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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

NERSC_Lightweight Distributed Metric Service (NERSC_LDMS) v4.4.2

Miscellany This LDMS Loftsman/Helm Chart horizontally scales LDMS daemons in order to achieve a 1Hz sample rate from over 5,000 nodes, collecting 38k metrics per minute on Perlmutter. This LMDS Configuration relies on already running `ldmsd` producers running on nodes, which produce metrics via sampler plugins. The Helm chart distributes the collection of metrics from producer acrross many aggregator and storage `ldmsd` daemons, ensuring no damon is overloaded and data loss is avoided.

Stile, John [Lawrence Berkeley National Laboratory↗
DOE OSTI2019

Remote Sensing of Sea Salt Aerosol below Trade Wind Clouds

Abstract Sea salt aerosol in the boundary layer below shallow cumulus clouds is remotely observed with a Ka-band cloud radar at the Barbados Cloud Observatory and is detected in 76% of the measurements over 1 year. Carried by convection, sea salt particles with a diameter larger than 500 nm show an upward motion of 0.2 m s−1 below shallow cumulus clouds for a 2-day case study. Caused by an increasing relative humidity with increasing altitude, the sea salt particles become larger as they move closer to the cloud base. By using combined measurements of a Ka-band cloud radar and a Raman lidar, the retrieved equivolumetric diameter of the hygroscopically grown sea salt particles is found to be between 6 and 11 μm with a total number concentration of 20 cm−3 near cloud base. Assuming a fixed shape parameter, a size distribution of sea salt particles under high-relative-humidity conditions below cloud base is estimated and agrees with measurements taken by a dry-deposition sampler and online aerosol observations. The methods outlined in this paper can be used in future studies to get a better understanding of the vertical and temporal sea salt distribution in the boundary layer and sea salt aerosol–cloud interaction processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. Furthermore, the combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Validation of KENO Delayed Neutron Fraction Capabilities

The delayed neutron fraction, which is necessary for the safe operation of reactors, varies by fissionable material and neutron spectrum. A prompt fission neutron spectrum has been included in the SCALE 6.2 release to account for the removal of delayed neutrons from precursor materials from the neutron balance. This paper describes how experimental measurements from criticality safety benchmarks were used to validate the SCALE calculational procedure for the delayed neutron fraction. Additionally, the effect of nuclear data uncertainty on the KENO calculation of β eff was examined with the SAMPLER sequence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2012

Shallow (2-meter) Temperature Surveys in Colorado

Shallow temperature surveys are useful in early-stage geothermal exploration to delineate surface outflow zones, with the intent to identify the source of upwelling, usually a fault. Detailed descriptions of the 2-meter survey method and equipment design can be found in Coolbaugh et al. (2007) and Sladek et al. (2007), and are summarized here. The survey method was devised to measure temperature as far below the zone of solar influence as possible, have minimal equilibration time, and yet be portable enough to fit on the back of an all-terrain vehicle (ATV); Figure 2). This method utilizes a direct push technology (DPT) technique where 2.3 m long, 0.54" outer diameter hollow steel rods are pounded into the ground using a demolition hammer. Resistance temperature devices (RTD) are then inserted into the rods at 2-meter depths, and allowed to equilibrate for one hour. The temperatures are then measured and recorded, the rods pulled out of the ground, and re-used at future sites. Usually multiple rods are planted over the course of an hour, and then the sampler returns back to the first station, measures the temperatures, pulls the rods, and so on, to eliminate waiting time. At Wagon Wheel Gap, 32 rods were planted around the hot springs between June 20 and July 1, 2012. The purpose was to determine the direction of a possible upflow fault or other structure. Temperatures at 1.5m and 2m depths were measured and recorded in the attribute table of this point shapefile. Several anomalous temperatures suggest that outflow is coming from a ~N60W striking fault or shear zone that contains the quartz-fluorite-barite veins of the adjacent patented mining claims. It should be noted that temperatures at 2m depth vary according to the amount of solar heating from above, as well as possible geothermal heating from below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Wet and dry plastic deposition data for western US National Atmospheric Deposition Program sites (2017-2019)

