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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Simons Observatory: Constraining inflationary gravitational waves with multitracer B-mode delensing

We introduce and validate a delensing framework for the Simons Observatory (SO), which will be used to improve constraints on inflationary gravitational waves by reducing the lensing noise in measurements of the B modes in CMB polarization. SO will initially observe CMB by using three small aperture telescopes and one large-aperture telescope. While polarization maps from small-aperture telescopes will be used to constrain inflationary gravitational waves, the internal CMB lensing maps used to delens will be reconstructed from data from the large-aperture telescope. Since lensing maps obtained from the SO data will be noise dominated on subdegree scales, the SO lensing framework constructs a template for lensing-induced B modes by combining internal CMB lensing maps with maps of the cosmic infrared background from Planck as well as galaxy density maps from the LSST survey. We construct a likelihood for constraining the tensor-to-scalar ratio r that contains auto and cross spectra between observed B modes and the lensing B-mode template. We test our delensing analysis pipeline on map-based simulations containing survey nonidealities, but that, for this initial exploration, does not include contamination from Galactic and extragalactic foregrounds. We find that the SO survey masking and inhomogeneous and atmospheric noise have very little impact on the delensing performance, and the r constraint becomes σ(r)≈0.0015 which is close to that obtained from the idealized forecasts in the absence of the Galactic foreground and is nearly a factor of 2 tighter than without delensing. We also find that uncertainties in the external large-scale structure tracers used in our multitracer delensing pipeline lead to bias much smaller than the 1σ statistical uncertainties.

Toshiya Namikawa↗
NASA NTRS2024

Large-scale Coronal Dimming Foreshadowing a Solar Eruption on 2011 October 1

Understanding large-scale solar eruptions requires detailed investigation of the entire system's evolution, including the magnetic environment enveloping the source region and searches for precursor activity prior to event onset. We combine stereoscopic observations from the Solar Dynamics Observatory (SDO) and STEREO-B spacecraft for several hours before a filament ejection, M1.2-class eruptive flare, and coronal mass ejection (CME) originating in NOAA active region (AR) 11305 on 2011 October 1. Two episodes of significant preeruption coronal dimming that occurred well to the southeast of the ejected filament are identified. The CME subsequently took off with a substantial component of velocity toward the dimming, which became very pronounced during eruption. We used SDO/Helioseismic and Magnetic Imager (HMI) data to reconstruct the magnetic environment of the system and found that it contains a null point near the dimming region. AR 11305 had quite complex connections to nearby ARs 11302 and 11306, as well as to other regions of decayed AR flux. The intensifying and spatially expanding precursor dimming was accompanied by southeastward rising motions of loops toward the null point and northeastward and southwestward motions of loops retracting away. These motions and the dimming are consistent with persistent magnetic reconnection occurring at the null point as it moved upward and southeastward, thereby removing a strapping magnetic field high above AR 11305. Eventually, the filament was ejected explosively toward the null point. We conclude that the breakout model for solar eruptions provides a compelling account of this event. Furthermore, we conjecture that preeruption dimmings may be much more frequent than currently recognized.

solar flares↗
NASA NTRSDate not supplied

Independent Verification and Validation for Artemis I Ascent Integrated Flight Performance Simulation

The NASA Engineering and Safety Center (NESC) has performed independent model development to support cross-model verification for the Space Launch System (SLS) Program since 2012 which culminated, for Artemis I, in a postflight reconciliation analysis of the Artemis I ascent trajectory (validation). This post-flight analysis was completed by both the NESC and the SLS Program. Upon successful completion of the Artemis I mission, multiple preflight simulations of the nominal ascent trajectory were updated with Day of Launch (DOL) conditions and simulated results were compared to reconstructed flight data derived from telemetry measurements. Dispersed trajectories were also produced using a combination of DOL conditions and preflight uncertainties, which ideally should bound the Artemis I flight data. Finally, multibody dynamics were simulated for some of the separation events to support clearance analyses. This paper focuses on validating and understanding the accuracy of the models by comparing simulated results against the Artemis I flight data. In addition, discrepancies uncovered between simulations led to opportunities to investigate areas for potential model improvement to refine preflight simulations for future Artemis missions. Included in this paper is background on the flight performance simulation tools, the postflight analysis approach, and a comparison of simulation results against the Artemis I flight data. Simulated results were found to generally be in close agreement with each other and the Artemis I flight data.

