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At least 523 records · Page 29

Incorporating UAS Traffic Management into Wildland Firefighting Operations: Initial Findings of Subject Matter Expert Interviews

Uncrewed Aircraft Systems (UASs) are being utilized throughout the disaster and emergency response domain, including in wildland firefighting operations. While UASs can offer safety benefits in comparison to crewed aircraft, such as removing the human pilot from the vehicle so that they are not exposed to the same risks and the ability to operate in low-visibility conditions, they are not without tradeoffs. For example, it can be challenging for UAS pilots (UASPs) to build situation awareness of the airspace in which their UAS is operating. In order to address some of the challenges associated with using UASs and provide greater assistance to the firefighters and incident personnel in the wildland firefighting environment, the National Aeronautics and Space Administration (NASA) launched the Advanced Capabilities for Emergency Response Operations (ACERO) project. Building on previous NASA research, ACERO will explore the implementation of a traffic management system in the wildland fire environment to enhance safety and support situation awareness. ACERO draws on the UAS Traffic Management (UTM) system previously demonstrated in an urban environment. However, a traffic management system implemented in the wildland fire environment is expected to look and function much differently in order to meet the unique needs of this domain. At the outset of the ACERO project, interviews were conducted with five UASPs who operate UASs at wildland fire incidents. The interviews focused on exploring UASPs’ initial insights about the application of a traffic management system in wildland firefighting and understanding the unique needs of this environment. The UASPs discussed a range of topics including, the shape, size, and organization of UAS operations in the wildland fire environment, information needs for a user interface, such as traffic and map information, an alerting function when other traffic nears their operation area, and the importance of conformance monitoring. The UASPs also discussed their willingness to share operational information to support safety. In this presentation, we describe the foundational work upon which ACERO will build and summarize the information and insights gathered during the UASP interviews, some of which have already informed the development of the ACERO work.

Uncrewed Aircraft Systems (UAS)↗

Terrestrial Proving Ground Capabilities Needed for Lunar In Situ Resource Utilization (ISRU) & Construction Concepts of Operation

Incorporating any new technology or system into a human exploration mission or architecture requires development well in advance of the mission to eliminate technology, cost, and schedule risk concerns. It is often stated that technologies need to be at a Technology Readiness Level (TRL) of 6, i.e. ‘system/subsystem model or prototype demonstration in a relevant environment (ground or space)’, by Authority To Proceed (ATP) or by the Preliminary Design Review (PDR) for the mission at the latest. There are two game changing capabilities for sustained human exploration of space that can have a significant effect on the overall exploration architecture and the technologies and systems included in the architecture. The first game changing capability, known as In Situ Resource Utilization (ISRU), involves the search for, acquisition, and processing of resources on the Moon and Mars into mission consumables and usable products, and the second is the ability to utilize space resources in the construction of roads, structures, and surface infrastructure. ISRU and surface construction capabilities have the potential to greatly reduce the cost and risk of human exploration while enabling sustained lunar surface and commercial operations. However, ISRU and surface construction systems are complex and must operate in extremely harsh environments, with abrasive regolith and pervasive dust, for long-periods of time, with potentially limited opportunities for maintenance and repair by humans. The complexity of these capabilities and operations also means that there are a limited number of companies that can design, build, and operate end-to-end systems on their own. The majority of the technologies being developed for these systems are by small companies and at the component or subsystem level. With the overarching strategy of the United States National Aeronautics and Space Administration (NASA) Space Technology Mission Directorate (STMD) to enable industry to implement ISRU and surface infrastructure for Artemis and space commercialization, it is therefore important to establish processes and capabilities to promote and foster collaborations among large and small companies involved in ISRU and surface infrastructure development. For ISRU and infrastructure systems and capabilities to be used in Artemis missions and future commercial lunar surface operations, a coordinated framework with virtual/physical integration and testing locations, or ‘Proving Grounds’, needs to be established and operated on a regular basis and open to all. This paper will discuss the ISRU and surface construction near and long-term concepts of operations, and review operations and lessons-learned from the previous ISRU analog field tests. From this information, requirements and capabilities will be proposed to support and enable the integration and testing of ISRU and construction systems with industry, academia, and international agencies, as well as what facilities and organizations could help establish these Proving Grounds.

