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At least 109 records · Page 6

AztechSat-1, a First Collaborative CubeSat Between NASA and Mexico

An international collaboration program for capacity building in space technology is being established between NASA and the Mexican Space Agency (AEM). Its objective is to develop a series of CubeSats collaboratively in a way that benefits both agencies. For AEM, this experience will support the development of human capital required for its space program. This project provides an opportunity for NASA future missions to benefit from commercially available technologies demonstrated in space. AEM was recently created by the Mexican Government to use and develop space technology in Mexico. Current AEM plans call for having the capability of developing its own communication satellites by 2030, so the need for having a Mexican cadre of space experts is mandatory. The program will start with the development and launching of AztechSat-1, the first AEM CubeSat project to be deployed from the International Space Station (ISS). Several public Mexican universities will participate in this project to demonstrate GlobalStar, a satellite communications provider using a constellation of LEO satellites, as an option for small satellite missions. AztechSat-1 mission objectives are:(1) Develop a flight ready CubeSat for deployment from the ISS; (2) Demonstrate GlobalStar´s Network as a method to advance communications in CubeSat missions. AztechSat-1 is envisioned as a 1U CubeSat and will be designed and constructed by Mexican graduate students from two major universities in Mexico: UNAM and IPN. The students will be mentored and supervised by researchers from NASA Ames Research Center (NARC). Flight acceptance tests are going to be done both at Mexican university labs as well as at NARC. Funding for the project will be provided concurrently by AEM, the Mexican participating universities, and other Mexican entities. The development of AztechSat-1 will emphasize the transfer of knowledge in space mission analysis and design, flight acceptance testing and other areas of space technology which are not well developed in Mexico yet. Mexican students will benefit from their mentoring from NASA researchers and will provide a multiplier effect in the development of the next generation of Mexican aerospace engineers. AztechSat-1 will be developed in a period of twelve months and will be launched by late 2015. AztechSat´s success will define the future of collaboration between NASA and AEM in capacity building. A plan for developing a series of AztechSat’s in a one per year basis, with increasing capabilities and complexity is currently being negotiated between NASA an AEM.

Martinez, Andres↗

International Data Collaboration for Risk-Based Safety and Mission Assurance

Some of the topics being discussed during this presentation are How things are being collaborating now, the Benefits from more data collaboration, the Opportunities for data collaboration and How can they share data. Additional information will be discussed through out the presentation slide deck.

Fischer, Gerd M.↗

NASA's Role in Gas Turbine Technology Development: Accelerating Technical Progress via Collaboration Between Academia, Industry, and Government Agencies

Given the maturity of the gas turbine engine since its invention and also considering the limited and flattened level of resources expected to be allocated for NASA aeronautics research and development, we ask the question are NASA technology investments still needed to enable future turbine engine-based propulsion systems? If so, what is NASA’s unique role to justify NASA’s investment? To address this topic, we will first review the accomplishments and the impact that NASA Glenn Research Center has made on turbine engine technologies over the last 78 years. Specifically, this paper discusses NASA’s role and contributions to turbine engine development, specific to both 1) NASA’s role in conducting experiments to understand flow physics and provide relevant benchmark validation experiments for Computational Fluid Dynamics (CFD) code development, validation, and assessment; and 2) the impact of technologies resulting from NASA collaborations with industry, academia, and other government agencies. Note that the scope of the discussion is limited to the NASA technology contributions with which the author was intimately associated, and does not represent the entirety of the NASA contributions to turbine engine technology. The specific research, development, and demonstrations discussed herein were selected to both 1) provide a comprehensive review and reference list of the technology and its impact, and 2) identify NASA’s unique role and highlight how NASA’s involvement resulted in additional benefit to the gas turbine engine community. Secondly, we will discuss current NASA collaborations that are in progress and provide a status of the results. Finally, we discuss the challenges anticipated for future turbine engine-based propulsion systems for civil aviation and identify potential opportunities for collaboration where NASA involvement would be beneficial. Ultimately, the gas turbine engine community will decide if NASA involvement is needed to contribute to the development of the design and analysis tools, databases, and technology demonstration programs to meet these challenges for future turbine engine-based propulsion systems.

Suder, Kenneth L.↗

Flight Awareness Collaboration Tool

NASA is developing the Flight Awareness Collaboration Tool (FACT) to support airline and airport operations during winter storms. The goal is to reduce flight delays and cancellations due to winter weather. FACT concentrates relevant information from the Internet and FAA databases on one screen for easy access. It provides collaboration tools for those managing the winter weather event including the airline operations center, airport authority (runway treatment), the Federal Aviation Administration air traffic control tower, and de-icing operators. Prediction tools are being added to improve FACT capabilities including one that anticipates changes in airport departure rates from weather forecasts. Future work includes adding more automated capabilities and collaborating with industry.

