Search NASA⌕ Search

SEARCH · Search NASA

Results for “Comparative visualization”

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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Dynamic functional imaging of brain glucose utilization using fPET-FDG

We report that glucose is the principal source of energy for the brain and yet the dynamic response of glucose utilization to changes in brain activity is still not fully understood. Positron emission tomography (PET) allows quantitative measurement of glucose metabolism using 2-[18F]-fluorodeoxyglucose (FDG). However, FDG PET in its current form provides an integral (or average) of glucose consumption over tens of minutes and lacks the temporal information to capture physiological alterations associated with changes in brain activity induced by tasks or drug challenges. Traditionally, changes in glucose utilization are inferred by comparing two separate scans, which significantly limits the utility of the method. We report a novel method to track changes in FDG metabolism dynamically, with higher temporal resolution than exists to date and within a single session. Using a constant infusion of FDG, we demonstrate that our technique (termed fPET-FDG) can be used in an analysis pipeline similar to fMRI to define within-session differential metabolic responses. We use visual stimulation to demonstrate the feasibility of this method. Ultimately, this new method has a great potential to be used in research protocols and clinical settings since fPET-FDG imaging can be performed with most PET scanners and data acquisition and analysis are straightforward. fPET-FDG is a highly complementary technique to MRI and provides a rich new way to observe functional changes in brain metabolism.

2-[18F]-fluorodeoxyglucose (FDG)↗
DOE OSTI2015

Vibrational modes of ultrathin carbon nanomembrane mechanical resonators

We report measurements of vibrational mode shapes of mechanical resonators made from ultrathin carbon nanomembranes (CNMs) with a thickness of approximately 1 nm. CNMs are prepared from electron irradiation induced cross-linking of aromatic self-assembled monolayers and the variation of membrane thickness and/or density can be achieved by varying the precursor molecule. Single- and triple-layer freestanding CNMs were made by transferring them onto Si substrates with square/rectangular orifices. The vibration of the membrane was actuated by applying a sinusoidal voltage to a piezoelectric disk on which the sample was glued. The vibrational mode shapes were visualized with an imaging Mirau interferometer using a stroboscopic light source. Several mode shapes of a square membrane can be readily identified and their dynamic behavior can be well described by linear response theory of a membrane with negligible bending rigidity. By applying Fourier transformations to the time-dependent surface profiles, the dispersion relation of the transverse membrane waves can be obtained and its linear behavior verifies the membrane model. By comparing the dispersion relation to an analytical model, the static stress of the membranes was determined and found to be caused by the fabrication process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Automated Cloud Based Long Short-Term Memory Neural Network Based SWE Prediction

Snow derived water is a critical component of the US water supply. Measurements of the Snow Water Equivalent (SWE) and associated predictions of peak SWE and snowmelt onset are essential inputs for water management efforts. This paper aims to develop an integrated framework for real-time data ingestion, estimation, prediction and visualization of SWE based on daily snow datasets. In particular, we develop a data-driven approach for estimating and predicting SWE dynamics using the Long Short-Term Memory neural network (LSTM) method. Our approach uses historical datasets (precipitation, air temperature, SWE, and snow thickness) collected at NRCS Snow Telemetry (SNOTEL) stations to train the LSTM network and current year data to predict SWE behavior. The performance of our prediction was compared for different prediction dates and prediction training datasets. Our results suggest that the proposed LSTM network can be an efficient tool for forecasting the SWE timeseries, as well as Peak SWE and snowmelt timing. Results showed that the window size impacts the model performance (where the Nash Sutcliffe efficiency (NSE) ranged from 0.96 to 0.85 and the Rooted Mean Square Error (RMSE) ranged from 0.038 to 0.07) with an optimum number that should be calibrated for different stations and climate conditions. In addition, by implementing the LSTM prediction capability in a cloud based site-monitoring platform, we automate model-data integration. By making the data accessible through a graphical web interface and an underlying API which exposes both training and prediction capabilities. The associated results can be made easily accessible to a broad range of stakeholders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Rhodopsin photoactivation dynamics revealed by quasi-elastic neutron scattering

