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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

On the flow induced vibration of an externally excited nuclear reactor experiment

An in-pile, drop-in experiment design is presently being designed and studied for the near-term deployment within the Advanced Test Reactor (ATR) located at the Idaho National Laboratory (INL); this experiment is termed the Miniplate-1 Large-B (MP-1 LB) Experiment. A number of explicit studies are performed during the design- and safety-related stage. Traditionally, a clear and logical methodology has been developed and utilized for analyses such as hydraulics, thermal-loads, mechanical loads, and others for these experiments. Recently a small component from a different experiment assembly mechanically separated while in the reactor’s core. While this experiment didn’t compromise the safety of the reactor, it led to a higher-level question which centered on whether the appropriate level of consideration was being made toward the fluid–structure-interactions of these experiments. The outcome yielded separate flow test experiments of like-for-like geometry in an experimental loop located at Oregon State University which produces experimental data compliant with applicable parts and requirements to ASME’s NQA-1 2008, 2009a standard – suitable for benchmark evaluation. Here, the objectives of this study are to (1) develop a process for handling and interpreting the mechanical response of the test elements during hydraulic testing, to (2) characterize the motion of a specific test element during a flow test which imposes a wide range of hydraulic conditions, and (3) provide objective observations toward the potential safety related implications that are tied to the synthesized data. The outcome of this study has led to a confident process in inspecting the experimental data, synthesized it for interpretation, identified several unique hydraulic characteristics of the experiment design which were previously unknown, and demonstrated that the likelihood for mechanical failure resulting from fluid-structure-interactions in the reactor is far below any criterion for concern of the element’s safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Thermal hydraulic analysis of the AFIP-7 irradiation test in the Advanced test Reactor – Model correlation and performance evaluation

We report as a system level code, RELAP5 is widely used in the nuclear field for the reactor hydraulic analysis. In the component/experimental level, it is frequently employed as well. This paper demonstrates that the RELAP5 flow simulation of the AFIP-7 irradiation experiment which has a complicated 3D geometry/flow path deviates by ~28% from the flow evaluation through a computational fluid dynamics (CFD) simulation, which has been validated against a flow test performed at Oregon State University. Thermal safety compliance analysis of an experiment planned to be irradiated in the Advanced Test Reactor is usually performed using the finite element analysis code, Abaqus. This research reveals the disadvantages of the Abaqus simulation in the flow instability and departure from nucleate boiling evaluations via a conjugate heat transfer analysis of the AFIP-7 irradiation experiment. As a result, a detailed CFD simulation is suggested for irradiation experiments with complicated flow paths, rather than a simplified RELAP5 simulation or hand calculations. The validated simulation approach will be integrated with the Boehmite correlations to investigate the oxide growth prediction on the fuel cladding in Part II of this research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The "Perfect Storm" for Distributed Wind Markets

Close to 1 GW of distributed wind has been installed across all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. Yet the number of installations varies greatly by state, even when wind resources are similar. This article examines three key factors that over the past thirteen years have shown to be enablers of success for distributed wind installations in the United States: 1) favorable policy environments, including consistent incentives, administrative support for cutting through red tape, and favorable interconnection, net metering, and permitting policies; 2) high electricity prices that would be displaced by wind energy generation, and, 3) favorable wind resources, enabling steady production of energy. Not all conditions need to be met simultaneously, yet of the studied markets for distributed wind in Iowa, New York, Washington, and Oregon, the most successful ones exhibit at least two out of the three conditions mentioned. We describe steps that policymakers, regulators, and market players have taken in the past to increase distributed wind installations in the United States.

Foster, Nikolas AF↗
DOE OSTI2021

Holistic Marine Energy Resource Assessments: A Wave and Offshore Wind Perspective of Metocean Conditions

Offshore wind and wave energy resources are possibly the last significantly untapped renewable energy resource, and could play a significant role in mitigating the worst impacts of climate change via the generation of renewable electricity. However, offshore wind and wave energy resource assessments have been conducted as independent parallel processes, with little interaction with regard to best practices, lessons learnt, or opportunities to create compatible methodologies for future utilization by the broader marine energy sector. Based on the latest technical specifications from the International Electrotechnical Commission, and the highest fidelity publicly available datasets, the offshore wind and wave conditions at the PacWave site off Oregon, USA were quantified. The results clearly show a significant untapped energy resource an annual average wave energy flux of ~35kW/m and a mean average wind speed of 7.8m/s. The offshore wind and wave energy resources both show significant seasonal variation, with offshore wind also featuring a consistent daily profile during summer. Finally, opportunities and challenges associated with developing a holistic assessment of offshore marine energy resources were discussed and recommendations provided.

