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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Artificial intelligence applied to process signal analysis

Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

Corsberg, Dan↗
NASA NTRS1992

A classification procedure for the effective management of changes during the maintenance process

During software operation, maintainers are often faced with numerous change requests. Given available resources such as effort and calendar time, changes, if approved, have to be planned to fit within budget and schedule constraints. In this paper, we address the issue of assessing the difficulty of a change based on known or predictable data. This paper should be considered as a first step towards the construction of customized economic models for maintainers. In it, we propose a modeling approach, based on regular statistical techniques, that can be used in a variety of software maintenance environments. The approach can be easily automated, and is simple for people with limited statistical experience to use. Moreover, it deals effectively with the uncertainty usually associated with both model inputs and outputs. The modeling approach is validated on a data set provided by NASA/GSFC which shows it was effective in classifying changes with respect to the effort involved in implementing them. Other advantages of the approach are discussed along with additional steps to improve the results.

Briand, Lionel C.↗
NASA NTRS1980

Mark 3 correlator hardware and software

The Mark 3 correlator system is described in some detail. The correlator system is based on a modular philosophy. Each correlator module independently processes the data from one track pair. Therefore, 28 modules are necessary to complete a full one baseline processor and 84 modules for a full 3 baseline processor. Each correlator module has two interfaces: (1) data and clock from each of the two tracks to be correlated and (2) Computer Automated Measurement and Control (CAMAC) dataway interface to the computer. The processor is organized around the IEEE CAMAC standard architecture, housing 15 correlator modules in each of 6 crates. This allows one pass processing of a full 3 baseline 28 track observation or a 6 baseline (4 station) 14 track observation. The correlator architecture allows easy expansion for up to 8 stations. The computer system is an HP 1000 system utilizing a 16 bit minicomputer with disc and tape peripherals. The processing software is also organized in a modular fashion with many independent but cooperative programs controlling the operation of the Mark 3 processor. Processing time through the correlator is normally real time or faster, with graphics displays providing real time monitor and control of the processing operation.

Whitney, A. R.↗
NASA NTRS1985

Permanent presence - Making it work; Proceedings of the Twenty-second Goddard Memorial Symposium, Greenbelt, MD, March 15, 16, 1984

Among the topics discussed are: electrophoresis operations in space for pharmaceutical processing; Space Station program operations; and Space Station platform configurations. Consideration is also given to: the human role in future space systems; EVA operations; spherical shell applications; and a container material for alloy processing in near-zero gravity. Among additional topics discussed are: Space Station platform thermal control; environmental control and life support for an evolving capability manned Space Station; and the commercial prospects of the Space Station.

Bekey, I.↗
NASA NTRS1986

Historical data and analysis for the first five years of KSC STS payload processing

General and specific quantitative and qualitative results were identified from a study of actual operational experience while processing 186 science, applications, and commercial payloads for the first 5 years of Space Transportation System (STS) operations at the National Aeronautics and Space Administration's (NASA) John F. Kennedy Space Center (KSC). All non-Department of Defense payloads from STS-2 through STS-33 were part of the study. Historical data and cumulative program experiences from key personnel were used extensively. Emphasis was placed on various program planning and events that affected KSC processing, payload experiences and improvements, payload hardware condition after arrival, services to customers, and the impact of STS operations and delays. From these initial considerations, operational drivers were identified, data for selected processing parameters collected and analyzed, processing criteria and options determined, and STS payload results and conclusions reached. The study showed a significant reduction in time and effort needed by STS customers and KSC to process a wide variety of payload configurations. Also of significance is the fact that even the simplest payloads required more processing resources than were initially assumed. The success to date of payload integration, testing, and mission operations, however, indicates the soundness of the approach taken and the methods used.

Ragusa, J. M.↗
NASA NTRS1993

The FOT tool kit concept

Flight operations and the preparation for it has become increasingly complex as mission complexities increase. Further, the mission model dictates that a significant increase in flight operations activities is upon us. Finally, there is a need for process improvement and economy in the operations arena. It is therefore time that we recognize flight operations as a complex process requiring a defined, structured, and life cycle approach vitally linked to space segment, ground segment, and science operations processes. With this recognition, an FOT Tool Kit consisting of six major components designed to provide tools to guide flight operations activities throughout the mission life cycle was developed. The major components of the FOT Tool Kit and the concepts behind the flight operations life cycle process as developed at NASA's GSFC for GSFC-based missions are addressed. The Tool Kit is therefore intended to increase productivity, quality, cost, and schedule performance of the flight operations tasks through the use of documented, structured methodologies; knowledge of past lessons learned and upcoming new technology; and through reuse and sharing of key products and special application programs made possible through the development of standardized key products and special program directories.

