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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Direct Simulation of Extinction in a Slab of Spherical Particles

The exact multiple sphere superposition method is used to calculate the coherent and incoherent contributions to the ensemble-averaged electric field amplitude and Poynting vector in systems of randomly positioned nonabsorbing spherical particles. The target systems consist of cylindrical volumes, with radius several times larger than length, containing spheres with positional configurations generated by a Monte Carlo sampling method. Spatially dependent values for coherent electric field amplitude, coherent energy flux, and diffuse energy flux, are calculated by averaging of exact local field and flux values over multiple configurations and over spatially independent directions for fixed target geometry, sphere properties, and sphere volume fraction. Our results reveal exponential attenuation of the coherent field and the coherent energy flux inside the particulate layer and thereby further corroborate the general methodology of the microphysical radiative transfer theory. An effective medium model based on plane wave transmission and reflection by a plane layer is used to model the dependence of the coherent electric field on particle packing density. The effective attenuation coefficient of the random medium, computed from the direct simulations, is found to agree closely with effective medium theories and with measurements. In addition, the simulation results reveal the presence of a counter-propagating component to the coherent field, which arises due to the internal reflection of the main coherent field component by the target boundary. The characteristics of the diffuse flux are compared to, and found to be consistent with, a model based on the diffusion approximation of the radiative transfer theory.

spheres↗
NASA NTRS2010

A Spectroscopic Search for Leaking Lyman Continuum at Zeta Approximately 0.7

We present the results of rest-frame, UV slitless spectroscopic observations of a sample of 32 z approx. 0.7 Lyman Break Galaxy (LBG) analogs in the COSMOS field. The spectroscopic search was performed with the Solar Blind Channel (SBC) on HST. While we find no direct detections of the Lyman Continuum we achieve individual limits (3sigma) of the observed non-ionizing UV to Lyman continuum flux density ratios, f(sub nu)(1500A)/f(sub nu)(830A) of 20 to 204 (median of 73.5) and 378.7 for the stack. Assuming an intrinsic Lyman Break of 3.4 and an optical depth of Lyman continuum photons along the line of sight to the galaxy of 85% we report an upper limit for the relative escape fraction in individual galaxies of 0.02 - 0.19 and a stacked 3sigma upper limit of 0.01. We find no indication of a relative escape fraction near unity as seen in some LBGs at z approx. 3. Our UV spectra achieve the deepest limits to date at any redshift on the escape fraction in individual sources. The contrast between these z approx. 0.7 low escape fraction LBG analogs with z approx. 3 LBGs suggests that either the processes conducive to high f(sub esc) are not being selected for in the z less than or approx.1 samples or the average escape fraction is decreasing from z approx. 3 to z approx. 1. We discuss possible mechanisms which could affect the escape of Lyman continuum photons

Bridge, Carrie R.↗
NASA NTRS2015

Mantle Water Contents Beneath the Rio Grande Rift (NM, USA): FTIR Analysis of Rio Puerco and Kilbourne Hole Peridotite Xenoliths

Peridotite xenoliths from the Rio Grande Rift (RGR) are being analyzed for H (sub 2) O contents by FTIR (Fourier Transform Infrared) as well as for major and trace element compositions. Nine samples are from the Rio Puerco Volcanic Field (RP) which overlaps the central RGR and southeastern Colorado Plateau; seventeen samples are from Kilbourne Hole (KH) in the southern RGR. Spinel Cr# (Cr/(Cr+Al)) (0.08-0.46) and olivine Mg# (Mg/(Mg plus Fe)) (0.883-0.911) of all RGR samples fall within the olivine-spinel mantle array from [1], an indicator that peridotites are residues of partial melting. Pyroxene H (sub 2) O in KH correlate with bulk rock and pyroxene Al (sub 2) O (sub 3).The KH clinopyroxene rare earth element (REE) variations fit models of 0-13 percent fractional melting of a primitive upper mantle. Most KH peridotites have bulk-rock light REE depleted patterns, but five are enriched in light REEs consistent with metasomatism. Variation in H (sub 2) O content is unrelated to REE enrichment. Metasomatism is seen in RP pyroxenite xenoliths [2] and will be examined in the peridotites studied here. Olivine H (sub 2) O contents are low (less than or equal to 15 parts per million), and decrease from core to rim within grains. This is likely due to H loss during xenolith transport by the host magma [3]. Diffusion models of H suggest that mantle H (sub 2) O contents are still preserved in cores of KH olivine, but not RP olivine. The average H (sub 2) O content of Colorado Plateau clinopyroxene (670 parts per million) [4] is approximately 300 parts per million higher than RGR clinopyroxene (350 parts per million). This upholds the hypothesis that hydration-induced lithospheric melting occurred during flat-slab subduction of the Farallon plate [5]. Numerical models indicate hydration via slab fluids is possible beneath the plateau, approximately 600 kilometers from the paleo-trench, but less likely approximately 850 kilometers away beneath the rift [6].

