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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗
DOE OSTI2023

The ARENA Test Bed – A Versatile Resource for I&C Development and Validation

The Accelerated and Real-time Experimental Nodal Assessment (ARENA) Test Bed at the Pacific Northwest National Laboratory (PNNL) is a versatile resource for development and validation of instrumentation and control (I&C) technologies. This capability was created to facilitate in-situ testing of nuclear electrical cables in various simulated operational environments. Using cable trays, a control box, and selected test components, low voltage cables can be staged to experience local adverse environments such as elevated temperature and water immersion. Cable condition can be continuously monitored over time to track the effect of local stresses using nondestructive assessment tools. A heads-up display (ARENA TV) plots key data in real-time for users. The ARENA Test Bed has recently been used to evaluate the potential for spread spectrum time domain reflectometry (SSTDR) to monitor thermal aging of a portion of live cable powering a three-phase motor. The arrangement provided the opportunity to directly compare the performance of the novel online SSTDR method with offline results from the more standard frequency domain reflectometry (FDR) method. The ability of SSTDR and FDR to identify the presence of water in immersed shielded and unshielded cables and to detect ground faults was also assessed. A digital twin is being developed to track and predict FDR signals from a thermally aging conceptual cable region to compare with measured signals from the ARENA physical counterpart. The test bed concept addresses an important need in nuclear I&C monitoring tool development. New tools and techniques can be developed in the test bed and validated versus known methods and physical measurements. Digital twins and machine learning engines can be populated with measured data in a controlled environment that would not be readily available in the actual nuclear power plant. Proposed monitoring strategies can be confirmed for effectiveness through objective evaluation. It is anticipated that the PNNL ARENA Test Bed will be a valuable resource in advancing nuclear plant instrumentation.

nuclear electrical cables, ARENA Test Bed, conditi↗
DOE OSTI2025

High-resolution leaf area index maps generated from unoccupied aerial system, Teller Mile 27, Seward Peninsula, Alaska

Leaf area index (LAI), a measure of the amount of one-side leaf area per ground unit, is an important indicator of plant carbon, energy, and water cycle. In the heterogeneous Arctic landscapes, it has been challenging to accurately measure LAI across species and space needed for Earth system model validation. Here, we use multispectral unoccupied aerial systems (UASs) to scale up and map leaf area index (LAI) , in a low-Arctic tundra landscape on the Seward Peninsula, Alaska. We linked previous published LAI measurements with high-resolution, UAS-collected multispectral data collected over the region of Next Generation Ecosystem Experiments in the Arctic (NGEE Arctic)’s Teller Mile Maker 27 site in 2022 to develop random forest (RF) machine learning models to predict and map LAI. 100 RF models were developed to account for uncertainties in ground LAI plot measurements and process scaling. This dataset includes a raster (*.tif) map of the mean LAI value of the 100 RF models, a raster (*.tif) map of the standard deviation of the RF-modeled LAI data, and a user guide (*.pdf).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vertical distribution of boundary layer new particle formation and implications for nanoparticle growth mechanisms (Final Report)

