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NASA NTRSDate not supplied

Medical System Foundation Overview for Long-Duration Lunar Orbit and Surface Operations Missions

The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a Medical System Foundation for Level of Care IV, as defined by NASA’s space flight human-system standards, for long-duration lunar orbit and surface operation missions by employing a systems engineering approach using model-based systems engineering tools. This Foundation model includes a concept of operations; functional decomposition; clinical content (medical conditions, capabilities, and resources); associated functional, interface and non-functional technical requirements; and traces to the current versions of NASA standards documents and parent-level (Program- and Vehicle habitat system level) requirements. Collectively, these components constitute a foundation that serves as a starting point for a medical system that meets the Level of Care IV requirement. The Foundation was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA, and information is presented in an easily accessible format that is understandable across disciplines. Stakeholders can use the Foundation to analyze the traces between medical capabilities, medical conditions, medical resources, and requirements and to identify medical system interfaces with other vehicle systems/subsystems. It can also be used as a basis for performing trades on risks vs. medical system mass and volume allocation. This discussion will focus on the processes through which the Medical System Foundation was developed, how the Foundation builds a bridge between the medical and engineering domains and facilitates communication between these communities, and how these processes can be applied more broadly to a crew health and performance system and other system domains. The presentation also discusses Foundation modifications based on the recently updated versions of the NASA 3001 Standards.

S. Lumpkins↗

NASA NTRS1998

Urban Environment Initiative

The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.

Source record↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods. REFERENCES [1] Open science in space. Nature Medicine, 2021. 27(9): p. 1485-1485. [2] Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. [3] Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5. [4] Whetzel, P.L., et al., BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res, 2011. 39(Web Server issue): p. W541-5.

informatics↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

knowledge↗

NASA NTRS2022

A Survey of Mathematical Structures for Lunar Networks

To sustain the current and increasing accessibility of space, a scalable communications infrastructure (i.e. the Solar System Internet, SSI) is necessary. The goal of this paper is to begin the discovery of the fundamental underlying mathematical structure of space networks to help the research community harness these structures for algorithm development and optimization. To ensure the applicability of the research, the approaches are considered through the lens of simulated scenarios inspired by the Artemis Back-to-the-Moon mission set for 2024. We note that any approach to an SSI must fit under the umbrella of Delay Tolerant Networking (DTN), due to celestial mobility, high link latencies, high variance in link latencies, disconnections, lack of end-to-end paths, and so on. These difficulties are exacerbated by the fact that the underlying structure of a space network is a time-evolving network and may experience multiple discontinuities in its topology. In this paper we propose several novel approaches to a mathematical foundation for Delay Tolerant Networking Theory that fall outside the traditional scope of temporal network theory. These techniques include methods from Topological Data Analysis, Dynamic Graph Analysis, Applied Algebraic Geometry, Probability Theory, and Game Theory. Some of these methods include tools adapted to the study of dynamic metric spaces, such as zigzag persistent homology and their higher parameter analogs. We find that several of these methods target desired engineering outcomes such as discovery and automatic sub-netting. While each approach is theoretical, they are also algorithmic in nature and offer immediate practical applications. The paper concludes with comparisons of the various methods along with suggestions for future work.

Delay tolerant networking↗

NASA NTRS2003

Transferring Knowledge from Observations and Models to Decision Makers: An Overview and Challenges