Schaffer, L. A.↗
DOE OSTI2021

Computationally Efficient Multiscale Neural Networks Applied to Fluid Flow in Complex 3D Porous Media

Abstract The permeability of complex porous materials is of interest to many engineering disciplines. This quantity can be obtained via direct flow simulation, which provides the most accurate results, but is very computationally expensive. In particular, the simulation convergence time scales poorly as the simulation domains become less porous or more heterogeneous. Semi-analytical models that rely on averaged structural properties (i.e., porosity and tortuosity) have been proposed, but these features only partly summarize the domain, resulting in limited applicability. On the other hand, data-driven machine learning approaches have shown great promise for building more general models by virtue of accounting for the spatial arrangement of the domains’ solid boundaries. However, prior approaches building on the convolutional neural network (ConvNet) literature concerning 2D image recognition problems do not scale well to the large 3D domains required to obtain a representative elementary volume (REV). As such, most prior work focused on homogeneous samples, where a small REV entails that the global nature of fluid flow could be mostly neglected, and accordingly, the memory bottleneck of addressing 3D domains with ConvNets was side-stepped. Therefore, important geometries such as fractures and vuggy domains could not be modeled properly. In this work, we address this limitation with a general multiscale deep learning model that is able to learn from porous media simulation data. By using a coupled set of neural networks that view the domain on different scales, we enable the evaluation of large ( $$>512^3$$ > 512 3 ) images in approximately one second on a single graphics processing unit. This model architecture opens up the possibility of modeling domain sizes that would not be feasible using traditional direct simulation tools on a desktop computer. We validate our method with a laminar fluid flow case using vuggy samples and fractures. As a result of viewing the entire domain at once, our model is able to perform accurate prediction on domains exhibiting a large degree of heterogeneity. We expect the methodology to be applicable to many other transport problems where complex geometries play a central role.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simultaneous Optical Transmission Spectroscopy of a Terrestrial, Habitable-zone Exoplanet with Two Ground-based Multiobject Spectrographs

Investigating the atmospheres of rocky exoplanets is key to performing comparative planetology between these worlds and the terrestrial planets that reside in the inner solar system. Terrestrial exoplanet atmospheres exhibit weak signals, and attempting to detect them pushes at the boundaries of what is possible for current instrumentation. We focus on the habitable-zone terrestrial exoplanet LHS 1140b. Given its 25-day orbital period and 2 hr transit duration, capturing transits of LHS 1140b is challenging. We observed two transits of this object, approximately 1 yr apart, which yielded four data sets thanks to our simultaneous use of the IMACS and LDSS3C multiobject spectrographs mounted on the twin Magellan telescopes at Las Campanas Observatory. We present a jointly fit white light curve, as well as jointly fit 20 nm wavelength-binned light curves from which we construct a transmission spectrum. Binning the joint white light-curve residuals to 3-minute time bins gives an rms of 145 ppm; binning down to 10-minute time bins gives an rms of 77 ppm. Our median uncertainty in R{sub p}{sup 2}/R{sub s}{sup 2} in the 20 nm wavelength bins is 260 ppm, and we achieve an average precision of 1.3× the photon noise when fitting the wavelength-binned light curves with a Gaussian process regression. Our precision on R{sub p}{sup 2}/R{sub s}{sup 2} is a factor of four larger than the feature amplitudes of a clear, hydrogen-dominated atmosphere, meaning that we are not able to test realistic models of LHS 1140b’s atmosphere. The techniques and caveats presented here are applicable to the growing sample of terrestrial worlds in the Transiting Exoplanet Survey Satellite era, as well as to the upcoming generation of ground-based giant segmented mirror telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Spatially Resolved, In Situ Carbon Isotope Analysis of Archean Organic Matter

