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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Markov Process to Evaluate the Value Proposition of a Risk-Informed Predictive Maintenance Strategy

To achieve high-capacity factors, the nuclear fleet has relied on labor-intensive and time-consuming operation and preventive maintenance programs for plant systems. Manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, along with time-based replacement of assets irrespective of condition, have resulted in a costly, labor-centric business model. Fortunately, there are technologies that can eliminate unnecessary preventive maintenance activities by deploying risk-informed predictive maintenance, enabling the transition to a technology-centric business model. The technology-centric business model will enable plants to optimize and automate maintenance activities, leading to cost reductions since labor is a rising cost and technology is a declining cost. The implementation of scalable technologies and methodologies across plant systems and across the nuclear fleet is critical for successful deployment of a risk-informed predictive maintenance strategy at commercial nuclear power plants. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report describes the technical basis using the Markov Process to evaluate the value proposition for the risk-informed predictive maintenance strategy for the circulating water system. The plant process data from the Salem nuclear plant’s circulating water system is utilized to develop a Markov chain risk models and formulation to estimate the loss and gain in revenue based on plant availability. The outcomes presented in this report provides the technical basis for extensive quantitative evaluation of a scalable risk-informed predictive maintenance strategy as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Hybrid Modeling of a Circulating Water Pump Motor

To achieve high capacity factors, the nuclear fleet has relied on labor-intensive and time-consuming operation and preventive maintenance programs for plant systems. Manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, along with the time-based replacement of assets irrespective of condition, have resulted in a costly, labor-centric business model. Fortunately, there are technologies that can eliminate unnecessary preventive maintenance activities by deploying risk-informed predictive maintenance, enabling the transition to a technology-centric business model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Green microalga Chromochloris zofingiensis conserves substrate uptake pattern but changes their metabolic uses across trophic transition

The terrestrial green alga Chromochloris zofingiensis is an emerging model species with potential applications including production of triacylglycerol or astaxanthin. How C. zofingiensis interacts with the diverse substrates during trophic transitions is unknown. To characterize its substrate utilization and secretion dynamics, we cultivated the alga in a soil-based defined medium in transition between conditions with and without glucose supplementation. Then, we examined its exometabolite and endometabolite profiles. This analysis revealed that regardless of trophic modes, C. zofingiensis preferentially uptakes exogenous lysine, arginine, and purines, while secreting orotic acid. Here, we obtained metabolomic evidences that C. zofingiensis may use arginine for putrescine synthesis when in transition to heterotrophy, and for the TCA cycle during transition to photoautotrophy. We also report that glucose and fructose most effectively inhibited photosynthesis among thirteen different sugars. The utilized or secreted metabolites identified in this study provide important information to improve C. zofingiensis cultivation, and to expand its potential industrial and pharmaceutical applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Is there warming in the pipeline? A multi-model analysis of the Zero Emissions Commitment from CO 2

Abstract. The Zero Emissions Commitment (ZEC) is the change in global mean temperature expected to occur following the cessation of net CO 2 emissions and as such is a critical parameter for calculating the remaining carbon budget. The Zero Emissions Commitment Model Intercomparison Project (ZECMIP) was established to gain a better understanding of the potential magnitude and sign of ZEC, in addition to the processes that underlie this metric. A total of 18 Earth system models of both full and intermediate complexity participated in ZECMIP. All models conducted an experiment where atmospheric CO 2 concentration increases exponentially until 1000 PgC has been emitted. Thereafter emissions are set to zero and models are configured to allow free evolution of atmospheric CO 2 concentration. Many models conducted additional second-priority simulations with different cumulative emission totals and an alternative idealized emissions pathway with a gradual transition to zero emissions. The inter-model range of ZEC 50 years after emissions cease for the 1000 PgC experiment is -0.36 to 0.29°C, with a model ensemble mean of -0.07 °C, median of -0.05°C, and standard deviation of 0.19°C. Models exhibit a wide variety of behaviours after emissions cease, with some models continuing to warm for decades to millennia and others cooling substantially. Analysis shows that both the carbon uptake by the ocean and the terrestrial biosphere are important for counteracting the warming effect from the reduction in ocean heat uptake in the decades after emissions cease. This warming effect is difficult to constrain due to high uncertainty in the efficacy of ocean heat uptake. Overall, the most likely value of ZEC on multi-decadal timescales is close to zero, consistent with previous model experiments and simple theory.

