Path Forward: Study Office Schedule and Resources
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X-Ray Astronomy X-Ray Surveyor↗
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Experiences in Applying Earth Observing Satellite Technology in SERVIR Regions with an Emphasis on Disasters: Successes, Lessons and Paths Forward
Earth observing satellites offer a unique perspective of our environment from the vantage point of space. Repeated measurements of the Earths subsystems such as the biosphere, atmosphere, lithosphere, hydrosphere, and of humans interactions with their environments, allow for a better understanding of Earth system processes, and they can provide input for decision making in areas of environmental management and disaster risk reduction. SERVIR is a joint initiative of the US National Aeronautics and Space Administration (NASA) and the US Agency for International Development (USAID) that began in 2005 and has been active in applying Earth observations for sustainable development in many regions around the world, recently the Lower Mekong and West Africa regions. This talk will highlight some successes achieved and lessons learned through SERVIR in Central America, Eastern Southern Africa, and the Hindu Kush-Himalaya region, focusing on disasters. We will also present opportunities for enhanced decision making with Earth observations and geospatial technologies in the Lower Mekong region.
SERVIR↗
Process Drivers, Inter-model Spread, and a Path Forward: What Do We Know About Arctic Amplification?
Over the recent decades, rapid changes have been observed in the Arctic resulting from enhanced surface warming in the Arctic relative to the rest of the globe, a phenomenon called Arctic Amplification. While surface-based amplification of Arctic warming in response to increased CO2 has been established. The driving mechanisms, relevant processes, and the relative roles of local and remote mechanisms to Arctic Amplification remain unclear. Research over the last decade has made it clear that coupling between the atmosphere, sea ice, and ocean play a key role in Arctic Amplification. This presentation summarizes recent research on the fundamental role that atmosphere-sea ice-ocean interactions and energy exchanges play in driving Arctic Amplification, how these interactions manifest as radiative climate feedbacks, and how these processes influence the differences in the projected Arctic climate change across CMIP5 and 6. We hypothesize that models that simulate larger warming do so by generating a larger local atmospheric circulation response that more effectively redistributes energy drawn from the ocean in sea ice retreat regions Arctic-wide and contributing to a larger increase in downwelling long wave radiation. This process is also fundamentally tied to the Arctic lapse rate feedback.
Patrick Charles Taylor↗
Process drivers, inter-model spread, and a path forward: What do we know about Arctic Amplification?
Over the recent decades, rapid changes have been observed in the Arctic resulting from enhanced surface warming in the Arctic relative to the rest of the globe, a phenomenon called Arctic Amplification. While surface-based amplification of Arctic warming in response to increased CO2 has been established. The driving mechanisms, relevant processes, and the relative roles of local and remote mechanisms to Arctic Amplification remain unclear. Research over the last decade has made it clear that coupling between the atmosphere, sea ice, and ocean play a key role in Arctic Amplification. This presentation summarizes recent research on the fundamental role that atmosphere-sea ice-ocean interactions and energy exchanges play in driving Arctic Amplification, how these interactions manifest as radiative climate feedbacks, and how these processes influence the differences in the projected Arctic climate change across CMIP5 and 6. We hypothesize that models that simulate larger warming do so by generating a larger local atmospheric circulation response that more effectively redistributes energy drawn from the ocean in sea ice retreat regions Arctic-wide and contributing to a larger increase in downwelling long wave radiation. This process is also fundamentally tied to the Arctic lapse rate feedback.
Arctic amplification↗
Process drivers, inter-model spread, and a path forward: What do we know about Arctic Amplification?
Over the recent decades, rapid changes have been observed in the Arctic resulting from enhanced surface warming in the Arctic relative to the rest of the globe, a phenomenon called Arctic Amplification. While surface-based amplification of Arctic warming in response to increased CO2 has been established. The driving mechanisms, relevant processes, and the relative roles of local and remote mechanisms to Arctic Amplification remain unclear. Research over the last decade has made it clear that coupling between the atmosphere, sea ice, and ocean play a key role in Arctic Amplification. This presentation summarizes recent research on the fundamental role that atmosphere-sea ice-ocean interactions and energy exchanges play in driving Arctic Amplification, how these interactions manifest as radiative climate feedbacks, and how these processes influence the differences in the projected Arctic climate change across CMIP5 and 6. We hypothesize that models that simulate larger warming do so by generating a larger local atmospheric circulation response that more effectively redistributes energy drawn from the ocean in sea ice retreat regions Arctic-wide and contributing to a larger increase in downwelling long wave radiation. This process is also fundamentally tied to the Arctic lapse rate feedback.
Patrick C. Taylor↗
Topical. Permanent Low-Earth Orbit Testbed for Welding and Joining: A Path Forward for the Commercialization of Space
NASA, defense, academia, and commercial space companies seek to develop orbital manufacturing to enhance mission capabilities. In-space welding and joining are needed for space-based manufacturing. We propose a permanent low-earth orbital welding and joining testbed for scientific study of relevant physical phenomena and development of welding and joining processes to technical maturity. Such data will enable integrated computational materials engineering(ICME)to elucidate the underlying physical and metallurgical processes needed to achieve critical space welding and joining operations.
In-space manufacturing↗
Embracing the fourth Industrial Revolution - Challenges, Opportunities and Path Forward for Propulsion
The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.
