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NASA NTRS2014

NASA Extreme Environment Mission Operations: Science Operations Development for Human Exploration

The purpose of NASA Extreme Environment Mission Operations (NEEMO) mission 16 in 2012 was to evaluate and compare the performance of a defined series of representative near-Earth asteroid (NEA) extravehicular activity (EVA) tasks under different conditions and combinations of work systems, constraints, and assumptions considered for future human NEA exploration missions. NEEMO 16 followed NASA's 2011 Desert Research and Technology Studies (D-RATS), the primary focus of which was understanding the implications of communication latency, crew size, and work system combinations with respect to scientific data quality, data management, crew workload, and crew/mission control interactions. The 1-g environment precluded meaningful evaluation of NEA EVA translation, worksite stabilization, sampling, or instrument deployment techniques. Thus, NEEMO missions were designed to provide an opportunity to perform a preliminary evaluation of these important factors for each of the conditions being considered. NEEMO 15 also took place in 2011 and provided a first look at many of the factors, but the mission was cut short due to a hurricane threat before all objectives were completed. ARES Directorate (KX) personnel consulted with JSC engineers to ensure that high-fidelity planetary science protocols were incorporated into NEEMO mission architectures. ARES has been collaborating with NEEMO mission planners since NEEMO 9 in 2006, successively building upon previous developments to refine science operations concepts within engineering constraints; it is expected to continue the collaboration as NASA's human exploration mission plans evolve.

Bell, Mary S.↗

NASA NTRS2007

The Challenges of Integrating NASA's Human, Budget, and Data Capital within the Constellation Program's Exploration Launch Projects Office

The U.S. Vision for Space Exploration directs NASA to retire the Space Shuttle in 2010 and replace it with safe, reliable, and cost-effective space transportation systems for crew and cargo travel to the Moon, Mars, and beyond. Such emerging space transportation initiatives face massive organizational challenges, including building and nurturing an experienced, dedicated team with the right skills for the required tasks; allocating and tracking the fiscal capital invested in achieving technical progress against an integrated master schedule; and turning generated data into useful knowledge that equips the team to design and develop superior products for customers and stakeholders. It has been more than 30 years since the Space Shuttle was designed; therefore, the current aerospace workforce has limited experience with developing new designs for human-rated spaceflight hardware. To accomplish these activities, NASA is using a wide range of state-of-the-art information technology tools that connect its diverse, decentralized teams and provide timely, accurate information for decision makers. In addition, business professionals are assisting technical managers with planning, tracking, and forecasting resource use against an integrated master schedule that horizontally and vertically interlinks hardware elements and milestone events. Furthermore, NASA is employing a wide variety of strategies to ensure that it has the motivated and qualified staff it needs for the tasks ahead. This paper discusses how NASA's Exploration Launch Projects Office, which is responsible for delivering these new launch vehicles, integrates its resources to create an engineering business environment that promotes mission success, which is defined by replacing the Space Shuttle by 2014 and returning to the Moon by 2020.

Kidd, Luanne↗

NASA NTRSDate not supplied

Human Specimen Repository: Sample Collection for the Future [#133-000445]

In early 2014, an executive memo was released directing the improvement of the management of and access to scientific collections funded by government resources. In the spirit of this memo, NASA’s Human Research Program (HRP) funded a project to review existing residual samples in long-term storage for viability, identification, and scientific significance. These samples were to be collected in a centralized location and a detailed inventory was to be conducted to create the Human Sample Repository (HSR). HSR would work to review data from over 27,000 samples, from flight research projects dating back to 1998. The samples themselves would be reviewed, re-labeled, and organized into easy to retrieve, long-term storage. In addition to the older residual samples, HSR would expand to include pristine samples from all consenting crew who have flown on International Space Station (ISS) missions. All samples inventoried and managed by HSR are intended for the same purpose; to support future research projects which will utilize advanced technologies or techniques, by providing one-of-a-kind sample collections that can not be replicated. With this mission in mind, HSR will continue to collect residual samples from HRP funded projects and pristine samples from consenting crew, to further build this unique collection and increase the diversity of flight samples available to the scientific community.

