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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Metal Bioavailability and Ecotoxicity of Bioremediated Oils and Tailings by BioTiger{sup TM}, a Microbial Consortium

Oil Sands and Mature Fine Tailings: Oil sand reserves are a major source of oil for the United States. Oil sands are a mixture of sand, clay, water, and bitumen. The refining process requires large volumes of water and generates hazardous Mature Fine Tailings (MFTs) that are stored in engineered settling ponds. They are of major environmental concern due to their persistence and difficulty to naturally biodegrade. MFT Contaminants of Concern: Naphthenic Acids (NAs), Polycyclic Aromatic Hydrocarbons (PAHs), Benzene, Toluene, Ethylbenzene and Xylene (BTEX), Metals, Residual Bitumen. BioTiger{sup TM} (BT{sup TM}), the SRNL patented 12 component microbial consortia was found to cometabolically degrade some NAs and PAHs. Previous studies performing short term exposure (48 hours and 7 days) to BT{sup TM} have resulted in increased toxicity due to the partial degradation of PAHs forming toxic intermediates. Objective: Evaluate the ecotoxicity of BT{sup TM} remediated MFTs exposed to a 2 week period w/ yeast (Y) extract. This work will determine BT{sup TM}'s remediation of MFTs from Fort McMurray, Alberta. Acute toxicity tests will be performed under section 9 of EPA's Method for Measuring Acute Toxicity using the freshwater organism, Ceriodaphnia dubia. Monitor BT{sup TM} growth through Most Probable Number (MPN) counts, pH, and metal bioavailability will also be evaluated. Preparing tailing solutions for biodegradation: BT{sup TM} components were grown in R2A media and combined. Mother BT{sup TM} was centrifuged at 7000 rpm for 20 minutes and resuspended in Bushnell Haus. 33 g of tailings were added to 1100 mL Bushnell Haus along with yeast extract (11 g) to create a 3% tailing solution. Treatments were performed in triplicate. Preparing solutions for toxicity tests using C. dubia: Supernatant was collected immediately after centrifuging at 7000 rpm for 20 min. Supernatant was filtered via a 0.22 μm sterile system. All treatments except MFT, Y peaked at T=4. This decrease in microbial growth could be associated with toxicity from intermediate byproducts. Treatments containing only MFTs decreased in the initial 11 days before growing significantly. Final solution for MFT, Y treatment had the highest pH. This could potentially be due to increased microbial activity linked with yeast consumption. All treatments except MFT, Y peaked at T=4. This decrease in microbial growth could be associated with toxicity from intermediate byproducts. Treatments containing only MFTs decreased in the initial 11 days before growing significantly. Future Direction: Await results from Acute Toxicity Tests and Metal Bioavailability Quantification of biosurfactant production. Evaluate hydrocarbon degradation byproducts using an analytical chemistry approach. More toxicity experiments with variations in time and conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bayesian Approach to Estimation of Water Table Elevations Using Historical Rasters as Prior Information 2019 - 20430

In cases of complex but only partially known geology and a lack of spatial control in observation well locations, water table elevation estimation is very challenging. In some cases, auxiliary information, such as observations of the movement of tracers, operation of injection and extraction wells, and calibration of groundwater models against the historical elevation data, can be combined with expert judgement to estimate flow directions in areas of sparse data and to aid in the production of more reliable contour maps (and associated rasters) than could be produced by relying on sparse well elevation data alone. Given a historical sequence of these raster maps, the question arises how to automate, to the extent possible, the process of producing new raster maps to reflect data from previous times, the current data and the operation of expert judgement. One solution is to adopt a Bayesian point of view and to regard the historical well elevation data, auxiliary information and historical raster maps as prior information. The well elevations for water table wells, as well as those for injection/extraction wells and the data associated with other relevant variables, can be viewed as predictors for the raster surface. From this prior information, we can, conditional on the values of these predictors for a new time period, compute an expected value map and a standard deviation map for the new raster. These then can be taken to specify a prior predictive distribution for the pixels in the new raster map. Then we condition the pixels, corresponding to water level observation wells within the raster, on the observed values in those wells (which in general will differ from the regression estimate) for the new time period. Given the smoothness of the water table surface, we then smooth the surface of deviations from the mean surface, based on the variograms of the historical rasters, and add this smoothed surface to the regression mean surface. The error structure of the produced raster map is defined by the regression error structure and the error due to smoothing based on the estimated variograms. This methodology has been developed and is being further refined for groundwater monitoring and remediation at LANL. It is a very flexible method that can also be applied with a variety of other predictors applied to model the water level wells in the area of interest over the historical record. The smoothness of the spatial process and its possible evolution over time can then be estimated from the residuals from this regression. This can be augmented by expert hydrogeological opinion based on site topography and hydrogeology. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Rapid Response Data Science for COVID-19

