Search NASA⌕ Search

SEARCH · Search NASA

Results for “Next Generation of Science”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Workshop Proceedings: Optical Systems Technology for Space Astrophysics in the 21st Century, volume 3

A technology development program, Astrotech 21, is being proposed by NASA to enable the launching of the next generation of space astrophysical observatories during the years 1995-2015. Astrotech 21 is being planned and will ultimately be implemented jointly by the Astrophysics Division of the Office of Space Science and Applications and the Space Directorate of the Office of Aeronautics and Space Technology. A summary of the Astrotech 21 Optical Systems Technology Workshop is presented. The goal of the workshop was to identify areas of development within advanced optical systems that require technology advances in order to meet the science goals of the Astrotech 21 mission set, and to recommend a coherent development program to achieve the required capabilities.

Ayon, Juan A.↗
NASA NTRS2001

Lessons from Adaptive Level One Accelerator (ALOA) System Implementation

The Adaptive Level One Accelerator (ALOA) system was developed as part of the Earth Science Data and Information System (ESDIS) project. The reconfigurable computing technologies were investigated for Level 1 satellite telemetry data processing to achieve computing acceleration and cost reduction for the next-generation Level 1 data processing systems. The MODIS instrument calibration algorithm was implemented using reconfigurable a computer. The system development process and the lessons learned throughout the design cycle are summarized in this paper.

Patel, Umesh D.↗
NASA NTRS2001

Cloud Structure and Cloud-Radiation Interaction: From Smallest Observable Scales (Less than 10 m) to GCM Grid Scales (More than 100 km)

In this presentation we review the fractal nature of internal cloud structure from cm- to km-scales as captured by in-situ probes during long horizontal penetrations by aircraft. We uncover the non-Poissonian spatial distribution of cloud droplets at submeter scales and confirm scale-invariant behavior for large scales. Based on these structural characteristics, we generate simple fractal cloud models that reproduce statistical scaling properties of real clouds. These stochastic models represent a link between nonlinear science, in general, and cloud-radiation interaction, in particular. Next we run three-dimensional radiative transfer computations on these synthetic fractal clouds and compare the structure of the resulting radiation fields with the known structure of the cloud model and with satellite images of real clouds. The different behaviors observed for small and large-scale variabilities will be discussed in detail. We find that while the large-scale fluctuations of the resulting radiation fields resemble those in the original scale-invariant cloud structure, the radiation at small scales is much smoother than its cloud liquid water counterpart. This violates scale-invariance and produces a scale-break at 0.2-0.5 km that is clearly observed in high-resolution satellite data such as from Landsat. Finally, we show how radiative transfer Green function theory in the photon diffusion limit explains (and predicts) the above phenomena of "radiative smoothing."

Marshak, Alexander↗
NASA NTRSDate not supplied

The HEROIX Broadband X-Ray Space Telescope Mission Concept

The High EneRgy Observatory for Imaging X-rays (HEROIX) Medium-Class Mission concept envisions a next-generation broadband X-ray observatory designed to meet the astrophysics community’s need for high-angular-resolution studies of the Cosmic X-ray Background. Building on the science legacy of NASA’s NuSTAR mission and more than 30 years of advances in replicated NiCo shell technology at NASA Marshall, HEROIX proposes a space observatory comprising four co-aligned telescopes achieving 5 arcsecond half-power diameter (HPD) angular resolution. This capability, approached by the resolution demonstrated in the FOXSI-4 sounding rocket mission and under development through the SuperHERO balloon mission, will be extended to energies up to 80 keV through multilayer coatings. Marshall’s inhouse precision optics manufacturing enables an integrated effective area of 380 cm² at 30 keV, which, combined with high-resolution optics, opens new windows into extreme astrophysical non-thermal processes.

Nick Thomas↗
DOE OSTI2025

Reflections on the role of MOOSE in Unleashing a Golden Era of American Energy Innovation

As the use of artificial intelligence spreads across most professions, projections for the expected energy consumption of these virtual assistants/workers dictate a large increase in energy production. Recent published estimates refer to up to a necessary tripling of nuclear energy production~\cite{iaea}. % TODO add citations This is supported by the new administration, calling on February 5th to "unleash Commercial Nuclear Power in the United States" and to launch the "long-awaited American nuclear renaissance"~\cite{doe-order}. The Department of Energy (DOE) is tasked with "enabl[ing] the rapid deployment and export of next generation nuclear technology". In terms of research of development, we must seek to "unleash American Energy Innovation", by "focus[ing] our time and resources on technologies that will advance basic science, grow America’s scientific leadership, reduce costs for American families [...]". To that end, the Department will "prioritize affordable, reliable, and secure energy technologies, including fossil fuels, advanced nuclear, geothermal, and hydropower." Following this call to action, we elect to examine the role of the open-source Multiphysics Object Oriented Simulation Environment (MOOSE)~\cite{moose3} in meeting the stated goals.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2020

