Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reference Model 2”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Measurement of the Z boson invisible width at $\sqrt{s}=13$ TeV with the ATLAS detector

A measurement of the invisible width of the Z boson using events with jets and missing transverse momentum is presented using 37 fb -1 of 13 TeV proton–proton data collected by the ATLAS detector in 2015 and 2016. The ratio of Z → inv to Z → ℓℓ events, where inv refers to non-detected particles and ℓ is either an electron or a muon, is measured and corrected for detector effects. Events with at least one energetic central jet with p T ≥ 110 GeV are selected for both the Z → inv and Z → ℓℓ final states to obtain a similar phase space in the ratio. The invisible width is measured to be 506 ± 2 (stat.) ± 12 (syst.) MeV and is the single most precise recoil-based measurement. The result is in agreement with the most precise determination from LEP and the Standard Model prediction based on three neutrino generations.

13000 GeV-cms↗
DOE OSTI2026

ARC disruption physics and strategy

Commonwealth Fusion Systems (CFS) plans to operate a tokamak power plant called ARC in the early 2030s. Tokamak plasmas have stability limits that, if crossed, lead to a rapid termination of the plasma, referred to as a disruption. Disruptions pose a melt risk to the first wall resulting from thermal and non-thermal particle heat fluxes, and an electromagnetic loading risk on all metal components within the equilibrium coils. A comprehensive set of models is used herein to provide an assessment of both mitigated and unmitigated ARC disruption loads. A preliminary massive gas injection system is baselined and a runaway electron mitigation coil option is proposed to close possible gaps in the baseline. It is predicted that all ARC disruption loads are within a factor of 2 of the disruption loads in SPARC, a tokamak presently under construction by CFS, and therefore SPARC provides an opportunity to calibrate models, test solutions and inform the design of ARC. The goal for ARC is disruption-free operation, however, the pragmatic design target is to withstand one mitigated disruption per day, and to restart the plasma following mitigation in tens of seconds without interrupting the power output. Unmitigated disruptions must be rare, and experience with unmitigated disruption impacts in SPARC will better define what rare means. The implications of this strategy for plasma disruptivity and disruption prediction are discussed, and operating the ARC scenario on SPARC is expected to refine the ARC final design and operational plan.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Theoretical study of IR and photoelectron spectra of small gallium-arsenide clusters

Relative stabilities of small Ga{sub n}As{sub m} clusters, as well as their structural electronic and vibrational properties, were computed and analysed using a CCSD(T) reference method since experimental data in this area are sparse or unknown. With the aim of investigating larger clusters, we explored several DFT functionals and basis sets able to mimic the reliable CCSD(T) approach. Among them, the PBE0/SBKJC+sp,d appears as the most efficient to describe the structural and vibrational properties since average differences of about 0.042Å and 5.1cm{sup −1} were obtained for bond lengths and fundamental vibrational frequencies, respectively for the first small clusters [1] of the series found from our GSAM method [2]. As further test, this model is used in order to investigate and revisit an experimental IR spectrum of Ga{sub n}As{sub m} mixture previously published by Li et al. [3]. More complicated is the difficulty which arises in the electronic description due to the presence of numerous low lying electronic states nearly degenerated to correctly describe the electronic structure. The case of Ga{sub 2}As will be discussed and the photoelectron spectra of the Ga{sub 2}As anion reanalyzed on the ground of our calculations [4] comparatively to the experimental spectra obtained by Neumark and co-workers [5].

