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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Ares I-X Flight Data Evaluation: Executive Overview

NASA's Constellation Program (CxP) successfully launched the Ares I-X flight test vehicle on October 28, 2009. The Ares I-X flight was a developmental flight test to demonstrate that this very large, long, and slender vehicle could be controlled successfully. The flight offered a unique opportunity for early engineering data to influence the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office (APO) established a set of 33 flight evaluation tasks to correlate flight results with prospective design assumptions and models. The flight evaluation tasks used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. Included within these tasks were direct comparisons of flight data with preflight predictions and post-flight assessments utilizing models and processes being applied to design and develop Ares I. The benefits of early development flight testing were made evident by results from these flight evaluation tasks. This overview provides summary information from assessment of the Ares I-X flight test data and represents a small subset of the detailed technical results. The Ares Projects Office published a 1,600-plus-page detailed technical report that documents the full set of results. This detailed report is subject to the International Traffic in Arms Regulations (ITAR) and is available in the Ares Projects Office archives files.

Huebner, Lawrence D.↗
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 NTRS2001

The Vertical Error Characteristics of GOES-derived Winds: Description and Impact on Numerical Weather Prediction

Errors in the height assignment of some satellite-derived winds exist because the satellites sense radiation emitted from a finite layer of the atmosphere rather than a specific level. Potential problems in data assimilation may arise because the motion of a measured layer is often represented by a single-level value. In this research, cloud and water vapor motion winds that are derived from the Geostationary Operational Environmental Satellites (GOES winds) are compared to collocated rawinsonde observations (RAOBs). An important aspect of this work is that in addition to comparisons at each assigned height, the GOES winds are compared to the entire profile of the collocated RAOB data to determine the vertical error characteristics of the GOES winds. The impact of these results on numerical weather prediction is then investigated. The comparisons at individual vector height assignments indicate that the error of the GOES winds range from approx. 3 to 10 m/s and generally increase with height. However, if taken as a percentage of the total wind speed, accuracy is better at upper levels. As expected, comparisons with the entire profile of the collocated RAOBs indicate that clear-air water vapor winds represent deeper layers than do either infrared or water vapor cloud-tracked winds. This is because in cloud-free regions the signal from water vapor features may result from emittance over a thicker layer. To further investigate characteristics of the clear-air water vapor winds, they are stratified into two categories that are dependent on the depth of the layer represented by the vector. It is found that if the vertical gradient of moisture is smooth and uniform from near the height assignment upwards, the clear-air water vapor wind tends to represent a relatively deep layer. The information from the comparisons is then used in numerical model simulations of two separate events to determine the forecast impacts. Four simulations are performed for each case: 1) A control simulation that assimilates no satellite wind data, 2) assimilation of all GOES winds according to their assigned single level height, 3) assimilation of all GOES winds spread over multiple levels, and 4) assimilation of all GOES winds spread over multiple levels, but with variations in the vertical influence of clear-air water vapor winds based on the moisture profile in the model. In the first case, a strong mid-latitude cyclone is present and the use of the satellite data results in improved storm tracks during the initial approx. 36 h forecast period. This is because the satellite data improves the analysis of the environment into which the storm progresses. Statistics for mean wind vector and height differences show that, with the exception of the height field at later times in the first case, the use of GOES winds improves the simulation with time. The simulation results suggest that it is beneficial to spread the GOES wind information over multiple levels, particularly when the moisture profile is used to define the vertical influence.

Rao, P. Anil↗
NASA NTRS1986

Machine vision and the OMV

The orbital Maneuvering Vehicle (OMV) is intended to close with orbiting targets for relocation or servicing. It will be controlled via video signals and thruster activation based upon Earth or space station directives. A human operator is squarely in the middle of the control loop for close work. Without directly addressing future, more autonomous versions of a remote servicer, several techniques that will doubtless be important in a future increase of autonomy also have some direct application to the current situation, particularly in the area of image enhancement and predictive analysis. Several techniques are presentet, and some few have been implemented, which support a machine vision capability proposed to be adequate for detection, recognition, and tracking. Once feasibly implemented, they must then be further modified to operate together in real time. This may be achieved by two courses, the use of an array processor and some initial steps toward data reduction. The methodology or adapting to a vector architecture is discussed in preliminary form, and a highly tentative rationale for data reduction at the front end is also discussed. As a by-product, a working implementation of the most advanced graphic display technique, ray-casting, is described.