Rhodopsin is a G-protein-coupled receptor (GPCR) responsible for vision under dim light conditions. During rhodopsin photoactivation, the chromophore retinal undergoes cis-trans isomerization, and subsequently dissociates from the protein yielding the opsin apoprotein [1]. What are the changes in protein dynamics that occur during the rhodopsin photoactivation process? Here, we studied the microscopic dynamics of the dark-state rhodopsin and the ligand-free opsin using quasi-elastic neutron scattering (QENS). The QENS technique tracks the individual hydrogen atom motions in the protein molecules, because the neutron scattering cross-section of hydrogen is much higher than other atoms [2-4]. We used protein (rhodopsin/opsin) samples with CHAPS detergent hydrated with heavy water. The solvent signal is suppressed due to the heavy water, so that only the signals from proteins and detergents are detected. The activation of proteins is confirmed at low temperatures up to 300 K by the mean-square displacement (MSD) analysis. Our QENS experiments conducted at temperatures ranging from 220 K to 300 K clearly indicate that the protein dynamic behavior increases with temperature. The relaxation time for the ligand-bound protein rhodopsin was longer compared to opsin, which can be correlated with the photoactivation. Moreover, the protein dynamics are orders of magnitude slower than the accompanying CHAPS detergent, which forms a band around the protein molecule in the micelle. Unlike the protein, the CHAPS detergent manifests localized motions that are the same as in the bulk empty micelles. Furthermore QENS provides unique understanding of the key dynamics involved in the activation of the GPCR involved in the visual process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM

We report three-dimensional (3D) X-ray micro-computed tomography (μCT) has been widely used in petroleum engineering because it can provide detailed pore structural information for a reservoir rock, which can be imported into a pore-scale numerical model to simulate the transport and distribution of multiple fluids in the pore space. The partial volume blurring (PVB) problem is a major challenge in segmenting raw μCT images of rock samples, which impacts boundaries and small targets near the resolution limit. We developed a deep-learning (DL)-based workflow for accurate and fast partial volume segmentation. The DL model's performance depends primarily on the training data quality and model architecture. This study employed the entropy-based-masking indicator kriging (IK-EBM) to segment 3D Berea sandstone images as training datasets. The comparison between IK-EBM and manual segmentation using a 3D synthetic sphere pack, which had a known ground truth, showed that IK-EBM had higher accuracy on partial volume segmentation. We then trained and tested the UNet++ model, a state-of-the-art supervised encoder-decoder model, for binary (i.e., void and solid) and four-class segmentation. We compared the UNet++ with the commonly used U-Net and wide U-Net models and showed that the UNet++ had the best performance in terms of pixel-wise and physics-based evaluation metrics. Specifically, boundary-scaled accuracy demonstrated that the UNet++ architecture outperformed the regular U-Net architecture in the segmentation of pixels near boundaries and small targets, which were subjected to the PVB effect. Feature map visualization illustrated that the UNet++ bridged the semantic gaps between the feature maps extracted at different depths of the network, thereby enabling faster convergence and more accurate extraction of fine-scale features. The developed workflow significantly enhances the performance of supervised encoder-decoder models in partial volume segmentation, which has extensive applications in fundamental studies of subsurface energy, water, and environmental systems.

02 PETROLEUM↗
DOE OSTI2016

Investigation of thin/well-tunable liquid/gas diffusion layers exhibiting superior multifunctional performance in low-temperature electrolytic water splitting