MacDougall, Andrew H.↗
NASA NTRS2001

A Model for Estimating the Numbers of Stars for Which Terrestrial Planets Can Be Detected

Borucki and Summers (1984) have suggested that extrasolar terrestrial planets can be detected by looking for transits. A discussion is presented of a model used to estimate the number of stars for which planets can be detected as a function of spectral type and luminosity, stellar brightness, planet size and realistic noise sources that must be considered. A choice for an optimum location of the field to search is described given the realistic constraints of a space mission and the desire to maximize the number of available stars.

Koch, David↗
NASA NTRS2011

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice.

Case, Jonathan L.↗
NASA NTRS2012

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS). In last year's NWA abstract on this topic, the suite of SPoRT products supported in the STRC EMS was presented, which includes a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This abstract and companion presentation describes recent upgrades made to the SST and GVF composites, as well as the real-time LIS runs. The Great Lakes sea-ice product is unchanged from 2011. The SPoRT SST composite product has been expanded geographically and as a result, the resolution has been coarsened from 1 km to 2 km to accommodate the larger domain. The expanded domain covers much of the northern hemisphere from eastern Asia to western Europe (0 N to 80 N latitude and 150 E to 10 E longitude). In addition, the NESDIS POES-GOES product was added to fill in gaps caused by the Moderate Resolution Imaging Spectroradiometer (MODIS) being unable to sense in cloudy regions, replacing the recently-lost Advanced Microwave Scanning Radiometer for EOS with negligible change to product fidelity. The SST product now runs twice per day for Terra and Aqua combined data collections from 0000 to 1200 UTC and from 1200 to 0000 UTC, with valid analysis times at 0600 and 1800 UTC. The twice-daily compositing technique reduces the overall latency of the previous version while still representing the diurnal cycle characteristics. The SST composites are available at approximately four hours after the end of each collection period (i.e. 1600 UTC for the nighttime analysis and 0400 UTC for the daytime analysis). The real-time MODIS GVF composite has only received minor updates in the past year. The domain was expanded slightly to extend further west, north, and east to improve coverage over parts of southern Canada. Minor adjustments were also made to the manner in which GVF is calculated from the distribution of maximum Normalized Difference Vegetation Index from MODIS. The presentation will highlight some examples of the substantial inter-annual change in GVF that occurred from 2010 to 2011 in the U.S. Southern Plains as a result of the summer 2011 drought, and the early vegetation green up across the eastern U.S. due to the very warm conditions in March 2012. Finally, the SPoRT LIS runs the operational Noah land surface model (LSM) in real time over much of the eastern half of the CONUS. The Noah LSM is continually cycled in real time, uncoupled to any model, and driven by operational atmospheric analyses over a long-term, multi-year integration. The LIS-Noah provides the STRC EMS with high-resolution (3 km) LSM initialization data that are in equilibrium with the operational analysis forcing. The Noah LSM within the SPoRT LIS has been upgraded from version 2.7.1 to version 3.2, which has improved look-up table attributes for several land surface quantities. The surface albedo field is now being adjusted based on the input real-time MODIS GVF, thereby improving the net radiation. Also, the LIS-Noah now uses the newer MODIS-based land use classification scheme (i.e. the International Biosphere-Geosphere Programme [IGBP]) that has a better depiction of urban corridors in areas where urban sprawl has occurred. STRC EMS users interested in initializing their LSM fields with high-resolution SPoRT LIS data should set up their model domain with the MODIS-IGBP 20-class land use database and select Noah as the LSM.

