SEARCH · Engineering Papers

Results for “distance measure”

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.

SourceResearch connectionFrom yearThrough year

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

At least 253 records · Page 14

All sources NASA NTRS DOE OSTI

DOE OSTI2025

HOD-dependent systematics for luminous red galaxies in the DESI 2024 BAO analysis

In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD models for LRGs, including the base 5-parameter vanilla model and two extensions to it, that we refer to as baseline and extended models. The baseline model is described by the 5 vanilla HOD parameters, an incompleteness factor and a velocity bias parameter, whereas the extended one also includes a galaxy assembly bias and a satellite profile parameter. We utilize the 25 dark matter simulations available in the AbacusSummit simulation suite at z=0.8 and generate mock catalogs for our different HOD models. To test the impact of the HOD modeling in the position of the BAO peak, we run BAO fits for all these sets of simulations and compare the best-fit BAO-scaling parameters α iso and α AP between every pair of HOD models. Furthermore, we do this for both Fourier and configuration spaces independently, using post-reconstruction measurements. We find a 3.3σ detection of HOD systematic for α AP in configuration space with an amplitude of 0.19%. For the other cases, we did not find a 3σ detection, and we decided to compute a conservative estimation of the systematic using the ensemble of shifts between all pairs of HOD models. By doing this, we quote a systematic with an amplitude of 0.07% in α iso for both Fourier and configuration spaces; and of 0.09% in α AP for Fourier space.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Machine learning materials properties with accurate predictions, uncertainty estimates, domain guidance, and persistent online accessibility

One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materials tailored for specific applications. However, realizing this vision requires both providing detailed uncertainty quantification (model prediction errors and domain of applicability) and making models readily usable. At present, it is common practice in the community to assess ML model performance only in terms of prediction accuracy (e.g. mean absolute error), while neglecting detailed uncertainty quantification and robust model accessibility and usability. Here, we demonstrate a practical method for realizing both uncertainty and accessibility features with a large set of models. We develop random forest ML models for 33 materials properties spanning an array of data sources (computational and experimental) and property types (electrical, mechanical, thermodynamic, etc). All models have calibrated ensemble error bars to quantify prediction uncertainty and domain of applicability guidance enabled by kernel-density-estimate-based feature distance measures. All data and models are publicly hosted on the Garden-AI infrastructure, which provides an easy-to-use, persistent interface for model dissemination that permits models to be invoked with only a few lines of Python code. We demonstrate the power of this approach by using our models to conduct a fully ML-based materials discovery exercise to search for new stable, highly active perovskite oxide catalyst materials.

domain of applicability↗

DOE OSTI2024

Red supergiant candidates for multimessenger monitoring of the next Galactic supernova

ABSTRACT We compile a catalogue of 578 highly probable and 62 likely red supergiants (RSGs) of the Milky Way, which represents the largest list of Galactic RSG candidates designed for continuous follow-up efforts to date. We match distances measured by Gaia DR3, 2MASS photometry, and a 3D Galactic dust map to obtain luminous bright late-type stars. Determining the stars’ bolometric luminosities and effective temperatures, we compare to Geneva stellar evolution tracks to determine likely RSG candidates, and quantify contamination using a catalogue of Galactic AGB in the same luminosity-temperature space. We add details for common or interesting characteristics of RSG, such as multistar system membership, variability, and classification as a runaway. As potential future core-collapse supernova progenitors, we study the ability of the catalogue to inform the Supernova Early Warning System (SNEWS) coincidence network made to automate pointing, and show that for 3D position estimates made possible by neutrinos, the number of progenitor candidates can be significantly reduced, improving our ability to observe the progenitor pre-explosion and the early phases of core-collapse supernovae.

Astronomy & Astrophysics↗

DOE OSTI2025

Information divergences to parametrize astrophysical uncertainties in dark matter direct detection

Astrophysical uncertainties in dark matter direct detection experiments are typically addressed by parametrizing the velocity distribution in terms of a few uncertain parameters that vary around some central values. Here we propose a method to optimize over all velocity distributions lying within a given distance measure from a central distribution. We discretize the dark matter velocity distribution as a superposition of streams and use a variety of information divergences to parametrize its uncertainties. With this, we bracket the limits on the dark matter–nucleon and dark matter–electron scattering cross sections, when the true dark matter velocity distribution deviates from the commonly assumed Maxwell-Boltzmann form. The methodology pursued is general and could be applied to other physics scenarios where a given physical observable depends on a function that is uncertain.

