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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Airplane Capabilities: Translating Non-Normal Information for Operational Decision-Making

We consider how a jet transport airplane interface supports the flight crew in managing airplane system failures (or non-normals) for continued safe flight and landing. The existing state of the art starts with a list of airplane system component failures and asks the flight crew to determine, with the help of non-normal procedures, the operational consequences of those failures. As airplane systems become more complex and interconnected, the flight crew's ability to determine operational consequences will become inadequate. We describe an approach that attempts to translate airplane system failures directly into airplane "capabilities," which is a set of basic airplane functions, such as the ability to stop after landing. This paper describes the overall framework for supporting flight crews in operational decision making and the initial efforts to develop a language and display concepts.

managing airplane system non-normals↗
NASA NTRS2017

Advancing Translational Space Research Through Biospecimen Sharing: Amplified Impact of Studies Utilizing Analogue Space Platforms

Biospecimen Sharing Programs (BSPs) have been organized by NASA Ames Research Center since the 1960s with the goal of maximizing utilization and scientific return from rare, complex and costly spaceflight experiments. BSPs involve acquiring otherwise unused biological specimens from primary space research experiments for distribution to secondary experiments. Here we describe a collaboration leveraging Ames expertise in biospecimen sharing to magnify the scientific impact of research informing astronaut health funded by the NASA Human Research Program (HRP) Human Health Countermeasures (HHC) Element. The concept expands biospecimen sharing to one-off ground-based studies utilizing analogue space platforms (e.g., Hindlimb Unloading (HLU), Artificial Gravity) for rodent experiments, thereby significantly broadening the range of research opportunities with translational relevance for protecting human health in space and on Earth. In this presentation, we will report on biospecimens currently being acquired from HHC Award Head-Down Tilt as a Model for Intracranial and Intraocular Pressures, and Retinal Changes during Spaceflight, and their availability. The BSP add-on to the project described herein has already yielded for HHC-funded investigators more than 4,700 additional tissues that would otherwise have been discarded as waste, with additional tissues available for analysis. Young (3-mo old) male and female rats and Older (9-mo old) male rats are being exposed to HLU for either 7, 14, 28, or 90 days. Additional groups are exposed to 90 days of unloading followed by either 7, 14, 28 days or 90 days of recovery (normal loading). Comparisons are made with non-suspended controls. Unused tissues are: Skin, Lungs, Thymus, Adrenals, Kidneys, Spleen, Hindlimb Muscles (Soleus, Extensor Digitorum Longus, Tibialis Anterior, Plantaris Gastrocnemius), Fat Pads, Reproductive Organs, and Intestines. Tissues are harvested, weighed, preserved then archived (with metadata) using a sample tracking system (CryoTrack). Preservation techniques include snap-freezing and RNALatersnap-freezing. Specimens were weighed at the time of dissection, and organ mass:body mass ratios analyzed to determine unloading effects across conditions and durations. The results corroborate previously reported effects of short-term exposure to microgravity or unloading exposure on various organs, and provide new insights into adaptation to long-duration unloading relevant to sustained spaceflight exposures on ISS.

biospecimen sharing↗
NASA NTRS2015

Translational Cell & Animal Research in Space 1965-2011

Translational Cell and Animal Research (TCAR). For nearly 50 years, the NASA Space Biology Program has funded, and Ames Research Center (ARC) has managed, a robust program of fundamental research including studies using a wide range of animal cells, tissues and organisms. Much of this research was conducted on spacecraft in microgravity environments including diverse platforms such as: Gemini Spacecraft, US Biosatellites, Apollo Command Modules, Skylabs, Russian Biosatellites, NASA Space Shuttles, NASA/Mir, and most recently, the International Space Station (ISS). During the Space Shuttle Era (1981–2011), the science of space biology took an enormous step forward with 45 missions that afforded researchers with new opportunities to conduct systematic and complex experiments aimed at a deeper understanding of how life adapts to the space environment. Beginning in the 1990s, the products of these experiments, comprised of research summaries and rare, unused biospecimens, were collected and catalogued within the ARC Life Sciences Data Archiving Office, a branch of NASA’s Life Sciences Data Archive (LSDA) managed from the NASA Johnson Spaceflight Center.

Ronca, April E.↗
NASA NTRS2018

NASA’s Mid-Atlantic Communities and Areas at Intensive Risk Demonstration: Translating Compounding Hazards to Societal Risk