Spatiotemporal variability in the carbon isotope composition of sedimentary organic matter (OM) preserves information about the evolution of the biosphere and of the exogenic carbon cycle as a whole. Primary compositions, and imprints of the post-depositional processes that obscure them, exist at the scale of individual sedimentary grains (mm to micron). Secondary ion mass spectrometry (SIMS) (1) enables analysis at these scales and in petrographic context, (2) permits morphological and compositional characterization of the analyte and associated minerals prior to isotopic analysis, and (3) reveals patterns of variability homogenized by bulk techniques. Here we present new methods for in situ organic carbon isotope analysis with sub-permil precision and spatial resolution to 1 micron using SIMS, as well as new data acquired from a suite of Archean rocks. Three analytical protocols were developed for the CAMECA ims1280 at WiscSIMS to analyze domains of varying size and carbon concentration. Average reproducibility (at 2SD) using a 6 micron spot size with two Faraday cup detectors was 0.4 %, and 0.8 % for analyses using 1 micron and 3 micron spot sizes with a Faraday cup (for C-12) and an electron multiplier (for C-13). Eight coals, two ambers, a shungite, and a graphite were evaluated for micron-scale isotopic heterogeneity, and LCNN anthracite (delta C-13 = -23.56 +/- 0.1 %, 2SD) was chosen as the working standard. Correlation between instrumental bias and H/C was observed and calibrated for each analytical session using organic materials with H/C between 0.1 and 1.5 (atomic), allowing a correction based upon a C-13H/C-13 measurement included in every analysis. Matrix effects of variable C/SiO2 were evaluated by measuring mm to sub-micron graphite domains in quartzite from Bogala mine, Sri Lanka. Apparent instrumental bias and C-12 count rate are correlated in this case, but this may be related to a crystal orientation effect in graphite. Analyses of amorphous Archean OM suggest that instrumental bias is consistent for 12C count rates as low as 10% relative to anthracite. Samples from the ABDP-9 (n=3; Mount McRae Shale, approximately 2.5 Ga), RHDH2a (n=2; Carrawine Dolomite and Jeerinah Fm, approximately 2.6 Ga), WRL1 (n=3; Wittenoom Fm, Marra Mamba Iron Formation, and Jeerinah Fm, approximately 2.6 Ga), and SV1 (n=1; Tumbiana Fm, approximately 2.7 Ga) drill cores, each previously analyzed for bulk organic carbon isotope composition, yielded 100 new, in situ data from Neoarchean sedimentary OM. In these samples, delta C-13 varies between -53.1 and -28.3 % and offsets between in situ and bulk compositions range from -8.3 to 18.8%. In some cases, isotopic composition and mode of occurrence (e.g. morphology and mineral associations) are statistically correlated, enabling the identification of distinct reservoirs of OM. Our results support previous evidence for gradients of oxidation with depth in Neoarchean environments driven by photosynthesis and methane metabolism. The relevance of these findings to questions of bio- and syngenicity as well as the alteration history of previously reported Archean OM will be discussed.

Williford, Kenneth H.↗
NASA NTRS1999

The New 20-Year Global Precipitation Climatology Project (GPCP) Merged Satellite and Rainguage Monthly Analysis

