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At least 919 records · Page 51

Weather forecasting expert system study

Weather forecasting is critical to both the Space Transportation System (STS) ground operations and the launch/landing activities at NASA Kennedy Space Center (KSC). The current launch frequency places significant demands on the USAF weather forecasters at the Cape Canaveral Forecasting Facility (CCFF), who currently provide the weather forecasting for all STS operations. As launch frequency increases, KSC's weather forecasting problems will be great magnified. The single most important problem is the shortage of highly skilled forecasting personnel. The development of forecasting expertise is difficult and requires several years of experience. Frequent personnel changes within the forecasting staff jeopardize the accumulation and retention of experience-based weather forecasting expertise. The primary purpose of this project was to assess the feasibility of using Artificial Intelligence (AI) techniques to ameliorate this shortage of experts by capturing aria incorporating the forecasting knowledge of current expert forecasters into a Weather Forecasting Expert System (WFES) which would then be made available to less experienced duty forecasters.

Source record↗

Constraint-based scheduling

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocations for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its applications to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Zweben, Monte↗

Constraint-based scheduling

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Zweben, Monte↗

Constraint-based scheduling

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Zweben, Monte↗

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

Shaw, Michael↗

Real-time automated failure analysis for on-orbit operations

A system which is to provide real-time failure analysis support to controllers at the NASA Johnson Space Center Control Center Complex (CCC) for both Space Station and Space Shuttle on-orbit operations is described. The system employs monitored systems' models of failure behavior and model evaluation algorithms which are domain-independent. These failure models are viewed as a stepping stone to more robust algorithms operating over models of intended function. The described system is designed to meet two sets of requirements. It must provide a useful failure analysis capability enhancement to the mission controller. It must satisfy CCC operational environment constraints such as cost, computer resource requirements, verification, and validation. The underlying technology and how it may be used to support operations is also discussed.

Kirby, Sarah↗

Tropospheric Wind Monitoring During Day-of-Launch Operations for NASA's Space Shuttle Program

The Environments Group at the National Aeronautics and Space Administration's Marshall Space Flight Center monitors the winds aloft above Kennedy Space Center (KSC) in support of the Space Shuttle Program day-of-launch operations. Assessment of tropospheric winds is used to support the ascent phase of launch. Three systems at KSC are used to generate independent tropospheric wind profiles prior to launch; 1) high resolution jimsphere balloon system, 2) 50-MHz Doppler Radar Wind Profiler (DRWP) and 3) low resolution radiosonde system. All independent sources are compared against each other for accuracy. To assess spatial and temporal wind variability during launch countdown each jimsphere profile is compared against a design wind database to ensure wind change does not violate wind change criteria.

Decker, Ryan↗

NASA Scientific Data Purchase Project: From Collection to User

NASA's Scientific Data Purchase (SDP) project is currently a $70 million operation managed by the Earth Science Applications Directorate at Stennis Space Center. The SDP project was developed in 1997 to purchase scientific data from commercial sources for distribution to NASA Earth science researchers. Our current data holdings include 8TB of remote sensing imagery consisting of 18 products from 4 companies. Our anticipated data volume is 60 TB by 2004, and we will be receiving new data products from several additional companies. Our current system capacity is 24 TB, expandable to 89 TB. Operations include tasking of new data collections, archive ordering, shipment verification, data validation, distribution, metrics, finances, customer feedback, and technical support. The program has been included in the Stennis Space Center Commercial Remote Sensing ISO 9001 registration since its inception. Our operational system includes automatic quality control checks on data received (with MatLab analysis); internally developed, custom Web-based interfaces that tie into commercial-off-the-shelf software; and an integrated relational database that links and tracks all data through operations. We've distributed nearly 1500 datasets, and almost 18,000 data files have been downloaded from our public web site; on a 10-point scale, our customer satisfaction index is 8.32 at a 23% response level. More information about the SDP is available on our Web site.