particle astrophysics↗

DOE OSTI2024

New Probe of the High- z Baryon Acoustic Oscillation Scale: BAO Tomography with CMB × LIM -Nulling Convergence

Standard rulers such as the baryon acoustic oscillation (BAO) scale serve as workhorses for precision tests of cosmology, enabling distance measurements that probe the geometry and expansion history of our Universe. Aside from BAO measurements from the cosmic microwave background (CMB), most standard ruler techniques operate at relatively low redshifts and depend on biased tracers of the matter density field. In a companion paper, we explored the scientific reach of nulling estimators, where CMB lensing convergence maps are cross-correlated with linear combinations of similar maps from line intensity mapping (LIM) to precisely null out the low-redshift contributions to CMB lensing. We showed that nulling estimators can be used to constrain the high redshift matter power spectrum and showed that this spectrum exhibits discernible BAO features. Here we propose using these features as a standard ruler at high redshifts that does not rely on biased tracers. Forecasting such a measurement at z ~ 5, we find that next-generation instruments will be able to constrain the BAO scale to 7.2% precision, while our futuristic observing scenario can constrain the BAO scale to 4% precision. In conclusion, this constitutes a fundamentally new kind of BAO measurement during early epochs in our cosmic history.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

FLIMJ: An open-source ImageJ toolkit for fluorescence lifetime image data analysis

In the field of fluorescence microscopy, there is continued demand for dynamic technologies that can exploit the complete information from every pixel of an image. One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM). FLIM allows for the measurement of how long a fluorophore stays in an excited energy state, and this measurement is affected by changes in its chemical microenvironment, such as proximity to other fluorophores, pH, and hydrophobic regions. This ability to provide information about the microenvironment has made FLIM a powerful tool for cellular imaging studies ranging from metabolic measurement to measuring distances between proteins. The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing. To address this need, we have created FLIMJ, an ImageJ plugin and toolkit that allows for easy use and development of extensible image analysis workflows with FLIM data. Built on the FLIMLib decay curve fitting library and the ImageJ Ops framework, FLIMJ offers FLIM fitting routines with seamless integration with many other ImageJ components, and the ability to be extended to create complex FLIM analysis workflows. Building on ImageJ Ops also enables FLIMJ’s routines to be used with Jupyter notebooks and integrate naturally with science-friendly programming in, e.g., Python and Groovy. We show the extensibility of FLIMJ in two analysis scenarios: lifetime-based image segmentation and image colocalization. We also validate the fitting routines by comparing them against industry FLIM analysis standards.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Observations Regarding Commonly Available Materials for Face Shield Emulated-Personal Protective Equipment

The Center for Disease Control has recommended that to reduce potential exposure to COVID-19 the public should wear cloth face coverings in public settings where other social distancing measures are difficult to maintain. These face coverings and other Emulated-Personal Protective Equipment (E-PPE) can be made by using Commonly Available Materials (CAMs). As E-PPE recommendations continue to flood the media, a Sandia COVID-19 LDRD effort, the Sandia E-PiPEline Team, systematically evaluated E-PPE design options considering their effectiveness, durability, build difficulty, build cost, and comfort. Using qualitative and semi-quantitative evaluation tools, results of the investigation are presented here to provide guidelines for home and office construction of E-PPE.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Observations Regarding Commonly Available Materials for Face Covering Emulated-Personal Protective Equipment

36 MATERIALS SCIENCE↗

DOE OSTI2020

E-PiPEline: Quick to Market Emulated-PPE using Commonly Available Materials

The Center for Disease Control has recommended the public to wear cloth face coverings in public settings that reduce potential exposure to COVID-19 where other social distancing measures are difficult to maintain (e.g., grocery stores and pharmacies) especially in areas of significant community based transmission. These face coverings and other Emulated-Personal Protective Equipment (EPPE) can be made by using Commonly Available Materials (CAMs). As part of the Sandia COVID-19 LDRD effort (funded under the Materials Science Investment Area), the Sandia E-PiPEline task evaluated E-PPE design options for face coverings and face shields considering their effectiveness, durability, build difficulty, build cost, and comfort. Observations from this investigation are presented here to provide guidelines for home construction of E-PPE. This executive summary includes a brief roadmap of the analysis methodology, two one-page handouts geared to be distributed to the public at large (one for E-PPE face coverings and one for E-PPE face shields), and additional observations regarding the potential solutions for E-PPE face coverings and face shields included to further support the one-page handouts.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