A new 20-year, monthly, globally complete precipitation analysis has been completed as part of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP). This Version 2 of the community generated data set is a result of combining the procedures and data sets as described. The global, monthly, 2.5x 2.5 degree latitude-longitude product utilizes precipitation estimates from low-orbit microwave sensors (SSM/1) and geosynchronous IR sensors and raingauge information over land. The low-orbit microwave estimates are used to adjust or correct the geosynchronous IR estimates, thereby maximizing the utility of the more physically-based microwave estimates and the finer time sampling of the geosynchronous observations. Information from raingauges is blended into the analyses over land. In the 1986-present period TOVS-based precipitation estimates are adjusted to GPCP fields and used in polar regions to produce globally-complete results. The extension back to 1979 utilizes the procedures of Xie and Arkin and their OLR Precipitation Index (OPI). The 20-year climatology of the Version 2 GPCP analysis indicates the expected features of a very strong Pacific Ocean ITCZ and SPCZ with maximum 20-year means approaching 10 mm/day. A similar strength maximum over land is evident over Borneo. Weaker maxima in the tropics occur in the Atlantic ITCZ and over South America and Africa. In mid-latitudes of the Northern Hemisphere the Western Pacific and Western Atlantic maxima have values of approximately 7 mm/day, while in the Southern Hemisphere the mid-latitude maxima are located southeast of Africa, in mid-Pacific as an extension of the SPCZ and southeast of South America. In terms of global totals the GPCP analysis shows 2.7 mm/day (3.0 mm/day over ocean; 2.1 mm/day over land), similar to the Jaeger climatology, but not other climatologies. Zonal averages peak at 6 mm/day at 7*N with mid-latitude peaks of about 3 mm/day at 40-45* latitude. Poleward of 45* the GPCP analysis shows larger zonally-averaged values than most previous satellite-based estimates, although the values are similar to tl,ie Jaeger climatology. Over both ocean areas and at high latitudes the analysis requires additional validation and comparison with special, independent data sets from field experiments and from the Tropical Rain Measuring Mission (TRMM) to confirm the absolute magnitude and variations of precipitation seen in the analysis. Interannual and other variations of the global fields will be shown focusing on the recent ('97-'99) ENSO event compared with previous events, including teleconnections at mid and high latitudes. An ENSO Precipitation Index (ESPI) calculated using the new data set will be described and related to the evolution of the ENSO events during the 20-year period.

Adler, Robert↗
DOE OSTI2020

Automated co-adding and energy calibration of large array microcalorimeter data with zero sample knowledge

State-of-the-art microcalorimeter spectrometers now contain large detector arrays with hundreds of individual pixels. Each individual pixel outputs a unique and non-linear response with respect to deposited energy. This work describes a pattern-recognition algorithm to combine these responses into a single energy-calibrated histogram, referred to as co-adding pixels. Photo-peaks from different pixels are matched together based upon how well the match aligns the centroids and heights of neighboring peaks. This usually results in around 100 co-adding calibration points from 30 to 300 keV for a several day acquisition of plutonium items with masses between 0.5 and 10 grams. An additional algorithm energy-calibrates this co-added spectrum using the fluoresced K x-ray emissions from a tantalum absorber and inherent x-ray escape peaks from the tin absorbers. Both algorithms operate without knowledge of the source and are fully automated. This work presents results from the acquisitions of high and low burnup plutonium, 10% enriched uranium, a 153 Gd calibration source, and a 57 Co+ 166m Ho calibration source. In all measurements, resolution defined as the full-width at half-maximum (FWHM) of photo-peaks is preserved between the individual pixel and co-added spectra at around 65 eV for incident photon energies between 60 and 208 keV. The energy calibration algorithm is approximate and yields a calibration curve off by an average of around 200 eV for incident photon energies between 60 and 208 keV.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗
DOE OSTI2021

Large-scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant

We investigate the use of approximate Bayesian neural networks (BNNs) in modeling hundreds of time delay gravitational lenses for Hubble constant (H 0 ) determination. Here, our BNN was trained on synthetic Hubble Space Telescope quality images of strongly lensed active galactic nuclei with lens galaxy light included. The BNN can accurately characterize the posterior probability density functions (PDFs) of model parameters governing the elliptical power-law mass profile in an external shear field. We then propagate the BNN-inferred posterior PDFs into an ensemble H 0 inference, using simulated time delay measurements from a plausible dedicated monitoring campaign. Assuming well-measured time delays and a reasonable set of priors on the environment of the lens, we achieve a median precision of 9.3% per lens in the inferred H 0 . A simple combination of a set of 200 test lenses results in a precision of 0.5 km s –1 Mpc –1 (0.7%), with no detectable bias in this H 0 recovery test. The computation time for the entire pipeline—including the generation of the training set, BNN training and H0 inference—translates to 9 minutes per lens on average for 200 lenses and converges to 6 minutes per lens as the sample size is increased. Being fully automated and efficient, our pipeline is a promising tool for exploring ensemble-level systematics in lens modeling for H 0 inference.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Development of New Lunar Highland Regolith Simulant, NUW-LHT-5M

