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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗
DOE OSTI2026

MAGIC: M arching Cubes Isosurface Uncertainty Visualization for G auss i an Uncertain Data With Spatial C orrelation

Here, in this paper, we study the propagation of data uncertainty through the marching cubes algorithm for isosurface visualization for correlated uncertain data. Consideration of correlation has been shown paramount for avoiding errors in uncertainty quantification and visualization in multiple prior studies. Although the problem of isosurface uncertainty with spatial data correlation has been previously addressed, there are two major limitations to prior treatments. First, there are no analytical formulations for uncertainty quantification of isosurfaces when the data uncertainty is characterized by a Gaussian distribution with spatial correlation. Second, as a consequence of the lack of analytical formulations,existing techniques resort to a Monte Carlo sampling approach, which is expensive and difficult to integrate into visualization tools. To address these limitations, we present a closed-form framework to efficiently derive uncertainty in marching cubes level-sets for Gaussian uncertain data with spatial correlation (MAGIC). To derive closed-form solutions, we leverage the Hinkley's derivation on the ratio of Gaussian distributions. With our analytical framework, we achieve a significant speed-up and enhanced accuracy of uncertainty quantification over classical Monte Carlo methods. We further accelerate our analytical solutions using many-core processors to achieve speed-ups up to 585× and integrability with production visualization tools for broader impact. We demonstrate the effectiveness of our correlation-aware uncertainty framework through experiments on meteorology, urban flow, and astrophysics simulation datasets.

Gaussian↗
DOE OSTI2026

Materializing Inter-Channel Relationships With Multi-Density Woodcock Tracking

Volume rendering techniques for scientific visualization have recently shifted toward Monte Carlo (MC) methods for their flexibility and robustness, but their use in multi-channel visualization remains underexplored. Traditional multi-channel volume rendering often relies on arbitrary, non-physically based color blending functions that hinder interpretation. Here, we introduce multi-density Woodcock tracking, a simple extension of Woodcock tracking that leverages an MC method to produce high-fidelity, physically grounded multi-channel renderings without arbitrary blending. By generalizing Woodcock’s distance tracking, we provide a unified blending modality that also integrates blending functions from prior works. We further implement effects that enhance boundary and feature recognition. By accumulating frames in real-time, our approach delivers high-quality visualizations with perceptual benefits, demonstrated on diverse datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Efficient Probabilistic Visualization of Local Divergence of 2D Vector Fields with Independent Gaussian Uncertainty

This work focuses on visualizing uncertainty of local divergence of two-dimensional vector fields. Divergence is one of the fundamental attributes of fluid flows, as it can help domain scientists analyze potential positions of sources (positive divergence) and sinks (negative divergence) in the flow. However, uncertainty inherent in vector field data can lead to erroneous divergence computations, adversely impacting downstream analysis. While Monte Carlo (MC) sampling is a classical approach for estimating divergence uncertainty, it suffers from slow convergence and poor scalability with increasing data size and sample counts. Thus, we present a two-fold contribution that tackles the challenges of slow convergence and limited scalability of the MC approach. (1) We derive a closed-form approach for highly efficient and accurate uncertainty visualization of local divergence, assuming independently Gaussian-distributed vector uncertainties. (2) We further integrate our approach into Viskores, a platform-portable parallel library, to accelerate uncertainty visualization. In our results, we demonstrate significantly enhanced efficiency and accuracy of our serial analytical (speed-up up to 1946×) and parallel Viskores (speed-up up to 19698×) algorithms over the classical serial MC approach. We also demonstrate qualitative improvements of our probabilistic divergence visualizations over traditional mean-field visualization, which disregards uncertainty. We validate the accuracy and efficiency of our methods on wind forecast and ocean simulation datasets.

Ouermi, Timbwaoga [University of Utah]↗
DOE OSTI2025

Orientation microscopy–assisted grain boundary analysis for protonic ceramic cell electrolytes

Abstract Grain boundaries in protonic ceramic cell (PCC) electrolytes hinder proton transport, reducing interfacial conductivity. In multicomponent PCC electrolytes, the inclusion of sintering aids further accentuates the complexity of grain boundaries. In this study, we synthesize nanocrystalline BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3− δ thin films via pulsed laser deposition and analyze their grain boundary character distributions using orientation data collected by precession electron diffraction technique. The results reveal an anisotropic distribution of grain boundary characters, with notably high populations of 180°‐tilt and twist grain boundaries. These findings provide critical insights into identifying the predominant grain boundaries in this PCC electrolyte material, assessing the vast five‐dimensional grain boundary space.

