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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ACCESS: A Visual to Near-infrared Spectrum of the Hot Jupiter WASP-43b with Evidence of H{sub 2}O, but No Evidence of Na or K

We present a new ground-based visual transmission spectrum of the hot Jupiter WASP-43b, obtained as part of the ACCESS Survey. The spectrum was derived from four transits observed between 2015 and 2018, with combined wavelength coverage between 5300 and 9000 Å and an average photometric precision of 708 ppm in 230 Å bins. We perform an atmospheric retrieval of our transmission spectrum combined with literature Hubble Space Telescope/WFC3 observations to search for the presence of clouds/hazes as well as Na, K, Hα, and H{sub 2}O planetary absorption and stellar spot contamination over a combined spectral range of 5318–16420 Å. We do not detect a statistically significant presence of Na i or K i alkali lines, or Hα in the atmosphere of WASP-43b. We find that the observed transmission spectrum can be best explained by a combination of heterogeneities on the photosphere of the host star and a clear planetary atmosphere with H{sub 2}O. This model yields a log evidence of 8.26 ± 0.42 higher than a flat (featureless) spectrum. In particular, the observations marginally favor the presence of large, low-contrast spots over the four ACCESS transit epochs with an average covering fraction f{sub het}=0.27{sub −0.16}{sup +0.42} and temperature contrast ΔT = 132 K ± 132 K. Within the planet’s atmosphere, we recover a log H{sub 2}O volume mixing ratio of −2.78{sub −1.47}{sup +1.38}, which is consistent with previous H{sub 2}O abundance determinations for this planet.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Multiplanet System TOI-421: A Warm Neptune and a Super Puffy Mini-Neptune Transiting a G9 V Star in a Visual Binary

We report the discovery of a warm Neptune and a hot sub-Neptune transiting TOI-421 (BD-14 1137, TIC 94986319), a bright (V = 9.9) G9 dwarf star in a visual binary system observed by the Transiting Exoplanet Survey Satellite (TESS) space mission in Sectors 5 and 6. We performed ground-based follow-up observations—comprised of Las Cumbres Observatory Global Telescope transit photometry, NIRC2 adaptive optics imaging, and FIbre-fed Echellé Spectrograph, CORALIE, High Accuracy Radial velocity Planet Searcher, High Resolution Échelle Spectrometer, and Planet Finder Spectrograph high-precision Doppler measurements—and confirmed the planetary nature of the 16 day transiting candidate announced by the TESS team. We discovered an additional radial velocity signal with a period of five days induced by the presence of a second planet in the system, which we also found to transit its host star. We found that the inner mini-Neptune, TOI-421 b, has an orbital period of P{sub b} = 5.19672 ± 0.00049 days, a mass of M{sub b} = 7.17 ± 0.66 M{sub ⊕}, and a radius of R{sub b} = 2.68{sub −0.18}{sup +0.19} R{sub ⊕}, whereas the outer warm Neptune, TOI-421 c, has a period of P{sub c} = 16.06819 ± 0.00035 days, a mass of M{sub c} = 16.42{sub −1.04}{sup +1.06} M{sub ⊕}, a radius of R{sub c} = 5.09{sub −0.15}{sup +0.16} R{sub ⊕}, and a density of ρ{sub c} = 0.685{sub −0.072}{sup +0.080} g cm{sup −3}. With its characteristics, the outer planet (ρ{sub c} = 0.685{sub −0.072}{sup +0.080} g cm{sup −3}) is placed in the intriguing class of the super-puffy mini-Neptunes. TOI-421 b and TOI-421 c are found to be well-suited for atmospheric characterization. Our atmospheric simulations predict significant Lyα transit absorption, due to strong hydrogen escape in both planets, as well as the presence of detectable CH{sub 4} in the atmosphere of TOI-421 c if equilibrium chemistry is assumed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

New Perspectives on the Exoplanet Radius Gap from a Mathematica Tool and Visualized Water Equation of State

Recent astronomical observations obtained with the Kepler and TESS missions and their related ground-based follow-ups revealed an abundance of exoplanets with a size intermediate between Earth and Neptune (1 R ⊕ ≤ R ≤ 4 R ⊕ ). A low occurrence rate of planets has been identified at around twice the size of Earth (2 × R ⊕ ), known as the exoplanet radius gap or radius valley. We explore the geometry of this gap in the mass–radius diagram, with the help of a Mathematica plotting tool developed with the capability of manipulating exoplanet data in multidimensional parameter space, and with the help of visualized water equations of state in the temperature–density (T–ρ) graph and the entropy–pressure (s–P) graph. We show that the radius valley can be explained by a compositional difference between smaller, predominantly rocky planets (<2 × R ⊕ ) and larger planets (>2 × R ⊕ ) that exhibit greater compositional diversity including cosmic ices (water, ammonia, methane, etc.) and gaseous envelopes. In particular, among the larger planets (>2 × R ⊕ ), when viewed from the perspective of planet equilibrium temperature (T eq ), the hot ones (T eq ≳ 900 K) are consistent with ice-dominated composition without significant gaseous envelopes, while the cold ones (T eq ≲ 900 K) have more diverse compositions, including various amounts of gaseous envelopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