Remote sensing provides a unique perspective on our dynamic planet, tracking changes and revealing the course of complex interactions. Long term monitoring and targeted observation combine with modeling and mapping to provide increased awareness of hydro-meteorological and geological hazards. Disasters often follow hazards and the goal of NASA’s Disasters Program is to look at the earth as a highly coupled system to reduce risk and enable resilience. Remote sensing and geospatial science are used as tools to help answer critical questions that inform decisions. Data is not the same as information, nor does understanding of processes necessarily translate into decision support for disaster preparedness, response and recovery. Accordingly, NASA is engaging the scientific and decision-support communities to apply remote sensing, modeling, and related applications in Communities and Areas at Intensive Risk (CAIR). In 2017, NASA’s Applied Sciences Disasters Program hosted a regional workshop to explore these issues with particular focus on coastal Virginia and North Carolina. The workshop brought together partners in academia, emergency management, and scientists from NASA and partnering federal agencies to explore capabilities among the team that could improve understanding of the physical processes related to these hazards, their potential impact to changing communities, and to identify methodologies for supporting emergency response and risk mitigation. The resulting initiative, the mid-Atlantic CAIR project, demonstrates the ability to integrate satellite derived earth observations and physical models into actionable, trusted knowledge. Severe storms and associated storm surge, sea level rise, and land subsidence coupled with increasing populations and densely populated, aging critical infrastructure often leave coastal regions and their communities extremely vulnerable. The integration of observations and models allow for a comprehensive understanding of the compounding risk experienced in coastal regions and enables individuals in all positions make risk-informed decisions. This initiative uses a representative storm surge case as a baseline to produce flood inundation maps. These maps predict building level impacts at current day and for sea level rise (SLR) and subsidence scenarios of the future in order to inform critical decisions at both the tactical and strategic levels. To accomplish this analysis, the mid-Atlantic CAIR project brings together Federal research activities with academia to examine coastal hazards in multiple ways: 1) reanalysis of impacts from 2011 Hurricane Irene, using numerical weather modeling in combination with coastal surge and hydrodynamic, urban inundation modeling to evaluate combined impact scenarios considering SLR and subsidence, 2) remote sensing of flood extent from available optical imagery, 3) adding value to remotely sensed flood maps through depth predictions, and 4) examining coastal subsidence as measured through time-series analysis of synthetic aperture radar observations. Efforts and results are published via ArcGIS story maps to communicate neighborhoods and infrastructure most vulnerable to changing conditions. Story map features enable time-aware flood mapping using hydrodynamic models, photographic comparison of flooding following Hurricane Irene, as well as visualization of heightened risk in the future due to SLR and land subsidence.

Rogers, Laura↗
NASA NTRSDate not supplied

Virtual Sensing with Unsupervised Image-to-Image Translation

Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem with partial labels and introduce a novel shared spectral reconstruction loss. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. On a downstream cloud detection task, we show that generating synthetic bands with our model improves segmentation performance beyond our baseline. Our proposed approach enables synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗
NASA NTRS1999

A Flexible Statechart-to-model-checker Translator

Many current-day software design tools offer some variant of statechart notation for system specification. We, like others, have built an automatic translator from (a subset of) statecharts to a model checker, for use to validate behavioral requirements.

statecharts↗
NASA NTRS2021

Spectral Synthesis for Geostationary Satellite-to-Satellite Translation

Earth-observing satellites carrying multispectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have different vantage points above the Earth and different spectral imaging bands resulting in inconsistent imagery from one to another. This presents challenges in building downstream applications. What if we could generate synthetic bands for existing satellites from the union of all domains? We tackle the problem of generating synthetic spectral imagery for multispectral sensors as an unsupervised image-to-image translation problem modeled with a variational autoencoder (VAE) and generative adversarial network (GAN) architecture. Our approach introduces a novel shared spectral reconstruction loss to constrain the high-dimensional feature space of multispectral images. Simulated experiments performed by dropping one or more spectral bands show that cross-domain reconstruction outperforms measurements obtained from a second vantage point. Our proposed approach enables the synchronization of multispectral data and provides a basis for more homogeneous remote sensing datasets.

Geostationary satellites↗
NASA NTRS2021

Topical: Reverse Translation Strategies to Support Cognitive and Behavioral Risk Characterization

A coordinated suite of measurements to assess humans and animals needs to be established to support the translation and harmonization of animal research data to the astronaut corps due to the necessity of using animal subjects for radiation testing. The identification of POLs and PELs for spaceflight stressors (i.e. space radiation, altered gravity, isolation and confinement, sleep disruption) individually and combined will depend on defining scaling factors or transfer functions that can be used to relate human and animal outcomes.

Gregory Nelson↗
NASA NTRSDate not supplied

Baseline Medical System Translation for the Impact Medical Database

NASA has developed a new evidence-based data-driven probabilistic risk assessment and tradespace analysis tool as a successor to the Integrated Medical Model (IMM). This updated decision support tool is known as IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). Whereas IMM focuses on the resources and risks associated with International Space Station (ISS) and Low Earth Orbit (LEO) missions, IMPACT estimates the frequency and consequences of medical conditions that might arise during exploration missions. One of the services offered by IMM is a series of generic or baseline medical systems associated with typical mission types or DRMs (Design Reference Missions), such that requestors may prioritize questions pertaining to the mission itself over the medical supplies indicated by the model outputs for that DRM. In a mission focused request, the appropriate baseline medical system is used in place of a prepared or optimized medical kit. In preparation, an effort was undertaken to create baseline systems of medical resources within IMPACT suitable for typical DRMs. Using an existing baseline medical system within IMM’s Integrated Medical Evidence Database (iMED) as a starting point, the resources found within the medical kit were compared to and substituted for equivalent resources available within the IMPACT MD (Medical Database). In consultation with clinicians with knowledge of IMPACT’s MD, each resource was matched as closely as possible to a similarly purposed resource in IMPACT, seeking to preserve the treatment capabilities and procedures offered by the IMM medical system while reconciling the differences in modeled resources and medical conditions between the models. To demonstrate the efficacy of this work, a prototype ISS medical system in IMPACT was translated from the baseline used in the IMM. The appropriate medical system was then run through its associated medical model to compare and validate the resultant risks and risk mitigation provided by each baseline ISS medical kit.

S Schwartz↗