Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “science”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

redMaGiC: Selecting luminous red galaxies from the DES Science Verification data

Here, we introduce redMaGiC, an automated algorithm for selecting luminous red galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the colour cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photo-zs are very nearly as accurate as the best machine learning-based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalogue sampling the redshift range z ϵ [0.2, 0.8]. Our fiducial sample has a comoving space density of 10 –3 (h –1 Mpc) –3 , and a median photo-z bias (zspec – zphoto) and scatter (σz/(1 + z)) of 0.005 and 0.017, respectively. The corresponding 5σ outlier fraction is 1.4 per cent. We also test our algorithm with Sloan Digital Sky Survey Data Release 8 and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1 per cent level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing

We measure the cross-correlation between weak lensing of galaxy images and of the cosmic microwave background (CMB). The effects of gravitational lensing on different sources will be correlated if the lensing is caused by the same mass fluctuations. We use galaxy shape measurements from 139 deg(2) of the Dark Energy Survey (DES) Science Verification data and overlapping CMB lensing from the South Pole Telescope (SPT) and Planck. The DES source galaxies have a median redshift of z(med) similar to 0.7, while the CMB lensing kernel is broad and peaks at z similar to 2. The resulting cross-correlation is maximally sensitive to mass fluctuations at z similar to 0.44. Assuming the Planck 2015 best-fitting cosmology, the amplitude of the DESxSPT cross-power is found to be A(SPT) = 0.88 +/- 0.30 and that from DESxPlanck to be A(Planck) = 0.86 +/- 0.39, where A = 1 corresponds to the theoretical prediction. These are consistent with the expected signal and correspond to significances of 2.9 sigma and 2.2 sigma, respectively. We demonstrate that our results are robust to a number of important systematic effects including the shear measurement method, estimator choice, photo-z uncertainty and CMB lensing systematics. We calculate a value of A = 1.08 +/- 0.36 for DESxSPT when we correct the observations with a simple intrinsic alignment model. With three measurements of this cross-correlation now existing in the literature, there is not yet reliable evidence for any deviation from the expected LCDM level of cross-correlation. We provide forecasts for the expected signal-to-noise ratio of the combination of the five-year DES survey and SPT-3G.

Kirk, D.↗
DOE OSTI2016

Galaxy bias from the Dark Energy Survey Science Verification data: Combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ~116 deg 2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1σ error bars in four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2–0.4), 0.97 ± 0.15 (z = 0.4–0.6), 1.38 ± 0.39 (z = 0.6–0.8), and 1.45 ± 0.56 (z = 0.8–1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Moreover, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Weak Lensing Analysis of SPT selected Galaxy Clusters using Dark Energy Survey Science Verification Data

We present weak-lensing (WL) mass constraints for a sample of massive galaxy clusters detected by the South Pole Telescope (SPT) via the Sunyaev-Zel'dovich effect (SZE). We use griz imaging data obtained from the Science Verification (SV) phase of the Dark Energy Survey (DES) to fit the WL shear signal of 33 clusters in the redshift range 0.25 <= z <= 0.8 with NFW profiles and to constrain a four-parameter SPT mass-observable relation. To account for biases in WL masses, we introduce a WL mass to true mass scaling relation described by a mean bias and an intrinsic, lognormal scatter. We allow for correlated scatter within the WL and SZE mass-observable relations and use simulations to constrain priors on nuisance parameters related to bias and scatter from WL. We constrain the normalization of the zeta-M-500 relation, A(SZ) = 12.0(-6.7)(+2.6) when using a prior on the mass slope B-SZ from the latest SPT cluster cosmology analysis. Without this prior, we recover A(SZ) = 10.8(-5.2)(+2.3) and B-SZ = 1.30(-0.44)(+0.22). Results in both cases imply lower cluster masses than measured in previous work with and without WL, although the uncertainties are large. The WL derived value of B-SZ is approximate to 20 per cent lower than the value preferred by the most recent SPT cluster cosmology analysis. The method demonstrated in this work is designed to constrain cluster masses and cosmological parameters simultaneously and will form the basis for subsequent studies that employ the full SPT cluster sample together with the DES data.