Introduction: NASA has a need for large quantities of lunar simulants that closely match future manned lunar missions at landing sites near the Lunar South Pole. The current simulant was designed to approximate NU-LHT-2M, and -4M, except using natural minerals and a fully synthetic, non-basaltic, high calcium glass. Washington Mills in Niagara Falls, NY was contracted to produce this new simulant due to their electric arc furnace (EAF) fusion technology and capabilities for crushing and sizing ceramics. The primary objectives of this work were: (1) to create a commercially produced simulant that contains a high fidelity, high calcium (An90+), low Mg/Fe glass without basaltic constituents; (2) to create a simulant that uses existing, terrestrially mined, and readily available minerals blended with a synthetic glass, and (3) accomplish objectives (1) and (2) using conventional processing methods capable of production levels that can meet substantial current and future demands of NASA projects. Another consideration was that highland simulants closest to meeting these requirements, NU-LHT-2M and -4M types, are out of production and largely out of stock. Design: The design chosen for development and production for this work is NU-LHT-2M, de-signed by Doug Stoeser and Douglas Rickman, which uses Stillwater anorthosite and norite rocks and synthetic glass. The composition targeted the average composition, glass content and particle size distribution of Apollo 16 samples [1]. The design utilizes two Stillwater minerals, anorthosite (37.7 wt.%), norite (17.6 wt.%), a commercially sourced olivine (4.7 wt.%), and a synthetic glass (40 wt.%). Processing: Stillwater rocks were hand collected and initially crushed by the USGS. Further crushing and milling was performed at Washing-ton Mills. For the glass, oxides were blended in the ap-propriate ratios, blended in a v-blender, and placed in a graphite lined, water cooled pot. The mixture was fused in Washington Mills’ pilot scale, 500 kW EAF. The molten glass was then poured into water and quenched to inhibit crystallization. Several pour/quench cycles were required to produce the total quantity of glass needed. Anorthosite, norite and olivine were milled together to the target particle size in a ball mill. The glass was ball milled separately. The complete simulant was produced by blending the milled materials. Particle size distribution, phase and chemical analyses of the materials was were per-formed at Washington Mills. Results: The glass composition was found to match the Apollo 16 oxide content average [1] quite well, with the exception of SiO2 and Fe2O3. The deviation of SiO2 and Fe2O3 from batched content was believed to be due to limitations inherent in the use of the arc furnace technique for these types of materials. A particle size distribution of the full simulant formulation closely matching the average for the Apollo 16 samples was also achieved. Fig. 1 shows the morphology of the final simulant particles. The size distribution is compared to the target in Fig. 2. Conclusions: A new lunar highlands type simulant containing a high-quality synthetic glass, closely matching an average composition of the Apollo 16 regolith was produced. Processing utilized easily scalable mineral and glass making methods.

simulant↗
DOE OSTI2025

Swelling and Fission Gas Release of U-10Mo and U-17Mo Following Neutron Irradiation at 250 – 500°C

The performance of metallic fuel alloys, U-10Mo and U-17Mo, was examined using the MiniFuel test system in the High Flux Isotope Reactor. Approximately 0.8 mm thick disks were irradiated at target temperatures of 250°C, 350°C, 450°C, and 500°C up to three different fission densities, culminating at a maximum fission density of 6.8 × 10 20 cm −3 . Fission rates decayed from 3 – 6 × 10 13 cm −3 s −1 to 2 – 4 × 10 13 cm −3 s −1 over the course of the longest, eight cycle, irradiation as the 235 U was consumed and the 239 Pu concentration accumulated. Actual irradiation temperature on the last day of irradiation was measured via dilatometry using the SiC passive thermometry recovered from the MiniFuel subcapsules and compared favorably with the thermal calculations using as-built geometry and test conditions. Furthermore, average simulated temperatures were within 50°C of the target temperatures, except for the 500°C irradiation, for which the temperature variation was 62°C, 32°C, and 90°C in the in two, four, and eight cycle irradiations, respectively. Fission gas release (FGR) measurements showed no release above recoil for any U-17Mo fuels or for the U-10Mo fuel irradiated at 250°C. Finally, significant (40%–80%) FGR was found for the medium- to highest-burnup U-10Mo samples irradiated at target temperatures 350°C–500°C. Significant FGR correlated with sample thickness swelling, which was as high as 13%–35% for high-release samples and below 7% for all other (low–gas release) samples.