Over the last 25 years, a tremendous progress has been made in the Earth science space-based remote sensing observations, technologies and algorithms. Such advancements have improved the predictability by providing lead-time and accuracy of forecast in weather, climate, natural hazards, and natural resources. It has further reduced or bounded the overall uncertainties by partially improving our understanding of planet Earth as an integrated system that is governed by non-linear and chaotic behavior. Many countries such US, European Community, Japan, China and others have invested billions of dollars in developing and launching space-based assets in the low earth (LEO) and geostationary (GEO) orbits. However, the wealth of this scientific knowledge that has potential of extracting monumental socio-economic benefits from such large investments have been slow in reaching to public and decision makers. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural competitiveness, disaster management, security, air quality and public health can directly take advantage. Nevertheless, we all live in a global economy that depends on access to the best available Earth Science information for all inhabitants of this planet. This paper surveys and examines a number such applications in terms of their architecture, maturity and economic applicability as they apply to the societal needs. A detailed analysis is also presented of various challenges and issues that pertain to a number of areas such as: (1) difficulties in making a speedy transition of data and information from observations and models to relevant Decision Support Systems (DSS) or tools, (2) data and models inter-operability issues, (3) limitations of spatial, spectral and temporal resolution, (4) communication limitations as dictated by the availability of image processing and data compression techniques. Additionally, the most critical element amongst all is the organizational and management boundaries that must be resolved at local, state, national and international levels to implement and realize free flow of such vital information. This paper also makes attempts to address this topic and discuss possible approaches to deal with this quandary.

Habib, Shahid↗

NASA NTRS2008

The NASA Real Time Mission Monitor - A Situational Awareness Tool for Conducting Tropical Cyclone Field Experiments

The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, aircraft state information, airborne and surface instruments, and weather state data in to a single visualization package for real time field experiment management. RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses (investigated African easterly waves and Tropical Storm Debby and Helene) during August-September 2006 in Cape Verde, the Tropical Composition, Cloud and Climate Coupling experiment during July-August 2007 in Costa Rica, and the Hurricane Aerosonde mission into Hurricane Noel in 2-3 November 2007. The integration and delivery of this information is made possible through data acquisition systems, network communication links, and network server resources built and managed by collaborators at NASA Marshall Space Flight Center (MSFC) and Dryden Flight Research Center (DFRC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols. Each field experiment presents unique challenges and opportunities for advancing the functionality of RTMM. A description of RTMM, the missions it has supported, and its new features that are under development will be presented.

Goodman, Michael↗

NASA NTRS2010

Utilizing Earth Observations for Societal Issues

Over the last four decades a tremendous progress has been made in the Earth science space-based remote sensing observations, technologies and algorithms. Such advancements have improved the predictability by providing lead-time and accuracy of forecast in weather, climate, natural hazards, and natural resources. It has further reduced or bounded the overall uncertainties by partially improving our understanding of planet Earth as an integrated system that is governed by non-linear and chaotic behavior. Many countries such as the US, European Community, Japan, China, Russia, India has and others have invested billions of dollars in developing and launching space-based assets in the low earth (LEO) and geostationary (GEO) orbits. However, the wealth of this scientific knowledge that has potential of extracting monumental socio-economic benefits from such large investments have been slow in reaching the public and decision makers. For instance, there are a number of areas such as water resources and availability, energy forecasting, aviation safety, agricultural competitiveness, disaster management, air quality and public health, which can directly take advantage. Nevertheless, we all live in a global economy that depends on access to the best available Earth Science information for all inhabitants of this planet. This presentation discusses a process to transition Earth science data and products for societal needs including NASA's experience in achieving such objectives. It is important to mention that there are many challenges and issues that pertain to a number of areas such as: (1) difficulties in making a speedy transition of data and information from observations and models to relevant Decision Support Systems (DSS) or tools, (2) data and models inter-operability issues, (3) limitations of spatial, spectral and temporal resolution, (4) communication limitations as dictated by the availability of image processing and data compression techniques. Additionally, the most critical element amongst all is the organizational and management boundaries that must be resolved at local, state, national and international levels to implement and realize free flow of such vital information.

