Results for “operator learning” — Page 17

NASA NTRS1990

CLEAR: Automating control centers with expert system technology

The Communications Link Expert Assistance Resource (CLEAR) is a fault-isolation expert system to be utilized in the operational environment of the Cosmic Background Explorer (COBE) Mission Operations Room (MOR). CLEAR will assist the COBE Flight Operations Team (FOT) during periods of real-time data acquisition by isolating faults in the spacecraft communication link with the Tracking and Data Relay Satellite (TDRS), providing advice on how to correct them, and logging the events for post-pass evaluation. After a brief introduction to the problem domain, the system requirements, tool selection, development approach, system operation and lessons learned during the transformation of the system from the prototype to the delivered, operation system are described.

Hughes, Peter M.↗

NASA NTRSDate not supplied

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗

NASA NTRSDate not supplied

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C. Dempsey↗

NASA NTRSDate not supplied

Automated Software for Crewed Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗

NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗

NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗

NASA NTRS1998

NASA/Mir Phase 1: A Lesson Learned in Long Duration Mission Planning and Operations

The NASA/Mir Phase I Program is a precursor to the assembly and operations of the International Space Station (ISS). The Phase I Program covers a four-year period and encompasses over ten shuttle flights to the Mir, culminating with the flight of STS-91 in June 1998. The Mir-Orbiting Station (Mir-OS) provides an excellent environment, both onboard and on the ground, for learning and studying the characteristics associated with crew-tended operations on long duration missions. By the end of the Phase I program, NASA astronauts will have accumulated over two years of continuous operations experience working and living onboard the Mir-OS. Ground controllers, working in Russia and at remote sites in the United States, will have gained valuable experience in the generation, maintenance, and coordination of the information and products required to support the long duration crew members onboard the Mir-OS. The experience gained by the crew and ground support personnel in the area of long duration mission operations has resulted in a number of factors that need to be considered in the definition and implementation of the processes and products for the ISS. While there are many areas in which experience has been gained, this paper focuses on the lessons learned regarding the level of detail and flexibility of crew timelines. Provided in this paper is an overview of the characteristics associated with long duration mission timeline development and execution, a summary of applicable lessons learned identified and documented through participation in the NASA/Mir Phase I Program, a detailed discussion of "Gross Timelines" as implementation which addresses the lessons learned. Also discussed are the challenges that must be overcome in getting the ISS program to recognize, evaluate, and learn from the crew and ground controller experience gained through participation in the NASA/Mir Phase I Program.

Hagopian, Jeff↗

NASA NTRS1978

An integrated optical preprocessor for multichannel analog data

As a precursor to the construction of a 16-channel device, a 3-channel integrated optical data preprocessor has been fabricated and tested. The device, which is fabricated in an outdiffused LiNbO3 waveguide, provides a signal related to the channel-by-channel difference between a prerecorded reference set and an incoming data set which is presented in the form of parallel analog voltages. The data are impressed upon the guided wave as a set of electrooptically induced phase shifts, and the comparison to the reference set is performed by holographic subtraction. The reference set can either be introduced as a separate operation or it can be 'learned' by the preprocessor during operation.

Verber, C. M.↗

NASA NTRS1979

Fabrication and testing of a three-channel integrated optical data preprocessor

As a precursor to the construction of a 16-channel device, a 3-channel integrated optical data preprocessor has been fabricated and tested. The device, which is fabricated in an outdiffused LiNbO3 waveguide, provides a signal related to the channel-by-channel difference between a prerecorded reference set and an incoming data set which is presented in the form of parallel analog voltages. The data are impressed upon the guided wave as a set of electrooptically induced phase shifts, and the comparison to the reference set is performed by holographic subtraction. The reference set can either be introduced as a separate operation or it can be 'learned' by the preprocessor during operation.

Verber, C. M.↗

NASA NTRS2001

Development of the Electron Drift Instrument (EDI) for Cluster

The Electron Drift Instrument (EDI) is a new technique for measuring electric fields in space by detecting the effect on weak beams of test electrons. This U.S. portions of the technique, flight hardware, and flight software were developed for the Cluster mission under this contract. Dr. Goetz Paschmann of the Max Planck Institute in Garching, Germany, was the Principle Investigator for Cluster EDI. Hardware for Cluster was developed in the U.S. at the University of New Hampshire, Lockheed Palo Alto Research Laboratory, and University of California, San Diego. The Cluster satellites carrying the original EDI instruments were lost in the catastrophic launch failure of first flight of the Arianne-V rocket in 1996. Following that loss, NASA and ESA approved a rebuild of the Cluster mission, for which all four satellites were successfully launched in the Summer of 2000. Limited operations of EDI were also obtained on the Equator-S satellite, which was launched in December, 1997. A satellite failure caused a loss of the Equator-S mission after only 5 months, but these operations were extremely valuable in learning about the characteristics and operations of the complex EDI instrument. The Cluster mission, satellites, and instruments underwent an extensive on-orbit commissioning phase in the Fall of 2000, carrying over through January 2001. During this period all elements of the instruments were checked and careful measurements of inter-experiments interferences were made. EDI is currently working exceptionally well in orbit. Initial results verify that all aspects of the instrument are working as planned, and returning highly valuable scientific information. The first two papers describing EDI on-orbit results have been submitted for publication in April, 2001. The principles of the EDI technique, and its implementation on Cluster are described in two papers by Paschmann et al., attached as Appendices A and B. The EDI presentation at the formal Cluster Commissioning Review, held at ESA Headquarters in Paris, is attached as Appendix C.