New particles can form high above ground in the atmosphere before such formation events are observed by ground-based instruments. Once formed, these particles can take up significant amounts of water vapor, which has implications on the mechanisms by which nanoparticles grow and, ultimately, impact cloud formation processes. These observations motivated the research performed in this project using a combination of modeling, laboratory experiments, and the analysis of field observations. We hypothesized is that ground-based measurements do not always accurately represent the location and timing of new particle formation events, nor do they adequately characterize the dominant physical and chemical processes that are responsible for the subsequent growth of newly formed particles. Essentially, we wanted to study the new particle formation process under conditions that we expect may be more relevant to the actual location in the atmosphere where such events take place, which are often characterized by higher relative humidities, lower temperatures, and a broader range of precursors and oxidants compared to those observed at ground level. This project had two main objectives, each of which directly addressed our hypothesis. Our first is to investigate the timing, distribution, meteorological conditions, and nanoparticle properties associated with boundary layer new particle formation through the analysis of ARM field campaigns such as HI-SCALE and long-term observations and observations performed in other locales such as in China and India where atmospheric conditions could play a crucial role in determining the mechanisms of new particle formation. This activity provided a comprehensive description, both in time and in space, of the gases and nanoparticle properties that are responsible for these events. We also performed modeling studies to explore the vertical profile and timing of new particle formation events from these campaigns. Our second objective was to perform laboratory and process-level modeling studies to investigate the role that conditions such as low ambient temperature, high relative humidity, and different oxidants such as nitrate radical play in determining unique chemical pathways for nanoparticle growth. In doing so, we revisited the representation of nanoparticle growth in global models and updated assumptions of formation and growth based on the findings of the field, laboratory, and process-level-model work. Our research provides crucial insights into the most important regions of the atmospheric boundary layer for future observational and modeling studies. It also identifies the most relevant environmental conditions, precursors, and oxidants that are responsible for nanoparticle growth, which will aid in the design of laboratory studies and process-level model experiments. The unique pathways that we discovered can be incorporated into regional and global models, thereby improving predictions and attribution of the role of new particle formation in, e.g., air pollution formation and cloud properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluation of Techniques for Vegetation Removal from UAV-Based Photogrammetric DSM near WIPP Land Withdrawal Act Boundary, NM

The Waste Isolation Pilot Plant is located within New Mexico's karst landscape and is the United States' only deep geologic radioactive waste repository which isolates transuranic waste from defense activities underground in a bedded salt formation. Characteristic karst topography in this region is made up of material (such as limestone) that can be dissolved by water over a long period of time, and includes features such as springs, surface streams, sinking streams, caves, and sinkholes. Karst features can potentially impact the integrity of the waste repository in the future and compromise WIPP's performance, particularly when coupled with incompatible land-use activities within the Land Withdrawal Act (LWA) boundary as well as increased water withdrawals outside the LWA. In order to better capture the ground surface topography to support hydrology modeling efforts, the U.S. DOE has enlisted FIU to develop a high-resolution digital elevation model (DEM). In a previous field study, a high-resolution digital surface model (DSM) of an adjacent representative site, Basin 6, was developed by photogrammetry using aerial images captured with unmanned aerial vehicles. The DSM generated was based on point clouds representing the entire landscapes, including points of terrain, vegetation and infrastructure. These above-ground features need to be removed to create a DSM/DEM with good representation of the bare ground. In recent years, many techniques including both pre- and post-processing of DSMs, were developed for vegetation removal with varied success. This research focuses on applying and comparing various vegetation removal methods using point clouds generated of the Basin 6 pilot study area. The 3D RGB-based point cloud classification using Python scripts was a modification of the procedure by Themistocleous (2019). The method using Liblas classifies the point cloud three-dimensionally, whereas the method by Themistocleous (2019) is two-dimensional. The preliminary result of the method using Liblas, however, still had a large amount of vegetation remaining compared to the Pix4D Machine Learning method. The vegetation layer remains highly visible in the DEMs processed using the vegetation indices as opposed to the Pix4D Machine Learning method, which produces a DEM where mostly bare ground is seen. Further modifications to the input parameters are required to improve the vegetation vs. bare ground classification using this approach. The next step will be to improve the method using Liblas and to also test other vegetation removal methods found in the literature review to compare them against the two described here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Beirut Explosion Yield and Mushroom Cloud Height - Effects of the Source Environment