Human Specimen Repository↗

NASA NTRS1987

Space station evolution: Planning for the future

The need for permanently manned presence in space has been recognized by the United States and its international partners for many years. The development of this capability was delayed due to the concurrent recognition that reusable earth-to-orbit transportation was also needed and should be developed first. While the decision to go ahead with a permanently manned Space Station was on hold, requirements for the use of the Station were accumulating as ground-based research and the data from unmanned spacecraft sparked the imagination of both scientists and entrepreneurs. Thus, by the time of the Space Station implementation decision in the early 1980's, a variety of disciplines, with a variety of requirements, needed to be accommodated on one Space Station. Additional future requirements could be forecast for advanced missions that were still in the early planning stages. The logical response was the development of a multi-purpose Space Station with the ability to evolve on-orbit to new capabilities as required by user needs and national or international decisions, i.e., to build an evolutionary Space Station. Planning for evolution is conducted in parallel with the design and development of the baseline Space Station. Evolution planning is a strategic management process to facilitate change and protect future decisions. The objective is not to forecast the future, but to understand the future options and the implications of these on today's decisions. The major actions required now are: (1) the incorporation of evolution provisions (hooks and scars) in the baseline Space Station; and (2) the initiation of an evolution advanced development program.

Diaz, Alphonso V.↗

NASA NTRS1999

The Tropical Rainfall Measuring Mission and Vern Suomi 's Vital Role

The Tropical Rainfall Measuring Mission was a new concept of measuring rainfall over the global tropics using a combination of instruments, including the first weather radar to be flown in space. An important objective of the mission was to obtain profiles of latent heat in order to initialize large-scale circulation models and to understand the relationship between short-term climate changes in relation to rainfall variability. The idea originated in the early 1980's from scientists at the Goddard Space Flight Center/NASA who had been involved with attempts to measure rain with a passive microwave instrument on Nimbus 5 and had compared its results with rain falling in the area covered by the GATE1 radar ships. Using an imaginary satellite flying over the GATE ships, scientists showed that a satellite with an inclined orbit of 30-35 degrees could obtain monthly rainfalls with a sampling error of less than 10 percent over 5 degree by 5 degree areas. The Japanese proposed that they could build a nadir-scanning rain radar for the satellite. Vern Suomi was excited by this mission from the outset, since he recognized the great importance of adequate rainfall measurements over the tropical oceans. He was a charter member of the Science Steering Team and prepared a large part of the Report. While the mission attracted strong support in the science community, it was opposed by some of the high-level NASA management who feared its competition for funds with some much larger Earth Science satellites. Vern was able to overcome this opposition and to generate Congressional support, so that the Project finally got underway on both sides of the Pacific in 1991. The paper will discuss the design of the satellite, its data system and ground validation program. TP.NM was successfully launched in late 1997. Early results will be described. 1 GATE stands for GARP Atlantic Tropical Experiment and GARP stands for Global Atmospheric Research Program.

Simpson, Joanne↗

NASA NTRS2005

Development of the Surface Management System Integrated with CTAS Arrival Tools

The Surface Management System (SMS) developed by NASA Ames Research Center in coordination with the Federal Aviation Administration (FAA) is a decision support tool to help tower traffic coordinators and Ground/Local controllers in managing and controlling airport surface traffic in order to increase capacity, efficiency, and flexibility. SMS provides common situation awareness to personnel at various air traffic control facilities such as airport traffic control towers (ATCT s), airline ramp towers, Terminal Radar Approach Control (TRACON), and Air Route Traffic Control Center (ARTCC). SMS also provides a traffic management tool to assist ATCT traffic management coordinators (TMCs) in making decisions such as airport configuration and runway load balancing. The Build 1 of the SMS tool was installed and successfully tested at Memphis International Airport (MEM) and received high acceptance scores from ATCT controllers and coordinators, as well as airline ramp controllers. NASA Ames Research Center continues to develop SMS under NASA s Strategic Airspace Usage (SAU) project in order to improve its prediction accuracy and robustness under various modeling uncertainties. This paper reports the recent development effort performed by the NASA Ames Research Center: 1) integration of Center TRACON Automation System (CTAS) capability with SMS and 2) an alternative approach to obtain airline gate information through a publicly available website. The preliminary analysis results performed on the air/surface traffic data at the DFW airport have shown significant improvement in predicting airport arrival demand and IN time at the gate. This paper concludes with recommendations for future research and development.

