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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Nerve-responsive troponin I slow promoter does not respond to unloading

We examined the regulation of the troponin I slow (TnIs) promoter during skeletal muscle unloading-induced protein isoform transition, by using a transgenic mouse line harboring the -4,200 to +12 base pairs region of the human TnIs promoter. Eighteen female transgenic mice ( approximately 30 g body mass) were randomly divided into two groups: weight-bearing (WB) controls (n = 9) and hindlimb unloaded (HU; n = 9). The HU mice were tail suspended for 7 days. Body mass was unchanged in the WB group but was reduced (-6%; P < 0.05) after the HU treatment. Absolute soleus muscle mass (-25%) and soleus mass relative to body mass (-16%) were both lower (P < 0.05) in the HU group compared with the WB mice. Northern blot analyses indicate that 7 days of HU result in a 64% decrease (P < 0.05) in the abundance of endogenous TnIs mRNA (microg/mg muscle) in the mouse soleus. Furthermore, there is a trend for the abundance of the fast troponin I mRNA to be increased (+34%). Analysis of transgenic chloramphenicol acetyltransferase activity in the soleus muscle revealed no difference (P > 0.05) between WB and HU groups. We conclude that additional elements are necessary for the TnIs gene to respond to an unloading-induced, slow-to-fast isoform transition stimulus.

Non-NASA Center↗
NASA NTRS2008

Space-Dynamically Responding Ultrasonic Matrix System

Space-Dynamically Responding Ultrasonic Matrix System (SpaceDRUMS) comprises a suite of hardware that enables containerless processing (samples of experimental materials can be processed without ever touching a container wall). Using a collection of 20 acoustic beam emitters, SpaceDRUMS can completely suspend a baseball-sized solid or liquid sample during combustion or heat-based synthesis. Because the samples never contact the container walls, materials can be produced in microgravity with an unparalleled quality of shape and composition. The ultimate goal of the SpaceDRUMS hardware is to assist with the development of advanced materials of a commercial quantity and quality, using the space-based experiments to guide development of manufacturing processes on Earth. T

Guigne, Jacques↗
NASA NTRS2004

Software Assists in Responding to Anomalous Conditions

Fault Induced Document Retrieval Officer (FIDO) is a computer program that reduces the need for a large and costly team of engineers and/or technicians to monitor the state of a spacecraft and associated ground systems and respond to anomalies. FIDO includes artificial-intelligence components that imitate the reasoning of human experts with reference to a knowledge base of rules that represent failure modes and to a database of engineering documentation. These components act together to give an unskilled operator instantaneous expert assistance and access to information that can enable resolution of most anomalies, without the need for highly paid experts. FIDO provides a system state summary (a configurable engineering summary) and documentation for diagnosis of a potentially failing component that might have caused a given error message or anomaly. FIDO also enables high-level browsing of documentation by use of an interface indexed to the particular error message. The collection of available documents includes information on operations and associated procedures, engineering problem reports, documentation of components, and engineering drawings. FIDO also affords a capability for combining information on the state of ground systems with detailed, hierarchically-organized, hypertext- enabled documentation.

James, Mark↗
NASA NTRSDate not supplied

Elevated CO2 Could Undermine an Exploration Crew's Ability to Independently Respond to Unanticipated, Time- and Safety-Critical Anomalies

Safety and mission critical anomalies are inevitable on NASA exploration missions. Delays and interruptions in communication with Earth-experts drives the requirement that crew resolve some time- and safety-critical anomalies on their own. The HRP, HFBP, Human-System Integration Architecture (HSIA) risk refers to the possibility that, during communication blackouts and thus the absence of vast ground expertise, a small crew may not be able to independently respond to unanticipated, time-critical malfunctions or to detect safety critical procedure errors.

carbon dioxide↗
NASA NTRS2018

Occluded Object Reconstruction for First Responders with Augmented Reality Glasses Using Conditional Generative Adversarial Networks

Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.

Chow, Edward↗
NASA NTRSDate not supplied

Informing New Concepts for UAS and Autonomous System Safety Management using Disaster Management and First Responder Scenarios