Fatig, Michael↗
NASA NTRS1992

Processing lunar soils for oxygen and other materials

Two types of lunar materials are excellent candidates for lunar oxygen production: ilmenite and silicates such as anorthite. Both are lunar surface minable, occurring in soils, breccias, and basalts. Because silicates are considerably more abundant than ilmenite, they may be preferred as source materials. Depending on the processing method chosen for oxygen production and the feedstock material, various useful metals and bulk materials can be produced as byproducts. Available processing techniques include hydrogen reduction of ilmenite and electrochemical and chemical reductions of silicates. Processes in these categories are generally in preliminary development stages and need significant research and development support to carry them to practical deployment, particularly as a lunar-based operation. The goal of beginning lunar processing operations by 2010 requires that planning and research and development emphasize the simplest processing schemes. However, more complex schemes that now appear to present difficult technical challenges may offer more valuable metal byproducts later. While they require more time and effort to perfect, the more complex or difficult schemes may provide important processing and product improvements with which to extend and elaborate the initial lunar processing facilities. A balanced R&D program should take this into account. The following topics are discussed: (1) ilmenite--semi-continuous process; (2) ilmenite--continuous fluid-bed reduction; (3) utilization of spent ilmenite to produce bulk materials; (4) silicates--electrochemical reduction; and (5) silicates--chemical reduction.

Knudsen, Christian W.↗
NASA NTRS2012

Automation and Process Improvement Enables a Small Team to Operate a Low Thrust Mission in Orbit Around the Asteroid Vesta

NASA's Dawn mission to the asteroid Vesta and dwarf planet Ceres launched September 27, 2007 and arrived at Vesta in July of 2011. This mission uses ion propulsion to achieve the necessary delta-V to reach and maneuver at Vesta and Ceres. This paper will show how the evolution of ground system automation and process improvement allowed a relatively small engineering team to transition from cruise operations to asteroid operations while maintaining robust processes. The cruise to Vesta phase lasted almost 4 years and consisted of activities that were built with software tools, but each tool was open loop and required engineers to review the output to ensure consistency. Additionally, this same time period was characterized by the evolution from manually retrieved and reviewed data products to automatically generated data products and data value checking. Furthermore, the team originally took about three to four weeks to design and build about four weeks of spacecraft activities, with spacecraft contacts only once a week. Operations around the asteroid Vesta increased the tempo dramatically by transitioning from one contact a week to three or four contacts a week, to fourteen contacts a week (every 12 hours). This was accompanied by a similar increase in activity complexity as well as very fast turn around activity design and build cycles. The design process became more automated and the tools became closed loop, allowing the team to build more activities without sacrificing rigor. Additionally, these activities were dependent on the results of flight system performance, so more automation was added to analyze the flight data and provide results in a timely fashion to feed the design cycle. All of this automation and process improvement enabled up the engineers to focus on other aspects of spacecraft operations, including spacecraft health monitoring and anomaly resolution.

ground system automation↗
NASA NTRS1986

Historical data retrieval study - Results for the first five years of KSC STS payload processing

This paper identifies general and specific quantitative and qualitative results from a study of actual operational experiences while processing 185 science, applications, and commercial payloads for the first five years of STS operations at NASA's Kennedy Space Center (KSC). All the non-DOD payloads from STS-2 through STS-33 were part of the study. The emphasis was placed on various program planning and events that affected KSC processing, payload experiences and improvements, payload hardware condition after arrival, services to customers, and the impact of STS operations and delays. From these initial considerations, operational drivers were identified, data for selected processing measurements collected and analyzed, processing criteria and options determined, and STS payload results and conclusions reached. The study showed a significant reduction in time and effort needed by STS customers and KSC to process a wide variety of payload configurations, although even the simplest payloads required more processing resources and time than were initially assumed.

Ragusa, J. M.↗
NASA NTRS2013

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters : Synthetic Sensor Radiance Formulation - Pt. 1

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

Simulations↗
NASA NTRS2013

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters: Equivalent Sensor Radiance Formulation - Part 1

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

Simulations↗
NASA NTRS2017

Earth Observing System (EOS) Aqua and Aura Space Weather Effects on Operational Collision Avoidance

This presentation will describe recent EOS Aqua and Aura operational collision avoidance experience during periods of solar and geomagnetic storm activity. It will highlight challenges faced by the operations team during short-notice, high-risk predicted close approaches. The presentation will highlight the evolution of the operational collision avoidance process for the EOS Aqua and Aura missions. The presentation will highlight operational challenges that have occurred, process improvements that have been implemented and identify potential future challenges.

Guit, Bill↗
NASA NTRS2002

Planning Systems for Distributed Operations

This viewgraph representation presents an overview of the mission planning process involving distributed operations (such as the International Space Station (ISS)) and the computer hardware and software systems needed to support such an effort. Topics considered include: evolution of distributed planning systems, ISS distributed planning, the Payload Planning System (PPS), future developments in distributed planning systems, Request Oriented Scheduling Engine (ROSE) and Next Generation distributed planning systems.