Patel, Sooraj [School of Aerospace and Mechanical ↗
DOE OSTI2025

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

Abstract The vitrification of high‐level waste (HLW) by heating a mixture of glass‐forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization algorithm that requires derivative information. Other UP methods often used for optimization under uncertainty (OUU) can be designed to work within an established constrained optimization framework. Methods of UP are evaluated in this study including iterative sampling approaches, first‐order approximations, and surrogate modeling with machine learning (ML). A method of dimensional reduction based on global sensitivity analysis is introduced to support the UP methods for the large dimensionality of the problem. Analytical UP methods able to achieve similar optimums 10 times faster than the baseline MC approach, and produce 93.9% similar output distributions are reported.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

RefAHL: a curated quorum sensing reference linking diverse LuxI-type signal synthases with their acyl-homoserine lactone products

Some bacteria use acyl-homoserine lactone (AHL) signals in quorum sensing, a type of cell-cell communication. Here, we present “RefAHL,” an updated, curated collection of LuxI-type AHL synthases with their AHL products and associated metadata. RefAHL is publicly available as a community resource to help catalog LuxI-type diversity encoded in (meta) genomic data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

ASCENT-TRAME BRIDGE

SF-25-116 Bridge for accessing Ascent extracts in a Trame application to create intuitive computational steering interfaces for HPC simulations.

MARRINAN, THOMASJOHN [Argonne National Laboratory ↗
DOE OSTI2025

AmeriFlux US-UTM UFLUX Matheson

This is the AmeriFlux version of the carbon flux data for the site US-UTM UFLUX Matheson. Site Description - This station is located in a wetland, surrounded by bulrushes

Ladig, Kathryn [Utah Geological Survey]↗
DOE OSTI2025

AmeriFlux US-UTW UFLUX Wellington

This is the AmeriFlux version of the carbon flux data for the site US-UTW UFLUX Wellington. Site Description - This station is located between two large pivots that irrigate alfalpha. The pivots are in line with the predominant wind direction. The farm is no-till and uses canal water to irrigate. The field is grazed by cattle in the early winter.

Ladig, Kathryn [Utah Geological Survey]↗
DOE OSTI2025

AmeriFlux US-UTV UFLUX Desert View

This is the AmeriFlux version of the carbon flux data for the site US-UTV UFLUX Desert View. Site Description - This station is located alongside a large pivot that irrigate alfalpha.

Ladig, Kathryn [Utah Geological Survey]↗
DOE OSTI2025

AmeriFlux FLUXNET-1F US-UTV UFLUX Desert View

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UTV UFLUX Desert View. This is the FLUXNET version of the carbon flux data for the site US-UTV UFLUX Desert View produced by applying the standard ONEFlux (1F) software. Site Description - This station is located alongside a large pivot that irrigate alfalpha.

Ladig, Kathryn [Utah Geological Survey]↗
DOE OSTI2026

AmeriFlux US-UTL UFLUX Pelican Lake

This is the AmeriFlux version of the carbon flux data for the site US-UTL UFLUX Pelican Lake. Site Description - This station is on a drip irrigated alflafa field

Menuz, Diane [Utah Geological Survey]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UTW UFLUX Wellington

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UTW UFLUX Wellington. This is the FLUXNET version of the carbon flux data for the site US-UTW UFLUX Wellington produced by applying the standard ONEFlux (1F) software. Site Description - This station is located between two large pivots that irrigate alfalpha. The pivots are in line with the predominant wind direction. The farm is no-till and uses canal water to irrigate. The field is grazed by cattle in the early winter.

Ladig, Kathryn [Utah Geological Survey]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UTM UFLUX Matheson

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UTM UFLUX Matheson. This is the FLUXNET version of the carbon flux data for the site US-UTM UFLUX Matheson produced by applying the standard ONEFlux (1F) software. Site Description - This station is located in a wetland, surrounded by bulrushes

Ladig, Kathryn [Utah Geological Survey]↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UTL UFLUX Pelican Lake

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UTL UFLUX Pelican Lake. This is the FLUXNET version of the carbon flux data for the site US-UTL UFLUX Pelican Lake produced by applying the standard ONEFlux (1F) software. Site Description - This station is on a drip irrigated alflafa field

Menuz, Diane [Utah Geological Survey]↗
DOE OSTI2025

NPFTURBULENCE-Turbulent Layers Promoting New Particle Formation Field Campaign Report

This field campaign took place at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) use facility’s Southern Great Plains (SGP) atmospheric observatory, located near Lamont, Oklahoma. The ArcticShark uncrewed aerial system conducted 10 research flights, accumulating 40.7 flight hours over the SGP site. Each flight originated from the Blackwell-Tonkawa Airport (BKN) and followed a “racetrack” pattern around the SGP field site. During these flights, mission scientists initiated vertical profiling based on the real-time performance of the aerosol instruments aboard the ArcticShark. Figure 1 below illustrates the flight paths of all missions.

54 ENVIRONMENTAL SCIENCES↗