Mcanulty, M. A.↗
NASA NTRS1998

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Larson, Jay W.↗
NASA NTRS2007

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗
NASA NTRS2012

Physics Based Modeling and Prognostics of Electrolytic Capacitors

This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors have become critical components in electronics systems in aeronautics and other domains. Degradations and faults in DC-DC converter unit propagates to the GPS and navigation subsystems and affects the overall solution. Capacitors and MOSFETs are the two major components, which cause degradations and failures in DC-DC converters. This type of capacitors are known for its low reliability and frequent breakdown on critical systems like power supplies of avionics equipment and electrical drivers of electromechanical actuators of control surfaces. Some of the more prevalent fault effects, such as a ripple voltage surge at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, if not corrected will propagate and distort the navigation solution. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

Kulkarni, Chetan↗
NASA NTRSDate not supplied

Predicting Air Traffic Management Initiatives Using Supervised Learning

Terminal Traffic Management Initiatives (TMIs) such as Ground Stops (GS) and Ground Delay Programs (GDP) are implemented to manage excess demand or lowered capacity at an airport. Air Traffic Flow Management (TFM) specialists identify situations such as aviation constraints, current and forecasted weather conditions, airport demand and capacity, and initiate TMIs for safe and orderly movement of air traffic. In this paper, we outline supervised learning techniques that can be used to predict and recommend TMIs at an airport based on current weather and airport conditions. Our research involves building classic Machine Learning (ML) models such as Logistic Regression, K-Nearest Neighbor, Random Forest and XGBoost, as well as Long short-term memory (LSTM) networks. We trained the models on 3-year historical data (weather, airport demand, capacity and TMIs) from Newark (EWR) airport which was selected based on its higher TMI implementation rates and varied weather conditions. Although Random Forest and XGBoost algorithms are able to predict if a TMI is needed or not, they have difficulty in predicting specific program type. For this purpose, we found that LSTM time-series forecasting models performed better as they also learn from past TMI program type sequences. This study also lays down the foundation for advanced modeling techniques and architectures to predict TMIs in advance for future periods. The ability to predict TMIs in advance will be highly beneficial to the traffic controllers and managers as this will help them to prepare for and manage TMIs more efficiently.

Manoj Agrawal↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

NASA has employed high-throughput molecular assays to identify sub-cellular changes impacting human physiology during spaceflight. Machine learning (ML) methods hold the promise to improve our ability to identify important signals within highly dimensional molecular data. However, the inherent limitation of study subject numbers within a spaceflight mission minimizes the utility of ML approaches. To overcome the sample power limitations, data from multiple spaceflight missions must be aggregated while appropriately addressing intra- and inter-study variabilities. Here we describe an approach to log transform, scale and normalize data from six heterogeneous, mouse liver derived transcriptomics datasets (ntotal=137) which enabled ML-methods to perform well (AUC ≥ 0.87) in classifying spaceflown vs ground control animals rather than mission-of-origin. Concordance was found between liver-specific biological processes identified from harmonized ML-based analysis and study-by-study classical omics analysis. This work demonstrates the feasibility of applying ML methods on integrated, heterogeneous datasets of small sample size.

Machine Learning↗
NASA NTRS1992

How to handle 6GBytes a night and not get swamped

The Macho Project has undertaken a 5 year effort to search for dark matter in the halo of the Galaxy by scanning the Magellanic Clouds for micro-lensing events. Each evening's raw image data will be reduced in real-time into the observed stars' photometric measurements. The actual search for micro-lensing events will be a post-processing operation. The theoretical prediction of the rate of such events necessitates the collection of a large number of repeated exposures. The project designed camera subsystem delivers 64 Mbytes per exposure with exposures typically occurring every 500 seconds. An ideal evening's observing will provide 6 Gbytes of raw image data and 40 Mbytes of reduced photometric measurements. Recognizing the difficulty of digging out from a snowballing cascade of raw data, the project requires the real-time reduction of each evening's data. The software team's implementation strategy centered on this non-negotiable mandate. Accepting the reality that 2 full time people needed to implement the core real-time control and data management system within 6 months, off-the-shelf vendor components were explored to provide quick solutions to the classic needs for file management, data management, and process control. Where vendor solutions were lacking, state-of-the-art models were used for hand tailored subsystems. In particular, petri nets manage process control, memory mapped bulletin boards provide interprocess communication between the multi-tasked processes, and C++ class libraries provide memory mapped, disk resident databases. The differences between the implementation strategy and the final implementation reality are presented. The necessity of validating vendor product claims are explored. Both the successful and hindsight decisions enabling the collection and processing of the nightly data barrage are reviewed.