Raw plastic counts and calculated plastic deposition rates for 11 National Atmospheric Deposition Program (NADP) sites in the western USA recorded from 2017-2019. Samples were collected to determine plastic deposition rates in remote locations and identify the potential sources of plastic to the atmosphere. Samples were collected using an Aerochem Metrics Wet and Dry sampler. Wet deposition refers to the material retained on a 0.45-micron filter. Dry deposition refers to the dry only deposition collected using a Dry Side Insert (DSI) (Brahney et al. 2020). Plastics are identified as either fibers or particles (includes small colored films). Wet deposition rates are recorded weekly and dry plastic deposition rates are based on monthly sampling intervals. Sites included are Grand Canyon National Park (AZ03), Joshua Tree National Park (CA67), Rocky Mountain National Park (CO98), Niwot Ridge (CO02), Ashley National Forest (UT95), East River SFA (CO10)), Craters of the Moon National Park (ID03), Great Basin National Park (NV05), Canyonlands National Park (UT09), Bryce Canyon Nationa Park (UT99), and Wind River Range (WY06). Data collection is being published in collaboration with the Department of Energy's research project, "Constraining physical understanding of aerosol loading, biogeochemistry, and snowmelt hydrology from hillslope to watershed scale in the East River Scientific Focus Areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effect of fluctuating redox conditions on trace metal release from wetland soils from South Carolina and stream sediments from Tennessee

Natural aquatic systems undergo fluctuating redox conditions due to microbial activity, varying water saturation levels, and nutrients dynamics. With fluctuating oxic and anoxic conditions, trace metals can be mobilized or sequestered in response to changes in iron and sulfur speciation and the concentrations and lability of organic carbon. We conducted a systematic laboratory-based microcosm study to examine the effect of redox fluctuations on trace metal mobility in samples collected from two different natural aquatic systems: riparian wetlands and a stream. We incubated water-saturated soils under three cycles of anoxic-oxic conditions (τanoxic:τoxic = 3) spanning 24 days and monitored the change in dissolved and bioavailable metal (copper (Cu), nickel (Ni), zinc (Zn), cobalt (Co), iron (Fe), and manganese (Mn)) concentrations. The dataset includes the results of the variation in metal concentrations due to redox fluctuations in wetland soils and stream sediments. Additionally, the variation in the bioavailable concentration of metals obtained using passive samplers based on diffuse gradient in thin-films technique is included in the dataset. We have also reported the change in the pH values and dissolved oxygen concentrations in the microcosms during the entire study of 24 days. The dataset also contains the dissolved organic carbon and sulfate concentrations, and the data on fractions of metals bound to reducible and oxidizable phases. For materials from both the wetlands and the stream, anoxic conditions favored Co and Zn release, which corresponded with the reductive dissolution of iron oxides. In contrast, dissolved Cu concentrations increased under oxic conditions for both sites and correlated positively with the release of sulfate. In wetland soils, dissolution of Fe (hydr)oxides increased Ni solubility; however, in stream sediments, Ni release occurred when sulfides or organic matter were oxidized. For stream sediments, each subsequent redox cycle increased the bioavailability of trace metals. Upon redox fluctuations in wetland soils, the bioavailability of Zn and Cu increased, whereas bioavailable Ni and Co decreased. This study illustrates that different trace metals display distinct bioavailability patterns during oxic-anoxic fluctuations in natural environments. The biogeochemical cycling of carbon and nitrogen in systems with redox fluctuations may be influenced by these patterns in trace metal availability in addition to the availability of electron donors and acceptors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Greenhouse Rhizobox Experiment with Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry data, Seward Peninsula, Alaska, 2024

Data collected from a greenhouse rhizobox experiment (2024) using soils and plants collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by porewater samplers (rhizons). Gas data consists of CO2 and CH4 surface soil fluxes measured with an FTIR (Fourier-transformed infrared red) analyzer. Plant and root data consists of biomass, root length. This study is a part of The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2 and CH4?Description of the contents of this data package: Rhizobox2024_Data.csv: This dataset contains plant, water and gas data. No software is needed to utilize them.nga535_flmd.csv: The file contains file level metadatanga535.dd.csv: This file contains the data dictionaryMethods.pdf: This file contains the data collection methods

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bayesian inference of Stochastic reaction networks using Multifidelity Sequential Tempered Markov Chain Monte Carlo

