.5) models, especially in the Western U.S. Temperature, relative humidity and wind speed were the most significant meteorological variables throughout the year in the Western U.S. Wind speed was the most significant meteorological variable for the cold season while temperature was the most significant variable for the warm season in the Midwestern and Southeastern U.S. Our study re-establishes the connection between PM (sub 2.5) and public health concerns including respiratory and cardiovascular diseases (asthma, high blood pressure, coronary heart disease, heart attack, and stroke). Using PM (sub 2.5) data and health data from the Centers for Disease Control and Prevention (CDC)'s Behavioral Risk Factor Surveillance System (BRFSS), our statistical analysis showed that heart attack and stroke occurrences had the strongest correlations with PM (sub 2.5).

Environmental Public Health↗
NASA NTRS2018

Mitigation of Polystyrene Microsphere Surface Contamination for Wind Tunnel Applications

Polystyrene latex (PSL) microspheres have been utilized as seed material for flow visualization in wind tunnels. However, PSL microspheres have been observed to strongly adhere to wind tunnel and model surfaces. Surface contamination on the cleaning screens that remove vorticity and provide laminar flow in the test section, is particularly problematic. Agglomeration of particles on these screens cause constriction of the airflow through the screen resulting in inconsistent airflow properties in the test section. The adhesion mechanism of PSL microspheres to wind tunnel screens and 316 stainless steel flat plates, were evaluated in a contamination apparatus where small sections of screen material were exposed to PSL-seeded airflow. Using a design of experiments (DOE) methodology airflow seeding parameters were changed to evaluate how these modifications affected the degree of surface contamination. The solution composition, comprised of ethanol and water, was determined to be the most significant factor in particle adhesion. Utilizing image analysis software, data were collected from the contaminated surfaces and incorporated to generate predictive particle contamination models. A relationship was identified between the solvent evaporation rate, and the morphology and magnitude of PSL contaminants on the test surfaces. This analysis can be extended to other solvent mixtures to provide insight into simultaneously improving wind tunnel testing capabilities while diminishing facility contamination.

Wohl, Christopher J.↗
NASA NTRS2019

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗
NASA NTRS2022

Greenhouse Gas Emission Estimations for 2016-2020 using the Sherlock Air Traffic Data Warehouse

Data and analyses are presented on the utilization of aircraft in the U.S. and the greenhouse gas emissions that they create. Commercial passenger and cargo aviation flight data, captured in the Sherlock data warehouse at NASA Ames over the five years from 2016 to 2020, is used to estimate the miles flown by major aircraft models. The estimates for aggregate annual number of flights are validated against data published by the Bureau of Transportation Statistics. The corresponding fuel usage is estimated using the International Civilian Aviation Organization (ICAO) fuel use tables and carbon dioxide emissions are calculated using a fuel-use multiplicative factor. A key conclusion of this analysis is that a small number of long-haul flights (with ranges greater than 2485 statute miles) create a disproportionately large fraction (30%) of annual total U.S. aviation-related carbon dioxide emissions, while a relatively large number of short flights (less than 311 statute miles) contribute a small net amount (less than 5%) of U.S. aviation-related carbon dioxide emissions. These U.S. results are consistent with a similar recent 2020 emissions study conducted by EUROCONTROL.

Emissions↗
NASA NTRSDate not supplied

Historical Domestic Flights from 2016-2020 with Estimations of Greenhouse Gas Emissions by Aircraft Type

Data and analyses are presented on the utilization of aircraft fuel in the U.S. and the greenhouse gas emissions that they create. Aggregated commercial passenger and freight aviation flight data from 2016-2020 is captured from the Bureau of Transportation Statistics website is used to augment flight data from the Sherlock data warehouse at NASA Ames is used to determine the miles flown by major aircraft models. The corresponding fuel burn is estimated using the International Civilian Aviation Organization fuel burn tables and carbon dioxide emissions are calculated using a fuel-burn multiplicative factor. One key conclusion of this analysis is that long haul flights (i.e. >2485 statute miles) create a disproportionately large amount of carbon dioxide emissions in the U.S while short flights (i.e. < 311 statute miles) contribute less than five percent of the U.S. aviation-related carbon dioxide emission. Although these short-haul flights may not have a large impact on overall carbon dioxide emissions, they will be a critical entry point for the adoption of future, larger fuel-efficient novel vehicles and the impact to future airport and infrastructure requirements. The final paper will present some estimates of the impact of advanced technologies on fuel burn and CO₂ emissions in various scenarios.

Susie Go↗