FGR↗
DOE OSTI2024

Measurement report: A comparison of ground-level ice-nucleating-particle abundance and aerosol properties during autumn at contrasting marine and terrestrial locations

Abstract. Ice-nucleating particles (INPs) are an essential class of aerosols found worldwide that have far-reaching but poorly quantified climate feedback mechanisms through interaction with clouds and impacts on precipitation. These particles can have highly variable physicochemical properties in the atmosphere, and it is crucial to continuously monitor their long-term concentration relative to total ambient aerosol populations at a wide variety of sites to comprehensively understand aerosol–cloud interactions in the atmosphere. Hence, our study applied an in situ forced expansion cooling device to measure ambient INP concentrations and test its automated continuous measurements at atmospheric observatories, where complementary aerosol instruments are heavily equipped. Using collocated aerosol size, number, and composition measurements from these sites, we analyzed the correlation between sources and abundance of INPs in different environments. Toward this aim, we have measured ground-level INP concentrations at two contrasting sites, one in the Southern Great Plains (SGP) region of the United States with a substantial terrestrially influenced aerosol population and one in the Eastern North Atlantic Ocean (ENA) region with a primarily marine-influenced aerosol population. These measurements examined INPs mainly formed through immersion freezing and were performed at a ≤ 12 min resolution and with a wide range of heterogeneous freezing temperatures (Ts above −31 °C) for at least 45 d at each site. The associated INP data analysis was conducted in a consistent manner. We also explored the additional offline characterization of ambient aerosol particle samples from both locations in comparison to in situ data. From our ENA data, on average, INP abundance ranges from ≈ 1 to ≈ 20 L−1 (−30 °C ≤ T ≤ −20 °C) during October–November 2020. Backward air mass trajectories reveal a strong marine influence at ENA with 75.7 % of air masses originating over the Atlantic Ocean and 96.6 % of air masses traveling over open water, but analysis of particle chemistry suggests an additional INP source besides maritime aerosols (e.g., sea spray aerosols) at ENA. In contrast, 90.8 % of air masses at the SGP location originated from the North American continent, and 96.1 % of the time, these air masses traveled over land. As a result, organic-rich SGP aerosols from terrestrial sources exhibited notably high INP abundance from ≈ 1 to ≈ 100 L−1 (−30 °C ≤ T ≤ −15 °C) during October–November 2019. The probability density function of aerosol surface area-scaled immersion freezing efficiency (ice nucleation active surface site density; ns) was assessed for selected freezing temperatures. While the INP concentrations measured at SGP are higher than those of ENA, the ns(T) values of SGP (≈ 105 to ≈ 107 m−2 for −30 °C ≤ T ≤ −15 °C) are reciprocally lower than ENA for approximately 2 orders of magnitude (≈ 107 to ≈ 109 m−2 for −30 °C ≤ T ≤ −15 °C). The observed difference in ns(T) mainly stems from varied available aerosol surface areas, Saer, from two sites (Saer,SGP > Saer,ENA). INP parameterizations were developed as a function of examined freezing temperatures from SGP and ENA for our study periods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

ResStock Measure Documentation: Residential Two-Stage Geothermal Heat Pump (4.0 COP, 20.5 EER) With Envelope Improvements and Advanced Air Sealing