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Bottom Fixed Platform Dynamics Models Assessing Surface Ice Interactions for Transitional Depth Structures in the Great Lakes: FAST8 – IceDyn

To create long-term solutions for offshore wind turbines in a variety of environmental conditions, CAE tools are needed to model the design-driving loads that interact with an offshore wind turbine system during operation. This report describes our efforts in augmenting existing CAE tools used for offshore wind turbine analysis with a new module that can provide simulation capabilities for ice loading on the system. This augmentation was accomplished by creating an ice-loading module coupled to FAST8, the CAE tool maintained by the NREL for simulating land-based and offshore wind turbine dynamics. The new module includes both static and dynamic ice loading that can be applied during a dynamic simulation of the response of an offshore wind turbine. The ice forces can be prescribed, or influenced by the structure’s compliant response, or by the dynamics of both the structure and the ice floe. The new module covers ice failure modes of spalling, buckling, crushing, splitting, and bending. The supporting structure of wind turbines can be modeled as a vertical or sloping form at the waterline. The Inward Battered Guide Structure (IBGS) foundation designed by Keystone Engineering for the Great Lakes was used to study the ice models coupled to FAST8. The IBGS foundation ice loading simulations in FAST8 were compared to the baseline simulation case without ice loading. The ice conditions reflecting those from Lake Huron at Port Huron and Lake Michigan at North Manitou were studied under near rated wind speed of 12 m/s for the NREL 5-MW reference turbine. Simulations were performed on ice loading models 1 through 4 and ice model 6 with their respective sub-models. The purpose of ice model 5 is to investigate ice loading on sloping structures such as ice-cones on a monopile and is not suitable for multi-membered jacketed structures like the IBGS foundation. The key response parameters from the simulations, shear forces and moments from the tower base and IBGS foundation base, were compared. Ice models 1 and 6 do not significantly affect the tower fore-aft shear and moment. However, ice model 2 (dynamic analyses), model 3 (random ice loading), and model 4 (multiple ice failure zone loading) show increased effect on the tower fore-aft shear and moment with significant effect from ice model 3.1. In general ice loading creates large reaction forces and moments at the base of the IBGS foundation; the largest occurred in model 1.1 (steady creep ice indentation loading) followed by model 3.1 (random creep ice indentation loading). In general the power production from the ice loading cases had little deviation from the baseline case without ice loading. For ultimate limit state (ULS), ice model 1.1 ice and 3.1 appear to be the ice most critical models to consider at an early stage of design. Ice model 4 is an important tool for assessing structural fatigue.

17 WIND ENERGY↗
DOE OSTI2021

A Spatially Explicit Individual-Based Modeling Approach to Evaluate the Cumulative Effects of Wind Energy Development on the Greater Sage-Grouse: Sensitivity Analysis and Validation of Key Parameters