Jung, Yoon C.↗

NASA NTRS2011

NASA Accident Precursor Analysis Handbook, Version 1.0

Catastrophic accidents are usually preceded by precursory events that, although observable, are not recognized as harbingers of a tragedy until after the fact. In the nuclear industry, the Three Mile Island accident was preceded by at least two events portending the potential for severe consequences from an underappreciated causal mechanism. Anomalies whose failure mechanisms were integral to the losses of Space Transportation Systems (STS) Challenger and Columbia had been occurring within the STS fleet prior to those accidents. Both the Rogers Commission Report and the Columbia Accident Investigation Board report found that processes in place at the time did not respond to the prior anomalies in a way that shed light on their true risk implications. This includes the concern that, in the words of the NASA Aerospace Safety Advisory Panel (ASAP), "no process addresses the need to update a hazard analysis when anomalies occur" At a broader level, the ASAP noted in 2007 that NASA "could better gauge the likelihood of losses by developing leading indicators, rather than continue to depend on lagging indicators". These observations suggest a need to revalidate prior assumptions and conclusions of existing safety (and reliability) analyses, as well as to consider the potential for previously unrecognized accident scenarios, when unexpected or otherwise undesired behaviors of the system are observed. This need is also discussed in NASA's system safety handbook, which advocates a view of safety assurance as driving a program to take steps that are necessary to establish and maintain a valid and credible argument for the safety of its missions. It is the premise of this handbook that making cases for safety more experience-based allows NASA to be better informed about the safety performance of its systems, and will ultimately help it to manage safety in a more effective manner. The APA process described in this handbook provides a systematic means of analyzing candidate accident precursors by evaluating anomaly occurrences for their system safety implications and, through both analytical and deliberative methods used to project to other circumstances, identifying those that portend more serious consequences to come if effective corrective action is not taken. APA builds upon existing safety analysis processes currently in practice within NASA, leveraging their results to provide an improved understanding of overall system risk. As such, APA represents an important dimension of safety evaluation; as operational experience is acquired, precursor information is generated such that it can be fed back into system safety analyses to risk-inform safety improvements. Importantly, APA utilizes anomaly data to predict risk whereas standard reliability and PRA approaches utilize failure data which often is limited and rare.