Maxwell, Theresa G.↗
NASA NTRSDate not supplied

Comparing Satellite Measurements of Volcanic SO2 Mass from OMI, OMPS and TROPOMI

Sulfur dioxide (SO2) is a major air pollutant that contributes to acid rain and aerosol formation (e.g., sulfates), adversely affects the environment and human health, and explosive volcanic SO2 emissions can impact climate. The majority of SO2 emissions are related to anthropogenic processes (e.g., fossil fuel burning, metal ore smelting operations), although natural processes such as volcanic eruptions and degassing also play an important role as anthropogenic SO2 emissions continue to decline. Generally, the most interest in volcanoes occurs during major eruptions. We will focus on comparing volcanic SO2 outgassing that occurs on an almost daily basis from lesser known volcanoes using satellite data. At NASA’s Global Sulfur Dioxide Monitoring Home page (https://so2.gsfc.nasa.gov/), we have been posting daily SO2 maps from 40 volcanic and industrial regions around the world using measurements from three satellite instruments; the Ozone Monitoring Instrument (OMI) onboard NASA’s Earth Observing System Aura satellite, the Ozone Monitoring and Profiler Suite (OMPS) onboard the NASA-NOAA Suomi National Polar-orbiting Partnership (NPP) satellite, and the TROPOspheric Monitoring Instrument (TROPOMI) onboard the ESA/Copernicus Sentinel-5 Precursor satellite. These instruments in low Earth sun-synchronous polar orbits with 1:30-2:00 pm equator crossing local time provide daily SO2 maps at different spatial resolutions: 13 x 24 km2, 50 x 50 km2 and 5.5 x 3.5 km2 for OMI, OMPS and TROPOMI respectively. Data from OMI are available since October 2004 (partial coverage since 2008), from OMPS since 2012 and from TROPOMI since 2018. We will present comparative SO2 mass time-series (see Hunga-Tonga plot) and statistical analyses of recent eruptions that have data from all the instruments.

SO2↗
NASA NTRS1994

Use of a multimission system for cost effective support of planetary science data processing

JPL's Multimission Operations Systems Office (MOSO) provides a multimission facility at JPL for processing science instrument data from NASA's planetary missions. This facility, the Multimission Image Processing System (MIPS), is developed and maintained by MOSO to meet requirements that span the NASA family of planetary missions. Although the word 'image' appears in the title, MIPS is used to process instrument data from a variety of science instruments. This paper describes the design of a new system architecture now being implemented within the MIPS to support future planetary mission activities at significantly reduced operations and maintenance cost.

Green, William B.↗
NASA NTRS2002

Process for a High Efficiency Class D Microwave Power Amplifier Operating in the S-Band

A process and product providing a High Efficiency Microwave Power Amplifier (HEMPA) which propagates S-Band microwave frequency square waves; utilizing a program simulating FETs at high DC-to-RF efficiencies, which analyses linear elements of selected FETs in a frequency domain, and non-linear elements of the FETs in a time domain, and converts the time domain values into the frequency domain, and performs DC and S-parameter simulated measurements based on predefined data for each FET. Individual FET parameters are extracted and isolated by converting the S-parameters to admittance or impedance parameters to derive FET models for each FET, which the program uses to provide a final output of a HEMPA circuit based on iterative simulations of an amplification circuit utilizing microwave topology and frequencies. Iterative simulations of the amplification circuit analyze output values of a plurality of cascaded stages of the FETs, which are arranged in a push-pull configuration.

William Herbert Sims, III↗
NASA NTRS1993

Process control and recovery in the Link Monitor and Control Operator Assistant

This paper describes our approach to providing process control and recovery functions in the Link Monitor and Control Operator Assistant (LMCOA). The focus of the LMCOA is to provide semi-automated monitor and control to support station operations in the Deep Space Network. The LMCOA will be demonstrated with precalibration operations for Very Long Baseline Interferometry on a 70-meter antenna. Precalibration, the task of setting up the equipment to support a communications link with a spacecraft, is a manual, time consuming and error-prone process. One problem with the current system is that it does not provide explicit feedback about the effects of control actions. The LMCOA uses a Temporal Dependency Network (TDN) to represent an end-to-end sequence of operational procedures and a Situation Manager (SM) module to provide process control, diagnosis, and recovery functions. The TDN is a directed network representing precedence, parallelism, precondition, and postcondition constraints. The SM maintains an internal model of the expected and actual states of the subsystems in order to determine if each control action executed successfully and to provide feedback to the user. The LMCOA is implemented on a NeXT workstation using Objective C, Interface Builder and the C Language Integrated Production System.

Lee, Lorrine↗