Allsman, R.↗
NASA NTRS2000

Results From F-18B Stability and Control Parameter Estimation Flight Tests at High Dynamic Pressures

A maximum-likelihood output-error parameter estimation technique has been used to obtain stability and control derivatives for the NASA F-18B Systems Research Aircraft. This work has been performed to support flight testing of the active aeroelastic wing (AAW) F-18A project. The goal of this research is to obtain baseline F-18 stability and control derivatives that will form the foundation of the aerodynamic model for the AAW aircraft configuration. Flight data have been obtained at Mach numbers between 0.85 and 1.30 and at dynamic pressures ranging between 600 and 1500 lbf/sq ft. At each test condition, longitudinal and lateral-directional doublets have been performed using an automated onboard excitation system. The doublet maneuver consists of a series of single-surface inputs so that individual control-surface motions cannot be correlated with other control-surface motions. Flight test results have shown that several stability and control derivatives are significantly different than prescribed by the F-18B aerodynamic model. This report defines the parameter estimation technique used, presents stability and control derivative results, compares the results with predictions based on the current F-18B aerodynamic model, and shows improvements to the nonlinear simulation using updated derivatives from this research.

Moes, Timothy R.↗
NASA NTRS2011

Six-Tube Freezable Radiator Testing and Model Correlation

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recovering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TradeMark) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested, namely MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Lillibridge, Sean↗
NASA NTRS2017

Ground Collision Avoidance System (Igcas)

The present invention is a system and method for aircraft ground collision avoidance (iGCAS) comprising a modular array of software, including a sense own state module configured to gather data to compute trajectory, a sense terrain module including a digital terrain map (DTM) and map manger routine to store and retrieve terrain elevations, a predict collision threat module configured to generate an elevation profile corresponding to the terrain under the trajectory computed by said sense own state module, a predict avoidance trajectory module configured to simulate avoidance maneuvers ahead of the aircraft, a determine need to avoid module configured to determine which avoidance maneuver should be used, when it should be initiated, and when it should be terminated, a notify Module configured to display each maneuver's viability to the pilot by a colored GUI, a pilot controls module configured to turn the system on and off, and an avoid module configured to define how an aircraft will perform avoidance maneuvers through 3-dimensional space.

Skoog, Mark A↗
NASA NTRS2006

A Case for Developing a Ground Based Replication of the Earth, Moon and Mars Spaceflight Infrastructure

When the systems are developed and in place to provide the services needed to operate en route and on the Lunar and Martian surfaces, an Earth based replication will need to be in place for the safety and protection of mission success. The replication will entail all aspects of the flight configuration end to end but will not include any closed loop systems. This would replicate the infrastructure from Lunar and Martian robots, manned surface excursions, through man and unmanned terrestrial bases, through the various types of communication systems and technologies, manned and un-manned space vehicles (large and small), to Earth based systems and control centers. An Earth based replicated infrastructure will enable checkout and test of new technologies, hardware, software updates and upgrades and procedures without putting humans and missions at risk. Analysis of events, what ifs and trouble resolution could be played out on the ground to remove as much risk as possible from any type of proposed change to flight operational systems. With adequate detail, it is possible that failures could be predicted with a high probability and action taken to eliminate failures. A major factor in any mission to the Moon and to Mars is the complexity of systems, interfaces, processes, their limitations, associated risks and the factor of the unknown including the development by many contractors and NASA centers. The need to be able to introduce new technologies over the life of the program requires an end to end test bed to analyze and evaluate these technologies and what will happen when they are introduced into the flight system. The ability to analyze system behaviors end to end under varying conditions would enhance safety e.g. fault tolerances. This analysis along with the ability to mine data from the development environment (e.g. test data), flight ops and modeling/simulations data would provide a level of information not currently available to operations and astronauts. In this paper we will analyze the beginnings of such a replication and what it could do in terms of reducing risk in the near term for development. We will analyze the Space Shuttle Main Engine (SSME) test lab which has to a large extent accomplished this replication for the SSME and has been highly successful in analyzing hardware and software problems and changes. The cost of replicating the flight system as proposed here could be very high if attempted as an afterthought. We will describe the initial steps for the development of a replication of this infrastructure starting with the communication infrastructure. The Constellation of Labs (CofL) under the Command, Control, Communication and Information (C3I) project for the NASA Exploration Initiative will provide the initial foundation upon which to base this replication. Simply put, there is very little margin for error in high latency situations e.g. en-route to/from Mars or in an autonomous process on the Lunar far side. Any thought out approach to reduce risk and increase safety needs to be accomplished end to end with the actual systems configuration.