I use crater dimensions to estimate the yield of the August 4th, 2020 Beirut explosion to be equivalent to approximately 1.4 kilotons of TNT with a lower bound of about 0.7 kilotons. Based on the amount of ammonium nitrate reported to have been stored at the Beirut harbor, I assume an upper bound for the yield of 2.75 kilotons. However, it is highly likely that the yield was less than 2.75 kilotons, since reported values for TNT equivalence of ammonium nitrate are typically much less than one hundred percent. The crater-size based yield estimates are based on crater radius estimates from satellite imagery and empirical curves and data for scaled crater radius from past chemical and nuclear explosions. I present evidence that suggests that the relatively large crater radius is due to a high degree of coupling of shock wave energy to the surrounding medium and a reduction of the effective stress because of a high level of saturation of the geologic media beneath the explosion. I provide yield estimates based on seismic body-wave magnitude and crater depth as corroborating evidence. I compare preliminary estimates for the maximum debris cloud height, based on cell phone videos/images, with predicted maximum heights for this yield range from empirical formulas and numerical cloud-rise models. Based on a preliminary analysis of cell phone footage, the observed maximum cloud height appears to be approximately 1600 m. This is much lower than that predicted using standard empirical formulas and buoyant cloud rise models. I present results from a modified buoyant cloud rise model that more accurately predicts the maximum cloud height by allowing for the inclusion of a fixed amount of air and/or water into the fireball at the start of cloud rise. The amount of mass that needs to be added at the start, to reproduce the observed maximum cloud height, is relatively small compared to the total mass entrained during cloud rise. A much greater amount of dry air or debris is required, relative to water, for an equivalent reduction in maximum cloud height. The ammonium nitrate is one possible source for water in the fireball since it was being stored in a very humid environment and ammonium nitrate is known to be hygroscopic. The ground beneath the explosion, especially if it were saturated, and the nearby harbor could also have been sources for water or debris in the fireball.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Methodology for Estimating the Energy and Moisture Budget of the Convective Boundary Layer Using Continuous Ground-Based Infrared Spectrometer Observations

Abstract Land–atmosphere interactions play a critical role in both the atmospheric water and energy cycles. Changes in soil moisture and vegetation alter the partitioning of surface water and energy fluxes, influencing diurnal evolution of the planetary boundary layer (PBL). The mixing-diagram framework has proven useful in understanding the evolution of the heat and moisture budget within the convective boundary layer (CBL). We demonstrate that observations from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site provide all of the needed inputs needed for the mixing-diagram framework, allowing us to quantify the impact from the surface fluxes, advection, radiative heating, encroachment, and entrainment on the evolution of the CBL. Profiles of temperature and humidity retrieved from the ground-based infrared spectrometer [Atmospheric Emitted Radiance Interferometer (AERI)] are a critical component in this analysis. Large-eddy simulation results demonstrate that mean mixed-layer values derived are shown to be critical to close the energy and moisture budgets. A novel approach demonstrated here is the use of network of AERIs and Doppler lidars to quantify the advective fluxes of heat and moisture. The framework enables the estimation of the entrainment fluxes as a residual, providing a way to observe the entrainment fluxes without using multiple lidar systems. The high temporal resolution of the AERI observations enables the morning, midday, and afternoon evolution of the CBL to be quantified. This work provides a new way to use observations in this framework to evaluate weather and climate models. Significance Statement The energy and moisture budget of the planetary boundary layer (PBL) is influenced by multiple sources, and accurately representing this evolution in numerical models is critical for weather forecasts and climate predictions. The mixing-diagram approach, driven by profiling observations as illustrated here, provides a powerful way to quantify the contributions from each of these sources. In particular, the energy and moisture mixed into the PBL from above the PBL can be determined accurately from ground-based remote sensors using this approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Meteorological and Soil Data from Ecohydrology Sensor Towers at Pump House and Snodgrass Mountain in East River Watershed, Colorado, 2019-2025