Groen, Frank↗

NASA NTRS2014

Use of Semi-Autonomous Tools for ISS Commanding and Monitoring

As the International Space Station (ISS) has moved into a utilization phase, operations have shifted to become more ground-based with fewer mission control personnel monitoring and commanding multiple ISS systems. This shift to fewer people monitoring more systems has prompted use of semi-autonomous console tools in the ISS Mission Control Center (MCC) to help flight controllers command and monitor the ISS. These console tools perform routine operational procedures while keeping the human operator "in the loop" to monitor and intervene when off-nominal events arise. Two such tools, the Pre-positioned Load (PPL) Loader and Automatic Operators Recorder Manager (AutoORM), are used by the ISS Communications RF Onboard Networks Utilization Specialist (CRONUS) flight control position. CRONUS is responsible for simultaneously commanding and monitoring the ISS Command & Data Handling (C&DH) and Communications and Tracking (C&T) systems. PPL Loader is used to uplink small pieces of frequently changed software data tables, called PPLs, to ISS computers to support different ISS operations. In order to uplink a PPL, a data load command must be built that contains multiple user-input fields. Next, a multiple step commanding and verification procedure must be performed to enable an onboard computer for software uplink, uplink the PPL, verify the PPL has incorporated correctly, and disable the computer for software uplink. PPL Loader provides different levels of automation in both building and uplinking these commands. In its manual mode, PPL Loader automatically builds the PPL data load commands but allows the flight controller to verify and save the commands for future uplink. In its auto mode, PPL Loader automatically builds the PPL data load commands for flight controller verification, but automatically performs the PPL uplink procedure by sending commands and performing verification checks while notifying CRONUS of procedure step completion. If an off-nominal condition occurs during procedure execution, PPL Loader notifies CRONUS through popup messages, allowing CRONUS to examine the situation and choose an option of how PPL loader should proceed with the procedure. The use of PPL Loader to perform frequent, routine PPL uplinks offloads CRONUS to better monitor two ISS systems. It also reduces procedure performance time and decreases risk of command errors. AutoORM identifies ISS communication outage periods and builds commands to lock, playback, and unlock ISS Operations Recorder files. Operation Recorder files are circular buffer files of continually recorded ISS telemetry data. Sections of these files can be locked from further writing, be played back to capture telemetry data that occurred during an ISS loss of signal (LOS) period, and then be unlocked for future recording use. Downlinked Operation Recorder files are used by mission support teams for data analysis, especially if failures occur during LOS. The commands to lock, playback, and unlock Operations Recorder files are encompassed in three different operational procedures and contain multiple user-input fields. AutoORM provides different levels of automation for building and uplinking the commands to lock, playback, and unlock Operations Recorder files. In its automatic mode, AutoORM automatically detects ISS LOS periods, then generates and uplinks the commands to lock, playback, and unlock Operations Recorder files when MCC regains signal with ISS. AutoORM also features semi-autonomous and manual modes which integrate CRONUS more into the command verification and uplink process. AutoORMs ability to automatically detect ISS LOS periods and build the necessary commands to preserve, playback, and release recorded telemetry data greatly offloads CRONUS to perform more high-level cognitive tasks, such as mission planning and anomaly troubleshooting. Additionally, since Operations Recorder commands contain numerical time input fields which are tedious for a human to manually build, AutoORM's ability to automatically build commands reduces operational command errors. PPL Loader and AutoORM demonstrate principles of semi-autonomous operational tools that will benefit future space mission operations. Both tools employ different levels of automation to perform simple and routine procedures, thereby offloading human operators to perform higher-level cognitive tasks. Because both tools provide procedure execution status and highlight off-nominal indications, the flight controller is able to intervene during procedure execution if needed. Semi-autonomous tools and systems that can perform routine procedures, yet keep human operators informed of execution, will be essential in future long-duration missions where the onboard crew will be solely responsible for spacecraft monitoring and control.

Brzezinski, Amy S.↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Reproducible, data-driven thermal protection system (TPS) research requires that experimental records from high-enthalpy testing be consistently structured, traceable, and accessible across campaigns and institutions. In practice, however, arcjet and plasma facilities data remain largely fragmented: raw diagnostics are stored in ad hoc formats, material sample histories are disconnected from test conditions, and metadata standards are absent, precluding systematic cross-campaign analysis and long-term reuse. BEAST (Backend for Experiment Analysis, Storage, and Traceability) is an open-source, web-based platform that addresses these limitations by providing a unified, queryable infrastructure for high-enthalpy ground-test data [1]. First presented at the 15th Ablation Workshop [2], BEAST has since undergone significant development. The platform ingests and structures multi-channel time-series diagnostics, facility configurations, and material property records within a common provenance model, ensuring end-to-end traceability from raw sensor acquisition to reduced experimental quantities. A versioned material library links specimen identity and processing history to the specific runs in which each sample was tested. An integrated modeling workbench enables training and evaluation of regression models directly on archived experimental data, supporting condition interpolation and the construction of empirical material response databases. Beyond its original deployment at NASA Ames Research Center, BEAST has been designed to be facility-agnostic, with ongoing efforts to extend its adoption to other facilities. Its modular architecture accommodates heterogeneous diagnostic setups and facility types, and its future open-source distribution allows institutions to build on a common data standard rather than maintaining isolated, bespoke solutions. BEAST is further integrated within a broader ecosystem of companion tools: arcjetCV [3] extracts recession rates and shock standoff distances from high-speed video using computer vision, and miniSTARscan [4] provides sub-minute, portable photogrammetric surface reconstruction of test articles before and after exposure. All tools share a common data schema, enabling seamless ingestion of surface geometry, imagery, and time-series data into a single, coherent experimental record.

