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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Biomass production chamber air analysis of wheat study (BWT931)

NASA's Controlled Ecological Life Support System (CELSS) biomass production chamber at John F. Kennedy Space Center provides a test bed for bioregenerative studies using plants to provide food, oxygen, carbon dioxide removal, and potable water to humans during long term space travel. Growing plants in enclosed environments has brought about concerns regarding the level of volatile organic compounds (VOC's) emitted from plants and the construction materials that make up the plant growth chambers. In such closed systems, the potential exists for some VOC's to reach toxic levels and lead to poor plant growth, plant death, or health problems for human inhabitants. This study characterized the air in an enclosed environment in which wheat cv. Yocora Rojo was grown. Ninty-four whole air samples were analyzed by gas chromatography/mass spectrometry throughout the eighty-four day planting. VOC emissions from plants and materials were characterized and quantified.

Batten, J. H.↗
NASA NTRS2004

Multispectral Scanner for Monitoring Plants

A multispectral scanner has been adapted to capture spectral images of living plants under various types of illumination for purposes of monitoring the health of, or monitoring the transfer of genes into, the plants. In a health-monitoring application, the plants are illuminated with full-spectrum visible and near infrared light and the scanner is used to acquire a reflected-light spectral signature known to be indicative of the health of the plants. In a gene-transfer- monitoring application, the plants are illuminated with blue or ultraviolet light and the scanner is used to capture fluorescence images from a green fluorescent protein (GFP) that is expressed as result of the gene transfer. The choice of wavelength of the illumination and the wavelength of the fluorescence to be monitored depends on the specific GFP.

Gat, Nahum↗
NASA NTRS2004

Fluid Flow Technology that Measures Up

From 1994 to 1996, NASA s Marshall Space Flight Center conducted a Center Director's Discretionary Fund research effort to apply artificial intelligence technologies to the health management of plant equipment and space propulsion systems. Through this effort, NASA established a business relationship with Quality Monitoring and Control (QMC), of Kingwood, Texas, to provide hardware modeling and artificial intelligence tools. Very detailed and accurate Space Shuttle Main Engine (SSME) analysis and algorithms were jointly created, which identified several missing, critical instrumentation needs for adequately evaluating the engine health status. One of the missing instruments was a liquid oxygen (LOX) flow measurement. This instrument was missing since the original SSME included a LOX turbine flow meter that failed during a ground test, resulting in considerable damage for NASA. New balanced flow meter technology addresses this need with robust, safe, and accurate flow metering hardware.

Source record↗
DOE OSTI2021

Performance Results for Sensor Assignment Problem as Solved on a Multi-Node Cluster

An earlier report described a procedure for optimal sensor set selection and its implementation on a computational cluster. This new and innovative capability was developed to facilitate a reduction in operations staffing levels to improve plant economics. By automating surveillance and maintenance tasks through early detection of degrading sensors and equipment, staff can be more efficiently deployed. The method uses automated reasoning and domain knowledge in the form of the conservation equations to infer from plant measurements the state of equipment health. Inclusion of domain knowledge addresses the problem that exists with pure data-driven methods that there are no rigorous guidelines for determining what constitutes an adequate sensor set. Formalizing the procedure for sensor set selection as we have done results in a more reliable and explainable diagnosis of plant equipment health. Importantly, from the standpoint of the plant owner, personnel are provided with an early and explicit diagnosis of an equipment problem. That in principle automates the process and eliminates having to send personnel into the plant to find the cause as typically occurs when a data-driven method detects an anomaly. In this report we describe first results obtained using a computational cluster to solve the sensor set selection problem as framed above. The case described addresses the problem of equipment health monitoring in the high-pressure (HP) feedwater system of a pressurized light water reactor as seen through the eyes of our collaborating utility partner. Maintenance of this system can amount to millions of dollars per year if equipment health issues go undiagnosed and lead to loss of function. On examining the potential that is inherent in the installed sensor set for diagnosing equipment health degradation, it was found that greater fault resolution capability can be achieved using a sensor set that is 20 percent fewer in number. The take-away is that compared to the installed sensor set there exists a more strategic assignment of sensors that will furnish better health monitoring capability and with fewer sensors. Where the problem defies solution by manual inspection, as is the case here, one can be found by an algorithm. The solution was obtained in four hours using 30 computational cores. The HP feedwater problem as posed above illustrates the added value of approaching the sensor selection problem as one amenable to algorithmic solution. This problem is of interest to advanced reactor designers and to utilities that are setting up remote monitoring and diagnostic centers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