This data package includes hourly meteorological and soil sensor data at eight ecohydrology monitoring sites in East River Watershed, Colorado as part of the Watershed Function Scientific Focus Area (WFSFA) research led by Lawrence Berkeley National Lab (LBNL). Four field sites were located on the hillslope of East River (ER) near Pump House (PH) at Mount Crested Butte (ER-PHS1 to 4), and the other four are in the Snodgrass Mountain (SG) area (SG-EHS5 to 8). In terms of vegetation cover, three sites are in montane grasslands (ER-PHS1, ER-PHS2, and SG-EHS5), three are below evergreen conifer canopy (ER-PHS3, SG-EHS6, and SG-EHS7), and two are below deciduous aspen canopy (ER-PHS4 and SG-EHS8). The monitoring period began in October 2019 at the East River sites, in October 2020 at SG-EHS5 and SG-EHS6, and in October 2021 at SG-EHS7 and SG-EHS8. In September 2024, all four East River sites were fully retired. The four Snodgrass Mountain sites remain active. Each site is equipped with a comprehensive suite of meteorological sensors on a tripod and soil sensors that measure weather, energy fluxes, and soil variables. This data package includes measurements from ten different types of sensors and up to thirteen individual sensors per site, including (1) a weather station (measurement height ranges from 2.8~3.8 meters (m) above ground), (2) a quantum sensor for photosynthetic active radiation (PAR) (2.4~3.3m), (3) a net radiometer (1.7~2.1m), (4) an infrared radiometer (1.6~2.2m), (5) a sonic distance sensor (1.5~1.9m), (6) a soil carbon dioxide (CO2) flux chamber (0m), (7) a soil heat flux plate (-0.05m below ground), (8) a soil oxygen sensor (-0.3m), (9) a soil water potential sensor (-0.3m), and (10) soil water content sensors at 3~4 depths (-1.15 ~ -0.1m). A total of twenty-three variables is reported in this data package, including (1) atmospheric variables: air temperature (TA), atmospheric pressure (PA), vapor pressure (VP), and vapor pressure deficit (VPD), (2) precipitation variables: rain precipitation (P) and snow depth (D_SNOW), (3) energy fluxes variables: four-component net radiation (NETRAD) (shortwave/longwave incoming/outgoing radiation, SW_IN, SW_OUT, LW_IN, LW_OUT), photosynthetic photon flux density (PPFD), and soil heat flux (G), (4) soil variables: soil water content (SWC), soil water potential (SWP), soil temperature (TS), soil bulk electrical conductivity (COND_SOIL), and soil gaseous oxygen concentration (O2_SOIL), (5) wind variables: two-dimensional wind speed (WS), gust speed (WS_MAX), and wind direction (WD), and (6) surface variables: surface infrared temperature (T_CANOPY) and soil CO2 flux (CO2_SOIL). Please see the Methods section for data processing and QA/QC steps taken to generate the hourly datasets. The following files are included in this data package (notes on version: v{x}-{y}, where x is the metadata version, and y is the data version, when applicable): (1) “metadata_site_v{x}-{y}.csv” - a site metadata file that summarizes location information of all sites, including site ID, description, coordinates, timeframe, elevation, and vegetation cover, (2) “metadata_instrument_v{x}-{y}.csv” - an instrument metadata file that summarizes sensor information of all sites, including sensor manufacturer and model, measurement height, and sampling and averaging interval of all variables, (3) "data_{SITE_ID}_v{x}-{y}.csv" - eight data files that contain hourly data of each site indicated by {SITE_ID} in the filename, (4) “/figure/data_{SITE_ID}_v{x}-{y}.png" - eight figures that help visualize data of each site indicated by {SITE_ID} in the filename, (5) “/photo/*” - photos of each site indicated by {SITE_ID} in the filename, and (6) four file level metadata (flmd.csv) and data dictionary (*_dd.csv) files that summarize file, header, column, and variable information of all files. Notes: (1) Measurement height: Each variable name is followed by conventional positional qualifiers “H_V_R”, where H indicates the relative horizontal positions of that specific variable, V the vertical positions, and R the replicates. In this data package, only the vertical qualifier V varies, and V increases from the highest vertical position (V=1) to the lowest. Variables with the same qualifier are not necessarily measured by the same sensor, and the same variable with the same qualifier across different sites are not necessarily measured at the same height. Please refer to “metadata_instrument.csv” for the sensor information and measurement heights, and whether a variable is measured below the canopy. (2) Variable availability: Snow depth is not available at ER-PHS3 and SG-EHS7. SWC, soil temperature, and soil bulk EC at the deepest depth (<-1m) are not available at SG-EHS6 and SG-EHS7. The missing value code for numeric variables is -9999, except for SWP. For SWP, the missing value code is +9999, because SWP values are negative. (3) Sampling frequency: Please refer to “metadata_instrument.csv” for the increase of sampling frequency of some variables from 30-min to 1-min at ER-PHS1 to 4 in July 2020. (4) Sensors: While the methods of each sensor are not detailed, all sensors are commercially available, and their methods can be found in their manuals. Please refer to “metadata_instrument.csv” for the sensor manufacturer and model information. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED-2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Review of analytical studies on seismic fluid-structure interaction of base-supported cylindrical tanks