Quinn, Jack↗

NASA NTRS2020

Ground System Milestones: 20 Years of Earth Observing Satellite Mission Operations

Aqua, Aura, and Terra are Earth observing satellites that serve in the Earth Observing System (EOS). Terra, the flagship mission of the EOS, was launched in 1998. Aqua was launched in 2002 and Aura was launched in 2004. Each spacecraft was designed for a 6 year lifespan. Currently, each spacecraft meets all mission and science requirements. As technology advances, the onboard hardware and software remain the same, however, our ground system progresses. In the past twenty years, many changes have taken place. Our goal is to describe the life of the ground system from launch, to present day, and touch on our future plans. The focus of our presentation will be how EOS has and continues to modernize our ground system for the future. We would like to share our experiences and give insight into the operational challenges of a 20 year old ground system. Our hope is for future mission operators and those maintaining potential age defying satellites to use our past experiences and lessons learned for future operational concepts.

Barrett, Grant↗

DOE OSTI2024

Towards accelerating particle-resolved direct numerical simulation with neural operators

In this paper, we present our ongoing work aimed at accelerating a particle-resolved direct numerical simulation model designed to study aerosol–cloud–turbulence interactions. The dynamical model consists of two main components—a set of fluid dynamics equations for air velocity, temperature, and humidity, coupled with a set of equations for particle (i.e., cloud droplet) tracing. Rather than attempting to replace the original numerical solution method in its entirety with a machine learning (ML) method, we consider developing a hybrid approach. We exploit the potential of neural operator learning to yield fast and accurate surrogate models and, in this study, develop such surrogates for the velocity and vorticity fields. We discuss results from numerical experiments designed to assess the performance of ML architectures under consideration as well as their suitability for capturing the behavior of relevant dynamical systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Real-time avoidance of the L-mode and H-mode density limit via machine-learned stability metrics

Reliable operation of burning plasma tokamaks will require robust control strategies to avoid macroscopic instability limits such as the L-mode and H-mode density limits (LDL, HDL). In this work, we explore closed-loop avoidance of these phenomena at DIII-D using machine-learned risk metrics. Feedback control is implemented via the ‘DL Supervisor’ scheme, which regulates the chosen risk metric by reducing the density target or increasing NBI heating in real-time. Using the LDL 25 risk metric, the LDL is reproducibly suppressed. We also introduce an HDL risk metric in this study, HDL 25 , which reduces the False Positive Rate by 2x compared to the Greenwald fraction. Applying this scaling to a plasma current ramp-down, we successfully avoid an HDL-driven H/L back-transition. These experiments constitute the first demonstration of real-time DL avoidance using machine-learned risk metrics. These instability metrics outline a path to safer high-density operation, more reliable ramp-down scenarios, and improved off-normal control for next-step devices such as ITER and SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2006

NASA Crew Launch Vehicle Approach Builds on Lessons from Past and Present Missions

