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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.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

In vivo nuclear magnetic resonance imaging

During the past year the Woodlands Baylor Magnetic Resonance Imaging (MRI) facility became fully operational. A detailed description of this facility is given. One significant instrument addition this year was the 100 MHz, 40cm bore superconducting imaging spectrometer. This instrument gives researchers the capability to acquire high energy phosphate spectra. This will be used to investigate ATP, phosphocreatinine and inorganic phosphate changes in normal and atrophied muscle before, during and after exercise. An exercise device for use within the bore of the imaging magnet is under design/construction. The results of a study of T sub 1 and T sub 2 changes in atrophied muscle in animals and human subjects are given. The imaging and analysis of the lower leg of 15 research subjects before and after 5 weeks of complete bedrest was completed. A compilation of these results are attached.

Leblanc, A.↗
NASA NTRS1994

Scientific investigations of atmospheric processes

Research was performed in atmospheric, dynamical, and thermodynamical processes and in other disciplines necessary to accomplish the following tasks: develop procedures for combining generalized radiative transfer codes with dynamic atmospheric model codes; perform diagnostic analysis of atmospheric processes to gain a better understanding of the evolution and development of mesoscale circulation systems and their precipitation structures; and to develop algorithms and software necessary to graphically display diagnostic sets on the MSFC McIDAS and EADS to facilitate scientific study and sensor capability evaluation. Research activities during this reporting period are detailed.

Source record↗
NASA NTRS2013

Precision Departure Release Capability (PDRC): NASA to FAA Research Transition

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations.

ATM↗
NASA NTRS1988

The NASA integrated test facility and its impact on flight research

The Integrated Test Facility (ITF), being built at NASA Ames-Dryden Flight Research Facility, will provide new test capabilities for emerging research aircraft. An overview of the ITF and the challenges being addressed by this unique facility are outlined. The current ITF capabilities, being developed with the X-29 Forward Swept Wing Program, are discussed along with future ITF activities.

Mackall, D. A.↗
NASA NTRS1976

Aircraft measurements and analysis of severe storms: 1975 field experiment

Three aircraft and instrumentation systems were acquired in support of the severe storm surveillance program. The data results indicate that the original concept of a highly mobile research aircraft capability for obtaining detailed measurements of wind, temperature, dew point, etc., near and within specifically designated severe storms is entirely feasible and has been demonstrated for the first time by this program. This program is unique in that it is designed to be highly mobile in order to move to and/or with the developing storm systems to obtain the necessary measurements. Previous programs have all been fixed to a particular location and therefore have had to wait for the storms to come within their network. The present research is designed around a highly mobile aircraft measurements group in order to maximize the storm cases during the field measurements program.

Sinclair, P. C.↗
DOE OSTI2024

Safety in Artificial Intelligence: Challenges and Opportunities for the U.S. National Labs and Beyond

This report discusses the importance of the critical and underexplored topic of artificial intelligence (AI) safety, as highlighted during the “Strategy Alignment on AI Safety” workshop convened at Lawrence Livermore National Laboratory (LLNL) in April 2024. Through a summary of keynote talks, panel discussions, and breakout sessions, world-leading AI safety experts from academic, industry, national labs, and government agencies clearly agree on the need for and importance of large-scale investments for research and capabilities in AI safety. With the field innovating at unprecedented rates, there is increasing urgency to develop novel evaluation methodologies that allow full considerations of risks/threats of AI technologies in different domains. Quantitative metrics and effective methodologies that can evaluate and audit the “safeness” of how a given AI technology is trained, deployed, or regulated are, at best, nascent for certain scenarios or, more commonly, nonexistent. This maturation gap presents the possibility of serious threats to national security, and further inaction may have serious consequences. Additionally, the gap between the public’s and research community’s perceptions of AI risks/rewards is significant. While numerous voices from the AI community have expressed concern that the risks could be so high that future AI systems could inflict extinction-level damage to humanity if deployed incorrectly, the public largely is aware only of risk in low-impact scenarios. This discrepancy highlights the crucial need for researchers to articulate to governmental bodies what, why, and when various AI risks matter as part of motivating funding requests. Thus, the call to action for this community is to pursue AI safety as a “Big Science” project on a scale comparable to the Manhattan Project. High risks and high payoffs are on the table, but safe AI is a fast-moving target, and large-scale investments are needed to guide development of this technology in a responsible way. We highlight the need for a multilayered solution combining the development of new methods and algorithmic approaches to mitigate threats with an active participation of the government(s) in setting high industry standards and regulations based on state-of-the-art technology. The U.S. Department of Energy (DOE) national laboratories have served as leading institutions for scientific innovation in the U.S. for more than 70 years. Drawing on their expertise in the AI community and their history of safeguarding critical and sensitive information, and as we look to the future, national labs are the best choice for evaluating and safeguarding AI technologies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Advances in Engine Test Capabilities at the NASA Glenn Research Center's Propulsion Systems Laboratory