As emerging flight operations become more prevalent and increasingly automated and distributed, the capabilities for managing safety of vehicles and operations will also need to evolve. To address this challenge, the National Academies has envisioned an In-Time Aviation Safety Management System (IASMS) capability for a wide range of aviation operations including current commercial operations as well as new entrants envisioned with advanced air mobility (AAM). The suite of IASMS services, functions, and capabilities (SFCs) would be implemented in a federated approach and would address trends as well as individual operations. Through predictive modeling and data analysis, IASMS is envisioned to identify arising risks so that they can be mitigated, in-time, before a safety incident occurs. IASMS and its requisite set of SFCs must leverage a wide range of information to perform. To better understand these new needs, FSF worked with the aviation and humanitarian communities to develop and validate scenarios that include traditional aviation operations and UAS operations intermingled as they are deployed for disaster management and first responder (DMFR) situations. The three scenarios developed include: • Post Natural disaster response, such as a hurricane, involving multiple parties utilizing traditional aviation and UAS to support rescue operations, surveil damage, and locate survivors needing assistance. • Wildfire fighting in remote locations with traditional aircraft for transport and fire-retardant delivery combined with UAS for surveillance of fire locations as well as to track individual firefighter locations. • Medical Operations and AAM in Urban Environments including passenger-carrying helicopters and AAM vehicles, medical missions (such as transport of radio-pharmaceuticals), and other UAS delivery operations (such as the delivery of defibrillators). Each scenario was developed and validated by representatives with expertise in humanitarian operations, urban and rural emergency response, air traffic management, UAS operations, and traditional flight operations. The scenario definitions address roles and responsibilities of individual actors, the appropriate utilization of UAS, and the actions taken by those actors to appropriately manage risks associated with the mission and environment. The risks to aviation traffic and to people on the ground explored included potential risks arising from incompatibilities in calculating reference altitudes (eg, differing uses of AGL, MSL, barometric, or GPS-derived values), loss of command and control (C2) communications, rapid changes in weather and winds, and physical interference. For each risk, IASMS SFCs were postulated in the context of monitoring services, risk assessment capabilities, and identifying appropriate mitigation strategies. The identified SFC capabilities were envisioned from known services postulated for IASMS and for UTM. For these unique environments, IASMS SFCs are needed to address conditions such as hazardous payloads, micro-climates and urban canyons, and the need to keep uninvolved air traffic out of the area where DMFR operations are being conducted. The second phase of analysis focused on inferring the specific information needs and the SFCs for IASMS, utilizing a structure of 16 information classes to organize requirements. For each of the risks identified in the workshops, it was postulated what data sources would be necessary to monitor critical aspects of the risk (eg, surrounding air traffic, ground population, terrain, etc). to be directly measured as well as data that would be derived, which implies additional SFCs for different actors to understand what information would likely be exchanged between parties. For an IASMS to be effective, additional research is needed to develop the advanced algorithms that can address the increasingly autonomous and complex operations in differing environments and to develop means of identifying unknown risks. Looking at these scenarios highlighted a number of research issues. These include the ability to quickly "cordon off" airspace thru temporary flight restrictions (TFRs) or other means, developing clear definitions to enable automation-based algorithms for prioritizing operations, defining airspace density metrics, standardization of altitude reporting, and establishing a basis for safety data metrics definition and collection. This paper seeks to outline the development of an IASMS in the context of the DMFR scenarios and resulting demonstrations. Utilizing this contextual approach, NASA will generate recommendations for an assured safety framework for AAM operations that enables AAM operations to safely access the NAS.

In Time Aviation Safety Management System↗
NASA NTRSDate not supplied

A Science-Focused Artificial Intelligence (AI) Responding in Real-Time to New Information: Capability Demonstration for Ocean World Missions