Robertson, Bryson↗
DOE OSTI2015

Model for Deriving the Direct Normal and Diffuse Horizontal Irradiance from the Global Tilted Irradiance

We developed a separation model for deriving the direct normal irradiance (DNI) and the diffuse horizontal irradiance (DHI) from the global tilted irradiance (GTI). The model is based on the DIRINT model, but substitutes the use of the GTI in place of the global horizontal irradiance (GHI) for determining the global clearness index (Kt). Additionally, an iterative method is used to adjust Kt to improve the derived values of the DNI and the DHI. The model is referred to as the GTI-DIRINT model. When using for model input the GTI measured with a pyranometer tilted at a small angle from the horizontal (10°), the deviations between the measured DNI and DHI and the GTI-DIRINT-modeled DNI and DHI were essentially the same as those for the DIRINT model when using the GHI for model input. Increasing the tilt angle from horizontal (as great as 44° for Eugene, Oregon) increased the deviations between the modeled and measured DNI and DHI, but our results were still reasonable. The GTI-DIRINT model provides reasonable values of DNI and DHI from the GTI, and if they are subsequently used with the Perez tilted surface model to model the GTI for orientations within 30° of the azimuth and tilt of the GTI used for model input, the result is as good or better than may be obtained when using a measured DNI and DHI, and without their significant instrumentation cost.

14 SOLAR ENERGY↗
DOE OSTI2018

A stochastic downscaling approach for generating high-frequency solar irradiance scenarios

Solar power is increasingly cost viable with solar photovoltaic (PV) installations becoming commonplace. PV planning and operational studies, however, require high-frequency solar irradiance scenarios to understand potential electric grid impacts due to the variability and uncertainty of the underlying solar resource. Existing remote sensing solar data products are often available over large spatial domains, but are limited in temporal resolution. For example, the global horizontal irradiance (GHI) component contained within the National Solar Radiation Database (NSRDB) is available at time resolution of 30 min on an approximately four-kilometer grid. In contrast, substantial solar variability is present at finer time scales and this article describes an algorithm to stochastically generate one-minute GHI from widely available sub-hourly NSRDB. A generalized linear modeling (GLM) framework is proposed, which includes non-Gaussian mixtures, and extends the literature involving the synthesis of GHI data. The model is trained on a set of sample locations around Oregon, USA, and validated across the USA using both the Surface Radiation Budget Network (SURFRAD) dataset and Solar Radiation Monitoring Laboratory (SRML) network. Simulated ensembles show good coverage properties and temporal correlation structure. The resulting downscaled ensembles allow for understanding the unpredictable variability inherent in GHI at locations without direct measurements. Here, future work can leverage the algorithm as part of a stochastic optimization of electric grid operations with high-penetration PV systems.

14 SOLAR ENERGY↗
DOE OSTI2023

Integration of a physics-based direct normal irradiance ($\mathrm{DNI}$) model to enhance the National Solar Radiation Database ($\mathrm{NSRDB}$)

The National Solar Radiation Database (NSRDB) is an extensively used dataset that furnishes satellite-retrieved solar resource data across the United States and an expanding list of other countries. Although the NSRDB uses a physical model to compute global horizontal irradiance (GHI), it currently employs an empirical approach based on surface observations to estimate cloudy-sky direct normal irradiance (DNI). Recently, a new physics-based approach, known as the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to improve DNI forecasting. FARMS-DNI integrates direct and scattered solar radiances within the circumsolar region, resulting in improved day-ahead forecasting of DNI by incorporating it into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study incorporates FARMS-DNI into the NSRDB algorithm to produce high-spatiotemporal-resolution DNI data from satellite data. The accuracy of the NSRDB based on FARMS-DNI is analyzed using surface observations from 19 sites situated within the National Oceanic and Atmospheric Administration (NOAA) Surface Radiation Budget (SURFRAD) and Solar Radiation (SOLRAD) networks, the University of Oregon (UO) network, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) network, and at the National Renewable Energy Laboratory (NREL). The results demonstrate that FARMS-DNI reduces the significant overestimation of DNI in the conventional NSRDB at all surface sites, particularly in cloud overcast conditions classified using both satellite retrievals and surface observations. Consequently, this new model can effectively improve the overall accuracy of the NSRDB. The results also suggest that further improvement of DNI estimates at individual time steps, however, requires advanced satellite techniques and precise identification of clouds and retrieval of cloud properties.