To address the need for an approach to evaluate cumulative ecological impacts of wind energy development, particularly those on critical wildlife habitats and species, the authors developed a proof-of-concept, landscape-based, spatially explicit individual-based modeling (IBM) framework for populations of the greater sage-grouse (Centrocercus urophasianus) in Albany County, Wyoming, based on published and other available information on the life history of the species. This sage-grouse IBM estimates the spatial and temporal movements of sage-grouse based on modeled effects of habitat characteristics and developments on sage-grouse condition, survivorship, and reproduction. After completing the initial version of the model, we conducted a series of sensitivity analyses of key model parameters and validation of lek occurrences and spatial distributions to better understand performance of the model relative to observed values of important life history characteristics. The parameter sensitivity analysis was conducted as a series of one-factor-at-a-time tests in which the values of selected parameters were individually varied to evaluate the corresponding effects on model output. We examined the model’s response to changes in parameter values to gain insight into the overall robustness of the model, identify key driver parameters, and initiate qualitative validation. Five functions selected for sensitivity analyses were (1) the rate of change in body condition in relationship to habitat suitability index (HSI) of occupied habitat (condition change rate), (2) the effect of competition between individuals with overlapping home ranges expressed as a percentage reduction in HSI (competition factor), (3) value of condition at which survivorship probability is equal to zero (zero survivorship condition), (4) the relationship between female body condition and clutch size, and (5) the relationship between female body condition and nest success. We varied the parameter values to be tested for the sensitivity analysis around the original value used in the model (i.e., tested values were higher and lower than the model’s original value) to examine the effect of this variation on the predicted output of the model. Model outputs evaluated in the sensitivity analysis included (1) predicted age-class distribution (as measured by the percentage of immature individuals within the population); (2) predicted sex ratio; (3) predicted age-sex class distribution (percent of population in each of six age-sex classes, i.e., male and female juveniles, yearlings, and adults); (4) lifespan; (5) population size; and (6) spatial distribution. Of the five parameters analyzed, condition change rate, survivorship, clutch size, and nest success did not substantially affect any of the evaluated model outputs. For the predicted age-class distribution, the percentage of immature individuals predicted by the model for these four parameters ranged from 61.9% to 65.0%, which was reasonable with respect to the reference values of 51.4 to 57.8% in published studies. The ratio of females to males ranged from 1.09 to 1.14, which was comparable to the reference values of 1.2 to 3.0 presented in an existing study. The predicted mean lifespan ranged from 1.62 to 1.74 years, which appears to be reasonable with respect to the reference values of 0.9 to 1.1 years for sharp-tail grouse and greater prairie chickens presented by published studies. The predicted population size ranged from 1,877 to 3,140. This prediction would be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county. The predicted spatial distribution was not substantially affected by the parameter values examined. In our sensitivity analyses, the only tested parameter that had a noticeable effect on model output was competition factor. Over the range of values tested for this parameter, predicted population size exhibited the largest range (from 1,833 to 4,737) of all parameters tested. As the competition factor increased, the predicted population size decreased. This reflects the effect competition had on the number of individuals that could co occur in high-quality habitat patches. Despite this apparently significant effect, the range of values appears to be reasonable with respect to our estimate of 5,000 yearlings and adults, which was based on the USFWS estimate for the state of Wyoming scaled to the number of leks in the county.

17 WIND ENERGY↗
DOE OSTI2024

Inverse-Velocity Transformation Wall Model for Reacting Turbulent Hypersonic Boundary Layers

The present study builds on prior work by taking advantage of the novel framework proposed by Griffin et al. (hereafter referred to as the GFM) as a baseline. The model is progressively extended to multicomponent reacting mixtures, accounting for differential diffusion and finite-rate chemistry in a similar fashion to Di Renzo & Urzay and Di Renzo et al. The accuracy of the present approach, as well the prior model of Di Renzo & Urzay, is assessed in an a priori sense for the first time in a turbulent reacting boundary layer, using the boundary-layer data of Williams et al. Five species are included in the present analysis, i.e., N s = 5, namely N 2 , O 2 , NO, N and O, a neutral mixture most representative of dissociation/recombination phenomena for temperatures below 6000 K. A schematic of a flow over a wedge representative of the described configuration is presented in Figure 1. The brief is organized as follows: In Section 2, the wall-model equations and the computational framework are presented. In Section 3, the a priori results of the proposed model are described and compared to the extended EWM. Finally, in Section 4, some conclusions are offered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Optimizing Long-term Monitoring of Radiation Air Dose Rates - 19169