The goal of this work is to develop energy efficiency, demand flexibility, and other retrofit end-use load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) measures. "Measures" refers to retrofits that can be applied to buildings during modeling. An "end-use savings shape" is the difference in energy consumption between a baseline building and a building with an energy efficiency, demand flexibility, or other retrofit measure applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step. ResStock is a highly granular, physics-based, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the residential building stock across the United States. The baseline model intends to represent the U.S. residential building stock as it existed in 2018. Technical documentation for the inputs and assumptions in the baseline building stock model is available in Reyna et al. (2025). Calibration and validation of the baseline model results are available in the final technical report of the End-Use Load Profiles project (Wilson, et al. 2022). This document focuses on a single end-use savings shape measure: Residential Two-Stage Geothermal Heat Pump (GHP) (4.0 COP, 20.5 EER) With Envelope Improvements. This measure combines a two-stage GHP with envelope improvements as a single package. As this package is a combination of two other measures, this document focused on documenting the results associated with this combination of technologies, with individual measure documents for two-stage GHPs and envelope improvements providing the information on the details of these measures. When the two technologies are combined, envelope improvements can modestly reduce energy consumption by a further 10%-15%, but also reduce the required size of the ground heat exchanger and heat pump by approximately 33% on average across all sites. The cost of installing envelope improvements in these homes is likely to be more than paid for by the reduction in equipment and drilling costs in these buildings for the majority of the stock.

15 GEOTHERMAL ENERGY↗
NASA NTRS2000

The Dust Content and Opacity of Actively Star-Forming Galaxies

We present far-infrared (FIR) photometry at 150 and 205 micron(s) of eight low-redshift starburst galaxies obtained with the Infrared Space Observatory (ISO) ISOPHOT. Five of the eight galaxies are detected in both wave bands, and these data are used, in conjunction with IRAS archival photometry, to model the dust emission at lambda approximately greater than 40 microns. The FIR spectral energy distributions (SEDs) are best fitted by a combination of two modified Planck functions, with T approx. 40 - 55 K (warm dust) and T approx. 20-23 K (cool dust) and with a dust emissivity index epsilon = 2. The cool dust can be a major contributor to the FIR emission of starburst galaxies, representing up to 60% of the total flux. This component is heated not only by the general interstellar radiation field, but also by the starburst itself. The cool dust mass is up to approx. 150 times larger than the warm dust mass, bringing the gas-to-dust ratios of the starbursts in our sample close to Milky Way values, once resealed for the appropriate metallicity. The ratio between the total dust FIR emission in the range 1-1000 microns and the IRAS FIR emission in the range 40 - 120 microns is approx. 1.75, with small variations from galaxy to galaxy. This ratio is about 40% larger than previously inferred from data at millimeter wavelengths. Although the galaxies in our sample are generally classified as "UV bright," for four of them the UV energy emerging shortward of 0.2 microns is less than 15% of the FIR energy. On average, about 30% of the bolometric flux is coming out in the UV-to-near-IR wavelength range; the rest is emitted in the FIR. Energy balance calculations show that the FIR emission predicted by the dust reddening of the UV-to-near-IR stellar emission is within a factor of approx. 2 of the observed value in individual galaxies and within 20% when averaged over a large sample. If our sample of local starbursts is representative of high-redshift (z approx. greater than 1), UV - bright star-forming galaxies, these galaxies' FIR emission will be generally undetected in submillimeter surveys, unless: (1) their bolometric luminosity is comparable to or larger than that of ultraluminous FIR galaxies and (2) their FIR SED contains a cool dust component.

Calzetti, Daniela↗
NASA NTRS1998

Vertical Profiles of Cloud Condensation Nuclei, Condensation Nuclei, Optical Aerosol, Aerosol Optical Properties, and Aerosol Volatility Measured from Balloons