The Propulsion Systems Laboratory at the National Aeronautics and Space Administration (NASA) Glenn Research Center is one of the premier U.S. facilities for research on advanced aeropropulsion systems. The facility can simulate a wide range of altitude and Mach number conditions while supplying the aeropropulsion system with all the support services necessary to operate at those conditions. Test data are recorded on a combination of steady-state and highspeed data-acquisition systems. Recently a number of upgrades were made to the facility to meet demanding new requirements for the latest aeropropulsion concepts and to improve operational efficiency. Improvements were made to data-acquisition systems, facility and engine-control systems, test-condition simulation systems, video capture and display capabilities, and personnel training procedures. This paper discusses the facility s capabilities, recent upgrades, and planned future improvements.

Pachlhofer, Peter M.↗
NASA NTRSDate not supplied

NASA HRP Food and Nutrition Risk Strategy

The Human Health Countermeasures (HHC) Element of NASA’s Human Research Program (HRP), along with other organizations within NASA, conduct research and capability developments to buy down the risk of performance decrement and crew illness due to inadequate food and nutrition. Food and nutrition are critical for health and performance both in low Earth orbit and on exploration missions. On the International Space Station (ISS), crewmembers share a defined set of pantry foods, and have limited preference and shelf-life foods (e.g. fruits and vegetables) from resupply missions. Exploration design reference missions (DRMs) will likely be more constrained than missions to ISS, where those crewmembers would be subject to a more restricted food system due to resource limitations. HRP food and nutrition research consists of studies to close the following research gaps: determination of the nutritional requirements to maintain health and performance for the defined DRMs, determining the nutrient content, safety, and acceptability of the spaceflight food system specific to DRM and vehicle constraints, development of countermeasures either within or in addition to the food system to mitigate decrements to health and performance by DRM, and the validation and integration of food system countermeasures in analogs and in flight. The current spaceflight food system is shelf-stable, consisting of freeze-dried foods, thermostabilized foods, natural form foods, and powdered beverages. Crops represent a food system countermeasure that has the potential to supplement the pre-packaged food system. As an applied research program, HRP goals for crop research are centered around three main themes: nutrition, safety, and acceptability. As crops advance through Crop Readiness Level evaluations, HHC partners with the sponsoring organization to ensure that HRP goals are met for crops to be consumed in spaceflight.

food↗
DOE OSTI2021

Brain Connectivity Workshop Series Report

The National Institutes of Health (NIH) BRAIN Initiative aims to accelerate development and application of technologies that show how individual brain cells in complex neural circuits interact at the speed of thought and action. Complete wiring diagrams of the mammalian brain will revolutionize the capabilities of researchers to formulate and test models of how activity within brain circuits drives coordinated function and behavior. A top priority for the BRAIN Initiative, motivated by the strategic guidance of the BRAIN 2.0 Working Group report, is to muster the resources and foster the collaborations needed to generate these wiring diagrams at the level of long-range projections (“projectomes”) and synapses (“connectomes”) in whole mammalian brains, including those from rodents, humans, and other large-brained mammals. Achieving the scale and resolution necessary to characterize and use these projectomes and connectomes will not only push the boundaries of current imaging and computational capabilities to generate faster, cheaper, and more scalable technologies, but also drive broad innovation in data science, artificial intelligence, and machine learning.