Radiation air dose rates near the Fukushima Daiichi Nuclear Power Plant (NPP) have been steadily decreasing over the past seven years since the accident in March 2011. After seven years, the radiation monitoring program is expected to transition from short-term emergency responses to long-term monitoring. The objectives of long-term monitoring are often different from early emergency responses, since extensive data accumulation has led to an understanding of contaminant distributions and mobility. The main long-term monitoring objectives are (1) to confirm system stability and the continuing reduction of contaminant and hazard levels, (2) to provide assurance for the public, (3) to accumulate the basic datasets for scientific knowledge and future preparation, and (4) to detect changes or anomalies in contaminant mobility (if they occur), or any unexpected processes or events. In this work, we have developed a methodology for optimizing the sampling locations of radiation air dose-rate monitoring. Three steps are taken in order to determine sampling locations in a systematic manner: (1) prioritizing the critical locations, such as schools or regulatory requirement locations, (2) diversifying locations across the key environmental controls that are known to influence contaminant mobility and distributions, and (3) capturing the heterogeneity of radiation air dose rates across the domain. In the second step, we use a Gaussian mixture model to identify the representative locations in multiple environmental variables, such as elevation and land-cover types. In the third step, we use a Gaussian process model to capture and estimate the heterogeneity of air dose rates across the domain. We use the integrated dose-rate map from the Bayesian geostatistical method as the reference map and distribute the sampling in such a way as to capture the heterogeneity of the reference map. Although we assume hypothetical sets of measurement locations to evaluate the performance of the methodology and algorithms, we have demonstrated this approach using real, spatially extensive datasets, including the integrated air-dose-rate map of 2016. Our results have shown that this approach allows us to add sampling locations in a systematic manner. Increasing the number of sampling locations can better capture the heterogeneity of dose rates, although the estimation error does not decrease further after a certain number of samples. We have also found that when there are restrictions such as pre-existing monitoring locations or the ones along roads, the spatial estimation becomes poor even with the same number of monitoring locations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

SPT-3G D1: Quadratic-Estimator CMB Lensing Reconstruction and Cosmology

We present a map of the cosmic microwave background (CMB) lensing potential reconstructed from observations taken during the 2019 and 2020 seasons with the third-generation camera on the South Pole Telescope (SPT), covering the $1500\,{\rm deg}^{2}$ SPT-3G Main field, referred to as the SPT-3G D1 dataset. From the multi-frequency temperature and polarization data, we reconstruct the CMB lensing field using a quadratic estimator that jointly accounts for the $T$, $E$, and $B$ fields and their covariance. The resulting lensing map is dominated by polarization information for $L \lesssim 600$ and provides the highest signal-to-noise measurement per mode reported to date. With nuisance parameters fixed to their best-fit values, we measure a lensing amplitude consistent with unity at $2\%$ precision relative to the $Λ$CDM model that best fits the combined Planck, ACT DR6, and SPT-3G D1 $TT/TE/EE$ likelihoods (${\rm CMB}_{\rm SPA}$). We further measure the structure-growth parameter $σ_{8}Ω_{\rm m}^{0.25}$ to be $0.6046\pm0.0096$ from the SPT-3G D1 lensing spectrum alone and $0.6020\pm0.0084$ when combined with ACT DR6 and Planck PR4 CMB lensing. By further combining this with ${\rm CMB}_{\rm SPA}$ and the latest DESI DR2 BAO data, we obtain $\sum m_ν < 0.072\,\mathrm{eV}$ (95% C.L.) when allowing the neutrino mass to vary within $Λ$CDM. Compared with previous work, the better agreement of our measurement with DESI DR2 BAO yields both this relaxed upper bound and reduced ($\mathord{\sim}2σ$) preferences for nonzero spatial curvature and for deviations of $(w_0,w_a)$ from the $Λ$CDM expectation. When we combine CMB lensing with the DES Y3 3$\times$2pt analysis, we obtain $S_{8}=0.811\pm0.011$, corresponding to a $1.4\%$ constraint on the late-time clustering amplitude. This precision is competitive with that obtained from the primary CMB within $Λ$CDM.

Omori, Y. [Chicago U., Astron. Astrophys. Ctr.; Ch↗
DOE OSTI2021

CFM-ID 4.0: More Accurate ESI MS/MS Spectral Prediction and Compound Identification

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction, and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID’s ability to predict ESI-MS/MS spectra from compounds by: (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions, in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a webservice and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid

Wang, Fei↗
DOE OSTI2015

Charge-dependent many-body exchange and dispersion interactions in combined QM/MM simulations