Case, Jonathan L.↗
NASA NTRS2012

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its NOAA/National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center Environmental Modeling System (EMS). The suite of SPoRT products for use in the EMS consists of a Sea Surface Temperature (SST) composite that includes a Lake Surface Temperature (LST) analysis over the Great Lakes, a Great Lakes sea-ice extent within the SST composite, a real-time Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This paper and companion poster describe each dataset and provide recent upgrades made to the SST, Great Lakes LST, GVF composites, and the real-time LIS runs.

Case, Jonathan L.↗
NASA NTRS2006

21st Century Lunar Exploration: Advanced Radiation Exposure Assessment

On January 14, 2004 President George W Bush outlined a new vision for NASA that has humans venturing back to the moon by 2020. With this ambitious goal, new tools and models have been developed to help define and predict the amount of space radiation astronauts will be exposed to during transit and habitation on the moon. A representative scenario is used that includes a trajectory from LEO to a Lunar Base, and simplified CAD models for the transit and habitat structures. For this study galactic cosmic rays, solar proton events, and trapped electron and proton environments are simulated using new dynamic environment models to generate energetic electron, and light and heavy ion fluences. Detailed calculations are presented to assess the human exposure for transit segments and surface stays.

Anderson, Brooke↗
DOE OSTI2020

Dynamics of Gas Bubbles From a Submarine Hydrocarbon Seep Within the Hydrate Stability Zone

We validate a new model for mass transfer and bubble transport for natural seeps on the continental margins using an integrated observation of a seep at 883 m in the Northern Gulf of Mexico. In the model, mass transfer is assumed to transition from clean to dirty bubble mass transfer rates following a characteristic hydrate formation time that depends on the initial bubble surface area and the hydrate subcooling. We show that buoyancy-induced upwelling is negligible for the bubble stream. We initialize the model using precise data observed at the seafloor and validate the model results to optical and acoustic measurements within the bubble stream. The model accurately predicts the acoustic attenuation of the bubble flare by lateral spreading and bubble shrinkage throughout the water column. In conclusion, the model shows that up to 99.4% by mass of the released gases from this seep dissolves into the ocean within the hydrate stability zone.

03 NATURAL GAS↗
DOE OSTI2024

Machine learning for the identification of phase transitions in interacting agent-based systems: A Desai-Zwanzig example

Deriving closed-form analytical expressions for reduced-order models, and judiciously choosing the closures leading to them, has long been the strategy of choice for studying phase- and noise-induced transitions for agent-based models (ABMs). In this paper, we propose a data-driven framework that pinpoints phase transitions for an ABM—the Desai-Zwanzig model—in its mean-field limit, using a smaller number of variables than traditional closed-form models. To this end, we use the manifold learning algorithm Diffusion Maps to identify a parsimonious set of data-driven latent variables, and we show that they are in one-to-one correspondence with the expected theoretical order parameter of the ABM. We then utilize a deep learning framework to obtain a conformal reparametrization of the data-driven coordinates that facilitates, in our example, the identification of a single parameter-dependent ordinary differential equation (ODE) in these coordinates. Additionally, we identify this ODE through a residual neural network inspired by a numerical integration scheme (forward Euler). We then use the identified ODE—enabled through an odd symmetry transformation—to construct the bifurcation diagram exhibiting the phase transition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Towards a robust out-of-the-box neural network model for genomic data

The accurate prediction of biological features from genomic data is paramount for precision medicine and sustainable agriculture. For decades, neural network models have been widely popular in fields like computer vision, astrophysics and targeted marketing given their prediction accuracy and their robust performance under big data settings. Yet neural network models have not made a successful transition into the medical and biological world due to the ubiquitous characteristics of biological data such as modest sample sizes, sparsity, and extreme heterogeneity. Here, we investigate the robustness, generalization potential and prediction accuracy of widely used convolutional neural network and natural language processing models with a variety of heterogeneous genomic datasets. Mainly, recurrent neural network models outperform convolutional neural network models in terms of prediction accuracy, overfitting and transferability across the datasets under study. While the perspective of a robust out-of-the-box neural network model is out of reach, we identify certain model characteristics that translate well across datasets and could serve as a baseline model for translational researchers.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