Mogford, Richard H.↗

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗

AI Foundation Models for Science: An Open Collaborative Initiative

Foundation Models (FMs), AI models designed to replace task-specific models, are increasingly being recognized for their versatility across numerous downstream applications. These models, trained using self-supervised techniques on any type of sequence data, circumvent the need for large annotated datasets, a major bottleneck in traditional AI model development. FMs can be applied to downstream tasks using few-shot learning and fine-tuning, significantly reducing the need for large labeled training datasets and computational resources. However, the development of FMs requires substantial resources, including access to data and compute power, expertise in the latest models, and specialized scientific knowledge for systematic evaluation. It is challenging for a single group to possess all these capabilities. To address this, NASA IMPACT has initiated an open collaborative effort, leveraging partnerships with the private sector and other groups within and outside NASA, to jointly build FMs. The overarching goal is to develop a consistent and collaborative approach to building FMs for high-value science datasets. This initiative has fostered collaboration within NASA and with external partners, including IBM Research, Clark University, DOE’s ORNL, ESA, and USGS. The effort focuses on identifying key datasets with a wide range of downstream applications, pretraining and building FMs using modified transformer architectures, evaluating compute infrastructure needs, and sharing models, pretraining and fine-tuning code, and data with the community. Furthermore, it aims to train the Earth science community to fine-tune these models for various downstream applications. Our initial effort resulted in the creation of a 100 million parameter HLS Geospatial Model within six months, which was released on HuggingFace. We are now expanding our scope to include data from weather and climate models and investigating multimodal models. We invite those interested in participating in this effort to join us by sharing their use cases, expertise, or data.

Rahul Ramachandran↗

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗

NASA's Human Research Program: Evolving Collaborations to Enable the Future of Human Spaceflight

Since its formation in 2007, the NASA Human Research Program’s (HRP) mission has been to reduce human health and performance risks for spaceflight exploration missions. The program has achieved this mission primarily through work in ground analogs and on the International Space Station. Over the last three years, NASA overall has seen transformative changes with the flight of Artemis I, formation of the Commercial LEO Destinations Program, commercial flights to the ISS, and new International Partners participating in human spaceflight. NASA’s HRP has embraced these new opportunities and is collaborating on all these fronts to collect biomedical research data. Artemis I marked the arrival of NASA’s new human spaceflight exploration missions. NASA has developed a Moon-to-Mars Architecture to map out how it will use the moon to de-risk and enable Mars missions. NASA’s HRP is a critical component to develop and deliver research and technologies for future Artemis Crew Health and Performance (CHP) Systems. The program is working closely with NASA’s Moon-to-Mars Office to ensure CHP deliverables are ready to demonstrate on the moon, as we also look toward Mars, and is developing the partnership strategies required to support these deliverables. Commercial space flights, both free flyer and suborbital missions and private astronaut missions to the ISS, are providing broader opportunities and subjects to characterize the space-induced changes to the human system and to test countermeasures. To better use these opportunities to achieve its mission, HRP has been working to understand the commercial spaceflight companies’ needs and then partner with them on aspects of mutual interest. In addition, NASA HRP continues to engage in long-standing relationships with its international partners through the International Space Life Sciences Working Group (ISLSWG) and other joint international groups. The Program is now also interested in sharing its knowledge and ability to collaborate on projects of mutual interest with new countries developing capabilities for human spaceflight. The next 10 years will shape how humanity partners on exploration missions to Mars. NASA’s HRP is committed to enabling and developing collaborative strategies with commercial and international partners to keep humans safe and productive as we explore longer and further into space.

Jancy McPhee↗

Enabling Collaborative Engineering and Science at JPL

We examine the issue of distributed collaboration at the Jet Propulsion Laboratory. With the goals of faster, better, cheaper missions, an efficient, seamless collaboration capabilitity is critical to future JPL space exploration missions.

collaboration↗

Collaborative Scheduling Using JMS in a Mixed Java and .NET Environment

A viewgraph presentation to demonstrate collaborative scheduling using Java Message Service (JMS) in a mixed Java and .Net environment is given. The topics include: 1) NASA Deep Space Network scheduling; 2) Collaborative scheduling concept; 3) Distributed computing environment; 4) Platform concerns in a distributed environment; 5) Messaging and data synchronization; and 6) The prototype.

.NET↗

Figures of Merit Remembrances of Those Who Built an Army-NASA Collaboration and a New Age of Rotary-Wing Technology 1965-1985

The authors of this book are the Figures of Merit—the scientists, engineers, technicians, secretaries, test pilots, managers, visionaries, and leaders who built a unique interagency collaboration under the Army-NASA Joint Agreement at Ames Research Center and ushered in a new age of rotary-wing technology. The U.S. Army Aeronautical Research Laboratory (AARL) was formed in 1965 to strengthen the Army’s capabilities in aviation R&D, and the Army-NASA collaboration at Ames was intended to benefit both agencies by sharing personnel and facilities for research in areas of common interest in low-speed aviation.

Rotary-Wing Technology↗

GeneLab Collaboration

In order to maximize the amount of omics data returned from space flight experiments, the GeneLab project can collaborate with Space Biology funded PIs. Here, we outline the process by which these collaborations take place.