Analytical solutions for seismic fluid-structure interaction (FSI) of tanks are used by analysts and engineers for a number of purposes, including preliminary sizing, risk assessment, and verification of numerical models. Analytical solutions for seismic FSI of tanks were first developed in the 1930s and have been extended and/or modified in the following nine decades to accommodate different seismic inputs and boundary conditions. This report reviews published analytical solutions for rigid and flexible, base-supported, cylindrical tanks subjected to unidirectional horizontal motion of a small amplitude. The studies parsed the fluid-structure (FSI) response into an impulsive and a convective component, and addressed frequencies of lateral motions of the tank (i.e., impulsive frequencies), hydrodynamic pressures, frequencies of waves (i.e., convective frequencies), wave heights, and reactions at the base. The solutions were categorized into exact and approximate solutions based on the methodologies used. Herein, FSI responses are calculated and compared for a range of tank dimensions using the analytical solutions from the different studies. The responses presented here are normalized to be unitless, and can be used for tanks with different dimensions and mechanical properties, and subjected to different input motions. A sample steel water tank is analyzed using the normalized solutions for two earthquake ground motions with different frequency contents. Ignoring tank flexibility may significantly underestimate seismic responses of the tank and its contained fluid. The approximate solutions, which have been widely used for decades, may not be sufficiently accurate in the modern era. Calculation errors in the reviewed studies are identified and corrected, and differences are quantified for the sample tank.

42 ENGINEERING↗
DOE OSTI2020

Understanding the Interplay between the Nonvalence and Valence States of the Uracil Anion upon Monohydration

In this work we present an ab initio investigation into the effect of monohydration on the interaction of uracil with low energy electrons. Electron attachment and photodetachment experimental studies have previously shown dramatic changes in uracil upon solvation with even a single water molecule, due to an inversion of the character of the ground state of the anion. Here we explore the interplay between the nonvalence and valence states of the uracil anion, as a function of geometry and site of solvation. Our model provides unambiguous interpretation of previous photoelectron studies, reproducing the binding energies and photoelectron images for bare uracil and a single isomer of the U•(H 2 O) 1 cluster. Furthermore, the results of this study provide insight into how electrons may attach to hydrated nucleobases. These results lay the foundations for further investigations into the effect of microhydration on the electronic structure and electron capture dynamics of nucleobases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Evaluation of four ground-based retrievals of cloud droplet number concentration in marine stratocumulus with aircraft in situ measurements

Abstract. Cloud droplet number concentration (Nd) is crucial for understanding aerosol–cloud interactions (ACI) and associated radiative effects. We present evaluations of four ground-based Nd retrievals based on comprehensive datasets from the Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The Nd retrieval methods use ARM ENA observatory ground-based remote sensing observations from a micropulse lidar, Raman lidar, cloud radar, and the ARM NDROP (Droplet Number Concentration) value-added product (VAP), all of which also retrieve cloud effective radius (re). The retrievals are compared against aircraft measurements from the fast cloud droplet probe (FCDP) and the cloud and aerosol spectrometer (CAS) obtained from low-level marine boundary layer clouds on 12 flight days during summer and winter seasons. Additionally, the in situ measurements are used to validate the assumptions and characterizations used in the retrieval algorithms. Statistical comparisons of the probability distribution function (PDF) of the Nd and cloud re retrievals with aircraft measurements demonstrate that these retrievals align well with in situ measurements for overcast clouds, but they may substantially differ for broken clouds or clouds with low liquid water path (LWP). The retrievals are applied to 4 years of ground-based remote sensing measurements of overcast marine boundary layer clouds at the ARM ENA observatory to find that Nd (re) values exhibit seasonal variations, with higher (lower) values during the summer season and lower (higher) values during the winter season. The ensemble of various retrievals using different measurements and retrieval algorithms such as those in this paper can help to quantify Nd retrieval uncertainties and identify reliable Nd retrieval scenarios. Of the retrieval methods, we recommend using the micropulse lidar-based method. This method has good agreement with in situ measurements, less sensitivity to issues arising from precipitation and low cloud LWP and/or optical depth, and broad applicability by functioning for both daytime and nighttime conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