Stochastic reaction network models are often used to explain and predict the dynamics of gene regulation in single cells.These models usually involve several parameters, such as the kinetic rates of chemical reactions, that are not directly measurable and must be inferred from experimental data. Bayesian inference provides a rigorous probabilistic frame-work for identifying these parameters by finding a posterior parameter distribution that captures their uncertainty.Traditional computational methods for solving inference problems such as Markov Chain Monte Carlo methods based on classical Metropolis-Hastings algorithm involve numerous serial evaluations of the likelihood function, which in turn requires expensive forward solutions of the chemical master equation (CME). We propose an alternate approach based on a multifidelity extension of the Sequential Tempered Markov Chain Monte Carlo (ST-MCMC) sampler. This algorithm is built upon Sequential Monte Carlo and solves the Bayesian inference problem by decomposing it into a sequence of efficiently solved subproblems that gradually increase both model fidelity and the influence of the observed data. We reformulate the finite state projection (FSP) algorithm, a well-known method for solving the CME, to produce a hierarchy of surrogate master equations to be used in this multifidelity scheme. To determine the appropriate fidelity, we introduce a novel information-theoretic criteria that seeks to extract the most information about the ultimate Bayesian posterior from each model in the hierarchy without inducing significant bias. This novel sampling scheme is tested with high performance computing resources using biologically relevant problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Stan : A Probabilistic Programming Language

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can also be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DES Y3 + KiDS-1000: Consistent cosmology combining cosmic shear surveys

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Nitrate Leaching from Continuous Corn, Perennial Grasses, and Poplar in the US Midwest

Leaching from annual corn ( Zea mays L.) crops is a primary source of nitrate (NO 3 - ) pollution of ground and surface waters. Here, we compare NO 3 - losses from no-till corn with losses from various alternative perennial cropping systems (switchgrass [ Panicum virgatum L.], miscanthus [ Miscanthus ×giganteus J.M. Greef & Deuter ex Hodkinson & Renvoiz], a native grass mixture, and restored prairie), as well as hybrid poplar ( Populus nigra L. × P. maximowiczii A. Henry ‘NM6’), all grown on a well-drained soil in Michigan. Soil water was sampled from below the root zone using suction cup samplers during nonfrozen periods (March–November) between 2009 and 2016. Leaching was estimated from NO 3 - concentrations in soil water and modeled drainage (percolation) rates. Drainage rates were not significantly different among crops, constituting ~30% of total annual precipitation. Aboveground net primary production (Mg ha -1 yr -1 ) averaged across the 7 yr was highest in poplar (30.8 ± 1.9 [SE]) followed by miscanthus (23.9 ± 2.4) and corn (20.4 ± 0.9). Volume-weighted mean NO 3 - concentrations (mg N L -1 ) and NO 3 - leaching (kg ha -1 yr -1 ) averaged across the 7 yr were 9.2 and 34.1, 2.3 and 5.9, and 3.0 and 7.2, respectively, for corn, perennial grasses and poplar. Approximately 10 to 32% of applied N was lost as NO 3 - from these crops, with the highest percent losses from poplar (32%) followed by corn (20%). Perennial cropping systems leached considerably more NO 3 - in first few years after planting, but over 7 yr they lost much less NO 3 - than corn. Perennial crops may therefore help ameliorate NO 3 - pollution in agricultural landscapes even if they receive modest N fertilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Method for Controlling Temperature Profiles and Water Table Depths in Laboratory Sediment Columns

Core Ideas Column experiments simulating subsurface environments require control of temperature profiles. A 2‐m‐tall laboratory sediment column reproduced vadose zone thermal and hydraulic conditions. Measured CO 2 profiles show the importance of microbial respiration below the root zone. Transport from the soil surface to groundwater is commonly mediated through deeper portions of the vadose zone and capillary fringe, where variations in temperature and water saturation strongly influence biogeochemical processes. This technical note describes a sediment column design that allows laboratory simulation of thermal and hydrologic conditions found in many field settings. Temperature control is particularly important because room temperature is not representative of most subsurface environments. A 2.0‐m‐tall column was capable of simulating profiles with temperatures ranging from 3 to 22°C, encompassing the full range of seasonal temperature variation observed in the deep vadose zone and capillary fringe of a semiarid floodplain in western Colorado. The water table was varied within the lower 0.8‐m section of the column, and profiles of water content and matric potential were measured. Vadose zone CO 2 collected from depth‐distributed gas samplers under representative seasonal conditions reflected the influences of temperature and water table depth on microbial respiration. Thus, realistic subsurface biogeochemical dynamics can be simulated in the laboratory through establishing column profiles that represent seasonal thermal and hydrologic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