This report describes the results of a seven day effort to assist subject matter experts address a problem related to COVID-19. In the course of this effort, we analyzed the 29K documents provided as part of the White House's call to action. This involved applying a variety of natural language processing techniques and compression-based analytics in combination with visualization techniques and assessment with subject matter experts to pursue answers to a specific question. In this paper, we will describe the algorithms, the software, the study performed, and availability of the software developed during the effort.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Earth System Digital Twins (ESDT) Technology for NASA Earth Science

For NASA's Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as an interactive and integrated multidomain, multiscale, digital replica of the state and temporal evolution of Earth systems. It dynamically integrates: relevant Earth system models and simulations; other relevant models (e.g., related to the world's infrastructure); continuous and timely (including near real time and direct readout) observations (e.g., space, air, ground, over/underwater, Internet of Things (IoT), socioeconomic); long-time records; as well as analytics and artificial intelligence tools. Effective ESDTs enable users to run hypothetical scenarios to improve the understanding, prediction of and mitigation/response to Earth system processes, natural phenomena and human activities as well as their many interactions. An ESDT is a type of integrated information system that, for example, enables continuous assessment of impact from naturally occurring and/or human activities on physical and natural environments. AIST ESDT strategic goals are to: 1. Develop information system frameworks to provide continuous and accurate representations of systems as they change over time; 2. Mirror various Earth Science systems and utilize the combination of Data Analytics, Artificial Intelligence, Digital Thread, and state-of-the-art models to help predict the Earth’s response to various phenomena; 3. Provide the tools to conduct "what if" investigations that can result in actionable predictions. The AIST ESDT thrust is developing capabilities toward the development of future digital twins of the Earth or of subcomponents of the Earth. This will enable the development of an overarching framework that will integrate New Observing Strategies (NOS) to enable new observation measurements, i.e., multi-source, coordinated, dynamic and responsive to needs and requests defined by Analytic Collaborative Frameworks (ACF) that enable agile science investigations fusing and analyzing very large amounts of diverse data. NOS and ACF capabilities along with open access to various science, infrastructure and human data, interconnected modeling, data assimilation, simulations, surrogate modeling, high-performance computing and advanced visualization, will define a powerful framework that could be utilized for local, regional or global and/or thematic digital twins. This presentation will describe a general overview of the AIST ESDT vision including prior work done in the areas of NOS and ACF as well as current and upcoming ESDT projects.