New framework for benchmarking decadal predictions leveraging the PCMDI Metric Package with interactive visualization

Reliable climate predictions across multiple timescales are increasingly critical as climate-related risks continue to rise. With the growing number and diversity of climate prediction systems, systematic intercomparison has become essential. Here, we present a comprehensive evaluation framework based on the PCMDI Metric Package to assess the performance of multiple decadal climate prediction systems. Unlike uninitialized simulations, initialized predictions exhibit bias and predictive skill that evolve with forecast lead time. To address this, we introduce (1) model-by-lead-time portrait plots, which efficiently summarize metrics of global temperature, precipitation, and Arctic/Antarctic sea-ice extent, and (2) an HTML-based interactive visualization platform that provides detailed regional and seasonal diagnostics of model bias, skill scores, and ensemble spread for each model and lead time. Comparisons with uninitialized simulations further quantify the relative impacts of initialization and external forcing on prediction skill. The proposed framework provides a scalable and transparent approach for multi-model climate prediction assessments and can be readily extended to a wide range of operational and research forecasting systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Electric Grid Visualization: Hourly Renewable Generation, Load, Unserved Load, and Locational Marginal Prices during a Heatwave

Visualization of hourly solar and wind generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018, 2058, and 2098. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided.

Climate Change↗
DOE OSTI2023

Urban-Scale Heat Wave Visualization: WRF-UCM modeling in Los Angeles, California

This visualization includes an E3SM-based animation of temperatures in North America during the July 2018 heat wave, followed by a higher resolution focus over Los Angeles using the WRF-UCM model to illustrate neighborhood-scale temperatures that account for urban features like buildings, waste heat, and vegetation, as well as sea breeze impacts. Finally, we show the potential impact of cool roofs to reduce temperatures.

Vahmani, Pouya↗
DOE OSTI2025

Electric Grid Visualization: Hourly Generation, Load, Unserved Load, and Locational Marginal Prices during a 2018 Heatwave

Visualization of hourly generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided as well as a county-level choropleth map of temperature.

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2019

Visualization of the flat electronic band in twisted bilayer graphene near the magic angle twist

Bilayer graphene was theorized to host a moire miniband with flat dispersion if the layers are stacked at specific twist angles known as the magic angles. Recently, such twisted bilayer graphene (tBLG) with the first magic angle twist was reported to exhibit correlated insulating state and superconductivity, where the presence of the flat miniband in the system is thought to be essential for the emergence of these ordered phases in the transport measurements. Tunneling spectroscopy and electronic compressibility measurements in tBLG have revealed a van Hove singularity that is consistent with the presence of the flat miniband. However, a direct observation of the flat dispersion in the momentum-space of such moire miniband in tBLG is still elusive. Here, we report the visualization of the flat moire miniband by using angle-resolved photoemission spectroscopy with nanoscale resolution (nanoARPES). The high spatial resolution in nanoARPES enabled the measurement of the local electronic structure of the tBLG. We clearly demonstrate the existence of the flat moire band near the charge neutrality for tBLG close to the magic angle at room temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2020

Apparatus and method for visualization of particles suspended in a fluid and fluid flow patterns using ultrasound

An apparatus and method for real-time visualization of particulate matter suspended in a static or flowing fluid and fluid flow patterns in a pipe, tube, conduit, or other container, are described. Ultrasonic scanning and detection of scattered sound from the particles in the fluid create a real-time image of the particles, or of flow patterns in the liquid. A mechanical wobbler directs a piezoelectric transducer over a chosen angle in an oscillatory manner. The transducer is operated in a pulse-echo mode wherein the same transducer detects the return signal from the target region through which particles are passing and/or a flow is present. The pulse-echo measurements are made rapidly and continuously during a single sweep of the transducer over the chosen angle. Received signals are processed in the ultrasound scanner electronics module and displayed as an image in real-time.