Accurate modeling of the molecular environment is critical in condensed phase simulations of chemical reactions. Conventional quantum mechanical/molecular mechanical (QM/MM) simulations traditionally model non-electrostatic non-bonded interactions through an empirical Lennard-Jones (LJ) potential which, in violation of intuitive chemical principles, is bereft of any explicit coupling to an atom’s local electronic structure. This oversight results in a model whereby short-ranged exchange-repulsion and long-ranged dispersion interactions are invariant to changes in the local atomic charge, leading to accuracy limitations for chemical reactions where significant atomic charge transfer can occur along the reaction coordinate. The present work presents a variational, charge-dependent exchange-repulsion and dispersion model, referred to as the charge-dependent exchange and dispersion (QXD) model, for hybrid QM/MM simulations. Analytic expressions for the energy and gradients are provided, as well as a description of the integration of the model into existing QM/MM frameworks, allowing QXD to replace traditional LJ interactions in simulations of reactive condensed phase systems. After initial validation against QM data, the method is demonstrated by capturing the solvation free energies of a series of small, chlorine-containing compounds that have varying charge on the chlorine atom. The model is further tested on the S{sub N}2 attack of a chloride anion on methylchloride. Results suggest that the QXD model, unlike the traditional LJ model, is able to simultaneously obtain accurate solvation free energies for a range of compounds while at the same time closely reproducing the experimental reaction free energy barrier. The QXD interaction model allows explicit coupling of atomic charge with many-body exchange and dispersion interactions that are related to atomic size and provides a more accurate and robust representation of non-electrostatic non-bonded QM/MM interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Using a 1D Radially Symmetric Coda Envelope Model for Robust Moment Magnitude ( M w ) Estimation in Iraq’s Tectonically Diverse Zones

Robust estimation of moment magnitude (M w ) can be challenging for Iraq due to the strong lateral heterogeneity across diverse tectonic zones. We aim to improve moment magnitude estimation by investigating the reliability of using a 1D coda envelope model in diverse tectonic zones of different lateral effects and offer a way forward for reliable estimates of M w for small events that are difficult to waveform model. Iraq comprises two main tectonic zones: (1) the Outer platform, consisting of the northwestern Zagros fold-thrust belt and the Mesopotamian foredeep, and (2) the Inner Arabian platform which is overlain by the Iraqi desert. A simple 1D coda envelope model was used because coda waves have a low sensitivity to the source and path heterogeneity. Three separate coda calibrations were conducted to investigate the robustness of a single 1D calibration to fit the country: Whole-region calibration, Zagros calibration, and Mesopotamia calibration. In the whole-region calibration, we used stations from both the Zagros and Mesopotamia zones. In the two other calibration models, we used only stations that were in those particular zones. Ground-truth reference spectra derived from the coda spectral ratio method were used to constrain high-frequency site terms. There was no drastic difference when comparing the moment magnitudes calculated from the waveform modeling and the three calibration models. The results show that the 1D coda envelope model is a reliable method even for a region with diverse tectonic zones. Therefore, we recommend using the whole-region calibration model for moment magnitude estimation that provides more complete path coverage and avoids biases introduced by path correction failures. The proposed calibration is a fundamental step in updating the comprehensive earthquake catalog and probabilistic seismic hazard assessments for Iraq.

58 GEOSCIENCES↗
DOE OSTI2018

The Impact of Divalent Cations on the Enrichment of Soluble Saccharides in Primary Sea Spray Aerosol