New Perspectives on the Exoplanet Radius Gap from a Mathematica Tool and Visualized Water Equation of State

Recent astronomical observations obtained with the Kepler and TESS missions and their related ground-based follow-ups revealed an abundance of exoplanets with a size intermediate between Earth and Neptune (1 R ⊕ ≤ R ≤ 4 R ⊕ ). A low occurrence rate of planets has been identified at around twice the size of Earth (2 × R ⊕ ), known as the exoplanet radius gap or radius valley. We explore the geometry of this gap in the mass–radius diagram, with the help of a Mathematica plotting tool developed with the capability of manipulating exoplanet data in multidimensional parameter space, and with the help of visualized water equations of state in the temperature–density (T–ρ) graph and the entropy–pressure (s–P) graph. We show that the radius valley can be explained by a compositional difference between smaller, predominantly rocky planets (<2 × R ⊕ ) and larger planets (>2 × R ⊕ ) that exhibit greater compositional diversity including cosmic ices (water, ammonia, methane, etc.) and gaseous envelopes. In particular, among the larger planets (>2 × R ⊕ ), when viewed from the perspective of planet equilibrium temperature (T eq ), the hot ones (T eq ≳ 900 K) are consistent with ice-dominated composition without significant gaseous envelopes, while the cold ones (T eq ≲ 900 K) have more diverse compositions, including various amounts of gaseous envelopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Evaluation of Four Ground-based Retrievals of Cloud Droplet Number Concentration in Marine Stratocumulus with Aircraft In Situ Measurements

Cloud droplet number concentration (N d ) is crucial for understanding aerosol-cloud interactions (ACI) and associated radiative effects. We present evaluations of four ground-based N d retrievals based on comprehensive datasets from the Atmospheric Radiation Measurements (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The N d retrieval methods use ARM ENA observatory ground-based remote sensing observations from a Micropulse lidar, Raman lidar, cloud radar, and the ARM NDROP Value-added Product (VAP), all of which also retrieve cloud effective radius (r e ). The retrievals are compared against aircraft measurements from the Fast-Cloud Droplet Probe (FCDP) and the Cloud and Aerosol Spectrometer (CAS) obtained from low-level marine boundary layer clouds on 12 flight days during summer and winter seasons. Additionally, the in situ measurements are used to validate the assumptions and characterizations used in the retrieval algorithms. Statistical comparisons of the probability distribution function (PDF) of the N d and cloud r e retrievals with aircraft measurements demonstrate that these retrievals align well with in situ measurements for overcast clouds, but they may substantially differ for broken clouds or clouds with low liquid water path (LWP). The retrievals are applied to four years of ground-based remote sensing measurements of overcast marine boundary layer clouds at the ARM ENA observatory to find that N d (r e ) values exhibit seasonal variations, with higher (lower) values during the summer season and lower (higher) values during the winter season. The ensemble of various retrievals using different measurements and retrieval algorithms such as those in this paper can help to quantify N d retrieval uncertainties and identify reliable N d retrieval scenarios. Of the retrieval methods, we recommend using the using the Micropulse lidar-based method given its good agreement with in situ measurements, it has less sensitivity to issues arising from precipitation and low cloud LWP/optical depth, and it has broad applicability by functioning for both day and nighttime conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

COGIHTO: Comprehensive Geothermal Integrated HVAC Retrofits in Disadvantaged Communities