14 SOLAR ENERGY↗
DOE OSTI2013

Characterization of oxygen and titanium diffusion at the anatase TiO2(001) surface

The diffusion of intrinsic defects in a single crystal anatase TiO2(001) film was explored by isotopic labeling and static secondary ion mass spectrometry. Using both 46Ti and 18O as isotopic labels, we show that the anatase surface responds to redox imbalances by diffusion of both Ti and O into the bulk under vacuum reduction and (at least) Ti from the bulk to the surface during oxidation. The diffusion of Ti between the bulk and surface in anatase TiO2(001) closely resembles what was observed in the literature for the rutile TiO2(110) surface, however the latter is not known to have oxygen diffusion between the bulk and surface under typical ultrahigh vacuum conditions. We speculate that the open lattice of the anatase bulk structure may facilitate independent diffusion of both point defects (Ti interstitials and O vacancies) or concerted diffusion of "TiO" subunits. The authors gratefully acknowledge S.A. Chambers of Pacific Northwest National Laboratory (PNNL) for providing the anatase samples. This research was supported by the U.S. Department of Energy (DOE) Office of Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division, the Office of Naval Research Contract Number 200CAR262, and the Oregon Nanoscience and Microtechnologies Institute. PNNL is operated for the U.S. DOE by Battelle under Contract Number DE05-AC76RL0 1830. The research was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility funded by the U.S. DOE Office of Biological and Environmental Research.

Herman, Gregory S.↗
DOE OSTI2016

Regional Influence of Aerosol Emissions from Wildfires Driven by Combustion Efficiency: Insights from the BBOP Campaign

Abstract Wildfires are important contributors to atmospheric aerosols and a large source of emissions that impact regional air quality and global climate. In this study, wildfire emissions in the Pacific Northwest region of the United States were characterized using real-time measurements near their sources using an aircraft, and farther downwind from a fixed ground site located at the Mt. Bachelor Observatory (~ 2700 m a.s.l.). The characteristics of aerosol emissions were found to depend strongly on the modified combustion efficiency (MCE), a qualitative index of the combustion processes of a fire. Organic aerosol emissions had negative correlations with MCE, whereas the carbon oxidation state of organic aerosol increased with MCE. The relationships between the aerosol properties and MCE were consistent between fresher emissions (~1 hour old) and emissions sampled after atmospheric transport (6 - 45 hours), suggesting that organic aerosol mass loading and chemical properties were strongly influenced by combustion processes at the source and conserved to a significant extent during regional transport. These results suggest that MCE can be a useful metric for describing aerosol properties of regionally transported wildfire emissions and their impacts on regional air quality and global climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Indoor versus Outdoor Air Quality during Wildfires

The human behavioral modification recommendations during wildfire events are based on particulate matter and may be confounded by the potential risks of gas-phase pollutants such as polycyclic aromatic hydrocarbons (PAHs). Moreover, the majority of adults spend over 90 percent of their time indoors where there is an increased concern of indoor air quality during wildfire events. We address these timely concerns by evaluating paired indoor and outdoor PAH concentrations in residential locations and their relationship with satellite model-based categorization of wildfire smoke intensity. Low density polyethylene passive air samplers were deployed at six residential sites for one week in Eugene, Oregon with matched indoor and outdoor samples and twenty-four-hour time resolution. Samples were then quantitatively analyzed for 63 PAH concentrations using gas-chromatography. A probabilistic principal components analysis was used to reduce all 63 PAHs into an aggregate measure. Linear regression of the first principal component against indoor versus outdoor shows that indoor gas-phase PAH concentrations are consistently equal or greater than outdoor concentrations. Regression against a satellite-based model for wildfire smoke shows that outdoor, but not indoor gas-phase PAH concentrations are likely associated with wildfire events. Furthermore, these results point towards the need to include gas-phase pollutants such as PAHs in air pollution risk assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Molecular Mechanics Simulations and Improved Tight-Binding Hamiltonians for Artificial Light Harvesting Systems: Predicting Geometric Distributions, Disorder, and Spectroscopy of Chromophores in a Protein Environment

We present molecular mechanics and spectroscopic calculations on prototype artificial light harvesting systems consisting of chromophores attached to a tobacco mosaic virus (TMV) protein scaffold. These systems have been synthesized and characterized spectroscopically, but information about the microscopic configurations and geometry of these TMV-templated chromophore assemblies is largely unknown. We use a Monte Carlo conformational search algorithm to determine the preferred positions and orientations of two chromophores, Coumarin 343 together with its linker and Oregon Green 488, when these are attached at two different sites (104 and 123) on the TMV protein. The resulting geometric information shows that the extent of disorder and aggregation properties and therefore the optical properties of the TMV-templated chromophore assembly are highly dependent on both the choice of chromophores and the protein site to which they are bound. We use the results of the conformational search as geometric parameters together with an improved tight-binding Hamiltonian to simulate the linear absorption spectra and compare with experimental spectral measurements. The ideal dipole approximation to the Hamiltonian is not valid because the distance between chromophores can be very small. Finally, we found that using the geometries from the conformational search is necessary to reproduce the features of the experimental spectral peaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Chemical Imaging of Atmospheric Biomass Burning Particles from North American Wildfires