Habib, Shahid↗

NASA NTRS2016

An Invited Preface for the Following Book: Astrobiologia, Uma Ciencia Emergente

Since the dawn of civilization, we have beheld at the beauty and wonder of the natural world around us and wondered how it came to be. We have pondered the past, and have been intrigued about the future. For this we are unique. Our ancestors looked to the vastness of space and thought surely there are others out there. We are now at a new time in human history where we can address these age-old questions with a scientific approach and study rigorously the three big questions of astrobiology: Where do we come from? Where are we going? and Are we alone? These fundamental questions of astrobiology correspond to those of humanity, and arguably, what makes us human. And so we cannot help but be drawn to the field. Unlike other scientific disciplines, Astrobiology draws on the latest advances in a multitude of fields, from evolutionary and molecular biology, to prebiotic and interstellar chemistry, from astrophysics to astronomy, with a healthy dose of earth and planetary science. Astrobiology is in reality a "metadiscipline" drawing on useful science wherever it is to be found. From a practical point of view, this endeavor requires the interaction of scientists who might not normally meet each other, much less work on a common research project. And, unlike most other scientific disciplines, Astrobiology has implications for how we see ourselves, and how we interact with the earth and beyond. "Where do we come from" touches on the "why" questions that have intrigued not just scientists but philosophers and theologians. "Where are we going" adds to these an economic and political involvement that is currently being played out with discussions of climate change. "And are we alone" will someday force us to face the fact that we as living creatures are not unique, or perhaps that we are utterly alone in the universe, the result of a chemical history that was so improbable as to result in a sample size of one. Either result will force ethical considerations of either "the other" and their relationship to us, or our solitude and thus responsibility as the only life form in our cosmos. So what is Astrobiology? Let's start with the "Where do we come from?" A biologist will approach this looking at the evolution of life on earth, using such traditional tools as comparative anatomy and paleontology and newer tools such as molecular techniques. But this doesn't address why this happened the way it did without a comprehensive understanding of the environment. What was the temperature at such and such a time? Was the earth in a snowball phase or being bombarded by meteorites -- or even just a single large, well-placed one such as struck off the Yucatan peninsula 65 million years ago. This event could not have been predicted by population genetics alone, yet it had the most profound influence on our evolution as without it, we could still be in a world dominated by dinosaurs with the mammals cowering under cover. But it is not enough to go back to LUCA, the Last Universal Common Ancestor of all extant life. One must go back to the dawn of life. How did life arise? What was the environmental backdrop that allowed it to happen? How did we happen to end up with a habitable planet? Indeed, what is the origin and evolution of our solar system, galaxy, biogenic elements all the way back to the Big Bang. The "Where are we going?" tends to be ignored in many astrobiology programs, but in fact this is of the most immediate importance to us. Whereas the past was dominated by physical and chemical processes, and organismal interactions, the future has a new major player: us. While we probably don't have the power (yet) to stop our galaxy passing through another, or even reset the sun or stop the movement of the moon away from the earth, all of these things will influence the future of life on earth. We are already proving that we have the power to visit other bodies in our solar system, either with humans or our robotic surrogates. We are changing our atmospheric composition and thus our climate. We have the power to render species extinct, including our own. But we also have the power to use these tools for the common good, to extend our lifetimes and reclaim our rivers and forests. Which will it be? And then there is the question where science fiction becomes a reality: "Are we alone?" While many people are anxious to find signs of intelligent life out there, such a creature may not share either our curiosity or values. But what if there was a beneficent alien civilization that could communicate with us, perhaps forging a mutual understanding? More likely in the forseeable future is finding a small life, less evolved, life form. Note I did not use the word "simple" as there is nothing "simple" about life, ever. Which brings us back to the question: what is life? So where does Brazil come in? For nearly a decade there has been interest in a Brazilian astrobiology program, from a small side meeting held by the Brazilian Exobiology Program (BEP) of the Brazilian National Research Council, held in Rio de Janeiro, Brazil, on August 12, 2009, in association with the IAU Assembly to subsequent workshops held in several locations and membership of the Brazilian program in the NASA Astrobiology Institute (NAI). Each time I go to Brazil, I am impressed by the enthusiasm of the community, both scientific and student, the latter an excellent omen for the future of astrobiology in Brazil. Facilities are being built to supplement the natural laboratories that Brazil is blessed to have. In my own lab I have been privileged to have a wonderful Brazilian postdoctoral fellow, Dr. Ivan Paulino-Lima, resulting in a daily reminder of the program. I am honored to have been part of the development of astrobiology in Brazil, and hope that this relationship will continue to flourish. Clearly to advance astrobiology needs new knowledge, a reorganization of that which is known, and space missions. To help the reader join on this quest, what follows is a buffet of topics that will allow the reader to nibble on the richness that is Astrobiology. And, like a fabulous meal, it should make you want more. Welcome to Astrobiology.