Bradford, Robert N.↗
NASA NTRS2018

Synthesizing a New Launch Vehicle Failure Probability Based on Historical Flight Data

New launch vehicles have historically had significantly higher failure rates in early flights than what has been predicted using Probabilistic Risk Assessment - PRA. This is because PRAs typically model a mature vehicle where a significant portion of the early failure probability contributors have been eliminated due to testing and improvements after actual field operation. To capture a more accurate early flight failure probability estimate, this paper develops a method that estimates ascent failure probability starting with the first flight based on historical launch vehicle records. With new launch vehicles being developed, such as the Space Launch System - SLS, a PRA model must be extended to cover early flight failure probability contributions that are either not covered in the mature-vehicle PRA or are underestimated. These failure probability contributions include design errors, quality control deficiencies, installation errors, and environmental impacts. There are also failure dependencies due to systemic errors that still exist due to limited entire-system testing.

Cross, Robert B.↗
NASA NTRS1972

A study of pilot modeling in multi-controller tasks

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem.

Whitbeck, R. F.↗
NASA NTRS1990

Final shuttle-derived atmospheric database: Development and results from thirty-two flights

The final Shuttle-derived atmospheric data base is presented. The relational data base is comprised of data from 32 Space Transportation System (STS) descent flights, to include available meteorology data taken in support of each flight. For the most part, the available data are restricted to the middle atmosphere. In situ accelerations, sensed by the tri-redundant Inertial Measurement Unit (IMU) to an accuracy better than 1 mg, are combined with post-flight Best Estimate Trajectory (BET) information and predicted, flight-substantiated Orbiter aerodynamics to provide determinations up to altitudes of 95 km. In some instances, alternate accelerometry data with micro-g resolution were utilized to extend the data base well into the thermosphere. Though somewhat limited, the ensemble of flights permit a reasonable sampling of monthly, seasonal, and latitudinal variations which can be utilized for atmospheric science investigations and model evaluations and upgrades as appropriate. More significantly, the unparallel vertical resolution in the Shuttle-derived results indicate density shears normally associated with internal gravity waves or local atmospheric instabilities. Consequently, these atmospheres can also be used as stress-atmospheres for Guidance, Navigation and Control (GN and C) system development and analysis as part of any advanced space vehicle design activities.

Findlay, John T.↗
NASA NTRS1999

PTA1 Helium Pressurization System Model

A transient model of the Propulsion Test Article 1 (PTA1) Helium Pressurization System was developed using the Generalized Fluid System Simulation Program (GFSSP). The model included feed lines from the facility interface to the engine purge interface and Liquid Oxygen (LOX) and Rocket Propellant 1 (RP-1) tanks, the propellant tanks themselves including ullage space and propellant feed lines to their respective pump interfaces. GFSSPs capability was extended to model a control valve to maintain ullage pressure within a specified limit and pressurization processes such as heat transfer between ullage gas, propellant and the tank wall. The purpose of the model is to predict the flow system characteristics in the entire pressurization system during 80 seconds of pre-pressurization operation, 420 seconds of pressurization stand-by operation and 150 seconds of engine operation. Subsequent to the work presented here, the PTA1 model has been updated to include the LOX and RP-1 pumps, while the pressurization option itself has been modified to include the effects of mass transfer. This updated model will be compared with PTA1 test data as it becomes available.

Steadman, Todd↗