Introduction: Artificial intelligence (AI) has long been considered a potential mechanism to explore increasingly challenging environments, including those with extreme temperatures and pressures, limited communication capabilities, or those with demanding terrain. We posit that missions in extreme environments could deploy an onboard AI focused on science observations and goals in order to augment a traditional concept(s) of operations (ConOps). An onboard AI capability could perform functions such as data analysis in order to make high-level decisions, including prioritized data transmission for analysis by ground-based teams or autonomously-guided follow-on analyses that maximize science return. Such a capability would empower missions to respond to scientific data of interest in real-time; a mission could make observations and perform a preliminary analysis to alert ground-based scientists to an observation of interest, enabling an informed, rapid response from Earth-based teams. Enceladus Case Study for Onboard AI: We are developing an onboard AI capability for real-time telemetry response that formulates and carries-out informed decisions in service to established mission goals, enabling increased science return of a mission. We focus our AI development for use on a constellation of SmallSats orbiting Enceladus. Our Enceladus case study tests autonomous decision-making capabilities in scenarios with complex orbital dynamics, plume ejecta, extreme cold environments, power restrictions, and a requirement to maximize science return for a potential positive detection of life, while critically evaluating the potential for false positives. Telemetry includes simulated scientific data, spacecraft onboard operational data (e.g., position, velocity, and rotation), and engineering hardware performance data. Enceladus SmallSat Constellation. Our constellation includes eight SmallSat spacecraft in an 8:35 resonant orbit-based formation, leveraging Saturn’s gravitational forces to maintain stable orbits with global coverage around Enceladus. To our knowledge, we simulate the first stable configuration of multiple spacecraft in closed orbits around Enceladus, using a full ephemeris force model (Russell and Lara, 2009). Each spacecraft’s orbit will precess, causing an eastward ground track shift (from an orbiter’s perspective) of each spacecraft for each orbit. However, all spacecraft return to their original positions relative to Enceladus after eight Enceladus revolutions around Saturn. We model communication pathways between SmallSats to understand how information would need to be transmitted across the constellation to enable AI-driven decision-making and resource allocation across the fleet. Capability Demonstration. Our simulated capability demonstration inputs position, velocity, and rotation telemetry from our Enceladus-focused constellation simulations, and mass spectrometry data collected from abiotic and biotic laboratory-analog ocean world experiments (Theiling et al., 2018; Theiling, 2021; Da Poian et al., 2023). Data from these experiments are used to simulate MS measurements and different scenarios of science observations for onboard analysis performed on each of the eight spacecraft. For these demonstrations, we integrate 24 machine learning (ML) algorithms into an onboard intelligence as a ‘knowledge base’, including algorithms evaluating data quality and those predicting (with % confidence) gas composition, ocean aqueous chemistry, and whether the sample was influenced by microbial life. The onboard AI capability is designed to use the knowledge base to come to a consensus-based decision in the interpretation of the observed data in order to request additional action outside of a pre-defined ConOps. Requested actions could include e.g., prioritized downlink to Earth (for analysis by ground-based teams) or follow-on analyses performed across the constellation. The spacecraft’s intelligent onboard planner must then determine whether sufficient resources (e.g., time, power, etc.) are available and weigh the request with mission priorities. In our simulation, the constellation is able to identify potential biosignatures using onboard ML algorithms, evaluate the confidence of that prediction, and perform follow-on analyses across the fleet to confirm the detection, in order to best prepare a transmission of these data to Earth-based teams.

astrobiology↗
DOE OSTI2017

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys : 1. Microtopography Determines How Active Layer Depths Respond to Changes in Temperature and Precipitation

Microtopographic variation that develops among features (troughs, rims, and centers) within polygonal landforms of coastal arctic tundra strongly affects movement of surface water and snow and thereby affects soil water contents (θ) and active layer depth (ALD). Spatial variation in ALD among these features may exceed interannual variation in ALD caused by changes in climate and so needs to be represented in projections of changes in arctic ALD. For this study, increases in near-surface θ with decreasing surface elevation among polygon features at the Barrow Experimental Observatory (BEO) were modeled from topographic effects on redistribution of surface water and snow and from lateral water exchange with a subsurface water table during a model run from 1981 to 2015. These increases in θ caused increases in thermal conductivity that in turn caused increases in soil heat fluxes and hence in ALD of up to 15 cm with lower versus higher surface elevation which were consistent with increases measured at BEO. The modeled effects of θ caused interannual variation in maximum ALD that compared well with measurements from 1985 to 2015 at the Barrow Circumpolar Active Layer Monitoring (CALM) site (R 2 = 0.61, RMSE = 0.03 m). For higher polygon features, interannual variation in ALD was more closely associated with annual precipitation than mean annual temperature, indicating that soil wetting from increases in precipitation may hasten permafrost degradation beyond that caused by soil warming from increases in air temperature. This degradation may be more rapid if increases in precipitation cause sustained wetting in higher features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 2. Microtopography Determines How CO 2 and CH 4 Exchange Responds to Changes in Temperature and Precipitation

Differences of surface elevation in arctic polygonal landforms cause spatial variation in soil water contents (θ), active layer depths (ALD), and thereby in CO 2 and CH 4 exchange. In this paper, we test hypotheses in ecosys for topographic controls on CO 2 and CH 4 exchange in trough, rim, and center features of low- and flat-centered polygons (LCP and FCP) against chamber and eddy covariance (EC) measurements during 2013 at Barrow, Alaska. Larger CO 2 influxes and CH 4 effluxes were measured with chambers and modeled with ecosys in LCPs than in FCPs and in lower features (troughs) than in higher (rims) within LCPs and FCPs. Spatially aggregated CO 2 and CH 4 fluxes from ecosys were significantly correlated with EC flux measurements. Lower features were modeled as C sinks (52–56 g C m -2 yr -1 ) and CH 4 sources (4–6 g C m -2 yr -1 ), and higher features as near C neutral (-2–15 g C m -2 yr -1 ) and CH 4 neutral (0.0–0.1 g C m -2 yr -1 ). Much of the spatial and temporal variations in CO 2 and CH 4 fluxes were modeled from topographic effects on water and snow movement and thereby on θ, ALD, and soil O 2 concentrations. Model results forced with meteorological data from 1981 to 2015 indicated increasing net primary productivity in higher features and CH 4 emissions in some lower and higher features since 2008, attributed mostly to recent rises in precipitation. Finally, small-scale variation in surface elevation causes large spatial variation of greenhouse gas (GHG) exchanges and therefore should be considered in estimates of GHG exchange in polygonal landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Hydraulic conductance, resistance, and resilience: how leaves of a tropical epiphyte respond to drought