EcoBOT: an AI/ML enabled automated phenotyping capability for model plants

Introduction: Advances in automation and AI/ML offer new opportunities for plant science, including design, modeling, and analysis. This study aimed to develop an automated platform for researching small model plants under axenic conditions and integrate it with AI/ML tools. Methods: The EcoBOT platform was developed, which consists of sterile containers (EcoFABs) for growing plants and imaging for monitoring plant growth and health. Brachypodium distachyon was grown on the EcoBOT, and its response to nutrient limitation and copper stress was evaluated. Results: The results showed that Brachypodium distachyon grown in the EcoBOT maintained sterility and responded to nutrient limitation and copper stress. Analysis of over 6,500 root and shoot images revealed varying sensitivity and response rates to copper. Bayesian Optimization was used to improve model accuracies relating copper concentrations to plant biomass via sequential experiments, resulting in a >30% improvement. Discussion: The findings of this study demonstrate the potential of the EcoBOT platform for researching plant responses to environmental factors. Future experiments could focus on relating other chemical stresses and microbial interactions to create generalized models of plant responses.

AI image analysis↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1996

Characterizing photosynthesis and transpiration of plant communities in controlled environments

CO2 and water vapor fluxes of hydroponically grown wheat and soybean canopies were measured continuously in several environments with an open gas exchange system. Canopy CO2 fluxes reflect the photosynthetic efficiency of a plant community, and provide a record of plant growth and health. There were significant diurnal fluctuations in root and shoot CO2 fluxes, and in shoot water vapor fluxes. Canopy stomatal conductance (Gc) to water vapor was calculated from simultaneous measurements of canopy temperature (Tcan) and transpiration rates (Tr). Tr in the dark was substantial, and there were large diurnal fluctuations in both Gc and Tr. Canopy net Photosynthesis (Pnet), Tr, and Gc increased with increasing net radiation. Gc increased with Tr, suggesting that the stomata of plants in controlled environments (CEs) behave differently from field-grown plants. A transpiration model based on measurements of Gc was developed for CEs. The model accurately predicted Tr from a soybean canopy.

NASA Discipline Life Support Systems↗
DOE OSTI2022

Biotic predictors improve species distribution models for invasive plants in Western U.S. Forests at high but not low spatial resolutions

Invasions by non-native plants threaten forest health and sustainability. The ability to predict areas at greatest risk to invasion is essential for informing both monitoring and management of invasive species. Species distribution models (SDMs) are often used to identify environmental correlates of a species’ occurrence and predict geographic areas that may be suitable for its presence and are commonly constructed using solely abiotic predictors. However, mounting evidence implies that not including biotic predictors in SDMs may yield less accurate models at some resolutions typical of landscape-scale models, although this possibility has rarely been evaluated in invasive plants. In this study, we determined whether including descriptors of the biotic environment improved the accuracy of SDMs built at five decreasing spatial resolutions for infestations of five common invasive plants in forests of California, Oregon, and Washington, USA and described environmental correlates of each species’ presence. Predictors of occurrence often echoed those identified in previous studies of the focal species, indicating that our models accurately identified important environmental drivers of occurrence. Including biotic predictors in the SDMs consistently improved model accuracy only at the highest resolution we examined, which may be due to the spatial scale at which biotic interactions primarily act to constrain species’ distributions, the particular biotic predictors we used in our models, or correlations between attributes of the abiotic and biotic environment. This finding suggests that, while the practice of building SDMs using abiotic predictors alone may generally yield models whose accuracy does not differ substantially from those that also include biotic predictors, the effects of biotic interactions on the distribution of invasive plants in forests may be detectable at larger scales than previously thought.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Homoeolog expression divergence contributes to time of day changes in transcriptomic and glucosinolate responses to prolonged water limitation in Brassica napus

SUMMARY Water availability is a major determinant of crop production, and rising temperatures from climate change are leading to more extreme droughts. To combat the effects of climate change on crop yields, we need to develop varieties that are more tolerant to water‐limited conditions. We aimed to determine how diverse crop types (winter/spring oilseed, tuberous, and leafy) of the allopolyploid Brassica napus , a species that contains the economically important rapeseed oilseed crop, respond to prolonged water limitation. We exposed plants to an 80% reduction in water and assessed growth and color on a high‐throughput phenotyping system over 4 weeks and ended the experiment with tissue collection for a time course transcriptomic study. We found an overall reduction in growth across cultivars but to varying degrees. Diel transcriptome analyses revealed significant accession‐specific changes in time‐of‐day regulation of photosynthesis, carbohydrate metabolism, and sulfur metabolism. Interestingly, there was extensive variation in which homoeologs from the two parental subgenomes responded to water limitation across crop types that could be due to differences in regulatory regions in these allopolyploid lines. Follow‐up experiments on select cultivars confirmed that plants maintained photosynthetic health during the prolonged water limitation while slowing growth. In two cultivars examined, we found significant time of day changes in levels of glucosinolates, sulfur‐ and nitrogen ‐rich specialized metabolites, consistent with the diel transcriptomic responses. These results suggest that these lines are adjusting their sulfur and nitrogen stores under water‐limited conditions through distinct time of day regulation.