ISRU↗

Improving operations: Metrics to Results

As a result of the mission failure of the Mars Climate Orbiter (MCO) spacecraft in 1999, the Jet Propulsion Laboratory (JPL) initiated the development of a Mission Operations Assurance (MOA) program to be implemented across all flight projects managed by JPL. One of the initiatives undertaken in 2001 was the collection of data on command file errors occurring in the operational phase of the mission. This paper defines command file errors and how and where they occur in the operations process. It also describes the problem reporting system (PRS) in use for mission operations at JPL. We examine the recent modifications to the PRS that enable the collection of metrics, specifically on command file errors. This paper discusses what the data show us since metrics have been collected for the operational missions conducted by JPL. We examine the evolution of an operational working group initiative to evaluate proximate, contributing, and root causes for the errors. As part of this discussion we see what the metrics have indicated over a decade. At the macro level, we can say that the aggregate command file error rate has been cut to roughly one third of the initial 2001 level by the end of 2011. Additionally, we explore efficient and innovative means to continually integrate the findings and recommendations from the working group back into the flight operations environment.

command file errors↗

Concept of Operations for RCO SPO

Reduced crew operations (RCO) refers to the reduction of crew members flying long-haul or military operations with more than one pilot onboard. Single pilot operations (SPO) refers to flying a commercial transport aircraft with only one pilot on board the aircraft, assisted by advanced onboard automation andor ground operators providing piloting support services. Properly implemented, RCO/SPO could provide operating cost savings while maintaining a level of safety no less than conventional two-pilot commercial operations. A concept of operations (ConOps) for any paradigm describes the characteristics of its various components and their integration in a multi-dimensional design space. This paper presents key options for humanautomation function allocation being considered by NASA in its ongoing development of RCO/SPO ConOps.

ConOps↗

Mars mission science operations facilities design

A variety of designs for Mars rover and lander science operations centers are discussed in this paper, beginning with a brief description of the Pathfinder science operations facility and its strengths and limitations. Particular attention is then paid to lessons learned in the design and use of operations facilities for a series of mission-like field tests of the FIDO prototype Mars rover. These lessons are then applied to a proposed science operations facilities design for the 2003 Mars Exploration Rover (MER) mission. Issues discussed include equipment selection, facilities layout, collaborative interfaces, scalability, and dual-purpose environments. The paper concludes with a discussion of advanced concepts for future mission operations centers, including collaborative immersive interfaces and distributed operations. This paper's intended audience includes operations facility and situation room designers and the users of these environments.

Ground Data System (GDC)↗

Integrated Human-Robotic Missions to the Moon and Mars: Mission Operations Design Implications

For most of the history of space exploration, human and robotic programs have been independent, and have responded to distinct requirements. The NASA Vision for Space Exploration calls for the return of humans to the Moon, and the eventual human exploration of Mars; the complexity of this range of missions will require an unprecedented use of automation and robotics in support of human crews. The challenges of human Mars missions, including roundtrip communications time delays of 6 to 40 minutes, interplanetary transit times of many months, and the need to manage lifecycle costs, will require the evolution of a new mission operations paradigm far less dependent on real-time monitoring and response by an Earthbound operations team. Robotic systems and automation will augment human capability, increase human safety by providing means to perform many tasks without requiring immediate human presence, and enable the transfer of traditional mission control tasks from the ground to crews. Developing and validating the new paradigm and its associated infrastructure may place requirements on operations design for nearer-term lunar missions. The authors, representing both the human and robotic mission operations communities, assess human lunar and Mars mission challenges, and consider how human-robot operations may be integrated to enable efficient joint operations, with the eventual emergence of a unified exploration operations culture.

human robotic missions↗

Re-Engineering the Mission Operations System (MOS) for the Prime and Extended Mission

One of the most challenging tasks in a space science mission is designing the Mission Operations System (MOS). Whereas the focus of the project is getting the spacecraft built and tested for launch, the mission operations engineers must build a system to carry out the science objectives. The completed MOS design is then formally assessed in the many reviews. Once a mission has completed the reviews, the Mission Operation System (MOS) design has been validated to the Functional Requirements and is ready for operations. The design was built based on heritage processes, new technology, and lessons learned from past experience. Furthermore, our operational concepts must be properly mapped to the mission design and science objectives. However, during the course of implementing the science objective in the operations phase after launch, the MOS experiences an evolutional change to adapt for actual performance characteristics. This drives the re-engineering of the MOS, because the MOS includes the flight and ground segments. Using the Spitzer mission as an example we demonstrate how the MOS design evolved for both the prime and extended mission to enhance the overall efficiency for science return. In our re-engineering process, we ensured that no requirements were violated or mission objectives compromised. In most cases, optimized performance across the MOS, including gains in science return as well as savings in the budget profile was achieved. Finally, we suggest a need to better categorize the Operations Phase (Phase E) in the NASA Life-Cycle Phases of Formulation and Implementation