Jacqueline Le Moigne↗
DOE OSTI2021

Plastic shrinkage of mortars cured with a paraffin-based compound – Bimodal neutron/X-ray tomography study

Early-age drying (immediately after casting) of mortars and the corresponding plastic shrinkage were studied using bimodal neutron/X-ray computed tomography. This novel, correlative 3D imaging mode enabled studying simultaneously and without any source of spurious perturbation the water migration and loss processes together with the corresponding deformations due to plastic shrinkage. Bimodal imaging opens up new possibilities for studying dynamic processes of coupled water transport and deformations in porous solids. The measurements were carried out on model systems (cylindrical mortar specimens with height of 19 mm). The study focused on the effect of a paraffin-based curing compound. Our results confirm that when the curing compound was applied directly onto the drying surface in a sufficient amount, both the evaporation rate and the rate of vertical displacement (settlement) were substantially reduced. The results shed a new light on the mechanisms of plastic shrinkage and the action of curing compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Short-term electricity load forecasting: Application-driven evaluation of machine learning models across spatial and temporal scales

As we transition towards a decarbonized economy, the integration of variable renewable energy resources and new demands (e.g., electric vehicles, heat pumps) into the electricity grid places unprecedented pressure on grid operators to effectively anticipate and manage peak load. In this context, machine learning algorithms are proving to be indispensable for accurate short-term load forecasting, a crucial task to address these challenges. This study benchmarks 6 machine learning algorithms, including three neural networks and three tree-based algorithms, across various levels of spatial aggregation and time horizons (1, 4, 8, 24, and 48 h). The central contribution of this work is the comparison and analysis of load forecasting models not only based on statistical metrics, but also based on a novel error metric, which evaluates the cost implications of forecast errors for power system stakeholders. Results show that tree-based models outperform neural networks, based on statistical metrics, and yield less skewed error distributions for most spatial scales. However, through the lens of the novel error metric, neural networks are the more competitive choice, especially for forecast horizons that exceed 8 h. The study concludes with actionable recommendations to grid operators and highlights the need for the development of error metrics that link forecasting accuracy to operational costs. To promote transparency and open science, the datasets and Python code are open-sourced via a supplementary repository.

Houben, Nikolaus↗
DOE OSTI2021

Roles of miR-204 in retinal development and maintenance

Highlights: • miR-204 plays an important role in the development, maintenance, and diseases of the retina. • Various layers of the retina including RPE express miR-204. • Retinoblastoma, age-related macular degeneration, glaucoma and optic nerve injury are among the most common retinopathies caused by miR-204 dysfunction. • miR-204 target genes are involved in diverse signaling pathways crucial for retinal physiology. The retina is the innermost part of the eye of most vertebrates and it is essential for vision. The development, maintenance, and function of this laminated structure is tightly regulated by numerous genes. Deficiencies in the expression of these genes as well as deregulation of various molecular mechanisms can cause retinopathies and blindness. MicroRNAs (miRNAs) are one of the most important and effective molecular regulatory mechanisms that underlie the biology of the retina. miRNAs have specific functional roles in the development and maintenance of different retinal layers and retinal cell types. While previous studies have reported a large number of miRNAs linked to development, maintenance and diseases of the retina, no comprehensive study has properly discussed and integrated data from these studies. Given the particular importance of miR-204 in retinal biology, we intend to critically discuss the expression and functional significance of this miRNA in the development, maintenance, and pathologies of the retina. Moreover, we explore biological processes through which miR-204 influences retinal pathophysiology. This review highlights the crucial functions of miR-204 in the retina and suggests the putative mechanism of miR-204 action in retinal biology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Preventing leaching from lead water pipes with electrochemistry: an exploratory study

Toxic levels of lead leaching from ageing water distribution infrastructure affect over 5000 public drinking water systems in the US. Pipe replacement, the most effective solution to this problem, is prohibitively expensive. Additionally, chemical conditioning of drinking water using orthophosphates, although cost-effective, does not quickly stop lead leaching once it has started. We propose a novel approach to stop lead leaching: to rapidly form an insoluble scale within lead pipes using an external power supply. We report on the feasibility of this approach by first anodizing lead coupons and lead pipes reclaimed from a local water distribution using a phosphate electrolyte and different potentials, pH values, and phosphate concentrations. We subsequently exposed these anodized lead coupons and pipes to synthetic tap water to evaluate their lead leaching rates. We found that polarizing lead coupons in the presence of a 0.05 M phosphate solution decreased lead leaching by up to a 100-fold, relative to leaching from polished bare lead. Similarly, polarizing the reclaimed lead pipes (with a preexisting scale) decreased lead leaching from an average of 36 ppb to 7 ppb. These results were observed when applying potentials that favor Pb(IV) formation, which resulted in the buildup of PbO 2 and Pb 5 (PO 4 ) 3 OH in both lead coupons and pipes. Our findings indicate that this novel technology has the potential to rapidly decrease equilibrium lead levels in tap water below the EPA action limit of 15 ppb, and thus deserves further exploration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Viricidal and bactericidal exciplex barrier-discharge lamps