Are we alone?↗

NASA NTRS2022

PAAV Concept Document

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) Concept Document, version 1.0, lays out the key challenges and potential solutions for the use of uncrewed aircraft (UA) technology for future regional air cargo operations. The challenges and solutions described in this document were informed by communications with the UA industry community (e.g., RTCA, the Federal Aviation Administration, and regional air cargo business operators), as well as the PAAV team’s research activities during the last two years including four tabletop exercises, a human-in-the-loop simulation study, a numerical simulation study, a functional allocation study, and flight data analysis (Appendix A). This document first describes the expected operational context of PAAV (Section 2), such as the flight mission, baseline UAS components, nominal operations, m:N operations (i.e., "m" remote pilots per "N" aircraft), and off-nominal operations. This context sets the scope for the PAAV concept development work. PAAV concept development assumes that UA operations will be increasingly autonomous. Thus, near- and far-term assumptions are defined (Section 3). PAAV identified seven key challenges for UA operations (Section 4): - Flight route planning - Separation and flow management - Traffic pattern integration - Contingency management - Taxi, takeoff, and landing - m:N operations - Communications operations The following 13 potential solutions to these challenges are then described (Section 5): - Scalable communications architecture - Data link - Designated UAS corridors - Crew planning for m:N operations - Flight route optimization - Traffic load-level control - Trajectory solutions with data link - Automated hazard avoidance for m:N operations - Traffic pattern integration (TPI) tool - Standard lost command and control (C2) link (LC2L) procedures - Automated hazard avoidance under LC2L - Auto-taxi, auto-takeoff, and auto-land - Ground control station (GCS) user interface for m:N operations The document attempts to link each of these solutions to one or more of the challenge areas. Novel solutions involving numerous automation technologies are needed to mitigate traffic and airspace management challenges, especially for realizing m:N operations and ensuring safety under LC2L conditions. The purpose of this document is to help understand alternatives and tradeoffs among potential solutions and provide a foundation for a cohesive PAAV concept that will be described and refined in subsequent concept versions.

Unmanned aircraft, uncrewed aircraft, regional air↗

NASA NTRS2009

Integrated System Health Management: Foundational Concepts, Approach, and Implementation

A sound basis to guide the community in the conception and implementation of ISHM (Integrated System Health Management) capability in operational systems was provided. The concept of "ISHM Model of a System" and a related architecture defined as a unique Data, Information, and Knowledge (DIaK) architecture were described. The ISHM architecture is independent of the typical system architecture, which is based on grouping physical elements that are assembled to make up a subsystem, and subsystems combine to form systems, etc. It was emphasized that ISHM capability needs to be implemented first at a low functional capability level (FCL), or limited ability to detect anomalies, diagnose, determine consequences, etc. As algorithms and tools to augment or improve the FCL are identified, they should be incorporated into the system. This means that the architecture, DIaK management, and software, must be modular and standards-based, in order to enable systematic augmentation of FCL (no ad-hoc modifications). A set of technologies (and tools) needed to implement ISHM were described. One essential tool is a software environment to create the ISHM Model. The software environment encapsulates DIaK, and an infrastructure to focus DIaK on determining health (detect anomalies, determine causes, determine effects, and provide integrated awareness of the system to the operator). The environment includes gateways to communicate in accordance to standards, specially the IEEE 1451.1 Standard for Smart Sensors and Actuators.