Geothermal heating and cooling (GHC) systems offer one of the most efficient approaches to provide space conditioning and water heating in buildings. Due to the relatively stable temperature of the ground year-round, these systems can provide an efficient solution to decarbonize heating systems. Yet this technology has faced limited market adoption due to its high first cost. This project seeks to address this barrier by designing a community GHC system at a public housing development in New York, taking advantage of load diversity (in terms of the timing and amount of heating / cooling used per person) that a larger community offers to reduce the size and thus first cost of a GHC system. Project success would result in societal benefit from reduced energy and fossil fuel use, reduced local emissions, and improved comfort, which would positively impact the health and well-being this community. This report presents the findings from Phase 1 project supported by the Department of Energy’s Geothermal Technologies Office and includes the technical design of a GHC at a public housing development in New York. To support the success of a potential deployment of a GHC system, the team conducted community engagement and prepared an assessment of the local workforce needs. The project team, led by EPRI, considered a subset of NYCHA housing developments that were previously identified by NYCHA as suitable for GHC retrofits. This report presents the site selection criteria the team developed and the overall score assigned to each of the eight developments considered. One site was selected for focus of the technical design: Stapleton Houses in Staten Island, a mid-size development with roughly 700 apartments across 6 buildings. The site has an existing hot water hydronic loop served by natural gas boilers for space heating and water heating. The technical design partner assessed baseline energy consumption at the site and established thermal models of the apartment buildings to assist in the design. The team considered several GHC system configurations and selected a hybrid geothermal design fed from water-source heat pumps with auxiliary gas boilers in a central plant. This design best leveraged the existing site configuration and minimized costs due to additional electrical infrastructure upgrades. The report also details the feedback received from community engagement efforts and the findings from the workforce needs assessment and workforce transition plan. Members of the site maintenance staff and the resident advisory council were interviewed for their input and feedback about both the site’s existing heating/cooling infrastructure and how a construction project would impact resident life. This feedback was taken into consideration when completing the geothermal system design. Research was conducted into existing workforce development opportunities available to NYCHA residents. A workforce development plan was established using information from NYCHA’s resident economic empowerment and sustainability group, along with training material and curriculum from the International Ground Source Heat Pump Association (IGSHPA).

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Characterizing Mesoscale Cellular Convection in Marine Cold Air Outbreaks With a Machine Learning Approach

Abstract During marine cold‐air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well‐recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment provided a comprehensive set of ground‐based in situ and remote sensing observations of MCAOs at a coastal location in northern Norway. MCAO periods that unambiguously exhibit open or closed MCC are determined. Individual cells observed with a profiling Ka‐band radar are identified using a watershed segmentation method. Using self‐organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM nodes contain some information about the location of the cell transect relative to the center of the MCC. This adds classification noise, requiring numerous cell transects to isolate cell dynamical information. The SOM‐based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectrum width, larger amounts of liquid water, lower surface precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation‐induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. More stratiform vertical cloud structures with weak vertical motions are common during closed MCC periods and are separated into precipitating and non‐precipitating stratiform cores. Convection is observed only occasionally in the closed MCC environment.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Mid–height seismic isolation of equipment in nuclear power plants

An innovative seismic isolation solution for designers of safety-class equipment in advanced nuclear power plants is introduced. The test specimen was a tall, slender, carbon steel vessel that could represent a reactor vessel, steam generator, or a heat exchanger in a nuclear power plant: 240 inches tall, outer diameter of 60 inches, and wall thickness of 1 inch. The vessel was supported by three radial mounts at its mid-height, near its center of gravity, on a steel frame. The vessel was subjected to three-component ground motions using a 6DOF earthquake simulator. The specimen was filled with water for testing to indirectly account for the fluid and internal equipment present inside a prototype vessel. Three configurations were tested: non-isolated, isolated using single Friction Pendulum (SFP) bearings, and isolated using triple Friction Pendulum (TFP) bearings. The test results demonstrate that mid-height seismic isolation is practical and enables a significant reduction in horizontal spectral accelerations. Furthermore, these outcomes are not specific to the spherical sliding bearings used in the experiments but are broadly applicable to mid-height, seismically isolated equipment.

42 ENGINEERING↗