Field measurements have shown that sub-micrometer sea spray aerosol (SSA) is significantly enriched in organic material, of which a large fraction has been attributed to soluble saccharides. Existing mechanistic models of SSA production struggle to replicate the observed enhancement of soluble organic material. Here, we assess the role for divalent cation mediated co-adsorption of charged surfactants and saccharides in the enrichment of soluble organic material in SSA. Using measurements of particle supersaturated hygroscopicity, we calculate organic volume fractions for molecular mimics of SSA generated from a Marine Aerosol Reference Tank. Large enhancements in SSA organic volume fractions (X org > 0.2) were observed for 50 nm dry diameter (d p ) particles in experiments where cooperative ionic interactions were favorable (e.g., palmitic acid, Mg 2+ , and glucuronic acid) at seawater total organic carbon concentrations (<1.15 mM C) and ocean pH. Significantly smaller SSA organic volume fractions (X org < 1.5 × 10 -3 ) were derived from direct measurements of soluble saccharide concentrations in collected SSA with dry diameters <250 nm, suggesting that organic enrichment is strongly size dependent. The results presented here indicate that divalent cation mediated co-adsorption of soluble organics to insoluble surfactants at the ocean surface may contribute to the enrichment of soluble saccharides in SSA. The extent to which this mechanism explains the observed enhancement of saccharides in nascent SSA depends strongly on the concentration, speciation, and charge of surfactants and saccharides in the sea surface microlayer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Characterizing half‐a‐degree difference: a review of methods for identifying regional climate responses to global warming targets

The Paris Agreement long‐term global temperature goal refers to two global warming levels: well below 2°C and 1.5°C above preindustrial. Regional climate signals at specific global warming levels, and especially the differences between 1.5°C and 2°C, are not well constrained, however. In particular, methodological challenges related to the assessment of such differences have received limited attention. This article reviews alternative approaches for identifying regional climate signals associated with global temperature limits, and evaluates the extent to which they constitute a sound basis for impacts analysis. Four methods are outlined, including comparing data from different greenhouse gas scenarios, sub‐selecting climate models based on global temperature response, pattern scaling, and extracting anomalies at the time of each global temperature increment. These methods have rarely been applied to compare 2°C with 1.5°C, but some demonstrate potential avenues for useful research. Nevertheless, there are methodological challenges associated with the use of existing climate model experiments, which are generally designed to model responses to different levels of greenhouse gas forcing, rather than to model climate responses to a specific level of forcing that targets a given level of global temperature change. Novel approaches may be required to address policy questions, in particular: to differentiate between half degree warming increments while accounting for different sources of uncertainty; to examine mechanisms of regional climate change including the potential for nonlinear responses; and to explore the relevance of time‐lagged processes in the climate system and declining emissions, and the resulting sensitivity to alternative mitigation pathways. WIREs Clim Change 2017, 8:e457. doi: 10.1002/wcc.457 This article is categorized under: Assessing Impacts of Climate Change > Scenario Development and Application

James, Rachel↗
DOE OSTI2013

Is the assumption of normality or log-normality for continuous response data critical for benchmark dose estimation?

Continuous responses (e.g. body weight) are widely used in risk assessment for determining the benchmark dose (BMD) which is used to derive a U.S. EPA reference dose. One critical question that is not often addressed in dose–response assessments is whether to model the continuous data as normally or log-normally distributed. Additionally, if lognormality is assumed, and only summarized response data (i.e., mean ± standard deviation) are available as is usual in the peer-reviewed literature, the BMD can only be approximated. In this study, using the “hybrid” method and relative deviation approach, we first evaluate six representative continuous dose–response datasets reporting individual animal responses to investigate the impact on BMD/BMDL estimates of (1) the distribution assumption and (2) the use of summarized versus individual animal data when a log-normal distribution is assumed. We also conduct simulation studies evaluating model fits to various known distributions to investigate whether the distribution assumption has influence on BMD/BMDL estimates. Our results indicate that BMDs estimated using the hybrid method are more sensitive to the distribution assumption than counterpart BMDs estimated using the relative deviation approach. The choice of distribution assumption has limited impact on the BMD/BMDL estimates when the within dose-group variance is small, while the lognormality assumption is a better choice for relative deviation method when data are more skewed because of its appropriateness in describing the relationship between mean and standard deviation. Additionally, the results suggest that the use of summarized data versus individual response data to characterize log-normal distributions has minimal impact on BMD estimates. - Highlights: • We investigate to what extent the distribution assumption can affect BMD estimates. • Both real data analysis and simulation study are conducted. • BMDs estimated using hybrid method are more sensitive to distribution assumption. • Summarized continuous data are adequate for BMD estimation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