Liquid/gas diffusion layers (LGDLs), which are located between the catalyst layer (CL) and bipolar plate (BP), play an important role in enhancing the performance of water splitting in proton exchange membrane electrolyzer cells (PEMECs). They are expected to transport electrons, heat, and reactants/products simultaneously with minimum voltage, current, thermal, interfacial, and fluidic losses. Here in this study, the thin titanium-based LGDLs with straight-through pores and well-defined pore morphologies are comprehensively investigated for the first time. The novel LGDL with a 400 μm pore size and 0.7 porosity achieved a best-ever performance of 1.66 V at 2 A cm -2 and 80 °C, as compared to the published literature. The thin/well-tunable titanium based LGDLs remarkably reduce ohmic and activation losses, and it was found that porosity has a more significant impact on performance than pore size. In addition, an appropriate equivalent electrical circuit model has been established to quantify the effects of pore morphologies. The rapid electrochemical reaction phenomena at the center of the PEMEC are observed by coupling with high-speed and micro-scale visualization systems. Lastly, the observed reactions contribute reasonable and pioneering data that elucidate the effects of porosity and pore size on the PEMEC performance. This study can be a new guide for future research and development towards high-efficiency and low-cost hydrogen energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-G-JeP4-01: An Assessment of a Microsoft Kinect V2 Sensor for Voluntary Breath-Hold Monitoring in Radiotherapy

Purpose: To determine whether the Microsoft Kinect Version 2 (Kinect v2), a commercial off-the-shelf (COTS) depth sensors designed for entertainment purposes, were robust to the radiotherapy treatment environment and could be suitable for monitoring of voluntary breath-hold compliance. This could complement current visual monitoring techniques, and be useful for heart sparing left breast radiotherapy. Methods: In-house software to control Kinect v2 sensors, and capture output information, was developed using the free Microsoft software development kit, and the Cinder creative coding C++ library. Each sensor was used with a 12m USB 3.0 active cable. A solid water block was used as the object. The depth accuracy and precision of the sensors was evaluated by comparing Kinect reported distance to the object with a precision laser measurement across a distance range of 0.6m to 2.0 m. The object was positioned on a high-precision programmable motion platform and moved in two programmed motion patterns and Kinect reported distance logged. Robustness to the radiation environment was tested by repeating all measurements with a linear accelerator operating over a range of pulse repetition frequencies (6Hz to 400Hz) and dose rates 50 to 1500 monitor units (MU) per minute. Results: The complex, consistent relationship between true and measured distance was unaffected by the radiation environment, as was the ability to detect motion. Sensor precision was < 1 mm and the accuracy between 1.3 mm and 1.8 mm when a distance correction was applied. Both motion patterns were tracked successfully with a root mean squared error (RMSE) of 1.4 and 1.1 mm respectively. Conclusion: Kinect v2 sensors are capable of tracking pre-programmed motion patterns with an accuracy <2 mm and appear robust to the radiotherapy treatment environment. A clinical trial using Kinect v2 sensor for monitoring voluntary breath hold has ethical approval and is open to recruitment. The authors are supported by a National Institute of Health Research (NIHR) Career Development Fellowship (CDF-2013-06-005). Microsoft Corporation donated three sensors. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Low Emissions Burner Technology for Metal Processing Industry using Byproducts and Biomass Derived Liquid Fuels (Final Report)

