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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Automating Trend Analysis for Spacecraft Constellations

Spacecraft trend analysis is a vital mission operations function performed by satellite controllers and engineers, who perform detailed analyses of engineering telemetry data to diagnose subsystem faults and to detect trends that may potentially lead to degraded subsystem performance or failure in the future. It is this latter function that is of greatest importance, for careful trending can often predict or detect events that may lead to a spacecraft's entry into safe-hold. Early prediction and detection of such events could result in the avoidance of, or rapid return to service from, spacecraft safing, which not only results in reduced recovery costs but also in a higher overall level of service for the satellite system. Contemporary spacecraft trending activities are manually intensive and are primarily performed diagnostically after a fault occurs, rather than proactively to predict its occurrence. They also tend to rely on information systems and software that are oudated when compared to current technologies. When coupled with the fact that flight operations teams often have limited resources, proactive trending opportunities are limited, and detailed trend analysis is often reserved for critical responses to safe holds or other on-orbit events such as maneuvers. While the contemporary trend analysis approach has sufficed for current single-spacecraft operations, it will be unfeasible for NASA's planned and proposed space science constellations. Missions such as the Dynamics, Reconnection and Configuration Observatory (DRACO), for example, are planning to launch as many as 100 'nanospacecraft' to form a homogenous constellation. A simple extrapolation of resources and manpower based on single-spacecraft operations suggests that trending for such a large spacecraft fleet will be unmanageable, unwieldy, and cost-prohibitive. It is therefore imperative that an approach to automating the spacecraft trend analysis function be studied, developed, and applied to missions such as DRACO with the intent that mission operations costs be significantly reduced. The goal of the Constellation Spacecraft Trend Analysis Toolkit (CSTAT) project is to serve as the pathfinder for a fully automated trending system to support spacecraft constellations. The development approach to be taken is evolutionary. In the first year of the project, the intent is to significantly advance the state of the art in current trending systems through improved functionality and increased automation. In the second year, the intent is to add an expert system shell, likely through the adaptation of an existing commercial-off-the-shelf (COTS) or government-off-the-shelf (GOTS) tool to implement some level of the trending intelligence that humans currently provide in manual operations. In the third year, the intent is to infuse the resulting technology into a near-term constellation or formation-flying mission to test it and gain experience in automated trending. The lessons learned from the real missions operations experience will then be used to improve the system, and to ultimately incorporate it into a fully autonomous, closed-loop mission operations system that is truly capable of supporting large constellations. In this paper, the process of automating trend analysis for spacecraft constellations will be addressed. First, the results of a survey on automation in spacecraft mission operations in general, and in trending systems in particular will be presented to provide an overview of the current state of the art. Next, a rule-based model for implementing intelligent spacecraft subsystem trending will be then presented, followed by a survey of existing COTS/GOTS tools that could be adapted for implementing such a model. The baseline design and architecture of the CSTAT system will be presented. Finally, some results obtained from initial software tests and demonstrations will be presented.

Davis, George↗
NASA NTRS1993

NASA trend analysis procedures

This publication is primarily intended for use by NASA personnel engaged in managing or implementing trend analysis programs. 'Trend analysis' refers to the observation of current activity in the context of the past in order to infer the expected level of future activity. NASA trend analysis was divided into 5 categories: problem, performance, supportability, programmatic, and reliability. Problem trend analysis uncovers multiple occurrences of historical hardware or software problems or failures in order to focus future corrective action. Performance trend analysis observes changing levels of real-time or historical flight vehicle performance parameters such as temperatures, pressures, and flow rates as compared to specification or 'safe' limits. Supportability trend analysis assesses the adequacy of the spaceflight logistics system; example indicators are repair-turn-around time and parts stockage levels. Programmatic trend analysis uses quantitative indicators to evaluate the 'health' of NASA programs of all types. Finally, reliability trend analysis attempts to evaluate the growth of system reliability based on a decreasing rate of occurrence of hardware problems over time. Procedures for conducting all five types of trend analysis are provided in this publication, prepared through the joint efforts of the NASA Trend Analysis Working Group.

Source record↗
DOE OSTI2015

Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2 , SO 2 , PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

NASA standard: Trend analysis techniques

This Standard presents descriptive and analytical techniques for NASA trend analysis applications. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. Use of this Standard is not mandatory; however, it should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend Analysis is neither a precise term nor a circumscribed methodology, but rather connotes, generally, quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this Standard. The document presents the basic ideas needed for qualitative and quantitative assessment of trends, together with relevant examples. A list of references provides additional sources of information.