cosmology: observations↗
DOE OSTI2024

Towards FAIR Workflows for Federated Experimental Sciences

A de-centralized, peer-to-peer AI metadata framework is demonstrated which can enable end-to-end metadata & lineage tracking for distributed Machine Learning pipelines spanning edge, High Performance Computing, and cloud environments. With a specific example of end-to-end microscopy algorithm and datasets, the proposed method shows how to enable reproducibility, audit trail, provenance of metadata artifacts. The emerging needs of automation in experimental sciences, ML-centric workflows, and FAIR metadata management across federated compute environments is addressed.

machine learning↗
DOE OSTI2025

Data for NB6 HBRR Science Design ORNL/TM-2025/3807

Data for the report (ORNL/TM-2025/3807) that describes the calculations and the Monte Carlo Ray Tracing simulations performed using the McStas package to determine the coatings and geometry for the NB-6 guide. It provides the information to inform the mechanical design, validation tests and verification that it meets the science requirements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Science and Engineering Alliance, Inc. (SEA) Activities to Increase Participation of Students from Underrepresented Groups in Science, Technology, Engineering and Mathematics (STEM) Programs

Using its 22 years of experience in developing the STCRP and recent success with the support of District of Columbia (DC) high school and middle school participation in the DOE Regional Science Bowl, SEA continues to strengthen and expand these activities. Considerable attention has been given over the years, to streamlining and executing all tasks associated with planning and implementing a successful program, with primary emphasis on the DOE Washington, D.C. Regional Science Bowl. With success in working with the DC high schools and middle schools, HBCUs and other MSIs, coupled with experience interacting with DOE national laboratories like Lawrence Livermore National Laboratory (LLNL), SEA provides a strong basis for adding value to the DOE’s diversity efforts. A faculty development component was added to the program.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Experimental Physical Sciences Vistas Performance through Science Winter 2017

This issue of Experimental Physical Sciences Vistas focuses on the integrated science that plays a critical role in Los Alamos National Laboratory’s support of the nation’s nuclear deterrent. I hope you will enjoy reading about these accomplishments, opportunities, and challenges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Predictive Science ASC Alliance Program (PSAAP) II: 2018 Review of the Carbon Capture Multidisciplinary Science Center (CCMSC) at the University of Utah

The review team convened at the University of Utah March 7-8, 2018, to review the Carbon Capture Multidisciplinary Science Center (CCMSC) funded by the 2 nd Predictive Science ASC Alliance Program (PSAAP II). Center leadership and researchers made very clear and informative presentations, accurately portraying their work and successes while candidly discussing their concerns and known areas in need of improvement.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Factual Document for the Basic Energy Sciences Workshop on Basic Research Needs for Catalysis Science to Transform Energy Technologies, May 8–10, 2017

Technical Perspectives Factual Document: This is a resource document for the Basic Energy Sciences Workshop on Basic Research Needs for Catalysis Science to Transform Energy Technologies on May 8–10, 2017. The following topics are discussed: Diversified Energy Feedstocks and Carriers, Novel Approaches to Energy Transformations, and Advanced Chemical Conversion Approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

NNSA-IAEC Science Area V Environmental ISR: Waste Management and Subsurface Science (Final Report FY18-FY20)

In August 2017, the U.S. National Nuclear Security Administration (NNSA) and the Israel Atomic Energy Commission (IAEC) launched a joint waste management program to evaluate the feasibility of siting a radioactive waste repository at intermediate depths in Israel. The bilateral collaboration involves three National Laboratories (LLNL, LANL, and Sandia), and the Nuclear Research Center, Negev, Geological Survey of Israel, and Ben Gurion University in Israel. This research is designed to assist with the evaluation of locations for an intermediate nuclear waste repository in Israel. This final report is a high-level summary of the results from the past three years by the team that worked on the WM-2: Radionuclide colloid-facilitated transport in fractured carbonate rock project for Science Area V, Environmental ISR: Subsurface Science and Waste Management. We have completed all of our tasks and met all of our milestones. MW-2 had three integrated tasks. Task 1 was laboratory experiments investigating colloid transport of radionuclides in natural fractured carbonate rocks from the Avdat formation, Israel. Task 2 was field experiments injecting radionuclide analogues pre-sorbed to clay colloids into fractured carbonate rock, and task 3 was numerical modeling of laboratory and field experimental results to assess the importance of colloids in the migration of relevant radionuclides. This task was incorporated into tasks 1 and 2. A 4 th task was initiated in FY20, to investigate the role of organics in facilitating radionuclide transport under the same conditions explored in task 1 due to the high organic content of the rocks being investigated for the immediate borehole locations. Preliminary results will be summarized here and the work will continue in FY21-23. The overall objective of this research is to evaluate the role of colloids (naturally occurring < 1 micron particles) in facilitating the transport of long-lived radionuclides from a nuclear waste repository situated in fractured carbonate rocks. Currently little data exists on radionuclide transport in carbonate rocks, but this is the main rock type available for siting a repository in Israel. Laboratory experiments were carried out in both Israel and the U.S., field experiments have taken place in Israel, and reactive transport modeling involved LLNL, LANL and Israel partner institutions. LLNL hosted a graduate student, Emily Tran, from Ben Gurion University in FY18 and FY19 and much of the work presented here was part of her PhD research.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Basic Energy Sciences Roundtable: Foundational Science for Carbon-Neutral Hydrogen Technologies