A Guided Approach to Setting up Your Workstation at Home [Slides]

Due to COVID-19 LANL has moved to a reality where most people are telecommuting from their homes and social distancing measures require a new normal. This requires the challenge of setting up an at home workstation to be as ergonomically friendly as possible. Sometimes space within the home is limited and office space may double as a dining space, kitchen counter or general use area. Other times, a desk and chair are present, but may not have the adjustability needed to provide a suitable long-term work environment. When setting up the home work environment remember to implement ergonomics basics.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2020

May 7, 2020 - Explosive Supercell Thunderstorm In The SE TX Panhandle

These lightning strikes can be more dangerous than “normal” lightning associated with a regular thunderstorm in that the “bolts from the blue” often occur well away from where the precipitation is occurring at the surface. “Bolts from the blue” occurred at a measured distance of 33 miles and an estimated 35 to 50 miles away from where the precipitation was occurring with this storm.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning

Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set while reducing computational costs. A predetermined number of RGRs is selected using an integrated unsupervised machine learning (UML) framework, which includes Euclidean distance measurement, multidimensional scaling (MDS), and a deterministic K-means (DK-means) clustering algorithm. In the context of the intricate 3D aquifer CO2 storage model, PUNQ-S3, these algorithms are utilized. The UML methodology selects five RGRs from a pool of 25 possibilities (20% of the total), taking into account the reservoir quality index (RQI) as a static parameter of the reservoir. To determine the credibility of these RGRs, their simulation results are scrutinized through the application of the Kolmogorov–Smirnov (KS) test, which analyzes the distribution of the output. In this assessment, 40 CO2 injection wells cover the entire reservoir alongside the full set. The end-point simulation results indicate that the CO2 structural, residual, and solubility trapping within the RGRs and full set follow the same distribution. Simulating five RGRs alongside the full set of 25 GRs over 200 years, involving 10 years of CO2 injection, reveals consistently similar trapping distribution patterns, with an average value of Dmax of 0.21 remaining lower than Dcritical (0.66). Using this methodology, computational expenses related to scenario testing and development planning for CO2 storage reservoirs in the presence of geological uncertainties can be substantially reduced.

Mahjour, Seyed Kourosh↗

DOE OSTI2020

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A Census of Star Formation in the Outer Galaxy. II. The GLIMPSE360 Field

We have conducted a study of star formation in the outer Galaxy from 65°< l < 265° in the region observed by the GLIMPSE360 program. This Spitzer warm mission program mapped the plane of the outer Milky Way with IRAC at 3.6 and 4.5 μm. We combine the IRAC, Wide-field Infrared Survey Explorer (WISE), and Two Micron All Sky Survey catalogs and our previous results from another outer Galaxy survey and identify a total of 47,338 young stellar objects (YSOs) across the field spanning >180° in Galactic longitude. Using the DBSCAN method on the combined catalog, we identify 618 clusters or aggregations of YSOs having five or more members. We identify 10,476 class I, 29,604 class II, and 7325 anemic class II/class III YSOs. The ratio of YSOs identified as members of clusters was 25,528/47,338, or 54%. We found that 100 of the clusters identified have previously measured distances in the WISE H ii survey. We used these distances in our spectral energy distribution (SED) fitting of the YSOs in these clusters, of which 96 had YSOs with <3σ fits. We used the derived masses from the SED model fits to estimate the initial mass function (IMF) in the inner and outer Galaxy clusters; dividing the clusters by galactocentric distances, the slopes were Γ = 1.87 ± 0.31 above 3 M {sub ⊙} for R {sub Gal} < 11.5 kpc and Γ = 1.15 ± 0.24 above 3 M {sub ⊙} for R {sub Gal} > 11.5 kpc. The slope of the combined IMF was found to be Γ = 1.92 ± 0.42 above 3 M {sub ⊙}. These values are consistent with each other within the uncertainties and with literature values in the inner Galaxy high-mass star formation regions. The slopes are likely also consistent with a universal Salpeter IMF.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Projected Cosmological Constraints from Strongly Lensed Supernovae with the Roman Space Telescope

