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NASA NTRS2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

anomaly detection↗

NASA NTRS2007

Digital Learning Network Education Events of NASA's Extreme Environments Mission Operations

NASA's Digital Learning Network (DLN) reaches out to thousands of students each year through video conferencing and web casting. The DLN has created a series of live education videoconferences connecting NASA s Extreme Environment Missions Operations (NEEMO) team to students across the United States. The programs are also extended to students around the world live web casting. The primary focus of the events is the vision for space exploration. During the programs, NEEMO Crewmembers including NASA astronauts, engineers and scientists inform and inspire students about the importance of exploration and share the impact of the project as it correlates with plans to return to the moon and explore the planet Mars. These events highlight interactivity. Students talk live with the aquanauts in Aquarius, the National Oceanic and Atmospheric Administration s underwater laboratory. With this program, NASA continues the Agency s tradition of investing in the nation's education programs. It is directly tied to the Agency's major education goal of attracting and retaining students in science, technology, and engineering disciplines. Before connecting with the aquanauts, the students conduct experiments of their own designed to coincide with mission objectives. This paper describes the events that took place in September 2006.

Paul, Heather↗

NASA NTRS1997

Collaborating Fuzzy Reinforcement Learning Agents

Earlier, we introduced GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Relearning and at the local level, each agent learns and operates based on ANTARCTIC, a technique for fuzzy reinforcement learning. In this paper, we show that it is possible for these agents to compete in order to affect the selected control policy but at the same time, they can collaborate while investigating the state space. In this model, the evaluator or the critic learns by observing all the agents behaviors but the control policy changes only based on the behavior of the winning agent also known as the super agent.

Berenji, Hamid R.↗

NASA NTRS2016

Synthetic Biologic Membrane

The International Space Station (ISS) is a test bed for the technologies that will be used to travel to Mars and beyond. The lessons learned from operating the ISS provide valuable direction to future research and technology development programs. One of the most critical and complicated subsystems on ISS is the life support system. The life support system keeps the crew alive by recycling both air and water. The ISS water recycling system has been operating since 2009 and one of the main lessons learned is that reliability is a key technology performance metric. In the long run reliability is a key cost driver and is a critical factor in insuring crew safety. For long duration missions such as the exploration of Mars, where resupply of spare parts from Earth is difficult if not impossible, reliability is even more important. This presentation will cover research into improving the reliability of ISS systems. It will discuss research into the development of a biomimetic membrane materials that provides self-regeneration capabilities for water recycling systems. It will also cover research into past failures of the ISS water recycling system caused by astronaut bone loss and the build-up of trace contaminates in the cabin.

Biology↗

NASA NTRS1992

Application of fuzzy logic-neural network based reinforcement learning to proximity and docking operations

As part of the Research Institute for Computing and Information Systems (RICIS) activity, the reinforcement learning techniques developed at Ames Research Center are being applied to proximity and docking operations using the Shuttle and Solar Max satellite simulation. This activity is carried out in the software technology laboratory utilizing the Orbital Operations Simulator (OOS). This interim report provides the status of the project and outlines the future plans.

Jani, Yashvant↗

NASA NTRS2013

Lessons Learned from the Stardust Sample Return Mission

These are science and mission design and operations lessons learned from the Stardust Mission, which returned grains from comet Wild-2 and fresh interstellar dust to Earth in 2006 [1]. Science Lessons: Major discoveries of the Stardust Wild-2 samples include the presence of numerous chondrules and CAI in a comet, which requires a much more dynamic early solar system than many had envisaged, and verified predictions made by models requiring outward flow of early solar system solids before the early nebular gas had dissipated [1-3]. No evidence has been found for the presence of live Al-26 in the comet, suggesting late accretion [4]. Carbonates and unusual sulfides were found which potentially require activity of liquid water within the comet, but to only a minor degree at best [5-6]. The presence of abundant thermally-metamorphosed silicates in Wild-2 appears to require assembly from an earlier generation of bodies [7]. The abundance of presolar grains in the Wild-2 samples appears to be below what has been found in most chondritic IDPs and primitive chondrites [1]. The bulk mineralogy of Wild-2 grains does not match the mineralogy from any single other known astromaterial [7], and is also strikingly unlike that inferred from Spitzer Telescope spectra of Comet Temple 1 dust [8]. Amino acids and other fragile organics have been detected among the Wild-2 samples [9], which highlights the critical importance of further developing techniques for organic analysis in small samples, and cleaning outbound spacecraft.

Zolensky, M. E.↗

NASA NTRS1991

Real Time Data System (RTDS)

Lessons learned from operational real time expert systems are examined. The basic system architecture is discussed. An expert system is any software that performs tasks to a standard that would normally require a human expert. An expert system implies knowledge contained in data rather than code. And an expert system implies the use of heuristics as well as algorithms. The 15 top lessons learned by the operation of a real time data system are presented.