Jacob Fleck↗
DOE OSTI2022

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development that requires often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments [https://arxiv.org/abs/2403.11872]. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2021

Adaptive neural network management system

A method and computer system for managing a neural network. Data is sent into an input layer in a portion of layers of nodes in the neural network. The data moves on an encode path through the portion such that an output layer in the portion outputs encoded data. The encoded data is sent into the output layer on a decode path through the portion back to the input layer to obtain a reconstruction of the data by the input layer. A determination is made as to whether an undesired amount of error has occurred in the output layer based on the data sent into the input layer and the reconstruction of the data. A number of new nodes is added to the output layer when a determination is present that the undesired amount of the error occurred, enabling reducing the error using the number of the new nodes.

Draelos, Timothy J.↗
DOE OSTI2020

Reconstruction of the interatomic forces from dynamic scanning transmission electron microscopy data

We explore the possibility for reconstruction of the generative physical models describing interactions between atomic units in solids from observational electron microscopy data. In this work, scanning transmission electron microscopy (STEM) is used to observe the dynamic motion of Si atoms at the edge of monolayer graphene under continuous electron beam illumination. The resulting time-lapsed STEM images represent the snapshots of observed chemical states of the system. We use two approaches: potential of mean force calculation using a radial distribution function and a direct fitting of the graphene–Si interatomic pairwise potentials with force matching, to reconstruct the force fields in the materials. These studies lay the foundation for quantitative analysis of materials energetics from STEM data through the sampling of the metastable states in the chemical space of the system.

42 ENGINEERING↗
DOE OSTI2022

Knock-on deuteron imaging for diagnosing the morphology of an ICF implosion at OMEGA

Knock-on deuteron imaging is a new diagnostic technique that is being implemented at the OMEGA laser facility to diagnose the morphology of an inertial confinement fusion (ICF) implosion. It utilizes the fact that some of the neutrons from deuterium–tritium (DT)-fusion reactions generated in the central hot-spot of an ICF implosion elastically scatter deuterons as they traverse the surrounding shell layer. The energy of these “knock-on” deuterons depends on the scattering angle, where the most energetic deuterons are forward-scattered and probe the shape of the central hot-spot, while lower-energy deuterons are made by side-scattering or slowing down in the fuel and carry information about the distribution of the dense DT-fuel layer surrounding the hot-spot. The first proof-of-concept tests have been conducted successfully. In these tests, three penumbral imagers with different views on an implosion recorded deuterons scattered from the dense shell of DT-gas-filled deuterated plastic shell implosions with prescribed offsets. Data from these experiments are presented here, along with novel analysis techniques that iteratively reconstruct the deuteron source from the data. Reconstructed hot-spot and shell radii agree with 1D hydro simulations and indicate a P1 asymmetry in the direction of the offset. A comparison of coaxial deuteron and x-ray images suggests the presence of a mix between the hot-spot and shell on the order of 15 μm. This new diagnostic capability will allow us to study asymmetries in unprecedented detail at OMEGA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Soyuz Landing Reconstructions

Introduction: Recent data show a landing-attributed injury rate among Soyuz crew members to be higher than predicted in original certification analysis. New vehicles being developed for NASA are being certified using analytical tools to quantify injury risk. This assessment will provide data to allow the Agency to evaluate whether these tools are able to capture true injury risk and allow a comparison between Soyuz landings and upcoming vehicles. Methods: A finite element model (FEM) of the Soyuz descent module (DM) and its landing environment were developed to recreate Soyuz landing conditions. Occupant breakout models composed of the Soyuz seat and Sokol helmet were then developed to evaluate occupant response. These models included both anthropomorphic test device (ATD) and human body model (HBM) surrogates in three anthropometric sizes. A generalized distribution analysis of the Soyuz landing environment was performed using landing variable distributions from available literature. Results were used to identify trends in vehicle landing acceleration with landing conditions and to compare landing model injury risk predictions with those estimated in vehicle certification analysis. Next, historic Soyuz landings identified as inducing occupant injury during were reconstructed using the developed landing model and estimated landing conditions. Results and Discussion: This assessment demonstrated the capability of certification metrics, which include a combination of vehicle- and occupant-level injury risk analysis, to identify elevated injury risk landing conditions. However, the developed landing load predictions were limited by available vehicle and landing condition data. Additional data, particularly landing acceleration data specific to historic Soyuz landing conditions, would greatly enhance this assessment’s findings.