Nicholson, Lamar↗

NASA's Autonomous Formation Flying Technology Demonstration, Earth Observing-1(EO-1)

NASA's first autonomous formation flying mission, the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft, recently completed its principal goal of demonstrating advanced formation control technology. This paper provides an overview of the evolution of an onboard system that was developed originally as a ground mission planning and operations tool. We discuss the Goddard Space Flight Center s formation flying algorithm, the onboard flight design and its implementation, the interface and functionality of the onboard system, and the implementation of a Kalman filter based GPS data smoother. A number of safeguards that allow the incremental phasing in of autonomy and alleviate the potential for mission-impacting anomalies from the on- board autonomous system are discussed. A comparison of the maneuvers planned onboard using the EO-1 autonomous control system to those from the operational ground-based maneuver planning system is presented to quantify our success. The maneuvers discussed encompass reactionary and routine formation maintenance. Definitive orbital data is presented that verifies all formation flying requirements.

Folta, David↗

Development of the Advanced Regolith Ground Operations (ARGO) Test Bed– A Robotic Construction Test Facility with Simulated Lunar Environments

NASA’s Artemis Program is working towards developing a sustained presence on the Moon and eventually Mars. To achieve this goal, robotic excavation, site preparation and construction technologies are under development to establish the capability to construct infrastructure such as launch/landing pads and radiation protection shelters. Technologies must be proven in simulated Lunar conditions prior surface demonstration missions. To that end, the Relevant Additive Construction Technology (REACT) Announcement of Collaboration Opportunities (ACO) project with AI Space Factory and the NASA Kennedy Space Center’s (KSC) Granular Mechanics and Regolith Operations Laboratory (a.k.a. Swamp Works) has developed the Advanced Regolith Ground Operations (ARGO) Test Bed. ARGO includes a ~1.5m x 1.5m x 1.2m (~5x5x4ft) vacuum chamber, cryogenically cooled thermal shroud, a 3-axis robotic positioning system, and a regolith bin. For the REACT project, a pellet extruder and feed hopper have been installed on ARGO to advance the Technology Readiness Level (TRL) of regolith-polymer composite Fused Deposition Modeling (FDM) additive construction systems, processes, and materials. This paper will focus on the design and operational characteristics of the ARGO Test Bed with pellet extruder.

Moon↗

Flight dynamics facility operational orbit determination support for the ocean topography experiment

The Ocean Topography Experiment (TOPEX/POSEIDON) mission is designed to determine the topography of the Earth's sea surface across a 3 yr period, beginning with launch in June 1992. The Goddard Space Flight Center Dynamics Facility has the capability to operationally receive and process Tracking and Data Relay Satellite System (TDRSS) tracking data. Because these data will be used to support orbit determination (OD) aspects of the TOPEX mission, the Dynamics Facility was designated to perform TOPEX operational OD. The scientific data require stringent OD accuracy in navigating the TOPEX spacecraft. The OD accuracy requirements fall into two categories: (1) on orbit free flight; and (2) maneuver. The maneuver OD accuracy requirements are of two types; premaneuver planning and postmaneuver evaluation. Analysis using the Orbit Determination Error Analysis System (ODEAS) covariance software has shown that, during the first postlaunch mission phase of the TOPEX mission, some postmaneuver evaluation OD accuracy requirements cannot be met. ODEAS results also show that the most difficult requirements to meet are those that determine the change in the components of velocity for postmaneuver evaluation.

Bolvin, D. T.↗

Automation of satellite operations: Experiences and future directions at NASA GSFC

The current state of satellite operation automation at the NASA Goddard Space Flight Center (GSFC), MD, is described, discussing the short term future and presenting a vision of how automation should be used in future systems. The automation practices currently applied in several current programs are surveyed. The rapidly evolving level of spacecraft autonomy is considered, reviewing how future onboard capabilities will affect ground based automation efforts. The optimum role of automation is discussed and automation principles are presented that can be used to identify favorable opportunities for simplifying and reducing the operating cost of spaceborne science missions.