Figueroa, Fernando↗

NASA NTRS2017

Operating Small Sat Swarms as a Single Entity: Introducing SODA

Swarm concepts are a growing topic of interest in the small satellite community. Compared to a small satellite constellation, a swarm has the distinction of being multiple spacecraft in close proximity, in approximately the same orbit. Furthermore, we envision swarms to have capabilities for cross-link communication and station-keeping. Of particular interest is a means to maintain operator-specified geometry, alignment, and/or separation.From NASA's decadal survey, it is clear that simultaneous measurements from a 3D volume of space are desired for a variety of Earth scientific studies. As this mission concept is ultimately extended to deep space, some degree of local control for the swarm to self-correct its configuration is required. We claim that the practicality of ground commanding each individual satellite in the swarm is simply not a feasible concept of operations. In other words, the current state-of-practice does not scale to very large swarms (e.g. 100 spacecraft or more) without becoming cost prohibitive. To contain the operations costs and complexity, a new approach is required: the swarm must be operated as a unit, responding to high-level specifications for relative position and velocity.The Mission Design Division at NASA Ames Research Center is looking to the near future for opportunities to develop satellite swarm technology. As part of this effort, we are developing SODA (Swarm Orbital Dynamics Advisor), a tool that provides the orbital maneuvers required to achieve a desired type of relative swarm motion. The purpose of SODA is two-fold. First, it encompasses the algorithms and orbital dynamics model to enable the desired relative motion of the swarm satellites. The process starts with the user specifying the properties of a swarm configuration. This could be as simple as varying in-track spacing of the swarm in one orbit, or as complex as maintaining a specified 3D geometrical orientation. We presume that science objectives will drive this choice. Given these inputs, the tool provides the most efficient maneuver(s) to achieve the objective.Second, SODA provides a variety of visualization tools. We acknowledge that the relationship between a desired relative motion amongst the swarm, and the corresponding orbital parameters for each individual satellite may not be immediately apparent for ground controllers and mission planners. The purpose of SODA's visualization tools is to illustrate this concept clearly with a variety of graphics and animations. After computing the optimal orbital maneuvers to modify the swarm, these results are simulated to demonstrate successful swarm control.Our emphasis in this paper is on the importance of relating the desired motion of the swarm satellites relative to one another with the required orbital element changes. One cannot joystick a drifting swarm satellite back into position; the underlying orbital mechanics dictate the most efficient recovery maneuvers. To illustrate this point, results from several case study simulations are presented. We conclude with our forward work for ongoing SODA development and potential science applications.

small satellites↗

NASA NTRS2010

Reconciling Scientific Aspirations and Engineering Constraints for a Lunar Mission via Hyperdimensional Interpolation

Virtually every NASA space-exploration mission represents a compromise between the interests of two expert, dedicated, but very different communities: scientists, who want to go quickly to the places that interest them most and spend as much time there as possible conducting sophisticated experiments, and the engineers and designers charged with maximizing the probability that a given mission will be successful and cost-effective. Recent work at NASA's Jet Propulsion Laboratory (JPL) seeks to enhance communication between these two groups, and to help them reconcile their interests, by developing advanced modeling capabilities with which they can analyze the achievement of science goals and objectives against engineering design and operational constraints. The analyses conducted prior to this study have been point-design driven. Each analysis has been of one hypothetical case which addresses the question: Given a set of constraints, how much science can be done? But the constraints imposed by the architecture team-e.g., rover speed, time allowed for extravehicular activity (EVA), number of sites at which science experiments are to be conducted- are all in early development and carry a great deal of uncertainty. Variations can be incorporated into the analysis, and indeed that has been done in sensitivity studies designed to see which constraint variations have the greatest impact on results. But if a very large number of variations can be analyzed all at once, producing a table that includes virtually the entire trade space under consideration, then we have a tool that enables scientists and mission architects to ask the inverse question: For a given desired level of science (or any other objective), what is the range of constraints that would be needed? With this tool, mission architects could determine, for example, what combinations of rover speed, EVA duration, and other constraints produce the desired results. Further, this tool would help them identify which technology-improvement investments would be likely to produce the largest or most important return. However, the number of variations that need to be considered for such analysis quickly balloons to an unwieldy size. If three variations are considered for each of six constraints-a very modest example-there are a total of 243 variations to consider. If it takes 40 minutes to compute each variation, as it does with HURON, our automated optimization system, then it would take 162 hours or nearly 7 days of round-the-clock computing to calculate the results. Adding further constraints or variations exponentially increases the amount of time that is needed.

