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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 91 records · Page 5

Dark Energy Survey year 1 results: Joint analysis of galaxy clustering, galaxy lensing, and CMB lensing two-point functions

We perform a joint analysis of the auto and cross-correlations between three cosmic fields: the galaxy density field, the galaxy weak lensing shear field, and the cosmic microwave background (CMB) weak lensing convergence field. These three fields are measured using roughly 1300 sq. deg. of overlapping optical imaging data from first year observations of the Dark Energy Survey (DES) and millimeter-wave observations of the CMB from both the South Pole Telescope Sunyaev-Zel’dovich survey and Planck. We present cosmological constraints from the joint analysis of the two-point correlation functions between galaxy density and galaxy shear with CMB lensing. We test for consistency between these measurements and the DES-only two-point function measurements, finding no evidence for inconsistency in the context of flat Λ CDM cosmological models. Performing a joint analysis of five of the possible correlation functions between these fields (excluding only the CMB lensing autospectrum) yields S 8 ≡ σ 8 $\sqrt{Ω_{m}}/0.3$ = 0.782$^{+0.019}_{-0.025}$ and Ω m = 0.260$^{+0.029}_{-0.019}$. We test for consistency between these five correlation function measurements and the Planck -only measurement of the CMB lensing autospectrum, again finding no evidence for inconsistency in the context of flat Λ CDM models. Combining constraints from all six two-point functions yields S 8 = 0.776$^{+0.014}_{-0.021}$ and Ω m = 0.271$^{+0.022}_{-0.016}$. These results provide a powerful test and confirmation of the results from the first year DES joint-probes analysis.

Abbott, T. M. C.↗

Using a Simple Binomial Model to Assess Improvement in Predictive Capability: Sequential Bayesian Inference, Hypothesis Testing, and Power Analysis

We present a Bayesian statistical methodology for identifying improvement in predictive simulations, including an analysis of the number of (presumably expensive) simulations that will need to be made in order to establish with a given level of confidence that an improvement has been observed. Our analysis assumes the ability to predict (or postdict) the same experiments with legacy and new simulation codes and uses a simple binomial model for the probability, {theta}, that, in an experiment chosen at random, the new code will provide a better prediction than the old. This model makes it possible to do statistical analysis with an absolute minimum of assumptions about the statistics of the quantities involved, at the price of discarding some potentially important information in the data. In particular, the analysis depends only on whether or not the new code predicts better than the old in any given experiment, and not on the magnitude of the improvement. We show how the posterior distribution for {theta} may be used, in a kind of Bayesian hypothesis testing, both to decide if an improvement has been observed and to quantify our confidence in that decision. We quantify the predictive probability that should be assigned, prior to taking any data, to the possibility of achieving a given level of confidence, as a function of sample size. We show how this predictive probability depends on the true value of {theta} and, in particular, how there will always be a region around {theta} = 1/2 where it is highly improbable that we will be able to identify an improvement in predictive capability, although the width of this region will shrink to zero as the sample size goes to infinity. We show how the posterior standard deviation may be used, as a kind of 'plan B metric' in the case that the analysis shows that {theta} is close to 1/2 and argue that such a plan B should generally be part of hypothesis testing. All the analysis presented in the paper is done with a general beta-function prior for {theta}, enabling sequential analysis in which a small number of new simulations may be done and the resulting posterior for {theta} used as a prior to inform the next stage of power analysis.

42 ENGINEERING↗

Cosmology From CMB Lensing and Delensed EE Power Spectra Using 2019-2020 SPT-3G Polarization Data

From CMB polarization data alone we reconstruct the CMB lensing power spectrum, comparable in overall constraining power to previous temperature-based reconstructions, and an unlensed E -mode power spectrum, with clear detections of the third through tenth acoustic peaks. The observations, taken in 2019 and 2020 with the South Pole Telescope (SPT) and the SPT-3G camera, cover 1500 deg 2 at 95, 150, and 220 GHz with arcminute resolution and roughly 4.9 µ K-arcmin coadded noise in polarization. The power spectrum estimates, together with systematic parameter estimates and a joint covariance matrix, follow from a Bayesian analysis using the Marginal Unbiased Score Expansion (MUSE) method. The E -mode spectrum at ℓ > 2000 and lensing spectrum at L > 350 are the most precise to date. Assuming the ΛCDM model, and using only these SPT data and priors on τ and absolute calibration from Planck, we find H 0 = 66.81 ± 0.81 km/s/Mpc, comparable in precision to the Planck determination and in 5.4 σ tension with the most precise H 0 inference derived via the distance ladder. We also find S 8 ≡ σ 8 (Ω m /0.3) 0.5 = 0.850 ± 0.017, providing further independent evidence of a slight tension with low-redshift structure probes. The ΛCDM model provides a good simultaneous fit to the combined Planck, ACT, and SPT data, and thus passes a powerful test. Combining these CMB datasets with BAO observations, we explore extensions to the ΛCDM model. We find that the effective number of neutrino species, spatial curvature, and primordial helium fraction are consistent with standard model values, and that the 95% confidence upper limit on the neutrino mass sum is 0.075 eV, close to the minimum sum expected from observations of solar and atmospheric neutrino oscillations. The SPT data are consistent with the somewhat weak (< 3 σ ) preference for excess lensing power seen in Planck and ACT data relative to predictions of the ΛCDM model given the combined Planck, ACT, and BAO data sets. Finally, we also detect at greater than 3 σ the influence of non-linear evolution in the CMB lensing power spectrum and discuss it in the context of the S 8 tension. Forthcoming SPT-3G analyses will feature deeper and wider observations in temperature and polarization, providing even tighter constraints and more powerful tests of the ΛCDM model.