Under the support of this grant a balloon-borne gondola containing a variety of aerosol instruments was developed and flown from Laramie, Wyoming, (41 deg N, 105 deg W) and from Lauder, New Zealand (45 deg S, 170 deg E). The gondola includes instruments to measure the concentrations of condensation nuclei (CN), cloud condensation nuclei (CCN), optically detectable aerosol (OA.) (r greater than or equal to 0.15 - 2.0 microns), and optical scattering properties using a nephelometer (lambda = 530 microns). All instruments sampled from a common inlet which was heated to 40 C on ascent and to 160 C on descent. Flights with the CN counter, OA counter, and nephelometer began in July 1994. The CCN counter was added in November 1994, and the engineering problems were solved by June 1995. Since then the flights have included all four instruments, and were completed in January 1998. Altogether there were 20 flights from Laramie, approximately 5 per year, and 2 from Lauder. Of these there were one or more engineering problems on 6 of the flights from Laramie, hence the data are somewhat limited on those 6 flights, while a complete data set was obtained from the other 14 flights. Good CCN data are available from 12 of the Laramie flights. The two flights from Lauder in January 1998 were successful for all measurements. The results from these flights, and the development of the balloon-bome CCN counter have formed the basis for five conference presentations. The heated and unheated CN and OA measurements have been used to estimate the mass fraction of the aerosol volatile, while comparisons of the nephelometer measurements were used to estimate the light scattering, associated with the volatile aerosol. These estimates were calculated for 0.5 km averages of the ascent and descent data between 2.5 km and the tropopause, near 11.5 km.

Deshler, T.↗
DOE OSTI2022

Sizing ice hydrometeor populations using the dual-wavelength radar ratio

Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, D v , provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of D v retrievals using DWR are around 0.6 mm when D v is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the entire particle size distribution (PSD), such as D v , and other sizes used in various applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Vitrification of Hanford Tank Wastes for Condensate Recycle and Feed Composition Changeover Testing (Rev. 1)

During the vitrification of Hanford Site nuclear waste at the Waste Treatment and Immobilization Plant (WTP), which is a part of the safe and efficient retrieval, treatment, and disposal mission of the U.S. Department of Energy Office of River Protection, the offgas condensate generated from the waste-to-glass conversion is currently planned to be concentrated by evaporation in the Effluent Management Facility (EMF). This concentrated condensate can then be recycled back to the incoming waste and vitrified. To test the recycle process, an apparatus was designed and built to mimic the EMF evaporator and was then used to concentrate a volume of condensate produced during the vitrification of a sample of Hanford tank 241-AP-107 (referred to herein as AP-107) waste in a continuous laboratory-scale melter (CLSM). The concentrated condensate was added to an additional sample of AP-107 waste, to mimic one round of the recycle process, and the combined solution was vitrified, producing a second round of recycle condensate. In the current study, the EMF test apparatus was used to concentrate the second-round recycle condensate under evaporation conditions (at 45 °C and 1.4 psia) designed to emulate EMF operation. The condensate was successfully concentrated by a factor of ~10 while retaining over 95 % of the technetium-99 (99Tc), Cs, and I inventories in the concentrate. Another portion of AP-107 waste was retrieved by Washington River Protection Solutions, LLC (WRPS) and transferred to Pacific Northwest National Laboratory (PNNL), where it was pretreated and then combined with the second-round recycle AP-107 condensate concentrate and glass-forming chemicals (GFCs) to form the two-time recycle AP-107 melter feed, approximating a second round to the recycling action to be performed at the WTP. A portion of AP-105 waste was also retrieved by WRPS and provided to PNNL for pretreatment and combining with GFCs to form AP-105 melter feed. The two-time recycle AP-107 and AP-105 melter feeds were processed consecutively in the CLSM. The CLSM run proceeded for 13.63 hours, producing 9.70 kg of glass for an average glass production rate of 1464 kg m 2 d -1 during the two-time recycle AP-107 feed charging and 1568 kg m 2 d -1 during the AP-105 feed charging. The rate during AP-107 charging was essentially equivalent to the rate when processing no-recycle AP-107 feed and lower than that achieved when processing one-time recycle AP-107 feed. However, all rates were within the potential range of variability when processing melter feeds with similar composition in the CLSM. Likewise, the rate during AP-105 charging was higher than the previous rate processing AP-105, but within the potential CLSM range. The cold-cap characteristics changed from the typically thin AP-107 cold cap to a foamy-edged cold cap as previously seen with AP-105 shortly after transitioning to the AP-105 melter feed. The glass produced during the CLSM run was within 10 % of its target composition for the primary glass components. The CaO and Li 2 O targets varied by more than 1 wt% between the two-time recycle AP-107 and AP-105 glass targets and it took about 2 turnovers of the CLSM glass inventory to reach a relative chemical steady state in the glass for CaO and Li 2 O after the melter feed inputs were switched.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