Ricono, Angela [University of Minnesota St. Paul M↗
DOE OSTI2025

Time-series RNA metabarcoding of the active Populus tremuloides root microbiome reveals hidden temporal dynamics and dormant core members

The rhizosphere is a critical interface between plant roots and soil, harboring diverse microbial communities that are essential to plant and ecosystem health. Although these communities exhibit stark temporal dynamics, their dormancy/activity transitions remain poorly understood. Such transitions may enable microbes to rapidly adjust functional contributions faster than community turnover alone would allow. Here, we used RNA metabarcoding to characterize the active fraction of microbial communities on the roots of quaking aspen (Populus tremuloides) in a time-series study across a natural environmental gradient. We explore cryptic temporal microbial community dynamics of rhizosphere communities at the ecosystem scale. The active rhizosphere bacterial and fungal communities were more temporally dynamic than total communities, while total communities exhibited a stronger response to site-specific conditions. Notably, some core microbiome members were often inactive, yielding a smaller “active core” subset. The fungal endophyte Hyaloscypha finlandica was the only microbe that was both present and active in all plots across all timepoints. Soil temperature strongly influenced both total and active community composition, with the fungal class Eurotiomycetes showing a temperature-dependent seasonal decline in abundance. Together, these results reveal that modulation of microbial activity levels is a key mechanism by which the plant root holobiont responds to environmental variation, and that even dominant symbionts may frequently persist in dormancy within the rhizosphere.

Community Structure and Diversity↗
DOE OSTI2022

Ecosystem consequences of introducing plant growth promoting rhizobacteria to managed systems and potential legacy effects

The rapidly growing industry of crop biostimulants leverages the application of plant growth promoting rhizobacteria (PGPR) to promote plant growth and health. However, introducing nonnative rhizobacteria may impact other aspects of ecosystem functioning and have legacy effects; these potential consequences are largely unexplored. Nontarget consequences of PGPR may include changes in resident microbiomes, nutrient cycling, pollinator services, functioning of other herbivores, disease suppression, and organic matter persistence. Importantly, we lack knowledge of whether these ecosystem effects may manifest in adjacent ecosystems. The introduced PGPR can leave a functional legacy whether they persist in the community or not. Legacy effects include shifts in resident microbiomes and their temporal dynamics, horizontal transfer of genes from the PGPR to resident taxa, and changes in resident functional groups and interaction networks. Ecosystem functions may be affected by legacies PGPR leave following niche construction, such as when PGPR alter soil pH that in turn alters biogeochemical cycling rates. Here, we highlight new research directions to elucidate how introduced PGPR impact resident microbiomes and ecosystem functions and their capacity for legacy effects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

From glomalin to glomalose: unraveling the molecular identity of the MAb32B11 antigen

Glomalin, a substance produced by arbuscular mycorrhizal (AM) fungi, haswell-documented benefits for plant and soil health, including water retention and soil aggre-gation. Glomalin quantification has been performed by enzyme-linked immunosorbent assay(ELISA) using a monoclonal antibody, MAb32B11, that has been described as targeting a heatshock protein 60 (RiHSP60). In this study, we re-examined the molecular nature of the antigen recognized byMAb32B11. MAb32B11 did not cross-react with the RiHSP60 polypeptide. Glomalin extracts of Rhizo-phagus irregularis showed strong and dose-dependent cross-reactivity with MAb32B11 evenwhen protein levels were undetectable, raising doubts about the proteinaceous nature of theantigen. Protease treatments of glomalin extracts did not affect the ELISA signal. However,treatment with periodate, which degrades polysaccharides, significantly reduced the signal. Astrong correlation between carbohydrate content and the ELISA signal was observed in glo-malin extracts. These findings indicate that MAb32B11 recognizes a carbohydrate, likely originating fromcell walls of AM fungi. Further analysis of glomalin extracts using size exclusion chromatogra-phy suggests that the epitope of MAb32B11 is a complex carbohydrate in the size range of511–600 kDa. Understanding the true nature of glomalin will enhance our ability to quantifyit accurately and leverage its agricultural benefits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Saprotrophic Fungus Induces Microscale Mineral Weathering to Source Potassium in a Carbon-Limited Environment