Studies of the effects of curvature on dilution jet mixing

An analytical program was conducted using both three-dimensional numerical and empirical models to investigate the effects of transition liner curvature on the mixing of jets injected into a confined crossflow. The numerical code is of the TEACH type with hybrid numerics; it uses the power-law and SIMPLER algorithms, an orthogonal curvilinear coordinate system, and an algebraic Reynolds stress turbulence model. From the results of the numerical calculations, an existing empirical model for the temperature field downstream of single and multiple rows of jets injected into a straight rectangular duct was extended to model the effects of curvature. Temperature distributions, calculated with both the numerical and empirical models, are presented to show the effects of radius of curvature and inner and outer wall injection for single and opposed rows of cool dilution jets injected into a hot mainstream flow.

Holdeman, James D.↗
NASA NTRS1988

A physical model for earthquakes. I - Fluctuations and interactions. II - Application to southern California

The idea that earthquakes represent a fluctuation about the long-term motion of plates is expressed mathematically through the fluctuation hypothesis, under which all physical quantities which pertain to the occurance of earthquakes are required to depend on the difference between the present state of slip on the fault and its long-term average. It is shown that under certain circumstances the model fault dynamics undergo a sudden transition from a spatially ordered, temporally disordered state to a spatially disordered, temporally ordered state, and that the latter stages are stable for long intervals of time. For long enough faults, the dynamics are evidently chaotic. The methods developed are then used to construct a detailed model for earthquake dynamics in southern California. The result is a set of slip-time histories for all the major faults, which are similar to data obtained by geological trenching studies. Although there is an element of periodicity to the events, the patterns shift, change and evolve with time. Time scales for pattern evolution seem to be of the order of a thousand years for average recurring intervals of about a hundred years.

Rundle, John B.↗
NASA NTRS2021

Multi-Physics Based Thermo-Well Fatigue Design Tool

In this study, mathematical-based models for fatigue life were developed for Resistance Temperature Detectors (RTDs)/thermo-wells in high-pressure, cryogenic flow environments. A literature review that identified bench-scale stainless steel fatigue data at cryogenic temperatures that can be used to validate fatigue life mathematical models was pursued. Developing the ability to predict the fatigue life of RTDs/thermo-wells in high-pressure, cryogenic flow environments, especially liquid oxygen (LOX), will lead to a lower incidence of RTD damage and failure during propulsion test activities. During this performance period, the project was transitioned to a computational RTD/thermos-well fatigue modeling effort rather than the previously proposed experimental fatigue testing in FY19 since the computational modeling approach will provide a better fundamental understanding of fatigue behavior at cryogenic temperatures prior to pursuing potentially costly experimental tests. Due to COVID-19 issues impairing access to some needed university partnerships, tools and lab facilities, FY20efforts are continuing into FY21 and will be reported upon in greater detail in the FY21 report

Harry Ryan↗
NASA NTRSDate not supplied

Architectures of Exoplanetary Systems: Towards a Multi-planet Model for Reproducing the Planet Radius Valley and Intra-system Size Similarity