Extended Mission↗

CloudSat Anomaly Recovery and Operational Lessons Learned

In April 2011, NASA's pioneering cloud profiling radar satellite, CloudSat, experienced a battery anomaly that placed it into emergency mode and rendered it operations incapable. All initial attempts to recover the spacecraft failed as the resultant power limitations could not support even the lowest power mode. Originally part of a six-satellite constellation known as the "A-Train", CloudSat was unable to stay within its assigned control box, posing a threat to other A-Train satellites. CloudSat needed to exit the constellation, but with the tenuous power profile, conducting maneuvers was very risky. The team was able to execute a complex sequence of operations which recovered control, conducted an orbit lower maneuver, and returned the satellite to safe mode, within one 65 minute sunlit period. During the course of the anomaly recovery, the team developed several bold, innovative operational strategies. Details of the investigation into the root-cause and the multiple approaches to revive CloudSat are examined. Satellite communication and commanding during the anomaly are presented. A radical new system of "Daylight Only Operations" (DO-OP) was developed, which cycles the payload and subsystem components off in tune with earth eclipse entry and exit in order to maintain positive power and thermal profiles. The scientific methodology and operational results behind the graduated testing and ramp-up to DO-OP are analyzed. In November 2011, the CloudSat team successfully restored the vehicle to consistent operational collection of cloud radar data during sunlit portions of the orbit. Lessons learned throughout the six-month return-to-operations recovery effort are discussed and offered for application to other R&D satellites, in the context of on-orbit anomaly resolution efforts.

cloud profiling radar satellite↗

Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA developers, and operational forecasters.

forecasting↗

Modeling Deicing Operations in Departure Scheduling Using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

modeling and simulation↗

Modeling Deicing Operations in Departure Scheduling using Fast Time Simulation

In winter snow conditions, aircraft need inspection for deicing service before takeoff. Deicing service is a procedure to remove frost, ice, slush, or snow from aircraft for safe operation. Deicing operations vary by airport in many ways. Some airports have designated deicing zones, whereas some use a closed runway or terminal area to perform the procedure. Nonetheless, deicing operations add extra workloads to controllers, and cause increased taxi traffic on the ground. NASA and Korea Aerospace Research Institute (KARI) have been collaborating to model deicing operations at Incheon International Airport (ICN). This paper describes the deicing model and the study of deicing operations in departure scheduling using fast time simulations. The deicing model uses a heuristic algorithm for deicing zone assignment. In the fast time simulations, the model uses probability distributions derived from actual operation data to model deicing request and deicing zone time. It is envisioned that such a deicing model can be useful in airport surface scheduling to provide decision support and improve traffic management performance in winter snow operations.

surface operation↗

Challenges of Operations in a Dynamic Environment: A Three-Year Perspective of SAGE III

The Stratospheric Aerosol and Gas Experiment~III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aide in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the instrument. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVA's. This active environment increases the need for the SAGE III/ISS operations team command the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team that has successfully managed the instrument around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in earth’s climate.

SAGE III↗

Operations Challenges in a Dynamic Environment: A Three-Year Perspective of SAGE III

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was delivered to the International Space Station (ISS) on 23 February 2017. The SAGE III/ISS payload was robotically installed external to the ISS and began acquiring science measurements on 17 March 2017. The SAGE III/ISS instrument retrieves vertical profiles of atmospheric ozone, multi-wavelength aerosol extinctions, and other gaseous species. This paper will focus on the improvements made to the operations of the SAGE III/ISS payload. A key focus of the operations team following commissioning was to create robust tools that aid in the operations of the payload. A close collaboration with the SAGE III/ISS ground systems team allowed for the development of web-based tools to continuously monitor the health of the payload. The mission operations team also worked with the SAGE III/ISS science team to gain a better sense of how the instrument works to maximize the quality and quantity of the science data collected. Another unique aspect of the SAGE III/ISS payload, that will be discussed, is the challenges of operating a hosted payload on the ISS; an active platform that has frequent attitude maneuvers, dockings, and EVAs. This active environment increases the need for the SAGE III/ISS operations team command to the payload. Through coordination and teamwork, SAGE III/ISS mission has developed an operations team, tool, and procedures that have successfully managed the payload around ISS activities and recovered from multiple instrument upsets. This has led the SAGE III/ISS payload to successfully surpass the acquisition metrics set forth prior to launch, allowing for the continued contribution to studying the atmospheric composition of the stratosphere and how it plays a role in Earth’s climate.