Preston Greenhalgh↗
DOE OSTI2020

Genome-resolved metagenomics and metatranscriptomics of microbial communities in three meander-bound floodplain soils along the East River, Colorado.

This dataset comprises paired environmental and genomic data for soil samples collected across meander-bound floodplains G (ERMG), L (ERML) and Z (ERMZ). A total of 96 soil samples (32 per floodplain) from the ~ 10-25 cm layer were collected in September 2015, during base flow conditions. An additional 32 soil samples were collected from ERML in September 2016, including three samples from a depth just above the water table. A subset of samples (14) collected in 2016 were used for metatranscriptomics as well as metagenomics. The data package includes: 1) A spread sheet with sample names, location and depth by meander-bound floodplain. 2) Total organic carbon (TOC), total inorganic carbon (TIC), total carbon (TC = TOC + TIC), total nitrogen (TN), and the TOC to TN ratio (TOC:N) from 2015 subsamples. 3) Soil chemistry for 2016 subsamples. 4) A spread sheet with elevation, Easting, Northing, and topographic position index (TPI) for each site sampled in 2015. 5) A kml file, which can be viewed in Google Earth, with the locations of the 96 soil sampling sites along the East River Watershed Floodplain in Colorado. Metagenomics and metatranscriptomics data, as well as reconstructed genomes, are available elsewhere (see data package methods and bioRxiv preprint for links to the data). 6) Two sets of reconstructed genomes with overlapping members (see bioRxiv preprint for description and associated data). Metagenomes and metatranscriptomes are available elsewhere (see data package methods and bioRxiv preprint). To view tar.gz files, the following software can be used: https://www.gnu.org/software/tar/, https://www.7-zip.org/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

GNET2: an R package for constructing gene regulatory networks from transcriptomic data

Abstract Motivation The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use. Results Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets. Availability and implementation The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2019

ADEPT Sounding Rocket One (SR-1) Flight Test

A sounding rocket flight test was conducted on a mechanically-deployed entry vehicle (DEV) known as the Adaptable Deployable Entry and Placement Technology (ADEPT). This flight test was a major milestone in a technology development campaign for ADEPT: the application of ADEPT for small secondary payloads. The test was conducted above White Sands Missile Range (WSMR), New Mexico on a SpaceLoft XL rocket on September 12, 2018. The first objective of the SR-1 flight test was to demonstrate that ADEPT could transform from a compact stowed configuration, separate from the launch vehicle, and successfully deploy exo-atmospherically into the desired low ballistic coefficient entry configuration. The second objective was to characterize the aerodynamic performance of the deployed configuration in order to evaluate the faceted blunt body geometry dynamic stability characteristics as it decelerated from supersonic to subsonic speeds.The ADEPT DEV had several sensors on-board and also leveraged third-party data sources for post-flight analysis and trajectory reconstruction. Based upon data review, the launch vehicle met exo-atmospheric delivery performance requirements of spin rate, no re-contact, separation velocity, and delivery altitude. The unique ADEPT forebody geometry (blunted octagonal pyramid, 0.7 m diameter at the rib tips) and aftbody configuration has never flown before. The forebody half cone angle at the ribs is 70 deg, while the half cone angle mid gore is 68.5 deg. The aftbody, where the 3U CubeSat 'payload' resides is a rectangular prism that extends ~ ½ the minimum forebody diameter behind the nose. Understanding DEV blunt body dynamic stability performance is critical for determining how they can be employed for atmospheric entry, descent and landing.The primary data products were used to perform flight mechanics analysis and reconstruct the as-flown trajectory. On-board video recovered post-flight demonstrated that the DEV achieved and maintained the desired entry configuration. Post-flight analyses showed that the vehicle met the threshold of achieving stable flight below Mach = 0.8. The ADEPT project has focused on ballistic, axisymmetric shapes as the logical 'first step' in mission infusion applications. With the current maturation and development of the ballistic (non-lifting) 1 m class ADEPT, the next step in ADEPT maturation is the focus on configurations that are capable of generating lift in order to accomplish aerocapture and precision landing mission capabilities. ADEPT is particularly attractive for evaluating various guidance and control approaches as the deployable structure enables attachment points for various actuation methods such as control surfaces, moving mass elements, or RCS thrusters. The ADEPT sounding rocket flight test provided a low-cost means of achieving significant system level maturity for the 1 m class ADEPT configuration. A description of the technology, system components, flight test execution, and conclusions will be described.

Cassell, Alan↗