79 ASTRONOMY AND ASTROPHYSICS↗

Centrality and pseudorapidity dependence of the transverse energy density in p Pb collisions at s N N = 5.02 TeV

The almost hermetic coverage of the CMS detector is used to measure the distribution of transverse energy, E T , over 13.2 units of pseudorapidity, η, for p Pb collisions at a center-of-mass energy per nucleon pair of s NN = 5.02 TeV. The huge angular acceptance exploits the fact that the CASTOR calorimeter at -6.6 < η < -5.2 is effectively present on both sides of the colliding system because of a switch in the proton-going and lead-going beam directions. This wide acceptance enables the study of correlations between well-separated angular regions and makes the measurement a particularly powerful test of event generators. For minimum bias p Pb collisions the maximum value of dE T / d η is 22GeV, which implies an E T per participant nucleon pair comparable to that of peripheral PbPb collisions at s NN =2.76TeV. The increase of dE T / d η with centrality is much stronger for the lead-going side than for the proton-going side. The η dependence of dE T / d η is sensitive to the η range in which the centrality variable is defined. Several modern generators are compared to these results but none is able to capture all aspects of the η and centrality dependence of the data and the correlations observed between different η regions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ultrasonic Measurements of Temperature Distribution in Extreme Environments: Results of Power Plant Testing

The most hardened insertion sensors do not perform reliably in extreme environmental conditions. We address this problem by developing an ultrasonic thermometry system for the measurements of segmental temperature distributions (MSTD) in solid materials and, specifically, across containments of energy conversion processes. The MSTD approach uses an echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features. In pulse-echo mode, these features produce a train of echoes in response to an external pulse of ultrasonic excitation created and acquired by a transducer located outside the extreme environment. The delays between the echoes encode the information on the temperature distribution in the corresponding segments of the ultrasonic propagation path, which we use to reconstruct an unknown temperature profile. This note describes the preliminary results and initial experience in applying the developed MSTD ultrasonic thermometry system to the measurements of temperatures in a utility-scale 500MW coal-fired boiler.

John, Mason↗

LDES-Sizing-and-siting-model (Power grid test cases for long-duration energy storage (LDES) siting) [SWR-25-75]

This repository contains code and data for performing a siting analysis of long-duration energy storage (LDES) in the 5-bus and RTS systems using the Sienna suite developed by the National Renewable Energy Laboratory for production cost modeling (PCM). This analysis involves moving the LDES component to different buses in the system, running a simulation, and considering the production cost of the simulation. Different system configurations are also analyzed with these scripts (such as moving load or renewable dispatch generators to different buses) to observe the impacts the system configuration has on optimal siting. This repository contains three sub directories discussed below. Both the 5-bus and RTS systems have two different initial configurations for the renewable energy components in them, one that is predominantly PV-driven and one that is predominantly wind-driven. Sienna suite can be found here: https://github.com/NREL-Sienna

Cole, David [University of Wisconsin]↗

Power Performance Test Report for the U.S. Department of Energy 1.5-Megawatt Wind Turbine

The U.S. Department of Energy (DOE) acquired and installed a 1.5-megawatt (MW) wind turbine at the National Wind Technology Center (NWTC) at the National Renewable Energy Laboratory (NREL). This turbine (hereafter referred to as the DOE 1.5) is envisioned to become an integral part of the research initiatives for the DOE Wind Program, such as Atmosphere to Electrons (A2e). A2e is a multiyear DOE research initiative targeting significant reductions in the cost of wind energy through an improved understanding of the complex physics governing wind flow into and through wind farms. For more information, visit http://energy.gov/eere/wind/atmosphere-electrons. To validate new and existing high-fidelity simulations, A2e must deploy several experimental measurement campaigns across different scales. Proposed experiments include wind tunnel tests, scaled field tests, and large field measurement campaigns at operating wind plants. Data of interest includes long-term atmospheric data sets, wind plant inflow, intra-wind plant flows (e.g., wakes), and rotor loads measurements. It is expected that new, high-fidelity instrumentation will be required to successfully collect data at the resolutions required to validate the high-fidelity simulations.

17 WIND ENERGY↗

Robot-Powered Reliability Testing at NREL's ESIF

With auto manufacturers expected to roll out fuel cell electric vehicles in the 2015 to 2017 timeframe, the need for a reliable hydrogen fueling infrastructure is greater than ever. That's why the National Renewable Energy Laboratory (NREL) is using a robot in its Energy Systems Integration Facility (ESIF) to assess the durability of hydrogen fueling hoses, a largely untested-and currently costly-component of hydrogen fueling stations. The automated machine mimics the repetitive stress of a human bending and twisting the hose to refuel a vehicle-all under the high pressure and low temperature required to deliver hydrogen to a fuel cell vehicle's onboard storage tank.

08 HYDROGEN↗

Robot-Powered Reliability Testing at NREL's ESIF

With auto manufacturers expected to roll out fuel cell electric vehicles in the 2015 to 2017 timeframe, the need for a reliable hydrogen fueling infrastructure is greater than ever. That's why the National Renewable Energy Laboratory (NREL) is using a robot in its Energy Systems Integration Facility (ESIF) to assess the durability of hydrogen fueling hoses, a largely untested—and currently costly—component of hydrogen fueling stations. The automated machine mimics the repetitive stress of a human bending and twisting the hose to refuel a vehicle—all under the high pressure and low temperature required to deliver hydrogen to a fuel cell vehicle's onboard storage tank.

42 ENGINEERING↗