Multi-planet systems provide crucial insights into the architectures and correlations within planetary systems, which in turn offer clues into their formation and evolution histories. Through the thousands of exoplanet candidates that it discovered, NASA's Kepler mission revealed that systems with multiple transiting planets are common. We describe a new model for inferring the exoplanet population observed by Kepler, which combines a semi-parametric description of planetary systems with a prescription for envelope mass-loss due to photoevaporation. This new model is a"hybrid" of the maximum AMD (angular momentum deficit) model in which the orbital excitations of the planets are drawn by distributing the system's critical AMD (He et al. 2020), and a photoevaporation model for sculpting the observed radius valley (Neil & Rogers 2020). This is an update to the SysSim suite of exoplanet population models derived from forward modeling the Kepler detection pipeline. The hybrid model is constrained by the observed statistics of multi-transiting systems, including additional constraints from the distribution of planet radii and their intra-system size patterns. This model is capable of producing a planet radius valley as well as a preference for planet size similarity. However, we find that the Kepler catalog exhibits features that are even more significant (i.e., it has a deeper observed radius valley and stronger size similarity) than the best-fit model. We use this model to infer the intrinsic planet radius valley as well as the distribution of primordial planet masses and core masses.

kepler↗
NASA NTRS1990

Analysis and design of a high power, digitally-controlled spacecraft power system

The progress to date on the analysis and design of a high power, digitally controlled spacecraft power system is described. Several battery discharger topologies were compared for use in the space platform application. Updated information has been provided on the battery voltage specification. Initially it was thought to be in the 30 to 40 V range. It is now specified to be 53 V to 84 V. This eliminated the tapped-boost and the current-fed auto-transformer converters from consideration. After consultations with NASA, it was decided to trade-off the following topologies: (1) boost converter; (2) multi-module, multi-phase boost converter; and (3) voltage-fed push-pull with auto-transformer. A non-linear design optimization software tool was employed to facilitate an objective comparison. Non-linear design optimization insures that the best design of each topology is compared. The results indicate that a four-module, boost converter with each module operating 90 degrees out of phase is the optimum converter for the space platform. Large-signal and small-signal models were generated for the shunt, charger, discharger, battery, and the mode controller. The models were first tested individually according to the space platform power system specifications supplied by NASA. The effect of battery voltage imbalance on parallel dischargers was investigated with respect to dc and small-signal responses. Similarly, the effects of paralleling dischargers and chargers were also investigated. A solar array and shunt model was included in these simulations. A model for the bus mode controller (power control unit) was also developed to interface the Orbital replacement Unit (ORU) model to the platform power system. Small signal models were used to generate the bus impedance plots in the various operating modes. The large signal models were integrated into a system model, and time domain simulations were performed to verify bus regulation during mode transitions. Some changes have subsequently been incorporated into the models. The changes include the use of a four module boost discharger, and a new model for the mode controller, which includes the effects of saturation. The new simulations for the boost discharger show the improvement in bus ripple that can be achieved by phase-shifted operation of each of the boost modules.

Lee, F. C.↗
NASA NTRS2004

Advanced Diagnostic System on Earth Observing One

In this infusion experiment, the Livingstone 2 (L2) model-based diagnosis engine, developed by the Computational Sciences division at NASA Ames Research Center, has been uploaded to the Earth Observing One (EO-1) satellite. L2 is integrated with the Autonomous Sciencecraft Experiment (ASE) which provides an on-board planning capability and a software bridge to the spacecraft's 1773 data bus. Using a model of the spacecraft subsystems, L2 predicts nominal state transitions initiated by control commands, monitors the spacecraft sensors, and, in the case of failure, isolates the fault based on the discrepant observations. Fault detection and isolation is done by determining a set of component modes, including most likely failures, which satisfy the current observations. All mode transitions and diagnoses are telemetered to the ground for analysis. The initial L2 model is scoped to EO-1's imaging instruments and solid state recorder. Diagnostic scenarios for EO-1's nominal imaging timeline are demonstrated by injecting simulated faults on-board the spacecraft. The solid state recorder stores the science images and also hosts: the experiment software. The main objective of the experiment is to mature the L2 technology to Technology Readiness Level (TRL) 7. Experiment results are presented, as well as a discussion of the challenging technical issues encountered. Future extensions may explore coordination with the planner, and model-based ground operations.

Hayden, Sandra C.↗