This research and development efforts produced low-emission burner technology capable of operating on natural gas as well as crude glycerin and/or fatty acids generated in biodiesel plants. The research was conducted in three stages (1) Concept definition leading to the design and development of a small laboratory scale burner, (2) Scale-up to prototype burner design and development, and (3) Technology demonstration with field vefiication. The burner design relies upon the Flow Blurring (FB) fuel injection based on aerodynamically creating two-phase flow near the injector exit. The fuel tube and discharge orifice both of inside diameter D are separated by gap H. For H < 0.25D, the atomizing air bubbles into liquid fuel to create a two-phase flow near the tip of the fuel tube. Pressurized two-phase fuel-air mixture exits through the discharge orifice, which results in expansion and breakup of air bubbles yielding a spray with fine droplets. First, low-emission combustion of diesel, biodiesel and straight VO (soybean oil) was achieved by utilizing FB injector to yield fine sprays for these fuels with significantly different physical properties. Visual images for these baseline experiments conducted with heat release rate (HRR) of about 8 kW illustrate clean blue flames indicating premixed combustion for all three fuels. Radial profiles of the product gas temperature at the combustor exit overlap each other signifying that the combustion efficiency is independent of the fuel. At the combustor exit, the NOx emissions are within the measurement uncertainties, while CO emissions are slightly higher for straight VO as compared to diesel and biodiesel. Considering the large variations in physical and chemical properties of fuels considered, the small differences observed in CO and NOx emissions show promise for fuel-flexible, clean combustion systems. FB injector has proven to be very effective in atomizing fuels with very different physical properties, and it offers a path forward to utilize both fossil and alternative liquid fuels in the same combustion system. In particular, experiments show that straight VO can be cleanly combusted without the need for chemical processing or preheating steps, which can result in significant economic and environmental benefits. Next, low-emission combustion of glycerol/methane was achieved by utilizing FB injector to yield fine droplets of highly viscous glycerol. Heat released from methane combustion further improves glycerol pre-vaporization and thus its clean combustion. Methane addition results in an intensified reaction zone with locally high temperatures near the injector exit. Reduction in methane flow rate elongates the reaction zone, which leads to higher CO emissions and lower NOx emissions. Similarly, higher air to liquid (ALR) mass ratio improves atomization and fuel pre-vaporization and shifts the flame closer to the injector exit. In spite of these internal variations, all fuel mixes of glycerol with methane produced similar CO and NOx emissions at the combustor exit. Results show that FB concept provides low emissions with the flexibility to utilize gaseous and highly viscous liquid fuels, straight VO and glycerol, without preheating or preprocessing the fuels. Following these initial experiments in quartz combustor, we demonstrated that glycerol combustion can be stably sustained in a metal combustor. Phase Doppler Particle Analyzer (PDPA) measurements in glycerol/methane flames resulted in flow-weighted Sauter Mean Diameter (SMD) of 35 to 40 μm, depending upon the methane percentage. This study verified that lab-scale dual-fuel burner using FB injector can successfully atomize and combust glycerol and presumably other highly viscous liquid fuels at relatively low HRR (<10 kW). For industrial applications, a scaled-up glycerol burner design thus seemed feasible.

03 NATURAL GAS↗
DOE OSTI2019

Visual Orbits of Spectroscopic Binaries with the CHARA Array. I. HD 224355

We present the visual orbit of the double-lined spectroscopic binary HD 224355 from interferometric observations with the CHARA Array, as well as an updated spectroscopic analysis using echelle spectra from the Apache Point Observatory 3.5 m telescope. By combining the visual and spectroscopic orbital solutions, we find the binary components to have masses of M 1 = 1.626 ± 0.005M ⊙ and M 2 = 1.608 ± 0.005M ⊙ , and a distance of d = 63.98 ± 0.26 pc. Using the distance and the component angular diameters found by fitting spectrophotometry from the literature to spectral energy distribution models, we estimate the stellar radii to be R 1 = 2.65 ± 0.21R ⊙ and R 2 = 2.47 ± 0.23R ⊙ . We then compare these observed fundamental parameters to the predictions of stellar evolution models, finding that both components are evolved toward the end of the main sequence with an estimated age of 1.9 Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Influence of Contrast Agent Dilution on Ballon Deflation Time and Visibility During Tracheal Balloon Dilation: A 3D Printed Phantom Study

PurposeTo determine the effect of contrast medium dilution during tracheal balloon dilation on balloon deflation time and visibility using a 3-dimensional (3D) printed airway phantom.Materials and MethodsA comparison study to investigate balloon deflation times and image quality was performed using two contrast agents with different viscosities, i.e., iohexol and ioxithalamate, and six contrast dilutions with a 3D printed airway phantom.ResultsCompared to 1:0 concentration, 3:1, 2:1, 1:1, 1:2, and 1:3, contrast/saline ratios resulted in a 46% (56.2 s), 59.8% (73.1 s), 74.9% (91.6 s), 81.7% (99.8 s), and 83.5% (102 s) reduction for iohexol, respectively, and a 51.8% (54.7 s), 63.8% (67.6 s), 74.7% (79.2 s), 80.5% (85.3 s), and 82.4% (87.4 s) reduction for ioxithalamate, respectively, in the mean balloon deflation time, although at the expense of decreased balloon opacity (3.5, 6.9, 11.1, 12.4, and 13.9%, for iohexol, respectively, and 3.2, 6, 9.6, 10.8, and 12.4%, for ioxithalamate, respectively).ConclusionsUse of a lower viscosity contrast agent and higher contrast dilution is considered to be able to reduce balloon deflation times and then simultaneously decrease visualization of balloons. The rapid balloon deflation time is likely to improve the safe performance of interventional procedures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Real-Time US-{sup 18}FDG-PET/CT Image Fusion for Guidance of Thermal Ablation of {sup 18}FDG-PET-Positive Liver Metastases: The Added Value of Contrast Enhancement