Hartley, Jonathan B.↗

Quantifying the Impact of Systems Interdependencies in Space Systems Architectures

Due to the high number of systems in a space mission architecture and to their complex interactions, identifying risk and critical operational dependencies is not obvious. Traditional systems engineering methodology and risk assessment does not capture the impact of interactions between systems nor the cascading effects of disruptions. Based on these considerations, the Systems Operational Dependency Analysis methodology was developed for use by systems analysts and decision makers. This methodology utilizes a parametric model of interdependencies between systems to quantify the direct and indirect impact of system disruptions on other systems, as well as identify root causes. The results are effective at providing decision support for prioritizing technology investment based on risk reduction associated with potential system disruptions. Expanding on research presented at IAC 2018 and based on a collaboration with NASA Marshall Space Flight Center, this paper applies the Systems Operational Dependency Analysis methodology to NASA Lunar Gateway in collaboration with NASA’s lunar exploration plans. The paper presents a hierarchical representation of the interdependencies between a Gateway habitat’s systems and subsystems, demonstrates quantification of the impact of disruption, and assesses the criticality of the constituent systems and subsystems.

Guariniello, Cesare↗

Supporting Crew Autonomy in Deep Space Exploration: Preliminary Onboard Capability Requirements and Proposed Research Questions. Technical Report of the Autonomous Crew Operations Technical Interchange Meeting

Communication delays are a critical challenge posed by long duration deep space exploration. Space missions historically have relied on an ever-present Mission Control Center (MCC) to direct operations in near real-time. As unanticipated anomalies that defeat fault detection and resolution systems do arise, the lack of real-time communication will significantly weaken what the MCC support represents: a reliable safety net for the flight crew through its deep and diverse areas of expertise and investigative resources. As a consequence, future space vehicles and habitats need to be equipped with capabilities to support the flight crew to operate with little or no ground support. Considerations must be given to vehicle and mission designs that will fortify the traditionally ground-centered safety net and forge new support systems, when communication delays exist. In August 2018, NASA’s Human Research Program, through its Human Factors and Behavioral Performance Element, convened a Technical Interchange Meeting (TIM) on Autonomous Crew Operations at NASA Ames Research Center. The goal of the meeting was to gather input from NASA centers, industry, academia, and branches of the Department of Defense (DoD) to address how intelligent technologies can be applied to augment onboard capabilities to support crew anomaly response. The TIM featured 24 presentations by 29 speakers and hosted a total of 59 attendees, including 43 from 5 NASA centers (Ames, Johnson, Langley, Marshall, and Jet Propulsion Lab) and 4 from the DoD (3 from Army Research Lab and 1 from Naval Postgraduate School), with remaining attendees from academia (e.g., UC Davis, CMU) and industry (e.g., IBM, Siemens). Discussions were centered around three themes: standards and guidelines, lessons learned in analog environments, and technologies. To help provide a framework for discussion, a concept matrix describing anomaly response processes was created prior to the TIM (Figure 1, page 6). The matrix captures the steps involved (monitoring and detection, diagnosis, solution development and evaluation, solution implementation and verification, resolution documentation) as well as the resources and capabilities required to support these steps (data, knowledge, analysis, synthesis, resource management). A wallpaper size printout of the matrix was utilized at the TIM to solicit attendee inputs along the three themes; the activity garnered 108 submissions of ideas. Overall, what emerged from TIM discussions was a picture of mismatch between crew anomaly response needs and support that can be provided by existing intelligent technologies. The needs are broad, spanning multiple steps and processes/resources, with many of which lacking support from existing technologies, such as knowledge management throughout the steps of problem solving (especially in resolution documentation) and manpower management. The solutions provided by existing intelligent technologies are specific to the steps/processes that they are designed to support and constrained to solving only problems similar to those that have occurred before. What is lacking from technologies is typically made up by humans, specifically their complex critical thinking, creative problem solving, and domain expertise. In the end, the TIM highlighted the pressing need to support responses to onboard anomalies during autonomous crew operations, particularly those that have eluded the system tests, inspection, and other assurance processes. Such anomalies can potentially threaten crew and vehicle safety, as well as significantly impact overall operations with additional workload. These fairly rare events are difficult to anticipate and prepare for, given the state-of-the-art in intelligent technologies. This is true even for anomalies that stem from “unknown knowns”—cases in which there is sufficient external information to characterize the problem but the overall pattern fails to be recognized by the problem solver, or in which the internal knowledge needed to solve a problem is held tacitly and potentially accessible by the problem solver but not articulated. It follows that the ability to tackle anomalies lies not only with the availability of relevant information and knowledge but also their accessibility in times of need. To that end, we propose research questions along the following three broad themes: • How intelligent technologies can help make relevant knowledge and information available? • How intelligent technologies can help make relevant knowledge and information accessible? • How intelligent technologies can help support the crew operating as a team in anomaly response processes?