Machine learning↗
Embracing the Fourth Industrial Revolution - Challenges, Opportunities and Path Forward for Propulsion
The aerospace industry is at a point where components are reaching design maturity and performance improvements are incremental. Aggressive goals to achieve sustainability and the threat of climate change necessitate a new paradigm. An artificial intelligence (AI) approach that enables revolutionary changes in system architecture, mission analysis and performance metrics is needed. The growing interest and development in the field of machine learning presents an opportunity to speed up by 10X or more the discovery, analysis and development of aerospace systems using artificial intelligence. Through IDEAS (Intelligent Design and Engineering of Aerospace Systems) we are embarking on a research and development effort that addresses this opportunity. The objective of IDEAS is to enable design of systems based on requirements. We discuss possible approaches to generating data, training models and applying them to near term applications. Results of recent workshops with industry, academia and other agencies to identify challenges to adopting AI and machine learning are presented.
Machine learning↗
Dynamic Testing of eVTOL Energy Storage Systems: Literature Review and Path Forward
Explore the source record for details and available documents.
aircraft testing↗
NASA’s Space Launch System: Artemis I Results and the Path Forward
The Artemis era of human space exploration beyond low Earth orbit launched at 1:47 a.m. EST on November 16, 2022. Artemis I was the first integrated flight of the agency’s new super heavy-lift rocket, the Space Launch System (SLS), and the next-generation spacecraft for astronauts, Orion. The mission sent an uncrewed Orion spacecraft into a distant retrograde orbit about the Moon. During the 25-day mission, NASA collected valuable data on the performance of the launch vehicle and crew spacecraft and information on the deep space environment where crews will soon operate. Orion splashed down approximately 80 miles off the coast of Baja, California, at the conclusion of the mission December 11. This paper will provide a summary of the launch campaign from vehicle integration and testing through completion of the upper stage phase with primary emphasis on SLS. It will also discuss highlights of progress on manufacturing and testing of SLS hardware and software for upcoming Artemis missions.
John Honeycutt↗
NASA’s Space Launch System: Artemis I Results and the Path Forward
On Nov. 16, 2022, NASA launched the Artemis I mission on the agency’s new SLS (Space Launch System) rocket. The debut launch of the integrated vehicle sent an uncrewed Orion spacecraft into a distant retrograde (DRO) orbit about the Moon to accomplish multiple mission objectives, including evaluating Orion’s heatshield at lunar return velocities and collecting critical data from the first flight of the new superheavy lift launch vehicle. Post-flight data analyses show that the rocket performed with a high degree of precision and accuracy. In addition to completing testing and launch of the Artemis I SLS in 2022, notable progress was made on hardware for future launch vehicles that will support Artemis missions II, III, IV, and V. The Artemis II core stage is mostly complete, and its RS-25 engines were integrated in the fall of 2023. The Artemis II solid rocket booster motor segments were shipped to the launch site in September 2023. Propellant tanks are being manufactured for additional missions, solid booster segments are being cast and prepared, software is being developed, and production of new RS-25 engines is underway. A more capable upper stage is in development, as well as a large adapter to encapsulate a 10-metric ton (t) co-manifested payload. This paper will provide details on the Artemis I flight as well as cover hardware progress for the future flights as available.
John Honeycutt↗
Foundation Models for Science: Potential, Challenges, and the Path Forward
Explore the source record for details and available documents.
Rahul Ramachandran↗
A common path forward for the immersive visualization community
Immersive visualization makes use of the medium of virtual reality (VR) - it is a subset of virtual reality focused on the application of VR technologies to scientific and information visualization. As the name implies, there is a particular focus on the physically immersive aspect of VR that more fully engages the perceptual and kinesthetic capabilities of the scientist with the goal of producing greater insight. The immersive visualization community is uniquely positioned to address the analysis needs of the wide spectrum of domain scientists who are becoming increasingly overwhelmed by data. The outputs of computational science simulations and high-resolution sensors are creating a data deluge. Data is coming in faster than it can be analyzed, and there are countless opportunities for discovery that are missed as the data speeds by. By more fully utilizing the scientists visual and other sensory systems, and by offering a more natural user interface with which to interact with computer-generated representations, immersive visualization offers great promise in taming this data torrent. However, increasing the adoption of immersive visualization in scientific research communities can only happen by simultaneously lowering the engagement threshold while raising the measurable benefits of adoption. Scientists time spent immersed with their data will thus be rewarded with higher productivity, deeper insight, and improved creativity. Immersive visualization ties together technologies and methodologies from a variety of related but frequently disjoint areas, including hardware, software and human-computer interaction (HCI) disciplines. In many ways, hardware is a solved problem. There are well established technologies including large walk-in systems such as the CAVE{trademark} and head-based systems such as the Wide-5{trademark}. The advent of new consumer-level technologies now enable an entirely new generation of immersive displays, with smaller footprints and costs, widening the potential consumer base. While one would be hard-pressed to call software a solved problem, we now understand considerably more about best practices for designing and developing sustainable, scalable software systems, and we have useful software examples that illuminate the way to even better implementations. As with any research endeavour, HCI will always be exploring new topics in interface design, but we now have a sizable knowledge base of the strengths and weaknesses of the human perceptual systems and we know how to design effective interfaces for immersive systems. So, in a research landscape with a clear need for better visualization and analysis tools, a methodology in immersive visualization that has been shown to effectively address some of those needs, and vastly improved supporting technologies and knowledge of hardware, software, and HCI, why hasn't immersive visualization 'caught on' more with scientists? What can we do as a community of immersive visualization researchers and practitioners to facilitate greater adoption by scientific communities so as to make the transition from 'the promise of virtual reality' to 'the reality of virtual reality'.
97 MATHEMATICS AND COMPUTING↗
The Los Alamos trails management program - the path forward in an era of interagency collaborations
Abstract Not Provided
54 ENVIRONMENTAL SCIENCES↗