Purpose: To assess the feasibility of US-{sup 18}FDG-PET/CT fusion-guided microwave ablation of liver metastases either poorly visible or totally undetectable with US, CEUS and CT, but visualized by PET imaging. Materials and Methods: Twenty-three patients with 58 liver metastases underwent microwave ablation guided by image fusion system that combines US with {sup 18}FDG-PET/CT images. In 28/58 tumors, {sup 18}FDG-PET/CT with contrast medium (PET/CECT) was used. The registration technical feasibility, registration time, rates of correct targeting, technical success at 24 h, final result at 1 year and complications were analyzed and compared between the PET/CT and PET/CECT groups. Results: Registration was successfully performed in all cases with a mean time of 7.8 + 1.7 min (mean + standard deviation), (4.6 + 1.5 min for PET/CECT group versus 10.9 + 1.8 min for PET/CT group, P < 0.01). In total, 46/58 (79.3%) tumors were correctly targeted, while 3/28 (10.7%) and 9/30 (30%) were incorrectly targeted in PET/CT and PET/CECT group, respectively (P < 0.05). Complete ablation was obtained at 24 h in 70.0% of cases (n = 40 tumors), 23/28 (82.1%) in the PET/CECT group and 17/30 (56.7%) in the PET/CT group (P < 0.037). Fourteen tumors underwent local retreatment (11 ablations, 2 with resection and 1 with stereotactic body radiation therapy), while 4 tumors could not be retreated because of distant disease progression and underwent systemic therapy. Finally, 54/58 (93.1%) tumors were completely treated at 1 year. One major complication occurred, a gastrointestinal hemorrhage which required surgical repair. Conclusions: Percutaneous ablation of {sup 18}FDG-PET-positive liver metastases using fusion imaging of real-time US and pre-acquired {sup 18}FDG-PET/CT images is feasible, safe and effective. Contrast-enhanced PET/CT improves overall ablation accuracy and shortens procedural duration time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

A comparison of two- and three-dimensional single-mode reshocked Richtmyer–Meshkov instability growth

The growth dynamics of two- and three-dimensional single-mode reshocked Richtmyer–Meshkov instability are compared systematically using data from high-resolution implicit large-eddy simulations of a model of the Mach 1.3 air(acetone) and sulfur hexafluoride (Jacobs and Krivets, 2005) shock tube experiment. The vorticity deposition by the incident shock and the dynamics of interface evolution are examined quantitatively and qualitatively. The perturbation amplitudes from the two- and three-dimensional simulations are compared to the experimental data and to the predictions of several nonlinear instability growth models. It is shown that the perturbation amplitudes from the two- and three-dimensional simulations with matching initial Richtmyer velocity are in excellent agreement with the experimental data. In addition, the dynamics of reshock (not considered in the experiment) are described in detail, and the post-reshock mixing layer amplitude growth rate is compared to the predictions of several reshock models. It is shown that using two-dimensional simulations to understand three-dimensional dynamics is valid only at early-to-intermediate times before reshock; at intermediate-to-late times after reshock the three-dimensional growth is generally larger than the corresponding two-dimensional growth. Furthermore, the reshock dynamics are also different between two and three dimensions. The quantitative results, together with visualizations of the flow field, were also used to contrast the difference between two- and three-dimensional vorticity and enstrophy dynamics.