autonomous crew operations↗

Development of the Advanced Regolith Ground Operations (ARGO) Test Bed – A Robotic Excavation and Construction Test Facility with Simulated Lunar Environments

NASA’s Artemis Program is working towards developing a sustained presence on the Moon and eventually Mars. To achieve this goal, robotic excavation, site preparation and construction technologies are under development to establish the capability to construct infrastructure such as launch/landing pads and radiation protection shelters. Technologies must be proven in simulated Lunar conditions prior to surface demonstration missions. To that end, the Relevant Additive Construction Technology (REACT) Announcement of Collaboration Opportunities (ACO) project with AI Space Factory and the NASA Kennedy Space Center’s (KSC) Granular Mechanics and Regolith Operations Laboratory (a.k.a. Swamp Works) has developed the Advanced Regolith Ground Operations (ARGO) Test Bed. ARGO includes a ~1.5m x 1.5m x 1.2m (~5x5x4ft) vacuum chamber, cryogenically cooled thermal shroud, 3-axis robotic positioning system, and regolith bin. For the REACT project, a pellet extruder, feed hopper, and heated 600mm x 600mm (23.6x23.6in) build plate have been installed on ARGO to advance the Technology Readiness Level (TRL) of regolith-polymer composite Fused Deposition Modeling (FDM) additive construction systems, processes, and materials. This paper will focus on the design and operational characteristics of the ARGO Test Bed with pellet extruder.

regolith↗

Development of the Advanced Regolith Ground Operations (ARGO) Test Bed: A Robotic Excavation and Construction Test Facility with Simulated Lunar Environments

NASA’s Artemis Program is working towards developing a sustained presence on the Moon and eventually Mars. To achieve this goal, robotic excavation, site preparation and construction technologies are under development to establish the capability to construct infrastructure such as launch/landing pads and radiation protection shelters. Technologies must be proven in simulated Lunar conditions prior to surface demonstration missions. To that end, the Relevant Additive Construction Technology (REACT) Announcement of Collaboration Opportunities (ACO) project with AI Space Factory and the NASA Kennedy Space Center’s (KSC) Granular Mechanics and Regolith Operations Laboratory (a.k.a. Swamp Works) has developed the Advanced Regolith Ground Operations (ARGO) Test Bed. ARGO includes a ~1.5m x 1.5m x 1.2m (~5x5x4ft) vacuum chamber, cryogenically cooled thermal shroud, 3-axis robotic positioning system, and regolith bin. For the REACT project, a pellet extruder, feed hopper, and heated 600mm x 600mm (23.6x23.6in) build plate have been installed on ARGO to advance the Technology Readiness Level (TRL) of regolith-polymer composite Fused Deposition Modeling (FDM) additive construction systems, processes, and materials. This paper will focus on the design and operational characteristics of the ARGO Test Bed with pellet extruder.

regolith↗

Sensor systems testbed for telerobotic navigation

A testbed has been developed for the study of sensor systems to be used in telerobotic operations. The program, conducted in conjunction with Johnson Space Center of NASA, addresses the navigational problems associated with target acquisition and rendezvous for teleoperated robotic work stations. The program will utilize a mobile platform which will support various sensor systems during their development and testing in an earth-based environment. The testbed has been developed in support of a program to develop sensor systems that will aid in rendezvous and docking operations to be conducted as a part of the space station program. A mobile platform has been used to permit testing of these components in a conventional laboratory environment with consequent savings in cost and complexity. The sensor systems, while representative of devices currently in use for robotic applications, are not considered prototypical of the ones that will be used in the final applications. The test program provided information that will support the design of system augmentations and will lead to a comprehensive test program for sensor development.

Thiele, A. W.↗

Space Weather Products at the Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second CCMC activity is to support Space Weather forecasting at national Space Weather Forecasting Centers. This second activity involves model evaluations, model transitions to operations, and the development of space weather forecasting tools. Owing to the pace of development in the science community, new model capabilities emerge frequently. Consequently, space weather products and tools involve not only increased validity, but often entirely new capabilities. This presentation will review the present state of space weather tools as well as point out emerging future capabilities.

Hesse, Michael↗