Muratore, John F.↗

NASA NTRS2000

ACTS Ka-Band Earth Stations: Technology, Performance, and Lessons Learned

The Advanced Communications Technology Satellite (ACTS) Project invested heavily in prototype Ka-band satellite ground terminals to conduct an experiments program with the ACTS satellite. The ACTS experiment's program proposed to validate Ka-band satellite and ground station technology. demonstrate future telecommunication services. demonstrate commercial viability and market acceptability of these new services, evaluate system networking and processing technology, and characterize Ka-band propagation effects, including development of techniques to mitigate signal fading. This paper will present a summary of the fixed ground terminals developed by the NASA Glenn Research Center and its industry partners, emphasizing the technology and performance of the terminals (Part 1) and the lessons learned throughout their six year operation including the inclined orbit phase of operations (Full Report). An overview of the Ka-band technology and components developed for the ACTS ground stations is presented. Next. the performance of the ground station technology and its evolution during the ACTS campaign are discussed to illustrate the technical tradeoffs made during the program and highlight technical advances by industry to support the ACTS experiments program and terminal operations. Finally. lessons learned during development and operation of the user terminals are discussed for consideration of commercial adoption into future Ka-band systems. The fixed ground stations used for experiments by government, academic, and commercial entities used reflector based offset-fed antenna systems ranging in size from 0.35m to 3.4m antenna diameter. Gateway earth stations included two systems, referred to as the NASA Ground Station (NGS) and the Link Evaluation Terminal (LET). The NGS provides tracking, telemetry, and control (TT&C) and Time Division Multiple Access (TDMA) network control functions. The LET supports technology verification and high data rate experiments. The ground stations successfully demonstrated many services and applications at Ka-band in three different modes of operation: circuit switched TDMA using the satellite on-board processor, satellite switched SS-TDMA applications using the on-board Microwave Switch Matrix (MSM), and conventional transponder (bent-pipe) operation. Data rates ranged from 4.8 kbps up to 622 Mbps. Experiments included: 1) low rate (4.8- 1 00's kbps) remote data acquisition and control using small earth stations, 2) moderate rate (1-45 Mbps) experiments included full duplex voice and video conferencing and both full duplex and asymmetric data rate protocol and network evaluation using mid-size ground stations, and 3) link characterization experiments and high data rate (155-622 Mbps) terrestrial and satellite interoperability application experiments conducted by a consortium of experimenters using the large transportable ground stations.

Reinhart, Richard C.↗

NASA NTRS2014

Lessons Learned in the First Year Operating Software Defined Radios in Space

Operating three unique software defined radios (SDRs) in a space environment aboard the Space Communications and Navigation (SCaN) Testbed for over one year has provided an opportunity to gather knowledge useful for future missions considering using software defined radios. This paper provides recommendations for the development and use of SDRs, and it considers the details of each SDRs approach to software upgrades and operation. After one year, the SCaN Testbed SDRs have operated for over 1000 hours. During this time, the waveforms launched with the SDR were tested on-orbit to assure that they operated in space at the same performance level as on the ground prior to launch to obtain an initial on-orbit performance baseline. A new waveform for each SDR has been developed, implemented, uploaded to the flight system, and tested in the flight environment. Recommendations for SDR-based missions have been gathered from early development through operations. These recommendations will aid future missions to reduce the cost, schedule, and risk of operating SDRs in a space environment. This paper considers the lessons learned as they apply to SDR pre-launch checkout, purchasing space-rated hardware, flexibility in command and telemetry methods, on-orbit diagnostics, use of engineering models to aid future development, and third-party software. Each SDR implements the SCaN Testbed flight computer command and telemetry interface uniquely, allowing comparisons to be drawn. The paper discusses the lessons learned from these three unique implementations, with suggestions on the preferred approach. Also, results are presented showing that it is important to have full system performance knowledge prior to launch to establish better performance baselines in space, requiring additional test applications to be developed pre-launch. Finally, the paper presents the issues encountered with the operation and implementation of new waveforms on each SDR and proposes recommendations to avoid these issues.

radio equipment↗

NASA NTRS2014

Lessons Learned in the First Year Operating Software Defined Radios in Space

Operating three unique software defined radios (SDRs) in a space environment aboard the Space Communications and Navigation (SCaN) Testbed for over one year has provided an opportunity to gather knowledge useful for future missions considering using software defined radios. This paper provides recommendations for the development and use of SDRs, and it considers the details of each SDR's approach to software upgrades and operation. After one year, the SCaN Testbed SDRs have operated for over 1000 hours. During this time, the waveforms launched with the SDR were tested on-orbit to assure that they operated in space at the same performance level as on the ground prior to launch to obtain an initial on-orbit performance baseline. A new waveform for each SDR has been developed, implemented, uploaded to the flight system, and tested in the flight environment. Recommendations for SDR-based missions have been gathered from early development through operations. These recommendations will aid future missions to reduce the cost, schedule, and risk of operating SDRs in a space environment. This paper considers the lessons learned as they apply to SDR pre-launch checkout, purchasing space-rated hardware, flexibility in command and telemetry methods, on-orbit diagnostics, use of engineering models to aid future development, and third-party software. Each SDR implements the SCaN Testbed flight computer command and telemetry interface uniquely, allowing comparisons to be drawn. The paper discusses the lessons learned from these three unique implementations, with suggestions on the preferred approach. Also, results are presented showing that it is important to have full system performance knowledge prior to launch to establish better performance baselines in space, requiring additional test applications to be developed pre-launch. Finally, the paper presents the issues encountered with the operation and implementation of new waveforms on each SDR and proposes recommendations to avoid these issues.