Extending Science from Lunar Laser Ranging

The Lunar Laser Ranging (LLR) experiment has accumulated 50 years of range data of improving accuracy from ground stations to the laser retroreflector arrays (LRAs) on the lunar surface. The upcoming decade offers several opportunities to break new ground in data precision through the deployment of the next generation of single corner-cube lunar retroreflectors and active laser transponders. This is likely to expand the LLR station network. Lunar dynamical models and analysis tools have the potential to improve and fully exploit the long temporal baseline and precision allowed by millimetric LLR data. Some of the model limitations are outlined for future efforts. Differential observation techniques will help mitigate some of the primary limiting factors and reach unprecedented accuracy. Such observations and techniques may enable the detection of several subtle signatures required to understand the dynamics of the Earth- Moon system and the deep lunar interior. LLR model improvements would impact multi- disciplinary fields that include lunar and planetary science, Earth science, fundamental physics, celestial mechanics and ephemerides.

Vishnu Viswanathan↗
DOE OSTI2025

Design and Development of Novel Equiatomic Refractory Multi Principal elemental Alloys Based on MoNbTi System for Use in Irradiation Environments

Multi Principal Elemental Alloys (MPEA) have emerged as promising materials for next-generation nuclear reactors due to their exceptional irradiation resistance. Eight equiatomic MPEA based on the MoNbTi system, comprising of elements with low thermal neutron absorption cross-sections were explored using a combined approach employing empirical parameter estimations, and CALPHAD simulations by which the phases and elemental segregation observed in all the alloys in the as-cast state were predicted. Solution heat treatment at 1500°C transformed five alloys into single-phase matrix materials, enhancing homogeneity and reducing hardness. The densities of the alloys ranged between 6.47 to 7.68 g/cm3, hardness between 472 and 656 VHN, Young’s modulus between 142 GPa to 169 GPa, shear modulus between 54 GPa and 62 GPa, bulk modulus between 117 GPa to 194 GPa and Poisson’s ratio between 0.3 to 0.35. The in-situ high temperature Xray diffraction results, differential scanning calorimetry and dilatometry results up to 1000°C suggested the high temperature phase stability of the MPEA. Subsequent ageing heat treatment at 800 and 1000 oC for 96 hours revealed significant secondary phase precipitation in MoNbTiZr, MoNbTiZrV, and MoNbTiCrA. Oxidation studies at 800 oC for 24 hours in air revealed superior oxidation resistance and cubic rate law dependence in Cr containing MPEA especially in MoNbTiCrAl, while severe mass gain resulting in total disintegration and exfoliation in MoNbTiZr and MoNbTiZrV. This comprehensive study underscores the potential of novel MPEA as promising materials for advanced nuclear reactor applications, shedding light on their microstructural control, mechanical properties, thermal stability, and oxidation resistance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Us participation in the construction of the T2k superfgd detector as part of the T2k ND280 upgrade

The neutrino physics field as a whole has made astonishing advances during the last two decades. Before 1998, there was no neutrino oscillation, meaning no neutrino mass and mixing. Today, neutrino oscillation is firmly established and we have measured all three mixing parameters and two mass parameters. Furthermore, these findings pave the way to determine the mass ordering/hierarchy and to explore Charge-Parity (CP) violation in the lepton sector, which may hold a critical key to our understanding of the matter−antimatter asymmetry in the universe, one of the most profound mysteries in science. In fact, T2K, a long baseline neutrino oscillation experiment based in Japan, has recently released the results that show initial hint of CP violation making the prospects of DUNE, a next generation long baseline neutrino oscillation experiment based in the US, discovering CP violation in neutrinos very bright.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2000