Source record↗
NASA NTRS1990

NASA standard: Trend analysis techniques

Descriptive and analytical techniques for NASA trend analysis applications are presented in this standard. Trend analysis is applicable in all organizational elements of NASA connected with, or supporting, developmental/operational programs. This document should be consulted for any data analysis activity requiring the identification or interpretation of trends. Trend analysis is neither a precise term nor a circumscribed methodology: it generally connotes quantitative analysis of time-series data. For NASA activities, the appropriate and applicable techniques include descriptive and graphical statistics, and the fitting or modeling of data by linear, quadratic, and exponential models. Usually, but not always, the data is time-series in nature. Concepts such as autocorrelation and techniques such as Box-Jenkins time-series analysis would only rarely apply and are not included in this document. The basic ideas needed for qualitative and quantitative assessment of trends along with relevant examples are presented.

Source record↗
NASA NTRS1992

Trend analysis for large solid rocket motors - A program level approach

This paper defines a program-level trend analysis effort that can be applied to large solid rocket motors. The effort is especially applicable to large segmented rocket motors such as the Space Transportation System's solid rocket boosters. Five types of trend analysis are discussed for different aspects of a rocket motor program, (performance, reliability, problem, supportability, and programmatic). Ideas are offered for implementing and performing a program-level trend analysis effort by giving suggestions for selecting computer capabilities, choosing parameters, selecting statistical processes, routine screening for trends, analyzing significant trends (for example, looking for related trends and determining if adverse trends are resolved), and reporting results of trend analysis. The use of program-level trending allows for the ability to easily transfer data between organizations and easily use the data to correlate trends from the various organizations to find causal relationships. Efficiency is enhanced from upper level management to the shop floor at vendor locations by using the same trend analysis software and methodology at all organizations.

Babbitt, Norman E., III↗
NASA NTRS1990

A case study in nonconformance and performance trend analysis

As part of NASA's effort to develop an agency-wide approach to trend analysis, a pilot nonconformance and performance trending analysis study was conducted on the Space Shuttle auxiliary power unit (APU). The purpose of the study was to (1) demonstrate that nonconformance analysis can be used to identify repeating failures of a specific item (and the associated failure modes and causes) and (2) determine whether performance parameters could be analyzed and monitored to provide an indication of component or system degradation prior to failure. The nonconformance analysis of the APU did identify repeating component failures, which possibly could be reduced if key performance parameters were monitored and analyzed. The performance-trending analysis verified that the characteristics of hardware parameters can be effective in detecting degradation of hardware performance prior to failure.

Maloy, Joseph E.↗
NASA NTRS1995

Trend analysis of in-situ spectral reflectance data from the Thermal Control Surfaces Experiment (TCSE)

The Thermal Control Surfaces Experiment (TCSE) on the LDEF was a comprehensive experiment that combined in-space measurements with extensive pre- and post-flight analyses of thermal control surfaces to determine the effects of exposure to the low earth orbit (LEO) space environment. The TCSE is the first space experiment to directly measure in-situ total hemispherical reflectance of thermal control surfaces in the same way they are routinely measured in the laboratory. In-space optical measurements performed by the TCSE provide the unique opportunity for trend analysis of the performance of materials in the space environment. Such trend analysis of flight data offers the potential to develop an empirical life time prediction model for several thermal control surfaces. For material research, trend analysis of the TCSE flight data, particularly the spectral data, can provide insight into the damage mechanisms of space exposure. Trend analysis for the TCSE samples has been limited to those materials that were not significantly eroded by the atomic oxygen (AO) environment. The performance of several materials on the LDEF mission was dominated by AO effects. Trend analysis was performed on both the detailed spectral reflectance measurements (in-space, pre-flight, and post-flight) and on the integrated solar absorptance. Results of this analysis for the five selected TCSE materials are presented along with the spectral flight data. Possible degradation and effects mechanisms will be discussed to better understand and predict the behavior of these materials in the LEO space environment.