The effects of biomass burning aerosols (BBA) on radiative forcing and cloud formation depend on chemical composition and the internal structures of individual particles within smoke plumes. To improve our understanding of the chemical and physical properties of BBA emitted at different times of the day and their evolution during atmospheric aging, we conducted a study as a part of the Fire Influence on Regional to Global Environments and Air Quality field campaign. Particle samples were collected onboard a research aircraft from smoke plumes from a wildfire in eastern Oregon during late afternoon and nighttime flights on August 28, 2019. A time-resolved aerosol collector was used to collect samples on substrates for offline spectromicroscopic imaging to investigate the single-particle characteristics of BBA particles. Approximately 20,400 individual particles from 10 selected samples were analyzed using computer-controlled scanning electron microscopy coupled with energy-dispersive X-ray microanalysis, revealing their elemental composition, morphology, and viscosity. Elemental microanalysis indicated that aged potassium is likely found in the form of K 2 SO 4 , KNO 3 , and possible K-organic salts. Further chemical speciation and carbon bonding mapping within individual particles were conducted using synchrotron-based scanning transmission X-ray microscopy (STXM) coupled with near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Real-time, water-soluble light absorption measurements were acquired using a particle-into-liquid sampler instrument coupled to a liquid waveguide capillary cell and total organic analyzer. In the late afternoon samples, 65% of the total particle number population consisted entirely of organic components, compared to 46% in the nighttime particles. These differences were attributed to discrepancies in composition at the time of emission and to the daytime condensation and accumulation of photochemically formed secondary organic material on existing BBA particles, a process that halts at night. Microscopy images indicated that particle viscosity was lower in the nighttime particles (<10 1 Pa·s), likely due to increased relative humidity and a higher contribution from hygroscopic inorganic components. The chemical heterogeneity of individual particles was quantified using STXM-derived mixing state parameters. The nature of carbon bonding within individual particles was inferred from the extent of carbon sp 2 hybridization derived from NEXAFS spectra. Average percentages of sp 2 hybridization range between 40% and 60%, with no noticeable differences between late afternoon and nighttime flights. These findings were compared with the online optical properties of both late afternoon and nighttime smoke plumes, providing valuable insights into the complex relationship between chemical composition and optical properties of BBA particles at different times of the day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Short-Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

Short-term Quantitative Precipitation Forecasting is important for flood forecasting, early flood warning, and natural hazard management. This study proposes a precipitation forecast model by extrapolating Cloud-Top Brightness Temperature (CTBT) using advanced Deep Neural Networks, and applying the forecasted CTBT into an effective rainfall retrieval algorithm to obtain the Short-term Quantitative Precipitation Forecasting (0–6 hr). To achieve such tasks, we propose a Long Short-Term Memory (LSTM) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), respectively. The precipitation forecasts obtained from our proposed framework, (i.e., LSTM combined with PERSIANN) are compared with a Recurrent Neural Network (RNN), Persistency method, and Farneback optical flow each combined with PERSIANN algorithm and the numerical model results from the first version of Rapid Refresh (RAPv1.0) over three regions in the United States, including the states of Oregon, Oklahoma, and Florida. We report our experiments indicate better statistics, such as correlation coefficient and root-mean-square error, for the CTBT forecasts from the proposed LSTM compared to the RNN, Persistency, and the Farneback method. The precipitation forecasts from the proposed LSTM and PERSIANN framework has demonstrated better statistics compared to the RAPv1.0 numerical forecasts and PERSIANN estimations from RNN, Persistency, and Farneback projections in terms of Probability of Detection, False Alarm Ratio, Critical Success Index, correlation coefficient, and root-mean-square error, especially in predicting the convective rainfalls. The proposed method shows superior capabilities in short-term forecasting over compared methods, and has the potential to be implemented globally as an alternative short-term forecast product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Human Mobility to Parks Under the COVID-19 Pandemic and Wildfire Seasons in the Western and Central United States