Low-Cost Approaches to Deep Space Missions

The past decade has brought about a radical transformation in NASA's planetary exploration program. At the beginning of this decade, NASA was focused on the Cassini mission to Saturn. Following on the heels of the successful Voyager and Galileo missions, Cassini represents the culmination of an evolution towards successively larger, more complex, and more expensive spacecraft. The Cassini spacecraft weighs in at over 5 metric tons, and carries an entry probe and a sophisticated suite of sensors supporting 27 different science investigations enabling a comprehensive scientific investigation of Saturn with a single spacecraft. The cost of this spacecraft exceeded $2B, including the cost of the large Titan IV launch vehicle. During Cassini development, NASA realized that it could no longer afford these "flagship" missions, and the agency moved aggressively towards a "faster, better, cheaper" design philosophy of focused science goals and simpler, rapidly-developed spacecraft, allowing much more frequent launches of smaller, lower-cost missions. The Mars Global Surveyor, launched in November 1996, is an example of this new paradigm. Developed in less than 3-years, MGS is only one-fifth the mass of Cassini, and only cost on the order of $220M. The reduced spacecraft mass allows use of the smaller, lower cost Delta launch vehicle. Currently in orbit about Mars, MGS carries a focused suite of six science instruments that are currently returning high-resolution remote sensing of the Martian surface. The future calls for continued even more aggressive mass and cost targets. Examples of these next-generation goals are embodied in the Mars Micromission spacecraft concept, targeted for launch in 2003. With a mass of only 200kg, this lightweight bus can be tailored to carry a variety of payloads to Mars or other inner-planet destinations. The design of the Micromission spacecraft enable them to be launched at extremely low cost as a secondary "piggyback" payload.

Squibb, G. F.↗
NASA NTRS2011

Extravehicular Activity Systems Education and Public Outreach in Support of NASA's STEM Initiatives

The exploration activities associated with NASA?s goals to return to the Moon, travel to Mars, or explore Near Earth Objects (NEOs) will involve the need for human-supported space and surface extravehicular activities (EVAs). The technology development and human element associated with these exploration missions provide fantastic content to promote science, technology, engineering, and math (STEM). As NASA Administrator Charles F. Bolden remarked on December 9, 2009, "We....need to provide the educational and experiential stepping-stones to inspire the next generation of scientists, engineers, and leaders in STEM fields." The EVA Systems Project actively supports this initiative by providing subject matter experts and hands-on, interactive presentations to educate students, educators, and the general public about the design challenges encountered as NASA develops EVA hardware for these missions. This paper summarizes these education and public efforts.

Paul, Heather L.↗
NASA NTRS2016

Successes with the Global Precipitation Measurement (GPM) Mission

Water is essential to our planet Earth. Knowing when, where and how precipitation falls is crucial for understanding the linkages between the Earth's water and energy cycles and is extraordinarily important for sustaining life on our planet during climate change. The Global Precipitation Measurement (GPM) Core Observatory spacecraft launched February 27, 2014, is the anchor to the GPM international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Status and successes in terms of spacecraft, instruments, retrieval products, validation, and impacts for science and society will be presented. Precipitation, microwave, satellite

microwave↗
NASA NTRS2017

Three Years of the Global Precipitation Measurement (GPM) Mission

Water is essential to our planet Earth. Knowing when, where and how precipitation falls is crucial for understanding the linkages between the Earth's water and energy cycles and is extraordinarily important for sustaining life on our planet during climate change. The Global Precipitation Measurement (GPM) Core Observatory spacecraft launched February 27, 2014, is the anchor to the GPM international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Status and successes in terms of spacecraft, instruments, retrieval products, validation, and impacts for science and society will be presented.

Precipitation↗
NASA NTRS2014

Inspiring the Next Generation: The International Space Station Education Accomplishments

The International Space Station (ISS) has a unique ability to capture the imagination of both students and teachers worldwide. Since 2000, the presence of humans onboard ISS has provided a foundation for numerous educational activities aimed at capturing that interest and motivating study in the sciences, technology, engineering and mathematics (STEM). Over 43 million students around the world have participated in ISS-related educational activities. Projects such as YouTube Space Lab, Sally Ride Earth Knowledge-based Acquired by Middle Schools (EarthKAM), SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) Zero-Robotics, Tomatosphere, and MAI-75 events among others have allowed for global student, teacher and public access to space through student classroom investigations and real-time audio and video contacts with crewmembers. Educational activities are not limited to STEM but encompass all aspects of the human condition. This is well illustrated in the Uchu Renshi project, a chain poem initiated by an astronaut while in space and continued and completed by people on Earth. With ISS operations now extended to 2024, projects like these and their accompanying educational materials are available to more students around the world. From very early on in the program's history, students have been provided with a unique opportunity to get involved and participate in science and engineering projects. Many of these projects support inquiry-based learning that allows students to ask questions, develop hypothesis-derived experiments, obtain supporting evidence and identify solutions or explanations. This approach to learning is well-published as one of the most effective ways to inspire students to pursue careers in scientific and technology fields. Ever since the first space station element was launched, a wide range of student experiments and educational activities have been performed, both individually and collaboratively, by all the international partner agencies, National Aeronautics and Space Administration (NASA), Canadian Space Agency (CSA), European Space Agency, (ESA), Japan Aerospace Exploration Agency (JAXA) and Russian Federal Space Agency (Roscosmos), and a number of non-participating countries, some under commercial agreements. Many of these programs still continue, and others are being developed and added to the stations tasks on a regular basis. These diverse student experiments and programs fall into one of the following categories: student-developed experiments; students performing classroom versions of ISS experiments; students participating in ISS investigator experiments; education competitions; students participating in ISS Engineering Education; Education Demonstrations and Cultural Activities. This paper summarizes some of the main student experiments and educational activities that have been conducted on the space station.