Weisbin, Charles R.↗

NASA NTRS2010

Streamlining Payload Integration

Payload integration onto space transport vehicles and the International Space Station (ISS) is a complex process. Yet, cargo transport is the sole reason for any space mission, be it for ferrying humans, science, or hardware. As the largest such effort in history, the ISS offers a wide variety of payload experience. However, for any payload to reach the Space Station under the current process, Payload Developers face a list of daunting tasks that go well beyond just designing the payload to the constraints of the transport vehicle and its stowage topology. Payload customers are required to prove their payload s functionality, structural integrity, and safe integration - including under less than nominal situations. They must also plan for or provide training, procedures, hardware labeling, ground support, and communications. In addition, they must deal with negotiating shared consumables, integrating software, obtaining video, and coordinating the return of data and hardware. All the while, they must meet export laws, launch schedules, budget limits, and the consensus of more than 12 panel and board reviews. Despite the cost and infrastructure overhead, payload proposals have increased. Just in the span from FY08 to FY09, the NASA Payload Space Station Support Office budget rose from $78M to $96M in attempt to manage the growing manifest, but the potential number of payloads still exceeds available Payload Integration Management manpower. The growth has also increased management difficulties due to the fact that payloads are more frequently added to a flight schedule late in the flow. The current standard ISS template for payload integration from concept to payload turn-over is 36 months, or 18 months if the payload already has a preliminary design. Customers are increasingly requiring a turn-around of 3 to 6-months to meet market needs. The following paper suggests options for streamlining the current payload integration process in order to meet customer schedule needs and reduce costs for both the integration support teams and the developers, without reducing quality or compromising safety. Issues for the key integration areas of planning, training, verification, and safety are presented in a Root-Cause Analysis study, with plausible solutions provided that involve technology and tools already available to the ISS community. Although based upon the ISS process, the payload integration techniques outlined herein also offer an integration template for any space transport endeavor.

Lufkin, Susan N.↗

NASA NTRS1993

The Mars mapper science and mission planning tool

The Mars Mapper Program (MOm) is an interactive tool for science and mission design developed for the Mars Observer Mission (MO). MOm is a function of the Planning and Sequencing Element of the MO Ground Data System. The primary users of MOm are members of the science and mission planning teams. Using MOm, the user can display digital maps of Mars in various projections and resolutions ranging from 1 to 256 pixels per degree squared. The user can overlay the maps with ground tracks of the MO spacecraft (S/C) and footprints and swaths of the various instruments on-board the S/C. Orbital and instrument geometric parameters can be computed on demand and displayed on the digital map or plotted in XY-plots. The parameter data can also be saved into files for other uses. MOm is divided into 3 major processes: Generator, Mapper, Plotter. The Generator Process is the main control which spawns all other processes. The processes communicate via sockets. At any one time, only 1 copy of MOm may operate on the system. However, up to 5 copies of each of the major processes may be invoked from the Generator. MOm is developed on the Sun SPARCStation 2GX with menu driven graphical user interface (GUI). The map window and its overlays are mouse-sensitized to permit on-demand calculations of various parameters along an orbit. The program is currently under testing and will be delivered to the MO Mission System Configuration Management for distribution to the MO community in 3/93.