The iSERIES™ radon progeny compensation algorithm and its application to air filters

Sandia has developed methods to perform a rapid count using Canberra’s iSERIES™ Alpha/Beta Counting System, the iSOLO™. The purpose of this report is to show that by using the iSERIES™ built-in radon progeny compensation algorithm, the radon progeny-free gross alpha air concentration can be determined for a sample taken using a high volume air sampler or a lapel device within a few hours post-sampling. Also, a special form of the Currie Minimum Detectable Activity estimation was derived for use with the radon progeny stripping algorithm after it was discovered that the expression used by the Canberra software did not take the counts due to radon progeny into consideration as part of the background. This rapid air sample analysis proves to be a vast improvement to the current method that has an average turn-around time between seven and ten days.

Fournier, Sean Donovan↗
DOE OSTI2012

A General Investigation of Optimized Atmospheric Sample Duration

ABSTRACT The International Monitoring System (IMS) consists of up to 80 aerosol and xenon monitoring systems spaced around the world that have collection systems sensitive enough to detect nuclear releases from underground nuclear tests at great distances (CTBT 1996; CTBTO 2011). Although a few of the IMS radionuclide stations are closer together than 1,000 km (such as the stations in Kuwait and Iran), many of them are 2,000 km or more apart. In the absence of a scientific basis for optimizing the duration of atmospheric sampling, historically scientists used a integration times from 24 hours to 14 days for radionuclides (Thomas et al. 1977). This was entirely adequate in the past because the sources of signals were far away and large, meaning that they were smeared over many days by the time they had travelled 10,000 km. The Fukushima event pointed out the unacceptable delay time (72 hours) between the start of sample acquisition and final data being shipped. A scientific basis for selecting a sample duration time is needed. This report considers plume migration of a nondecaying tracer using archived atmospheric data for 2011 in the HYSPLIT (Draxler and Hess 1998; HYSPLIT 2011) transport model. We present two related results: the temporal duration of the majority of the plume as a function of distance and the behavior of the maximum plume concentration as a function of sample collection duration and distance. The modeled plume behavior can then be combined with external information about sampler design to optimize sample durations in a sampling network.

CTBT↗
DOE OSTI2013

Solid Phase Characterization of Tank 241-C-108 Residual Waste Solids Samples

This report presents the results for solid phase characterization (SPC) of solid samples removed from tank 241-C-108 (C-108) on August 12-13,2012, using the off-riser sampler. Samples were received at the 222-S Laboratory on August 13 and were described and photographed. The SPC analyses that were performed include scanning electron microscopy (SEM) using the ASPEX(R)l scanning electron microscope, X-ray diffraction (XRD) using the Rigaku(R) 2 MiniFlex X-ray diffractometer, and polarized light microscopy (PLM) using the Nikon(R) 3 Eclipse Pol optical microscope. The SEM is equipped with an energy dispersive X-ray spectrometer (EDS) to provide chemical information. Gary A. Cooke conducted the SEM analysis, John A. Pestovich performed the XRD analysis, and Dr. Heinz J. Huber performed the PLM examination. The results of these analyses are presented here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Petascale Hierarchical Modeling VIA Parallel Execution

The research allows more effective model building. By allowing researchers to fit complex models to large datasets in a scalable manner, our algorithms and software enable more effective scientific research. In the new area of “big data,” it is often necessary to fit “big models” to adjust for systematic differences between sample and population. For this task, scalable and efficient model-fitting tools are needed, and these have been achieved with our new Hamiltonian Monte Carlo algorithm, the no-U-turn sampler, and our new C++ program, Stan. In layman’s terms, our research enables researchers to create improved mathematical modes for large and complex systems.

97 MATHEMATICS AND COMPUTING↗