42 ENGINEERING↗
DOE OSTI2025

ADEPT: A Pedagogical Framework for Integrating Agentic AI with Deterministic Scientific Workflows

The integration of Large Language Models (LLMs) into scientific research promises to accelerate discovery, yet a significant gap remains between the dynamic reasoning of Artificial Intelligence (AI) agents and the static, deterministic nature of canonical scientific workflows. This paper introduces ADEPT (Agentic Discovery and Exploration Platform for Tools), a reference architecture and pedagogical framework explicitly designed to bridge this gap. ADEPT's primary mission is to provide a transparent, "glass-box" environment where researchers and engineers can learn to effectively wrap established scientific software (e.g., BLAST, Nextflow pipelines) and compose it into reliable, agent-driven workflows. We describe its modular, multi-server architecture, which leverages the Model Context Protocol (MCP) for tool serving, LangGraph for robust agentic orchestration, and a secure nsjail-based sandbox for safe code execution. By prioritizing architectural clarity, safety, and modularity, ADEPT serves as an extensible blueprint for building trustworthy AI-augmented systems and fosters the collaborative development necessary to responsibly employ agentic AI for science. We provide practical examples of how to adapt and extend this framework, highlighting its utility in workforce development and AI-readiness capabilities across research and development projects.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

NASA's Rodent Research Project: Validation of Flight Hardware, Operations and Science Capabilities for Conducting Long Duration Experiments in Space

Research using rodents is an essential tool for advancing biomedical research on Earth and in space. Rodent Research (RR)-1 was conducted to validate flight hardware, operations, and science capabilities that were developed at the NASA Ames Research Center. Twenty C57BL/6J adult female mice were launched on Sept 21, 2014 in a Dragon Capsule (SpaceX-4), then transferred to the ISS for a total time of 21-22 days (10 commercial mice) or 37 (10 validation mice). Tissues collected on-orbit were either rapidly frozen or preserved in RNA later at less than or equal to -80 C (n=2/group) until their return to Earth. Remaining carcasses were rapidly frozen for dissection post-flight. The three controls groups at Kennedy Space Center consisted of: Basal mice euthanized at the time of launch, Vivarium controls, housed in standard cages, and Ground Controls (GC), housed in flight hardware within an environmental chamber. FLT mice appeared more physically active on-orbit than GC, and behavior analysis are in progress. Upon return to Earth, there were no differences in body weights between FLT and GC at the end of the 37 days in space. RNA was of high quality (RIN greater than 8.5). Liver enzyme activity levels of FLT mice and all control mice were similar in magnitude to those of the samples that were optimally processed in the laboratory. Liver samples collected from the intact frozen FLT carcasses had RNA RIN of 7.27 +/- 0.52, which was lower than that of the samples processed on-orbit, but similar to those obtained from the control group intact carcasses. Nonetheless, the RNA samples from the intact carcasses were acceptable for the most demanding transcriptomic analyses. Adrenal glands, thymus and spleen (organs associated with stress response) showed no significant difference in weights between FLT and GC. Enzymatic activity was also not significantly different. Over 3,000 tissues collected from the four groups of mice have become available for the Biospecimen Sharing Program. Together, these validation flight findings demonstrate the capability to support long-duration RR on the ISS to achieve both basic science and biomedical objectives.

rodents↗
NASA NTRS2014

WetLab-2: Tools for Conducting On-Orbit Quantitative Real-Time Gene Expression Analysis on ISS

The objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform capable of conducting gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens sampled or cultured on orbit. The project has selected a Commercial-Off-The-Shelf (COTS) qRT-PCR system, the Cepheid SmartCycler and will fly it in its COTS configuration. The SmartCycler has a number of advantages including modular design (16 independent PCR modules), low power consumption, rapid ramp times and the ability to detect up to four separate fluorescent channels at one time enabling multiplex assays that can be used for normalization and to study multiple genes of interest in each module. The team is currently working with Cepheid to enable the downlink of data from the ISS to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project has adapted commercial technology to design a module that can lyse cells and extract RNA of sufficient quality and quantity for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. The WetLab-2 system is capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. The ability to conduct qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples. The system can be used to validate terrestrial analyses of samples returned from ISS by providing on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experiment parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Researchers will also be able to sample multigenerational changes in organisms. Finally, the system can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-7 in June 2015.

quantitative PCR↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗
NASA NTRS2022