The United States Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with a new human-rated system suitable for missions to the Moon and Mars. The Crew Exploration Vehicle (CEV) that the new Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station and be capable of carrying crews back to lunar orbit and of supporting missions to Mars orbit. NASA is using its extensive experience gained from past and ongoing launch vehicle programs to maximize the CLV system design approach, with the objective of reducing total lifecycle costs through operational efficiencies. To provide in-depth data for selecting this follow-on launch vehicle, the Exploration Systems Architecture Study was conducted during the summer of 2005, following the confirmation of the new NASA Administrator. A team of aerospace subject matter experts used technical, budget, and schedule objectives to analyze a number of potential launch systems, with a focus on human rating for exploration missions. The results showed that a variant of the Space Shuttle, utilizing the reusable Solid Rocket Booster as the first stage, along with a new upper stage that uses a derivative of the RS-25 Space Shuttle Main Engine to deliver 25 metric tons to low-Earth orbit, was the best choice to reduce the risks associated with fielding a new system in a timely manner. The CLV Project, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operation of this new human-rated system. The CLV Project works closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch system . leveraging a wealth of lessons learned from Shuttle operations. The CL V is being designed to reduce costs through a number of methods, ranging from validating requirements to conducting trades studies against the concept design. Innovations such as automated processing will build on lessons learned from the Shuttle, other launch systems, Department of Defense operations experience, and subscale flight tests such as the Delta Clipper-Experimental Advanced (DCXA) vehicle operations that utilized minimal touch labor, automated cryogen ic propellant loading , and an 8-hour turnaround for a cryogenic propulsion system. For the CLV, the results of hazard analyses are contributing to an integrated vehicle health monitoring system that will troubleshoot anomalies and determine which ones can be solved without human intervention. Such advances will help streamline the mission operations process for pilots and ground controllers alike. In fiscal year 2005, NASA invested approximately $4.5 billion of its $16 bill ion budget on the Space Shuttle. The ultimate goal of the CLV Project is to deliver a safe, reliable system designed to minimize lifecycle costs so that NASA's budget can be invested in missions of scientific discovery. Lessons learned from developing the CLV will be applied to the growth path for future systems, including a heavy lift launch vehicle.

Dumbacher, Daniel L.↗

NASA NTRS2019

UAS Service Supplier Checkout: How UTM Confirmed Readiness of Flight Tests with UAS Service Suppliers

NASA collaborated with industry partners to develop and test the small Unmanned Aircraft System (sUAS) Traffic Management (UTM) research platform, a software prototype used for developing airspace integration requirements for sUAS operations. The lessons learned from these activities will help inform the Federal Aviation Administration (FAA) on what is needed to safely manage sUAS operations. A core component of the UTM platform is the UAS Service Supplier (USS), which acts as a communications bridge to meet the regulatory and operational requirements. As the UTM partners began USS flight tests, NASA found that it was difficult to get all USSs functioning at comparable quality levels to ensure successful flight tests. Also, NASA anticipated that the FAA would encounter similar challenges when they begin to register USSs for operational use. These realizations led to the development of USS Checkout, a set of processes and tools designed to increase flight test efficiency. We learned that a good USS Checkout process is balanced for simplicity versus test coverage, and is amenable to automation. We also learned that when USS Checkout is a USS prerequisite for flight tests, flight tests were more efficient and effective.

Smith, Irene Skupniewicz↗

NASA NTRS2011

Benefits of Operational Consideration into the Guidance, Navigation, and Control Design of Spacecraft

The following paper points out historical examples where operational consideration into the GN&C design could have helped avoid operational complexity, reduce costs, ensure the ability for a GN&C system to be able to adapt to failures, and in some cases might have helped save mission objectives. A costly repeat of mistakes could befall a program if previous operational lessons, especially from operators of vehicles with similar GN&C systems, are not considered during the GN&C design phase of spacecraft. The information gained from operational consideration during the design can lead to improvements of the design, allow less ground support during operations, and prevent repetition of previous mistakes. However, this benefit can only occur if spacecraft operators adequately capture lessons learned that would improve future designs for operations and those who are designing spacecraft incorporate inputs from those that have previously operated similar GN&C systems.

Morris, Mark C.↗

NASA NTRS1994

Re-Engineering the Multimission Command System at the Jet Propulsion Laboratory

This paper will discuss the design and implementation of the command software, especially trade-offs and lessons learned from practical operational use in JPL's Advanced Multimission Operations System.The command system provides an advanced multimission environment for secure, concurrent commanding of multiple spacecraft. The lessons learned have resulted in a re-engineering of the command system, especially in its user interface and new automation capabilities. This paper will also discuss new development work including a multimission command database toolkit, a universal command translator for sequencing and real-time commands, and incorporation of telecommand capabilities for new missions.

re-engineering↗

NASA NTRS2018

Lessons Learned During the Transition of SORCE Science Operations to Daylight Only Operations

In July 2013, NASA's Solar Radiation and Climate Experiment experienced a battery anomaly which placed it into safemode halting all science observations. Initial attempts to recover the spacecraft to an operational configuration failed due to the reduced capacity of the battery. As the keystone mission for measuring total solar irradiance, and the cornerstone mission for measuring the solar spectral irradiance there was a strong motivation for developing a new operations concept that would allow SORCE to resume daily measurements of the Sun. The operations team faced many challenges over the next several months. For a five-day period in late 2013 the operations team was able resume science observations to cross-calibrate SORCE data with a new instrument launched in November 2013. After the cross-calibration campaign was completed a new operations concept was deployed which allowed SORCE to perform daylight only operations. In this mode of operations all non-essential components are powered off at each eclipse entry and then turned back on at sunrise. In March 2014 SORCE resumed making daily measurements of the Sun. This paper will review the events and lessons learned from the six-month recovery effort.

Spacecraft Anomaly↗