Alleyne, Camille W.↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗
DOE OSTI2026

Generative Electrolyte Solvent and Formulation Discovery

Molecular mixtures and/or formulations are of great importance in fields ranging from materials science to pharmaceuticals to chemistry. In batteries, electrolytes are complex molecular mixtures consisting of multiple salts and solvents and additives at different concentrations that dictate battery capacity, safety, and cycle life, among others. Unfortunately, due to the complex composition and infinite design space as well as the conflicting property requirements, electrolyte design is the rate-determining step in the design of next generation battery chemistries. In this work, we develop a transformer-based generative AI model − ElectrolyteGPT − capable of generating solvents and electrolyte formulations to satisfy a wide range of desired property requirements. First, we curate an electrolyte-relevant database and develop a new line notation for formulations. Then, we show that ElectrolyteGPT can generate solvents and formulations conditioned on a wide range of important electrolyte properties such as ionic conductivity, oxidative stability, Coulombic efficiency, viscosity, and more. Finally, we experimentally synthesize the generated solvents and fabricate the electrolyte formulations and show that they can meet the desired property requirements and enable longterm cycling in energy-dense anode-free lithium metal batteries. Our work showcases the ability of generative models to address challenges in molecular mixture design for next generation batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Powdery mildew effectors AVR A1 and BEC1016 target the ER J‐domain protein Hv ERdj3B required for immunity in barley

Abstract The barley powdery mildew fungus, Blumeria hordei (Bh), secretes hundreds of candidate secreted effector proteins (CSEPs) to facilitate pathogen infection and colonization. One of these, CSEP0008, is directly recognized by the barley nucleotide‐binding leucine‐rich‐repeat (NLR) receptor MLA1 and therefore is designated AVR A1 . Here, we show that AVR A1 and the sequence‐unrelated Bh effector BEC1016 (CSEP0491) suppress immunity in barley. We used yeast two‐hybrid next‐generation interaction screens (Y2H‐NGIS), followed by binary Y2H and in planta protein–protein interactions studies, and identified a common barley target of AVR A1 and BEC1016, the endoplasmic reticulum (ER)‐localized J‐domain protein Hv ERdj3B. Silencing of this ER quality control (ERQC) protein increased Bh penetration. Hv ERdj3B is ER luminal, and we showed using split GFP that AVR A1 and BEC1016 translocate into the ER signal peptide‐independently. Overexpression of the two effectors impeded trafficking of a vacuolar marker through the ER; silencing of Hv ERdj3B also exhibited this same cellular phenotype, coinciding with the effectors targeting this ERQC component. Together, these results suggest that the barley innate immunity, preventing Bh entry into epidermal cells, requires ERQC. Here, the J‐domain protein Hv ERdj3B appears to be essential and can be regulated by AVR A1 and BEC1016. Plant disease resistance often occurs upon direct or indirect recognition of pathogen effectors by host NLR receptors. Previous work has shown that AVR A1 is directly recognized in the cytosol by the immune receptor MLA1. We speculate that the AVR A1 J‐domain target being inside the ER, where it is inapproachable by NLRs, has forced the plant to evolve this challenging direct recognition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation

The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. However, addressing complex urban and environmental management challenges often demands deep expertise in domain science and informatics. This expertise is essential for deriving data and simulation-driven insights that support informed decision-making. In this context, we investigate the potential of leveraging the pre-trained Large Language Models (LLMs) to create knowledge representations for supporting operations research. By adopting ChatGPT-4 API as the reasoning core, we outline an applied workflow that encompasses natural language processing, Methontology-based prompt tuning, and Generative Pre-trained Transformer (GPT), to automate the construction of scenario-based ontologies using existing research articles and technical manuals of urban datasets and simulations. From these ontologies, knowledge graphs can be derived using widely adopted formats and protocols, guiding various tasks towards data-informed decision support. The performance of our methodology is evaluated through a comparative analysis that contrasts our AI-generated ontology with the widely recognized pizza ontology, commonly used in tutorials for popular ontology software. We conclude with a real-world case study on optimizing the complex system of multi-modal freight transportation. Our approach advances urban decision support systems by enhancing data and metadata modeling, improving data integration and simulation coupling, and guiding the development of decision support strategies and essential software components.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