Wilkes, Donald R.↗
NASA NTRS1977

Analyses of atmospheric extinction data obtained by astronomers. I - A time-trend analysis of data with internal accidental errors obtained at four observatories

Long-term time-trend analysis was performed on astronomical atmospheric extinction data in wideband UBV and various narrow-band systems recorded at Cerro Tololo, Kitt Peak, Lick, and McDonald observatories. All of the data had to be transformed into uniform monochromatic extinction data before trend analysis could be performed. The paper describes the various reduction techniques employed. The time-trend analysis was then carried out by the method of least squares. A special technique, called 'histogram shaping', was employed to adjust for the fact that the errors of the reduced monochromatic extinction data were not essentially Gaussian. On the assumption that there are no compensatory background and local extinction changes, the best values obtained for extinction trends due to background aerosol changes during the years 1960 to 1972 are 0.006 + or - 0.013 (rms) and 0.009 + or - 0.009 (rms) stellar magnitudes per air mass per decade in the blue and yellow wavelength regions, respectively.

Taylor, B. J.↗
DOE OSTI2020

Subsurface Trend Analysis domains for the northern Gulf of Mexico

Geologic domains for the northern Gulf of Mexico derived using the Subsurface Trend Analysis (STA) method. The domains were postulated using geologic province, lithologic, and structural information and validated using statistical methods. Publication detailing the STA method: Rose, K., Bauer, J.R., and Mark-Moser, M. (2020) Subsurface trend analysis, a multi-variate geospatial approach for subsurface evaluation and uncertainty reduction, Interpretation, vol. 8, issue 1 https://library.seg.org/doi/abs/10.1190/int-2019-0019.1 Detailed discussion of domain formation and analysis: Mark-Moser, M., Miller, R., Bauer, J., Rose, K., and C. Disenhof. 2018, Analysis of Subsurface Reservoir Properties Using a Novel Geospatial Approach, Offshore Gulf of Mexico. NETL-TRS-2018 https://edx.netl.doe.gov/dataset/detailed-analysis-of-geospatial-trends-of-hydrocarbon-accumulations-offshore-gulf-of-mexico

geology↗
NASA NTRS1994

Seasonal trend analysis of published ground-based and TOMS total ozone data through 1991

A seasonal trend analysis of published Dobson (including stations' newly revised and Brewer-simulated Dobson) total ozone data through 1991 from a network of 56 stations has been performed, using three different data periods. The trend results for the longest data period 1964 - 1991 indicate substantial negative trends in ozone in the higher northern latitudes during the winter and spring seasons, some evidence of negative trend in the higher southern latitudes (30 deg S - 55 deg S) during all seasons, and trends close to zero for all seasons over the 30 deg S - 30 deg N latitude range. For the shortest data period, November 1978 through 1991, there is a clear indication that trends have become more negative in the higher northern latitudes, especially during the winter and spring seasons, and also in the higher southern latitudes in all seasons. A seasonal trend analysis of zonal averages of total ozone mapping spectrometer (TOMS) satellite total ozone data for the comparable period November 1978 through 1991 has also been performed, and moderately good agreement is found between trends in Dobson and TOMS data over this period.

Reinsel, Gregory C.↗
NASA NTRS1990

The NASA trend analysis program

The four main areas of the NASA trend analysis program (problem/reliability, performance, supportability, and programmatic trending) are defined and illustrated with examples from Space Shuttle applications. Emphasis is on the programmatic-trending component of the program and several of the statistical techniques used. Also described is the NASA safety, reliability, maintainability, and quality assurance management information center, used to focus management attention on key near-term launch concerns and long-range mission trend issues.

Crawford, J. Larry↗
NASA NTRS1989

Lessons learned from trend analysis of Shuttle Payload Processing problem reports

In the wake of the Challenger accident, NASA has placed an increasing emphasis on trend analysis techniques. These analyses provide meaningful insights into system and hardware status, and also develop additional lessons learned from historical data to aid in the design and operation of future space systems. This paper presents selected results from such a trend analysis study that was conducted on the problem report data files for the Shuttle Payload Processing activities. Specifically, the results shown are for the payload canister system which interfaces with and transfers payloads from their processing facilities to the orbiter.

Heuser, Robert E.↗
NASA NTRS1990

STARS - Supportability Trend Analysis and Reporting System for the National Space Transportation System

The concept, implementation, and long-range goals of a Supportability Trend Analysis and Reporting System (STARS) for the National Space Transportation System (NSTS) are discussed. The requirement was established as a direct result of the recommendations of the Rogers Commission investigation of the circumstances of the Space Shuttle Challenger accident. STARS outlines the requirements for the supportability-trend data collection, analysis, and reporting requirements that each of the project offices supporting the Space Shuttle are required to provide to the NSTS program office. STARS data give the historic and predictive logistics information necessary for all levels of NSTS management to make safe and cost-effective decisions concerning the smooth flow of Space Shuttle turnaround.

Graham, Leroy J.↗