42 ENGINEERING↗
DOE OSTI2019

Hurricane Harvey Flood

Online supplement to Attributable human-induced changes in the magnitude of flooding in the Houston, Texas region during Hurricane Harvey, by Michael Wehner and Christopher Sampson. Geospatial data to visualize the attributable flooding in the greater Houston during Hurricane Harvey as simulated by the Fathom hydraulical model in a geotiff file format is provided at https://portal.nersc.gov/cascade/Harvey/ . The public is encouraged to download this open access data and investigate their own neighborhoods of interest using free or commercial software. A detailed validation of the baseline simulated "flood that was" for every neighborhood is outside the scope of this article but individuals can compare the simulation to their own experiences. The public is then invited to compare the "flood that might have been" had there not been a human interference in the climate system to the simulated actual flood in these neighborhoods. The variety of scientific opinions as to the human effect on precipitation and their effect on the flood are presented as detailed in the table below. A pair of high risk scenarios of the effect of a future warmer climate and a hypothetical storm similar to Harvey is also provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints

Abstract Dimension reduction techniques are an essential part of the climate analyst’s toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative , sparse , and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection.

Weylandt, Michael↗
DOE OSTI2023

Residential Solar-Adopter Income and Demographic Trends: 2023 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 3.4 million residential rooftop solar systems installed through 2022, representing 86% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: (1) Median solar adopter income was about $\$117$k/year in 2022, compared to a U.S. median of about $\$69$k/year for all households and $\$86$k/year for all owner-occupied households; (2) The degree of income skew varies significantly across all states, but all exhibit some positive income skew relative to all households in the state, with median solar-adopter incomes ranging from 108-180% of the respective state-median income for all households; (3) Roughly 45% of solar adopters in 2022 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 23% were below 80% of AMI, often used to define “low-income”; (4) Solar adoption continues to shift toward less affluent households, with the median current income of solar adopters dropping from $\$140$k for households that installed systems in 2010 to $\$117$k in 2022; (5) PV systems installed in 2022 by households earning less than $50k had a median size of 6.1 kW, 34% were third-party owned, and 5% included battery storage, compared to corresponding values of 7.6%, 17%, and 15% for households earning more than 200 dollars k; and (6) Compared to all households in their respective state, solar adopters tend to be negligibly more rural; have higher home values; and are more likely to be college educated, identify as non-Hispanic white, live outside a disadvantaged community (DAC), be middle-aged, work in a business or financial occupation, and own a single-family home In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households.

14 SOLAR ENERGY↗
DOE OSTI2020

Robo-AO M-dwarf Multiplicity Survey: Catalog

We analyze observations from Robo-AO’s field M dwarf survey taken on the 2.1 m Kitt Peak telescope and perform a multiplicity comparison with Gaia DR2. Through its laser-guided, automated system, the Robo-AO instrument has yielded the largest adaptive optics M dwarf multiplicity survey to date. After developing an interface to visually identify and locate stellar companions, we selected 11 low-significance Robo-AO detections for follow-up on the Keck II telescope using NIRC2. In the Robo-AO survey we find 553 candidate companions within 4″ around 534 stars out of 5566 unique targets, most of which are new discoveries. Using a position cross-match with DR2 on all targets, we assess the binary recoverability of Gaia DR2 and compare the properties of multiples resolved by both Robo-AO and Gaia. The catalog of nearby M dwarf systems and their basic properties presented here can assist other surveys which observe these stars, such as the NASA TESS mission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A Virtual Reality Visualization Tool for Neuron Tracing

Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks or months manually tracing neurons using 2D image stacks. We present a design study of a new virtual reality (VR) system, developed in collaboration with trained neuroanatomists, to trace neurons in microscope scans of the visual cortex of primates. We hypothesize that using consumer-grade VR technology to interact with neurons directly in 3D will help neuroscientists better resolve complex cases and enable them to trace neurons faster and with less physical and mental strain. We discuss both the design process and technical challenges in developing an interactive system to navigate and manipulate terabyte-sized image volumes in VR. Using a number of different datasets, we demonstrate that, compared to widely used commercial software, consumer-grade VR presents a promising alternative for scientists.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