Lo, Martin W.↗

NASA NTRS2002

The Summer Robotic Autonomy Course

We offered a first Robotic Autonomy course this summer, located at NASA/Ames' new NASA Research Park, for approximately 30 high school students. In this 7-week course, students worked in ten teams to build then program advanced autonomous robots capable of visual processing and high-speed wireless communication. The course made use of challenge-based curricula, culminating each week with a Wednesday Challenge Day and a Friday Exhibition and Contest Day. Robotic Autonomy provided a comprehensive grounding in elementary robotics, including basic electronics, electronics evaluation, microprocessor programming, real-time control, and robot mechanics and kinematics. Our course then continued the educational process by introducing higher-level perception, action and autonomy topics, including teleoperation, visual servoing, intelligent scheduling and planning and cooperative problem-solving. We were able to deliver such a comprehensive, high-level education in robotic autonomy for two reasons. First, the content resulted from close collaboration between the CMU Robotics Institute and researchers in the Information Sciences and Technology Directorate and various education program/project managers at NASA/Ames. This collaboration produced not only educational content, but will also be focal to the conduct of formative and summative evaluations of the course for further refinement. Second, CMU rapid prototyping skills as well as the PI's low-overhead perception and locomotion research projects enabled design and delivery of affordable robot kits with unprecedented sensory- locomotory capability. Each Trikebot robot was capable of both indoor locomotion and high-speed outdoor motion and was equipped with a high-speed vision system coupled to a low-cost pan/tilt head. As planned, follow the completion of Robotic Autonomy, each student took home an autonomous, competent robot. This robot is the student's to keep, as she explores robotics with an extremely capable tool in the midst of a new community for roboticists. CMU provided undergraduate course credit for this official course, 16-162U, for 13 students, with all other students receiving course credit from National Hispanic University.

Nourbakhsh, Illah R.↗

NASA NTRS1998

Research and Technology 1997

NASA Lewis Research Center is responsible for developing and transferring critical technologies that address national priorities in aeropropulsion and space applications in partnership with U.S. industries, universities, and Government institutions. As NASA s designated Lead Center for Aeropropulsion, our role is to develop, verify, and transfer aeropropulsion technologies to U.S. industry. As NASA s designated Center of Excellence in Turbomachinery, our role is to develop new and innovative turbomachinery technology to improve the reliability, performance, efficiency and affordability, capacity, and environmental compatibility of future aerospace vehicles. We also maintain a science and technology development role in aeropropulsion, communications, space power and onboard propulsion, and microgravity fluid physics and combustion. We are committed to enabling non-aerospace U.S. industries to benefit directly from the technologies developed through our programs to maximize the benefit to the Nation and the return on each taxpayer s investment. In addition, we are aggressively pursuing continuous improvement in our management and business practices and striving for diversity in our workforce as together we push the edge of technology in space and aeronautics. The Lewis Research Center is a unique facility located in an important geographical area, the southwest corner of Cleveland, Ohio. Situated on 350 acres of land adjacent to the Cleveland Hopkins International Airport, Lewis comprises more than 140 buildings that include 24 major facilities and over 500 specialized research and test facilities. Additional facilities are located at Plum Brook Station, which is about 50 miles west of Cleveland. Over 3700 people staff Lewis, including civil service employees and support service contractors. Over half of them are scientists and engineers, who plan, conduct or oversee, and report on our research tasks and projects. They are assisted by technical specialists, skilled workers, and an administrative staff. Our end product is knowledge. This report is designed to help us make this knowledge fully available to potential users the aircraft engine industry, the energy industry, the automotive industry, the aerospace industry, and others. It is organized so that a broad cross section of the community can readily use it. Each article begins with a short introductory paragraph that should prove to be a valuable tool for the layperson. These articles summarize the progress made during the year in various technical areas and portray the technical and administrative support associated with Lewis technology programs. We hope that the information is useful to all. If additional information is desired, readers are encouraged to contact the researchers identified in the articles and to visit Lewis on the World Wide Web (http://www.lerc.nasa.gov/). This document is available on the World Wide Web (http://www.lerc.nasa.gov/WWW/RT).

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Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

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