One of the primary mission objectives of the Roman Space Telescope is to investigate the nature of dark energy with a variety of methods. Observations of Type I supernovae (SNe Ia) will be one of the principal anchors of the Roman cosmology program through traditional luminosity distance measurements. This SNe Ia cosmology program can provide another valuable cosmological probe, without altering the strategy of the mission: time delay cosmography with gravitationally lensed supernova (SN). In this work, we forecast lensed SN cosmology constraints with the Roman Space Telescope, while providing useful tools for future work. Using the anticipated characteristics of the Roman SNe Ia survey, we have constructed mock catalogs of expected resolved lensing systems, as well as strongly lensed Type Ia and core-collapse (CC) SN light curves, including microlensing effects. We predict Roman will find ~11 lensed SNe Ia and ~20 CCSNe, depending on the survey strategy. Next, we estimate the time delay precision obtainable with Roman (Ia: ~2 days, CC: ~3 days), and use a Fisher matrix analysis to derive projected constraints on H 0 ,Ω m , and the dark energy equation of state, w, for each SNe Ia survey strategy. Here, a strategy optimized for the discovery of high-redshift SNe Ia is preferred when considering the constraints possible from both SNe Ia and lensed SN cosmology, also delivering ~1.5 times more lensed SNe than other proposed survey strategies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

A Probabilistic Autoencoder for Type Ia Supernova Spectral Time Series

We construct a physically parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of Type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an autoencoder that is interpreted probabilistically after training using a normalizing flow. We demonstrate that the PAE learns a low-dimensional latent space that captures the nonlinear range of features that exists within the population and can accurately model the spectral evolution of SNe Ia across the full range of wavelength and observation times directly from the data. By introducing a correlation penalty term and multistage training setup alongside our physically parameterized network, we show that intrinsic and extrinsic modes of variability can be separated during training, removing the need for the additional models to perform magnitude standardization. We then use our PAE in a number of downstream tasks on SNe Ia for increasingly precise cosmological analyses, including the automatic detection of SN outliers, the generation of samples consistent with the data distribution, and solving the inverse problem in the presence of noisy and incomplete data to constrain cosmological distance measurements. We find that the optimal number of intrinsic model parameters appears to be three, in line with previous studies, and show that we can standardize our test sample of SNe Ia with an rms of 0.091 ± 0.010 mag, which corresponds to 0.074 ± 0.010 mag if peculiar velocity contributions are removed.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

What Does the Milky Way Look Like?

In spite of much work, the overall spiral structure morphology of the Milky Way remains somewhat uncertain. In the last two decades, accurate distance measurements have provided us with an opportunity to solve this issue. Using the precise locations of very young objects, for the first time, we propose that our galaxy has a multiple-arm morphology that consists of two-arm symmetry (the Perseus and Norma Arms) in the inner parts and that extends to the outer parts, where there are several long, irregular arms (the Centaurus, Sagittarius, Carina, Outer, and Local Arms).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

ELVES-Dwarf. I. Satellite Systems of Eight Isolated Dwarf Galaxies in the Local Volume

The satellite populations of Milky Way (MW)–mass systems have been extensively studied, significantly advancing our understanding of galaxy formation and dark matter physics. In contrast, the satellites of lower-mass dwarf galaxies remain largely unexplored, despite hierarchical structure formation predicting that dwarf galaxies should host their own satellites. We present the first results of the ELVES-Dwarf survey, which aims to statistically characterize the satellite populations of isolated dwarf galaxies in the Local Volume (4 < D < 10 Mpc). We identify satellite candidates in integrated light using Legacy Surveys data and achieve completeness down to M g ≈ −9 mag. We then confirm the association of satellite candidates with host galaxies using surface-brightness fluctuation distances measured from Hyper Suprime-Cam data. We surveyed eight isolated dwarf galaxies with stellar masses ranging from sub-Small Magellanic Cloud to Large Magellanic Cloud scales $(10^{7.8} < M^{\textrm{host}}_{\star} < 10^{9.5} M_⊙)$, and confirmed six satellites with stellar masses between 10 5.6 and 10 8 M ⊙ . Most confirmed satellites are star-forming, in contrast to the primarily quiescent satellites observed around MW-mass hosts. By comparing observed satellite abundances and stellar mass functions with theoretical predictions, we find no evidence of a “missing satellite problem” in the dwarf galaxy regime.

Li, Jiaxuan 嘉轩李 [Princeton University, NJ (United ↗