Premise Because of its broad range in the neotropical rainforest and within tree canopies, the tank bromeliad Guzmania monostachia was investigated as a model of how varying leaf hydraulic conductance ( K leaf ) could help plants resist and recover from episodic drought. The two pathways of K leaf , inside and outside the xylem, were also examined to determine the sites and causes of major hydraulic resistances within the leaf. Methods We measured leaf hydraulic conductance for plants in the field and laboratory under wet, dry, and rewetted conditions and applied physiological, anatomical, and gene expression analysis with modeling to investigate changes in K leaf . Results After 7 d with no rain in the field or 14 days with no water in the glasshouse, K leaf decreased by 50% yet increased to hydrated values within 4 d of tank refilling. Staining to detect embolism combined with modeling indicated that changes outside the xylem were of greater importance to K leaf than were changes inside the xylem and were associated with changes in intercellular air spaces (aerenchyma), aquaporin expression and inhibition, and cuticular conductance. Conclusions Low values for all conductances during drying, particularly in pathways outside the xylem, lead to hydraulic resilience for this species and may also contribute to its broad environmental tolerances.

North, Gretchen B.↗
DOE OSTI2020

Tropical understory herbaceous community responds more strongly to hurricane disturbance than to experimental warming

The effects of climate change on tropical forests may have global consequences due to the forests’ high biodiversity and major role in the global carbon cycle. In this study, we document the effects of experimental warming on the abundance and composition of a tropical forest floor herbaceous plant community in the Luquillo Experimental Forest, Puerto Rico. This study was conducted within Tropical Responses to Altered Climate Experiment (TRACE) plots, which use infrared heaters under free-air, open-field conditions, to warm understory vegetation and soils + 4°C above nearby control plots. Hurricanes Irma and María damaged the heating infrastructure in the second year of warming, therefore, the study included one pretreatment year, one year of warming, and one year of hurricane response with no warming. We measured percent leaf cover of individual herbaceous species, fern population dynamics, and species richness and diversity within three warmed and three control plots. Results showed that one year of experimental warming did not significantly affect the cover of individual herbaceous species, fern population dynamics, species richness, or species diversity. In contrast, herbaceous cover increased from 20% to 70%, bare ground decreased from 70% to 6%, and species composition shifted pre to posthurricane. The negligible effects of warming may have been due to the short duration of the warming treatment or an understory that is somewhat resistant to higher temperatures. Our results suggest that climate extremes that are predicted to increase with climate change, such as hurricanes and droughts, may cause more abrupt changes in tropical forest understories than longer-term sustained warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Responding to the US national pollinator plan: a case study in Michigan

The long‐term health of pollinators is a critical issue for the functioning of natural habitats and for agricultural production. In response to widespread public concern about the future of these ecologically and economically important animals, in 2015 the US Government released a national strategy to support pollinators, including research priorities, directives for funding, and timelines for achieving three overarching goals. Five years after this strategic plan was released, we evaluate progress toward the national targets for improved honey bee ( Apis mellifera ) overwintering survival, expanded pollinator habitat, and larger monarch butterfly ( Danaus plexippus ) populations, and find that the three goals of the plan have not yet been reached. Our research and extension programs to improve the health of honey bees, wild bees, and monarch butterflies in the US state of Michigan are described, providing opportunities to contribute to the national pollinator goals.

Bloom, Elias H.↗
DOE OSTI2013

Colloid-in-Liquid Crystal Gels that Respond to Biomolecular Interactions

This paper advances the design of stimuli-responsive materials based on colloidal particles dispersed in liquid crystals (LCs). Specifically, thin films of colloid-in-liquid crystal (CLC) gels undergo easily visualized ordering transitions in response to reversible and irreversible (enzymatic) biomolecular interactions occurring at the aqueous interfaces of the gels. In particular, LC ordering transitions can propagate across the entire thickness of the gels. However, confinement of the LC to small domains with lateral sizes of~10 μm does change the nature of the anchoring transitions, as compared to films of pure LC, due to the effects of confinement on the elastic energy stored in the LC. The effects of confinement are also observed to cause the response of individual domains of the LC within the CLC gel to vary significantly from one to another, indicating that manipulation of LC domain size and shape can provide the basis of a general and facile method to tune the response of these LC-based physical gels to interfacial phenomena. Ultimately, the results presented in this paper establish that CLC gels offer a promising approach to the preparation of self-supporting, LC-based stimuli-responsive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