Plants rely on potassium for many critical biological processes, but most soils are potassium limited. Moving potassium from the inaccessible, mineral-bound pool to a more bioavailable form is crucial for sustainably increasing local potassium concentrations for plant growth and health. Here, we use a synthetic soil habitat (mineral doped micromodels) to study and directly visualize how the saprotrophic fungus, Fusarium sp. DS 682, weathers K-rich soil minerals. After 30 days of fungal growth, both montmorillonite and illite (secondary clays) had formed as surface coatings on primary K-feldspar, biotite, and kaolinite grains. The distribution of montmorillonite differed depending on the proximity to a carbon source, where montmorillonite was found to be associated with K-feldspar closer to the carbon (C) source, which the fungus was inoculated on, but associated with biotite at greater distances from the C source. The distribution of secondary clays is likely due to a change in the type of fungal exuded organic acids; from citric to tartaric acid dominated production with increasing distance from the C source. Thus, the main control on the ability of Fusarium sp. DS 682 to weather K-feldspar is proximity to a C source to produce citric acid via the TCA cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ultra-Wideband Microwave Imaging System for Root Phenotyping

The roots are a vital organ for plant growth and health. The opaque surrounding environment of the roots and the complicated growth process means that in situ and non-destructive root phenotyping face great challenges, which thus spur great research interests. The existing methods for root phenotyping are either unable to provide high-precision and high accuracy in situ detection, or they change the surrounding root environment and are destructive to root growth and health. Thus,we propose and develop an ultra-wideband microwave scanning method that uses time reversal to achieve in situ root phenotyping nondestructively. To verify the method’s feasibility, we studied an electromagnetic numerical model that simulates the transmission signal of two ultra-wideband microwave antennas. The simulated signal of roots with different shapes shows the proposed system’s capability to measure the root size in the soil. Experimental validations were conducted considering three sets of measurements with different sizes, numbers and locations, and the experimental results indicate that the developed imaging system was able to differentiate root sizes and numbers with high contrast. The reconstruction from both simulations and experimental measurements provided accurate size estimation of the carrots in the soil, which indicates the system’s potential for root imaging.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Hogan, Christine A.↗
NASA NTRS1998

Fiber-Optic Coupled Lidar Receiver System to Measure Stratospheric Ozone

The measurement of ozone in the atmosphere has become increasingly important over the past two decades. Significant increases of ozone concentrations in the lower atmosphere, or troposphere, and decreases in the upper atmosphere, or stratosphere, have been attributed to man-made causes. High ozone concentrations in the troposphere pose a health hazard to plants and animals and can add to global warming. On the other hand, ozone in the stratosphere serves as a protective barrier against strong ultraviolet (UV) radiation from the sun. Man-made CFC's (chlorofluorocarbons) act as a catalyst with a free oxygen atom and an ozone molecule to produce two oxygen molecules therefore depleting the protective layer of ozone in the stratosphere. The beneficial and harmful effects of ozone require the study of ozone creation and destruction processes in the atmosphere. Therefore, to provide an accurate model of these processes, an ozone lidar system must be able to be used frequently with as large a measurement range as possible. Various methods can be used to measure atmospheric ozone concentrations. These include different airborne and balloon measurements, solar occulation satellite techniques, and the use of lasers in lidar (high detection and ranging,) systems to probe the atmosphere. Typical devices such as weather balloons can only measure within the direct vicinity of the instrument and are therefore used infrequently. Satellites use solar occulation techniques that yield low horizontal and vertical resolution column densities of ozone.

Harper, David Brent↗
NASA NTRS2001

Oleoresin, Chemistry and Spectral Reflectance in "Stressed" Lodgepole and White Bark Pine, Mammoth Mountain, California

Development of methods to identify the physical and chemical character of materials on the earth's surface is one of the foci of hyperspectral remote sensing activities. Enhancing the ability to elucidate changes in foliar chemistry that relate to the health of a plant is a benefit to plant physiologists, foresters, and plant ecologists, as well as geologist and environmental scientists. Vegetation covers the landscape throughout the temperate and tropical regions of the earth. The existence of vegetation in these areas presents special problems to remote sensing systems since geologic bedrock and alteration zones are masked. At times, however, alterations in the soil/sediment geochemical environment result in foliar chemical changes that are detectable via remote sensing. Examples include monitoring of chlorophyll reflectance/fluorescence and equivalent water thickness indices as indicators of drought-induced plant stress. Another processing and interpretation approach used with hyperspectral data has been principal components analysis (PCA). Rowan et al. used PCA to identify absorption feature patterns obtained from vegetated areas with discrete bedrock geology or mineralization as the substrate. Many researchers highlight the need to advance our ability for hyperspectral imaging in vegetated areas as a near-term priority.

Hickey, James C.↗