2D photofragmentation LIF imaging of H 2 O 2 and HO 2 in the effluent of an atmospheric-pressure plasma jet: effects of solid and liquid interfaces

Two-dimensional (2D) absolute measurements of hydrogen peroxide (H 2 O 2 ) and approximations of the hydroperoxyl radical (HO 2 ) in the effluent of a COST Reference Microplasma Jet operated with a He/H 2 O feed gas are presented. Gas-phase densities are mapped using photofragmentation laser-induced fluorescence (PF-LIF) under three boundary conditions: open effluent, a solid target, and a liquid target. A novel method is presented for separating PF-LIF signals from H 2 O 2 and HO 2 using comparative measurements in oxygen-rich and oxygen-free environments to exploit the preferential formation of HO 2 in the presence of molecular oxygen. This separation strategy is supported by results from a plug-flow plasma chemistry model. Measured densities agree closely with model predictions in both magnitude and trend, while the 2D experimental distributions provide additional insight into the spatial dependencies of these species. In particular, the results show distinct differences in species transport depending on the target type: solid surfaces induce lateral deflection and reduced centerline densities, whereas liquid interfaces promote axial accumulation and higher near-axis concentrations.

atmospheric-pressure plasma jet (APPJ)↗
DOE OSTI2016

Updated constraints on velocity and momentum-dependent asymmetric dark matter

We present updated constraints on dark matter models with momentum-dependent or velocity-dependent interactions with nuclei, based on direct detection and solar physics. We improve our previous treatment of energy transport in the solar interior by dark matter scattering, leading to significant changes in fits to many observables. Based on solar physics alone, DM with a spin-independent q{sup 4} coupling provides the best fit to data, and a statistically satisfactory solution to the solar abundance problem. Once direct detection limits are accounted for however, the best solution is spin-dependent v{sup 2} scattering with a reference cross-section of 10{sup −35} cm{sup 2} (at a reference velocity of v{sub 0}=220 km s{sup −1}), and a dark matter mass of about 5 GeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

CO2 and CH4 Fluxes across Polygon Geomorphic Types, Barrow, Alaska, 2006-2010

Carbon flux data are reported as Net Ecosystem Exchange (NEE), Gross Ecosystem Exchange (GEE), Ecosystem Respiration (ER), and Methane (CH4) flux. Measurements were made at 82 plots across various polygon geomorphic classes at research sites on the Barrow Environmental Observatory (BEO), the Biocomplexity Experiment site on the BEO, and the International Biological Program (IBP) site a little west of the BEO. ArcView GIS files available of the Land Cover Type Classifications.This product is a compilation of data from 27 plots as presented in Lara et al. (2012), data from six plots presented in Olivas et al. (2010); and from 49 plots described in (Lara et al. 2014). Measurements were made during the peak of the growing seasons during 2006 to 2010. At each of the measurement plots (except Olivas et al., 2010) four different thicknesses of shade cloth were used to generate CO2 light response curves. Light response curves were used to normalize photosynthetically active radiation that is diurnally variable to a peak growing season average ~400 umolm-2sec-1. At the Olivas et al. (2010) plots, diurnal patterns were characterized by repeated sampling. CO2 measurements were made using a closed-chamber photosynthesis system and CH4 measurements were made using a photo-acoustic multi-gas analyzer. In addition, plot-level measurements for thaw depth (TD), water table depth (WTD), leaf area index (LAI), and normalized difference vegetation index (NDVI) are summarized by geomorphic polygon type. Citations can be found within the related references field. This dataset includes one zipped file, one pdf, and one .txt file.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).

54 ENVIRONMENTAL SCIENCES↗