space communication↗

NASA NTRS2014

Using AUTORAD for Cassini File Uplinks: Incorporating Automated Commanding into Mission Operations

As the Cassini spacecraft embarked on the Solstice Mission in October 2010, the flight operations team faced a significant challenge in planning and executing the continuing tour of the Saturnian system. Faced with budget cuts that reduced the science and engineering staff by over a third in size, new and streamlined processes had to be developed to allow the Cassini mission to maintain a high level of science data return with a lower amount of available resources while still minimizing the risk. Automation was deemed an important key in enabling mission operations with reduced workforce and the Cassini flight team has made this goal a priority for the Solstice Mission. The operations team learned about a utility called AUTORAD which would give the flight operations team the ability to program selected command files for radiation up to seven days in advance and help minimize the need for off-shift support that could deplete available staffing during the prime shift hours. This paper will describe how AUTORAD is being utilized by the Cassini flight operations team and the processes that were developed or modified to ensure that proper oversight and verification is maintained in the generation and execution of radiated command files.

Goo, Sherwin↗

NASA NTRSDate not supplied

Data-Centric Operational Design Domain Characterization for Machine Learning-Based Aeronautical Products

We give for Machine Learning (ML)-based aeronautical products, a first rigorous characterization of Operational Design Domains (ODDs). Unlike in other application sectors (such as self-driving road vehicles) where ODD development is scenario-based, our approach is data-centric: we propose the dimensions along which the parameters that define an ODD can be explicitly captured, using a top-down approach starting from system specifications, and a bottom-up approach starting from detailed ML Model (MLM) designs. Then we give a categorization of the data that ML-based applications can encounter in operation, identifying their system-level relevance and impact. Specifically, we discuss how those data categories are useful to determine: (1) the requirements necessary to drive the design of MLMs; (2) the potential effects on the MLM and higher levels of the system hierarchy; (3) the learning assurance processes that may be needed, and (4) system architectural considerations. We illustrate the underlying concepts with an example of an aircraft flight envelope. The approach in this paper is one of the cornerstones of a future process guidance for development and certification/approval of safety-related aeronautical products implementing Artificial Intelligence (AI), currently being developed through aviation industry-based consensus, jointly by the SAE G-34 Committee for AI in aviation, and EUROCAE WG-114 for AI.

Aeronautical products↗

NASA NTRS2006

Spitzer Space Telescope Sequencing Operations Software, Strategies, and Lessons Learned

The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.

missions operations↗

NASA NTRS2019

Simulation-to-Flight 1 (STF-1): Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2019, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC Technologies, and four independent professor-student teams at West Virginia University.

CubeSat↗

NASA NTRS2019

STF-1 Ground Operations - Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2018, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC2 Technologies, and four independent professor-student teams at West Virginia University.

Suder, Mark↗

NASA NTRS2013

Lessons Learned for Improving Spacecraft Ground Operations

NASA policy requires each Program or Project to develop a plan for how they will address Lessons Learned. Projects have the flexibility to determine how best to promote and implement lessons learned. A large project might budget for a lessons learned position to coordinate elicitation, documentation and archival of the project lessons. The lessons learned process crosses all NASA Centers and includes the contactor community. o The Office of The Chief Engineer at NASA Headquarters in Washington D.C., is the overall process owner, and field locations manage the local implementation. One tool used to transfer knowledge between program and projects is the Lessons Learned Information System (LLIS). Most lessons come from NASA in partnership with support contractors. A search for lessons that might impact a new design is often performed by a contractor team member. Knowledge is not found with only one person, one project team, or one organization. Sometimes, another project team, or person, knows something that can help your project or your task. Knowledge sharing is an everyday activity at the Kennedy Space Center through storytelling, Kennedy Engineering Academy presentations and through searching the Lessons Learned Information system. o Project teams search the lessons repository to ensure the best possible results are delivered. o The ideas from the past are not always directly applicable but usually spark new ideas and innovations. Teams have a great responsibility to collect and disseminate these lessons so that they are shared with future generations of space systems designers. o Leaders should set a goal for themselves to host a set numbers of lesson learned events each year and do more to promote multiple methods of lessons learned activities. o High performing employees are expected to share their lessons, however formal knowledge sharing presentation are not the norm for many employees.

Bell, Michael↗

NASA NTRSDate not supplied

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRS2021

A Cognitive Walkthrough of Multiple Drone Delivery Operations

unmanned aircraft systems↗