42 ENGINEERING↗
DOE OSTI2020

High Performance Computing Systems Tools, Visualization, and Management

High Performance Computing (HPC) systems are complex setups of servers, storage devices, network switches, and cables that are specifically designed to accommodate hundreds of users running highly computationally intensive applications at a time. These applications require numerous softwares, licenses, and various levels of storage as well. All of these resources must be monitored and managed by HPC administrators, which presents a daunting task. In this project, I created numerous software tools as part of an HPC Visualization and Management system, which is now used by HPC administrators on a daily basis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Overview of the Circular Economy Lifecycle Assessment and VIsualization (CELAVI) Framework

A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. This presentation will review and contrast nine current impact assessment methods and describe their granularity, scope, data requirements, and capabilities within the context of identifying regional and sectoral transfers of impacts that could result from transitioning to a circular economy for energy systems. The review of current approaches highlights the need for a new hybrid circularity assessment framework that leverages multiple methods. We describe one such approach: the Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework. CELAVI uses system dynamics to model material flows for multiple circular economy pathways, network theory to track the spatial and sectoral flow of functional units across a graph, and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable enough to accommodate multiple energy materials and multiple energy technologies. CELAVI's hybridization of multiple existing methods yields additional capabilities, which may help answer questions about how flows between the technosphere and ecosphere may evolve if the circularity of energy systems is modified.

circular economy↗
DOE OSTI2020

In-Situ Visualization of Long-Range Defect Interactions at the Edge of Melting

Connecting a bulk material’s microscopic defects to its macroscopic properties is an age-old problem in materials science. Long-range interactions between dislocations (line defects) are known to play a key role in how materials deform or melt, but we lack the tools to connect these dynamics to the macroscopic properties. We introduce time-resolved dark-field X-ray microscopy to directly visualize how dislocations move and interact over hundreds of micrometers, deep inside bulk aluminum. With real-time movies, we reveal the thermally activated motion and interactions of dislocations that comprise a boundary, and show how weakened binding forces inhomogeneously destabilize the structure at 99% of the melting temperature. Connecting dynamics of the microstructure to its stability, we provide important opportunities to guide and validate multiscale models that are yet untested.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2020

Towards Trust-Augmented Visual Analytics for Data-Driven Energy Modeling

The promise of data-driven predictive modeling is being increasingly realized in various science and engineering disciplines, where experts are used to the more conventional, simulation-driven modeling practices. However, trust remains a bottleneck for greater adoption of machine learning-based models for domain experts, who might not be necessarily trained in data science. In this paper, we focus on the building energy domain, where physics-based simulations are being complemented or replaced by machine learning-based methods for forecasting energy supply and demand at various spatio-temporal scales. We study the trust problem in close collaboration with energy scientists and engineers and describe how visual analytics can be leveraged for alleviating this trust bottleneck for stakeholders with varying degrees of expertise and analytics goals in this domain.

Kandakatla, Akshith R.↗
DOE OSTI2020

Parallel Particle Advection Bake-Off for Scientific Visualization Workloads

There are multiple algorithms for parallelizing particle advection for scientific visualization workloads. While many previous studies have contributed to the understanding of individual algorithms, our study aims to provide a holistic understanding of how algorithms perform relative to each other on various workloads. To accomplish this, we consider four popular parallelization algorithms and run a “bake-off” study (i.e., an empirical study) to identify the best matches for each. The study includes 216 tests, going to a concurrency of up to 8192 cores and considering data sets as large as 34 billion cells with 300 million particles. Overall, our study informs three important research questions: (1) which parallelization algorithms perform best for a given workload?, (2) why?, and (3) what are the unsolved problems in parallel particle advection? In terms of findings, we find that the seeding box is the most important factor in choosing the best algorithm, and also that there is a significant opportunity for improvement in execution time, scalability, and efficiency.

Pugmire, Dave↗
DOE OSTI2021

TracKlinic: Diagnosis of Challenge Factors in Visual Tracking

Generic visual object tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracker, and when they work together can make things even more complicated. Despite a great amount of efforts devoted to understanding the behavior of trackers, reliable and quantifiable ways for studying the per factor tracking behavior remain barely available. Addressing this issue, in this paper we contribute to the community a tracking diagnosis toolkit, TracKlinic, for diagnosis of challenge factors of tracking algorithms. TracKlinic consists of two novel components focusing on the data and analysis aspects, respectively. For the data component, we carefully prepare a set of 2,390 annotated videos, each involving one and only one major challenge factor. When analyzing an algorithm for a specific challenge factor, such one-factor-per-sequence rule greatly inhibits the disturbance from other factors and consequently leads to more faithful analysis. For the analysis component, given the tracking results on all sequences, it investigates the behavior of the tracker under each individual factor and generates the report automatically. With TracKlinic, a thorough study is conducted on ten state-of-the-art trackers on nine challenge factors (including two compound ones). The results suggest that, heavy shape variation and occlusion are the two most challenging factors faced by most trackers. Besides, out-of-view, though does not happen frequently, is often fatal. By sharing TracKlinic1, we expect to make it much easier for diagnosing tracking algorithms, and to thus facilitate developing better ones.

97 MATHEMATICS AND COMPUTING↗