GeneLab↗

Scaling Climbing Collaborative Mobile Manipulators for Outfitting a Tall Lunar Tower and Truss Structures

In-space and planetary truss structures like the Tall Lunar Tower (TLT) can greatly benefit from truss climbing collaborative mobile manipulators (C2M2) for outfitting and other servicing tasks. Mobile robotic systems traversing truss structures will allow for improved access to the structure for placing equipment and routing cables after the structure has been assembled. The C2M2 is designed to provide access to the structure through collaborative mobile robotics. A series of gaits are developed allowing the robot to reach any point on the structure and validate the capabilities of the joint configuration. Scaling the system during the design phase is a necessary process given the wide range of trusses in development and payloads which are required for outfitting. The variable features of the system are the actuators and the length of the links connecting the two-degrees of freedom (DOF) modules. A scaling method was developed for determining the range of usable link lengths for a selected actuator in a design environment. The focus of the design is on a six-DOF robot arranged with two-DOF at each end and at the center. Two grippers are mounted at each end for grappling on the truss and holding cargo.

Collaborative Robotics↗

Eleven Countries, an Integrated Spacecraft: the Story of International Collaboration that Built the Orion Spacecraft and Powered the Success of the Artemis I Mission

The quest to return humans to the Moon in the next step towards humanity's exploration of space is more alive than ever. After a great deal of achievements, failures, and lessons learned, the Artemis I mission set o to the Moon on November 16, 2022, with the goal of testing a new rocket, the Space Launch System, and a new spacecraft, Orion: designed, assembled, and tested across two continents, and 11 countries. Behind this mission, decades of experience with the International Space Station, Autonomous Transfer Vehicle operations, and many other program collaborations built the know-how on how to succeed together in the toughest environment | deep space. The Artemis I mission proved to be an incredible success, meeting 161 total mission objectives, including 21 developed during the flight based on outperforming spacecraft. It was also a case-study in international collaboration, given that ESA, NASA, and industry partners Airbus and Lockheed Martin for the first time had to design, build, test, and fly a fully integrated human-rated spacecraft, with most critical functions dependent and interconnected across U.S. and European systems. The U.S.-built Orion Crew Module and Crew Module Adapter and European-built European Service Module (ESM) shared critical interfaces and commodities, from propulsion, avionics, active/passive thermal, electrical power generation, storage and distribution to the software that managed it all. In this paper, we will describe relevant aspects of the integrated spacecraft design, providing context for the challenges that the team faced in all phases required to get Orion ready to fly, and provide a direct account of how the joint team formed, trained, and supported the operations of the successful Artemis I mission. We will also explore the evolution of the partnerships, given that these allow a multi-national e ort to sustain the program production, share costs, leverage a broader base of engineering expertise, and build more diverse capabilities over the long haul to support the Artemis goals and objectives. Lastly, we will cover critical lessons learned and how the Orion Program has implemented these in preparation of the next Artemis missions to repeat the success of Artemis I. The purpose of this paper is to document knowledge we gained and lessons we learned through the development of an integrated Orion spacecraft, since it is imperative we build on this now, at the dawn of the Artemis Program, an international endeavor to push human space exploration.

Deep Space Exploration↗

University/industry collaboration in remote sensing education

A graduate level course covering the development and structure of geographical information systems and the acquisition and processing of LANDSAT data for input to these systems is described. A portion of the course was devoted to hands-on classification of LANDSAT digital tapes utilizing both university and private industry processing systems. This industry/university collaboration was extremely successful and resulted in a high quality course. It gave the students an excellent experience in working in a real-world client/consultant relationship undertaken to accomplish a specific task. There were two key factors in the success of the collaboration. First, there was a very careful product definition and advance meetings between the University faculty and the company personnel to be involved. Second, the students were not taken into the industrial facility until late in the course, after they had a reasonable knowledge of the physical bases of remote sensing, the concept of spectral signatures, and the fundamentals of pattern analysis.

Ragan, R. M.↗

Electronic collaboration: Some effects of telecommunication media and machine intelligence on team performance

Both NASA and DoD have had a long standing interest in teamwork, distributed decision making, and automation. While research on these topics has been pursued independently, it is becoming increasingly clear that the integration of social, cognitive, and human factors engineering principles will be necessary to meet the challenges of highly sophisticated scientific and military programs of the future. Images of human/intelligent-machine electronic collaboration were drawn from NASA and Air Force reports as well as from other sources. Here, areas of common concern are highlighted. A description of the author's research program testing a 'psychological distancing' model of electronic media effects and human/expert system collaboration is given.

Wellens, A. Rodney↗

Collaboration technology and space science

A summary of available collaboration technologies and their applications to space science is presented as well as investigations into remote coaching paradigms and the role of a specific collaboration tool for distributed task coordination in supporting such teleoperations. The applicability and effectiveness of different communication media and tools in supporting remote coaching are investigated. One investigation concerns a distributed check-list, a computer-based tool that allows a group of people, e.g., onboard crew, ground based investigator, and mission control, to synchronize their actions while providing full flexibility for the flight crew to set the pace and remain on their operational schedule. This autonomy is shown to contribute to morale and productivity.

Leiner, Barry M.↗