A brief review is presented of investigations performed in 2002 – 2020 on ultraviolet inactivation of bacteria, vital cells, and viruses by using excilamps. The excilamp models that have been developed at the Institute of High-Current Electronics, SB RAS are briefly described. Scientific data acquired by now show that excilamps on KrCl{sup *}, KrBr{sup *}, and XeBr{sup *} molecules are an alternative to low-pressure mercury lamps with respect to optical parameters. These sources of optical radiation exhibit a bactericidal effect, and emission of KrCl and KrBr excilamps demonstrates viricidal action. The latter is actual due to expansion of coronavirus disease. (paper)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

We need a solid scientific basis for nature-based climate solutions in the United States

Nature-based climate solutions (NbCS) have courted both enthusiastic support and considerable controversy. Defined as deliberate human actions that manipulate ecosystems to improve the planet’s greenhouse gas balance, NbCS provoke disagreement, in large part because their implementation has so far outpaced a science-based understanding of their long-term climate mitigation potential.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Removal of Institutional Controls at CERCLA Site ANL-01 Ditches A, B and C at the Materials and Fuels Complex

ANL-01 is a Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) site within Operable Unit (OU) 9-04 at the Materials and Fuels Complex (MFC). The ANL-01 site includes the Industrial Waste Pond and its associated ditches. Ditches A, B and C within ANL-01 were remediated in accordance with the Final Record of Decision for Argonne National Laboratory - West (DOE-CH 1998a). Due to the success of the selected and contingent remedies for the ditches and the determination that they are protective of human health and the environment, institutional controls (ICs) are no longer required and Idaho National Laboratory (INL) recommends termination of the ICs. In addition, the documentation requirements of the INL Site-wide Institutional Controls, and Operations and Maintenance Plan for CERCLA Response Actions (DOE-ID 2017) have been met to allow termination to occur.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Energy Equity and Environmental Justice Summit Report 2022

Pacific Northwest National Laboratory (PNNL) hosted a limited-engagement Energy Equity and Environmental Justice (EEEJ) Summit on September 28, 2022, with the Department of Energy (DOE) Office of Economic Impact and Diversity (DOE-ED) and DOE national laboratories: Argonne National Laboratory, Idaho National Laboratory, Lawrence Livermore National Laboratory, National Renewable Energy Laboratory, Oak Ridge National Laboratory, Sandia National Laboratories, and Savannah River National Laboratory. The goal of the Summit was for labs to highlight their capabilities in the EEEJ space and connect them to DOE-ED’s mission and goals as well as share lessons learned and best practices in our various programmatic spaces. The event commenced with an opening address from Director Shalanda Baker (DOE-ED), which included a call to action for the national labs. Three presentation panels followed, giving insights to the programs stewarded by national laboratories that are currently taking steps to enhance the way science is implemented through equity and justice lenses. A roundtable discussion concluded the Summit and highlighted lessons learned, gaps, challenges, opportunities, and future needs that will improve the impact and partnership of EEEJ work at DOE, national laboratories, at other agencies and institutions, and in other programmatic areas. Interest among participants to stay connected and coordinated and to partner on EEEJ work across labs was emphasized, including a suggestion to establish an intra-laboratory community of practice.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

State-space receptive fields of semicircular canal afferent neurons in the bullfrog