Basic research to identify and understand the fundamental principles governing hydrogen processes is essential for achieving a carbon-neutral, hydrogen-based energy and chemical infrastructure. In August 2021, the Office of Basic Energy Sciences (BES)—in coordination with the US Department of Energy (DOE) technology Offices of Energy Efficiency and Renewable Energy, Fossil Energy and Carbon Management, and Nuclear Energy—held a roundtable titled, “Foundational Science for Carbon-Neutral Hydrogen Technologies,” to discuss the scientific and technical barriers for carbon-neutral hydrogen production, storage, and utilization. Four priority research opportunities (PROs) were identified to address these scientific and technical challenges and accelerate progress toward the realization of energy-efficient, carbon-neutral cycles for hydrogen processes. The PROs are as follows: Discover and Control Materials and Chemical Processes to Revolutionize Electrolysis Systems; Manipulate Hydrogen Interactions to Harness the Full Potential of Hydrogen as a Fuel; Elucidate the Structure, Evolution, and Chemistry of Complex Interfaces for Energy- and Atom-Efficiency; and Understand and Limit Degradation Processes to Enhance the Durability of Hydrogen Systems.

08 HYDROGEN↗
DOE OSTI2020

Replicating Machine Learning Experiments in Materials Science

Transparency and reproducibility are important aspects of validation for Machine Learning (ML) models that are not fully understood and applies independently of the application domain.We offer a case study of reproducibility that highlights the challenges encountered when attempting to reproduce analyzes obtained with Machine Learning methods in materials informatics. Our study explores prediction results obtained with ML models and issues in training data serving as input. We discuss challenges related to theory-driven and numerical errors in training data, lack of reproducibility across platforms and versions, and effects of randomness when varying hyperparameters. In addition to model accuracy, a main metric of interest in the ML community, our results show that model sensitivity may be equally important for applying ML in domain applications such a materials science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

OBSERVATION AND CONFIRMATION OF SIX STRONG-LENSING SYSTEMS IN THE DARK ENERGY SURVEY SCIENCE VERIFICATION DATA

We report the observation and confirmation of the first group- and cluster-scale strong gravitational lensing systems found in Dark Energy Survey data. Through visual inspection of data from the Science Verification season, we identified 53 candidate systems. We then obtained spectroscopic follow-up of 21 candidates using the Gemini Multi-object Spectrograph at the Gemini South telescope and the Inamori-Magellan Areal Camera and Spectrograph at the Magellan/Baade telescope. With this follow-up, we confirmed six candidates as gravitational lenses: three of the systems are newly discovered, and the remaining three were previously known. Of the 21 observed candidates, the remaining 15 either were not detected in spectroscopic observations, were observed and did not exhibit continuum emission (or spectral features), or were ruled out as lensing systems. The confirmed sample consists of one group-scale and five galaxy-cluster-scale lenses. The lensed sources range in redshift z ∼ 0.80–3.2 and in i -band surface brightness i {sub SB} ∼ 23–25 mag arcsec{sup −2} (2″ aperture). For each of the six systems, we estimate the Einstein radius θ {sub E} and the enclosed mass M {sub enc}, which have ranges θ {sub E} ∼ 5″–9″ and M {sub enc} ∼ 8 × 10{sup 12} to 6 × 10{sup 13} M {sub ⊙}, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Mapping and simulating systematics due to spatially-varying observing conditions in DES science verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.

79 ASTRONOMY AND ASTROPHYSICS↗