SAGE III↗

Predictive Model for Workload in Remote Operators During sUAS Contingency Scenarios

The increase in automated capabilities of small Uncrewed Aerial Systems (sUAS) has enabled the human operators to manage larger numbers of vehicles simultaneously. As this happens, the operational paradigm shifts to an m:N configuration where multiple operators (m) are managing multiple vehicles (N) together. However, many questions about how operators will interact with each other and share interaction across the vehicle pool are yet unanswered. Therefore, stakeholders from government and industry have partnered to develop ground control station concepts for such operations. The work presented in this paper aims to identify factors that contribute to operator workload. A supervised machine learning-based method built using Support Vector Machines and K-fold cross-validation was used to create workload prediction models for various NASA TLX subscales by leveraging features related to interactions and their relative timings during m:N operations. Results show that the models yielded fairly high predictive accuracies ranging from ~60-75%.

workload prediction↗

A Decision Support System for Extravehicular Operations Under Significant Communication Latency

Within the next few decades, humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant two-way communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) performing an EVA and an Earth-based mission control. Next-generation operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the on-planet extravehicular crewmember(s), and intermediate mission support from intravehicular crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. For this purpose, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automating the tracking and projection of consumables usage over an EVA timeline, providing real-time probabilistic safety assessments of an EVA timeline given consumables constraints, and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the intravehicular crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g. training bias.

Mars↗

A Decision Support System for Extravehicular Operations Under Significant Communication Latency

Humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) and Earth-based mission control. Nextgeneration operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the onplanet extravehicular crewmember(s), and intermediate mission support from intravehicular (IV) crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. Thus, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automatically tracking and projecting consumables usage over an EVA timeline, providing real-time probabilistic safety assessments and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the IV crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g., training bias.

Mars↗

PersEIDS: A Biomedical Decision Support System for Extravehicular Operations Under Significant Communication Latency

Humanity hopes to perform extravehicular activities (EVAs) on the surface of Mars; however, several technical and operational challenges must first be overcome. Foremost among these challenges is managing a significant communication latency between Earth and Mars. Current and historical paradigms of EVA operations have required near-real-time communication between the crewmember(s) and Earth-based mission control. Nextgeneration operational paradigms for supporting deep space exploration will necessitate a distributed decision authority system, including delayed Earth-based mission control, the onplanet extravehicular crewmember(s), and intermediate mission support from intravehicular (IV) crewmember(s) within real-time communication range. This latter group is of particular interest: they must provide operations support without the plentiful resources available to mission control on Earth. Thus, NASA is developing the Personalized EVA Informatics and Decision Support (PersEIDS) software platform. PersEIDS is designed to bolster operator situational awareness and offload operator workload by automatically tracking and projecting consumables usage over an EVA timeline, providing real-time probabilistic safety assessments and recommending alternative EVA timeline(s) when the active timeline is not expected to be completed under consumables limits. The PersEIDS concept of operations, use cases, and models will be presented. A limited version of PersEIDS was demonstrated during a three-day-long study where each day a roughly four-hour-long simulated Martian EVA was performed in virtual reality at the NASA Johnson Space Center. The first day was a control trial without PersEIDS support; the second and third days represented different levels of decision support provided by PersEIDS to the IV crewmember acting as mission control. With PersEIDS support, the IV crewmember was able to manage the mission to completion faster and with more remaining consumables; however, additional testing is required to understand confounding factors, e.g., training bias.

Mars↗

Roadmap to Cooperative Operating Practices for Strategic Conflict Detection and Resolution in the Upper Class E Traffic Management Concept

As the governing body of flight operations in the highly anticipated emergent area of Upper Class E airspace (60,000 ft and above), the Federal Aviation Administration (FAA) has recognized the potential for a possible extensible traffic management system for new entrants into this domain. Following the successes with Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and Advanced / Urban Air Mobility (AAM / UAM) Traffic Management programs, FAA put forth an initial concept of operations for supporting the start of the Upper Class E Traffic Management (ETM) concept. Like UTM and AAM / UAM, ETM is envisioned to also be a community-based, industry driven cooperative management concept. However, tailoring it to be adaptable to the atmospheric communication, navigation, and surveillance deficits, as well as the diverse vehicle and mission profiles operating in the ETM environment will be the challenge. As such, the National Aeronautics and Space Administration (NASA) Ames Research Center has been investigating several technologies that will help enable industry in the development of this new type of cooperative operating environment. These technologies are being prototyped and will be tested in a collaborative evaluation of an initial ETM system in late 2023. The evaluation will concentrate on building out ETM system technologies that will inform the participants regarding operational intent sharing, strategic conflict detection, and the resultant deconfliction process. In addition to the technical aspects, key roles and responsibilities will need to be defined. This will be done through exploring community-agreed upon Cooperative Operating Practices (COPs) that include procedures and capabilities to aid in timely, strategic conflict identification and resolution to be developed during the evaluation. As an initial step to the evaluation, the ETM research team at NASA Ames solicited industry feedback on various aspects of ETM operations from subject matter experts. A virtual tabletop walkthrough session was held over a two-day period to follow a roadmap through the functional steps needed to build COPs, focusing on strategic conflict detection and resolution.

Upper Class E Traffic Management (ETM)↗