Database↗

NASA NTRSDate not supplied

BEAST: Expanding Sustainable Data Infrastructure for High-Enthalpy Facilities

Database↗

NASA NTRSDate not supplied

Defining Services, Functions, and Capabilities for an Advanced Air Mobility (AAM) In-time Aviation Safety Management System (IASMS)

NASA’s vision for Advanced Air Mobility (AAM) Mission is to help emerging aviation markets to safely develop an air transportation system that moves people and cargo between places previously not served or underserved by aviation. The integration of new operational paradigms and vehicle classes in this system requires a transformation of the National Airspace System (NAS) that includes substantive changes critical for assuring safety. These changes are compelled by unique challenges posed by AAM to the safety management system (SMS). These challenges were assessed by committees of the National Academies in their reports on a vision for an In-time Aviation Safety Management System (IASMS) and a blueprint for AAM [1,2]. In their description of an IASMS, the top recommendation was development of a concept of operations (ConOps) for IASMS. This paper describes the high-priority recommendations from the National Academies for its IASMS vision and how they are addressed through a distributed system-of-systems architecture. The IASMS architecture is structured on the services, functions, and capabilities (SFCs) necessary for In-time System-wide Safety Assurance (ISSA)initially developed for urban air mobility (UAM). The paper then posits where these SFCs would reside across vehicles, airspace, or service suppliers such as Supplemental Data Service Providers (SDSPs), and how SFCs scale with increasing complexity in design and operations of AAM. SFCs are foundational building blocks for a system that targets an individual or family of risks using a Monitor-Assess-Mitigate risk paradigm for anomalies, precursors and trends. An IASMS could be conceived that uses a portfolio of SFCs for AAM in general or prioritizes SFCs for a specific domain or operation.

K Ellis↗

NASA NTRS2008

Application of Pi Preform Composite Joints in Fabrication of NASA Composite Crew Module Demonstration Structure

This paper will describe unique and extensive use of pre-woven and impregnated pi cross-sections in fabrication of a carbon composite demonstration structure for the Composite Crew Module (CCM) Program. The program is managed by the NASA Safety and Engineering Center with participants from ten NASA Centers and AFRL. Multiple aerospace contractors are participating in the design development, tooling and fabrication effort as well. The goal of the program is to develop an agency wide design team for composite habitable spacecraft. The specific goals for this development project are: a) To gain hands on experience in design, building and testing a composite crew module. b) To validate key assumptions by resolving composite spacecraft design details through fabrication and testing of hardware. This paper will focus on the design and fabrication issues supporting selection of the Lockheed Martin patented Pi pre-form to provide sound composite joints a numerous locations in the structure. This abstract is based on Preliminary Design data. The final design will continue to evolve through the fall of 2007 with fabrication mostly completed by conference date.

Higgins, John E.↗

NASA NTRS2011

Testing Strategies and Methodologies for the Max Launch Abort System

The National Aeronautics and Space Administration (NASA) Engineering and Safety Center (NESC) was tasked to develop an alternate, tower-less launch abort system (LAS) as risk mitigation for the Orion Project. The successful pad abort flight demonstration test in July 2009 of the "Max" launch abort system (MLAS) provided data critical to the design of future LASs, while demonstrating the Agency s ability to rapidly design, build and fly full-scale hardware at minimal cost in a "virtual" work environment. Limited funding and an aggressive schedule presented a challenge for testing of the complex MLAS system. The successful pad abort flight demonstration test was attributed to the project s systems engineering and integration process, which included: a concise definition of, and an adherence to, flight test objectives; a solid operational concept; well defined performance requirements, and a test program tailored to reducing the highest flight test risks. The testing ranged from wind tunnel validation of computational fluid dynamic simulations to component ground tests of the highest risk subsystems. This paper provides an overview of the testing/risk management approach and methodologies used to understand and reduce the areas of highest risk - resulting in a successful flight demonstration test.