Receptive fields are commonly used to describe spatial characteristics of sensory neuron responses. They can be extended to characterize temporal or dynamical aspects by mapping neural responses in dynamical state spaces. The state-space receptive field of a neuron is the probability distribution of the dynamical state of the stimulus-generating system conditioned upon the occurrence of a spike. We have computed state-space receptive fields for semicircular canal afferent neurons in the bullfrog (Rana catesbeiana). We recorded spike times during broad-band Gaussian noise rotational velocity stimuli, computed the frequency distribution of head states at spike times, and normalized these to obtain conditional pdfs for the state. These state-space receptive fields quantify what the brain can deduce about the dynamical state of the head when a single spike arrives from the periphery. c2001 Elsevier Science B.V. All rights reserved.

Non-NASA Center↗
NASA NTRSDate not supplied

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗
NASA NTRS2020

Unknowability in Climate Science: Chaos, Structure, and Society

The limits to knowledge in climate forecasts arise from three mechanisms. One is inherent to the complex nonlinearity of the climate system, one is related to inherent imperfection of models in representing the real world, and one is a reflection on the coupling of our knowledge of potential future states and real-world actions that may be taken to avoid some subset of them. I refer to these limits as chaos, structure, and society. I provide background on how each adds to the unknowability of climate, and demonstrate that this unknowability is limited; not all aspects of past and future climates are unknowable.

Climate science↗
NASA NTRS2021

SMD Technology Highlights

Two technology highlights from the Science Mission Directorate (SMD) Planetary Science Division and Biological and Physical Sciences division are featured: a) The Dynamic Radioisotope Power Systems Project (DRPS) may enable lunar science payloads to survive and thrive during the harsh lunar night. New robust DRPS have been built and delivered by industry and are in the process of being tested at NASA’s Glenn Research Center. b) NASA's Plant Water Management (PWM) project is demonstrating that even without the help of gravity, hydroponic plant watering methods can enable plant habitats aboard crewed or robotic space missions. On Earth, plants draw water upwards through the roots against gravity, via capillary action, which orients the plant and enables display of its canopy (foliage and branches) for optimal photosynthesis and transpiration. The plant grows above the nutrient-rich soil as the water U.S. Astronaut Kate Rubins poses with PWM after nearly doubling the science returns of the ISS experiment by drawing on her wealth of wet lab operations and handling experience—on Earth and in space.

RPS↗
NASA NTRS2018

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗
NASA NTRSDate not supplied

Exploring our Changing Planet through NASA’s Earth Information Center and Novel Methods for Earth Science Communication

In June 2023, NASA unveiled the Earth Information Center (EIC), an interagency initiative which invites the global community to explore how our planet is changing through interactive installations, captivating visualizations, and novel storytelling. Existing in both physical and virtual space, the EIC serves as a gateway to actionable information collected through an expanding fleet of Earth observing satellites and sensors. The EIC features data driven visualizations, near real-time information, immersive experiences, and curated stories that highlight the applications of publicly available data to address environmental challenges across nine thematic areas: agriculture, biodiversity, disasters, greenhouse gases, air quality, sea level rise, sustainable energy, water resources, and wildfires. Designed by an interdisciplinary team, EIC exhibits are developed to reach a wide base of end-users across multiple learning modalities. During the first year of operation, the inaugural location of the EIC at NASA Headquarters in Washington, DC, welcomed an estimated 24,000 visitors, hosted over 145 tours for domestic and international organizations, supported NASA’s Earth Day 2024 programming, and led six STEM programs for diverse student communities. With lessons learned from the first year of being open to the public and a variety of novel science communication tools in development, the EIC is expanding the mission’s reach by collaborating with museums and visitor centers. Through these collaborations, we aim to inform a broader demographic about the unprecedented changes observed in Earth’s climate and inspire communities to learn more about their one and only home, planet Earth.

Nicole Ramberg-Pihl↗