COSMO: The COronal Solar Magnetism Observatory

The COronal Solar Magnetism Observatory (COSMO) will make the first synoptic, simultaneous measurements of magnetic and plasma properties of the global solar atmosphere, filling crucial gaps in our understanding of the drivers of solar eruptions and the evolution of the coronal magnetic field on time scales from minutes to decades. - COSMO uniquely addresses critical Heliophysics science. With an unparalleled combination of large field of view and high magnetic sensitivity, the 1.5m COSMO Large Coronagraph (LC) opens a new window on coronal magnetism on global scales. Along with K-Coronagraph (K-Cor) middle-corona observations and the Chromosphere and Prominence Magnetometer (ChroMag) observations of the photosphere and chromosphere, these capabilities enable researchers to finally answer crucial questions about solar eruptions, coronal heating/solar wind acceleration, and the solar dynamo. - COSMO is mature. K-Cor has been operating at the Mauna Loa Solar Observatory (MLSO) since 2013 and ChroMag is soon to be deployed. Also at MLSO, the 20cm Upgraded Coronal Multichannel Polarimeter (UCoMP) is proving the power of global coronal spectropolarimetry and whetting the community’s appetite for the unprecedented sensitivity of the LC. - COSMO is low risk. A recent development: the NSF-funded COSMO Site and Design Advancement (COSADA) is a three-year effort currently underway that reduces risk through site selection and final design of the LC. - COSMO has broad community support. The fact that COSMO fills a critical gap in our observational capabilities was recognized in the last Solar and Space Physics Decadal Survey. COSMO builds on the legacy and thriving user base of the MLSO, which has provided global synoptic solar observations to the community for over sixty years. - COSMO is complementary to other solar telescopes. The breakthrough observations obtained by COSMO will not be provided by any other current or proposed observatory, and will enhance the value of other ground- and space-based Heliophysics assets.

Steven Tomczyk↗
NASA NTRS1990

Knowledge representation to support reasoning based on multiple models

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

Gillam, April↗
NASA NTRS1978

Life sciences experiments in the first Spacelab mission

The development of the Shuttle Transportation System (STS) by the United States and the Spacelab pressurized modules and pallets by the European Space Agency (ESA) presents a unique multi-mission space experimentation capability to scientists and researchers of all disciplines. This capability is especially pertinent to life scientists involved in all areas of biological and behavioral research. This paper explains the solicitation, evaluation, and selection process involved in establishing life sciences experiment payloads. Explanations relative to experiment hardware development, experiment support hardware (CORE) concepts, hardware integration and test, and concepts of direct Principal Investigator involvement in the missions are presented as they are being accomplished for the first Spacelab mission. Additionally, discussions of future plans for life sciences dedicated Spacelab missions are included in an attempt to define projected capabilities for space research in the 1980s utilizing the STS.

Huffstetler, W. J.↗
DOE OSTI2024

Emergency Management of Tomorrow Research – Task 3B Research and Development Community Awareness: Eliciting Emergency Management Stakeholder Input

The Department of Homeland Security (DHS) Science and Technology Directorate (S&T) is partnering with Pacific Northwest National Laboratory (PNNL) to execute the Emergency Management (EM) of Tomorrow Research (EMOTR) program to identify current EM research, elicit capability needs from EM practitioners, and identify where technology, such as artificial intelligence (AI), may benefit the future of EM and emergency operations centers. This report details the methodology, analysis, and insights of interviews and focus groups conducted as part of the task to elicit stakeholder input.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Capability Needs for Irradiated and Radioactive Materials Research (Ad hoc Committee Summary Report)

It is essential for the U.S. nuclear energy community to have access to world-leading equipment suitable for conducting research on both nuclear fuels and structural materials, including neutron irradiated–and therefore activated–materials. To address future research infrastructure requirements to support the DOE-NE mission, the Office of Reactor Fleet and Advanced Reactor Deployment established an ad hoc committee to gather information on potential capability gaps for radioactive materials and radiation effects research. This document summarizes the discussions of the committee addressing the high-level challenges in irradiated and radioactive materials research and the capabilities needed to address these challenges. After considering the various needs, the committee agreed on the four top-level targets and priority capability gaps.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