Schaible, Dawn M.↗

NASA NTRS2014

SpaceCube v2.0 Space Flight Hybrid Reconfigurable Data Processing System

This paper details the design architecture, design methodology, and the advantages of the SpaceCube v2.0 high performance data processing system for space applications. The purpose in building the SpaceCube v2.0 system is to create a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. The SpaceCube v2.0 system leverages seven years of board design, avionics systems design, and space flight application experiences. This paper shows how SpaceCube v2.0 solves the increasing computing demands of space data processing applications that cannot be attained with a standalone processor approach.The main objective during the design stage is to find a good system balance between power, size, reliability, cost, and data processing capability. These design variables directly impact each other, and it is important to understand how to achieve a suitable balance. This paper will detail how these critical design factors were managed including the construction of an Engineering Model for an experiment on the International Space Station to test out design concepts. We will describe the designs for the processor card, power card, backplane, and a mission unique interface card. The mechanical design for the box will also be detailed since it is critical in meeting the stringent thermal and structural requirements imposed by the processing system. In addition, the mechanical design uses advanced thermal conduction techniques to solve the internal thermal challenges.The SpaceCube v2.0 processing system is based on an extended version of the 3U cPCI standard form factor where each card is 190mm x 100mm in size The typical power draw of the processor card is 8 to 10W and scales with application complexity. The SpaceCube v2.0 data processing card features two Xilinx Virtex-5 QV Field Programmable Gate Arrays (FPGA), eight memory modules, a monitor FPGA with analog monitoring, Ethernet, configurable interconnect to the Xilinx FPGAs including gigabit transceivers, and the necessary voltage regulation. The processor board uses a back-to-back design methodology for common parts that maximizes the board real estate available. This paper will show how to meet the IPC 6012B Class 3A standard with a 22-layer board that has two column grid array devices with 1.0mm pitch. All layout trades such as stack-up options, via selection, and FPGA signal breakout will be discussed with feature size results. The overall board design process will be discussed including parts selection, circuit design, proper signal termination, layout placement and route planning, signal integrity design and verification, and power integrity results. The radiation mitigation techniques will also be detailed including configuration scrubbing options, Xilinx circuit mitigation and FPGA functional monitoring, and memory protection.Finally, this paper will describe how this system is being used to solve the extreme challenges of a robotic satellite servicing mission where typical space-rated processors are not sufficient enough to meet the intensive data processing requirements. The SpaceCube v2.0 is the main payload control computer and is required to control critical subsystems such as autonomous rendezvous and docking using a suite of vision sensors and object avoidance when controlling two robotic arms.

Xilinx FPGA↗

NASA NTRSDate not supplied

Exploring the Moon: Training Astronauts for Artemis Missions

For the first time in over 50 years, NASA scientists are training astronauts assigned to lunar missions. The successful Artemis 1 test flight in 2022 set the stage for future human missions to the Moon. The Artemis II mission will send astronauts to fly by the Moon, providing the first opportunity since Apollo for humans to directly observe and document the lunar surface from a few thousand kilometers, including the lunar far side. Artemis III will be the first human mission to land and explore the Moon’s surface near the lunar South Pole. To prepare for Artemis exploration, geology training for the Artemis II crew and detailed training plans for Artemis III and beyond are in full swing. NASA scientists have been working for several years with the Flight Operations Directorate (FOD) at the Johnson Space Center on a progressive geology training program that starts with incoming astronaut classes, offers opportunities to maintain the geology proficiency between flight assignments, and trains the broader engineering-operations-management community in geology and field operations. In the spring of 2023, our team developed an introductory week-long class called Lunar Fundamentals and delivered this content to the Artemis II crew, as well as key NASA Flight Control Team members. The Lunar Fundamentals curriculum combines basic geographic and geologic information about the Moon; includes detailed content on major geologic processes, the lunar environment, lunar volatiles, and sample science; provides historical context of our growing knowledge about the Moon; and introduces new lunar data sets and tools for exploring the lunar surface. With the Lunar Fundamentals foundation, we continue development of the advanced planetary science classroom content for the Artemis III crew, together with field training science objectives and plans. Partnering with our FOD colleagues, we are building an integrated training plan for lunar science, exploration field methods, and operational skills to ensure that the Artemis astronauts exploring the Moon will have the necessary foundation in geology and lunar science to achieve mission success.