In 2020, people's health suffered a great crisis under the dual effects of the COVID-19 pandemic and the extensive, severe wildfires in the western and central United States. Parks, including city, national, and cultural parks, offer a unique opportunity for people to maintain their recreation behaviors following the social distancing protocols during the pandemic. However, massive forest wildfires in western and central US, producing harmful toxic gases and smoke, pose significant threats to human health and affect their recreation behaviors and mobility to parks. In this study, we employed the geographically and temporally weighted regression (GTWR) Models to investigate how COVID-19 and wildfires jointly shaped human mobility to parks, regarding the number of visits per capita, dwell time, and travel distance to parks, during June - September 2020. We detected strong correlations between visitations and COVID-19 incidence in southern Montana, western Wyoming, Colorado, and Utah before August. However, the pattern was weakened over time, indicating the decreasing trend of the degree of concern regarding the pandemic. Moreover, more park visits and lower dwell time were found in parks further away from wildfires and less air pollution in Washington, Oregon, California, Colorado, and New Mexico, during the wildfire season, suggesting the potential avoidance of wildfires when visiting parks. This study provides important insights on people's responses in recreation and social behaviors when facing multiple severe crises that impact their health and wellbeing, which could support the preparation and mitigation of the health impacts from future pandemics and natural hazards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire

Warmer and drier climate has contributed to increased occurrence of large, high severity wildfires in the Pacific Northwest, drawing concerns for water quality and ecosystem recovery. While nutrient fluxes generally increase post-fire, the composition of organic matter (OM) transported to streams immediately following a fire is poorly constrained, yet can play an integral role in downstream water quality and biogeochemistry. Here, we quantified the spatiotemporal patterns of dissolved OM (DOM) chemistry for five streams burned by wildfires in Oregon, USA in 2020. We sampled over a 24-hour storm event one month after the fire, revealing variable temporal behavior in DOM dynamics. DOM chemistry was directly related with burn severity spatially. Specifically, nitrogen and aromatic character of DOM increased in streams burned at greater severity. Our results suggest a spatial overprinting of DOM dynamics immediately following fire activity and highlight a key gap in our knowledge of post-fire DOM transport to streams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sensitivity Analysis of Wind and Turbulence Predictions With Mesoscale‐Coupled Large Eddy Simulations Using Ensemble Machine Learning

Abstract Coupling between mesoscale models and large‐eddy simulation (LES) models is increasingly used to more realistically represent the wide range of scales of atmospheric motions affecting boundary layer winds and turbulence that need to be simulated accurately for applications such as wind energy. However, such mesoscale‐to‐microscale coupled modeling frameworks are potentially affected by a large number of uncertain closure parameters. Here, we investigate the sensitivity associated with six closure parameters related to a 1.5‐order subgrid‐scale turbulence closure for an ensemble of mesoscale‐coupled LES. The simulations are performed using the Weather Research and Forecasting model nested from horizontal resolutions of greater than a kilometer down to tens of meters. Closure parameters are varied to generate perturbed parameter ensembles for two case studies of highly sheared, convective boundary layers observed in the Columbia Basin of Oregon and Washington during the Second Wind Forecast Improvement Project. Machine learning algorithms are used to explore the sensitivity of LES predictions, considering the effects of the perturbed physical parameters alongside categorical factors such as the case study identity, measurement location, and LES resolution. For the conditions we examine, a single parameter, the eddy viscosity coefficient, is the dominant source of parametric sensitivity and its importance is comparable to the categorical factors for several of the simulation response variables we examine.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Thermally Significant Fluid Seepage Through Thick Sediment on the Juan de Fuca Plate Entering the Cascadia Subduction Zone

We use heat flux measurements colocated with seismic reflection profiles over a buried basement high on the Juan de Fuca plate ∼25 km seaward of the deformation front offshore Oregon to test for the presence of hydrothermal circulation in the oceanic crust. We also revisit heat flux data crossing a buried basement high ∼25 km seaward of the deformation front ∼150 km north, offshore Washington. Seafloor heat flux is inversely correlated with sediment thickness, consistent with vigorous hydrothermal circulation in the basement aquifer homogenizing temperatures at the top of the basement. Heat flux immediately above the summit of the basement highs is greater than expected solely from conduction. Fluid seepage at rates of ∼2.6–5.4 cm yr −1 in a 1–1.5 km-wide conduit through ∼800–1,300 m thick sediment sections above these basement highs can explain these observations. Observations of thermally significant fluid seepage through sediment >225 m thick on oceanic crust are unprecedented. High sediment permeability, high fluid overpressure in the basement, or a combination of both is required to drive fluid seepage at the observed rates. We infer that rapid seepage occurs because the basement highs rise above the low permeability basal sediment with their tops protruding into the base of high permeability Nitinat or Astoria Fan sediment. Seepage from basement highs penetrating into the submarine fans can affect the thermal state of crust entering the subduction zone.

58 GEOSCIENCES↗