Astronauts training↗

NASA NTRSDate not supplied

Identifying Common Use Cases across Extensible Traffic Management (xTM) for Interactions with Air Traffic Controllers

NASA’s Extensible Traffic Management (xTM) builds on the foundation and the architecture of Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concept and extends it broadly to other domains, such as Advanced / Urban Air Mobility (AAM/UAM) and Upper Class E Traffic Management (ETM). These xTM concepts assume the ability to fly in airspace that is authorized to operate solely under xTM services and mostly without any air traffic control (ATC) support. However, they also assume circumstances in which the xTM vehicles would need to operate in conventional ATC-managed airspace, both during nominal and off-nominal scenarios. Due to the vast differences in the xTM vehicle performances and missions, there is a concern that ATC may have difficulty in safely managing the xTM traffic and providing appropriate services to all vehicles, unless a consistent set of roles, procedures, and data exchange requirements are defined across the diverse set of xTM vehicle operations. In this paper, we describe a set of use cases that have been identified in UTM, AAM/UAM, and ETM operations that are related to ATC interactions, and we propose to categorize these use cases across xTM domains based on common trigger events. Organizing the use cases from the perspective of ATC roles per each trigger event is expected to provide the first step in discovering common procedures and data requirements across xTM domains that could help ease the controllers’ cognitive task load and allow them to manage these interactions more safely.

Extensible Traffic Management (xTM)↗

NASA NTRS1990

Transition flight control room automation

The Workstation Prototype Laboratory is currently working on a number of projects which can have a direct impact on ground operations automation. These projects include: (1) The fuel cell monitoring system (FCMS), which will monitor and detect problems with the fuel cells on the shuttle. FCMS will use a combination of rules (forward/backward) and multithreaded procedures, which run concurrently with the rules, to implement the malfunction algorithms of the EGIL flight controllers. The combination of rule-based reasoning and procedural reasoning allows us to more easily map the malfunction algorithms into a real-time system implementation. (2) A graphical computation language (AGCOMPL) is an experimental prototype to determine the benefits and drawbacks of using a graphical language to design computations (algorithms) to work on shuttle or space station telemetry and trajectory data. (3) The design of a system will allow a model of an electrical system, including telemetry sensors, to be configured on the screen graphically using previously defined electrical icons. This electrical model would then be used to generate rules and procedures for detecting malfunctions in the electrical components of the model. (4) A generic message management (GMM) system is being designed for real-time applications as a message management system which sends advisory messages to a user. The primary purpose of GMM is to reduce the risk of overloading a user with information when multiple failures occur and to assist the developer in the devising an explanation facility. The emphasis of our work is to develop practical tools and techniques, including identification of appropriate software tools to support research, application, and tool building activities, while determining the feasibility of a given approach.

Welborn, Curtis Ray↗

NASA NTRSDate not supplied

Novel Observing Strategies (NOS) and Earth System Digital Twins (ESDT) for Disaster Resilience

"Earth systems have now been observed continuously for more than 50 years, not only from space but also from airplanes, balloons and in-situ sensors. With the addition of commercial remote sensing providers, many more Internet-of-Things sensors and new NASA and international observatories being planned, these incredible amounts of data will soon be augmented by even larger amounts of diverse data and therefore will become more and more difficult to access, integrate, understand and utilize. At the same time, because of climate change and its impacts, in order to predict, manage, and mitigate the effects of extreme science events and disasters, the information produced by all of this data needs to be optimized, organized and analyzed in such a way that it can be utilized by traditional as well as many new non-traditional users. This calls for the development of observing systems that are agile, coordinated and responsive to events of interest, and for information systems to be dynamic, interactive and fast. With these objectives in mind, the Advanced Information Systems Technology (AIST) Program has been developing technologies that will allow for the development of Novel Observing Strategies (NOS) in a distributed, coordinated fashion (i.e., similar to an “Internet-of-Earth-Things”), as well as for the development of novel information systems or Earth System Digital Twins (ESDT) that will build a digital replica of the past and current states of the Earth systems, will derive forecasts of future states under nominal assumptions and will also offer the capability to investigate many hypothetical evolution scenarios under varying impact assumptions. Both NOS and ESDT will be facilitated by the unprecedented advances of Artificial Intelligence technologies, especially Machine Learning (ML), for extracting relevant information from these large amounts of data, for fusing and assimilating diverse data together and for running complex models faster. Together NOS and ESDT will help build the capabilities needed to anticipate, predict and mitigate the effects of future disasters."

Earth Science Remote Sensing; Information Systems↗