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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Image Classification Using Convolutional Neural Networks to Automate Visual Inspection of CCO Containers (Rev. 1)

The Savannah River Site is automating the receipt and inspection of Criticality Control Overpack drums to aid in nuclear waste disposal. The Advanced Engineering group is automating this receipt and inspection process to assist the site’s goals. Part of this process includes visually inspecting CCO drums to ensure that no defects or security risks are present. This research focuses on developing a machine learning model to automatically classify drums as passing or failing inspection. The machine learning model was implemented using the open-source Tensorflow library and uses a Convolutional Neural Network architecture to extract features and differentiate between images. The model was able to achieve an average of 85% accuracy on a dataset of 288 drums. This project’s goal was to prove the validity of computer vision in an automation process and provide a starting place for continued research.

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

Spatially resolved charge-transfer kinetics at the quantum dot–microbe interface using fluorescence lifetime imaging microscopy

Integrating the optoelectronic properties of quantum dots (QDs) with biological enzymatic systems to form microbe-semiconductor biohybrids offers promising prospects for both solar-to-chemical conversion and light-modulated biochemical processes. Developing these nano–bio hybrid systems necessitates a deep understanding of charge-transfer dynamics at the nano–bio interface. Photoexcited carrier transfer from QDs to microbes is driven by complex interactions, with emerging insights into the relevant thermodynamic and kinetic factors. The heterogeneities of both microbes and QD ensembles pose significant challenges in mechanistic understanding, which is critical for designing advanced nano–bio hybrids. We used fluorescence lifetime imaging microscopy to analyze charge transfer between a CdSe QD film andShewanella oneidensismicrobes. We correlated the spatiotemporal fluorescence data with an analytical model. Our analysis revealed two distinct distributions of QD de-excitation pathways. The characteristics of these distributions: 1) a faster transfer rate ( k ¯ E T 1 = 1.5 10 9 s - 1 ), with a lower acceptor number ( N ¯ a 1 = 0.03 ) and 2) a slower transfer rate ( k ¯ E T 2 = 4.1 10 8 s - 1 ) with a higher acceptor number ( N ¯ a 2 = 0.18 ). We assign these distributions to the indirect and direct electron transfer mechanisms, respectively. Our findings demonstrate how spectroscopic imaging can uncover fundamental electron transfer mechanisms at complex interfaces, offering valuable design principles for future nano–bio hybrids.

Science & Technology - Other Topics↗
DOE OSTI2024

Gas pore correlations in laser powder bed fusion of Al6061

Additive manufacturing (AM) of metal materials based on powder bed fusion technology is widely used now in many industries. A known limitation of this type of manufacturing is the formation of gas pores in the bulk material. Here we present a combined X-ray imaging and mid-infrared pyrometry study of pore formation in side-by-side tracks of Al6061 for different processing conditions using both in-situ and post-processing analysis. By carefully quantifying the distributions and correlations of pore positions, we show that an existing pore in one track often catalyzes the formation of another pore in an adjacent track. In a raster scan strategy commonly used to construct bulk material, this phenomenon has the result of forming subsurface perforations, or lines of pores transverse to the scanning direction in a rastered patch. If controlled, this effect can be eliminated to improve the yield strength of the build, or exploited to create programmable failures for specific purposes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs including Radar, SWIR, Thermal, Geophysics, Geology, and Wells. The files for the Desert Peak Geothermal Site are used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Desert Peak Geothermal Field.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

HME MicroCT Data Acquisition, Processing and Data Request Overview

This document is a short summary of the steps required for MicroCT evaluation of a specimen. This includes data acquisition through image analysis, for the Explosives Threat Assessment (ETA) program. Expected outputs for each stage are outlined. Information and data shall be shipped to LLNL as described herein.

42 ENGINEERING↗
DOE OSTI2023

Using Low-Field Nuclear Magnetic Resonance and X-Ray Computed Microtomography Imaging to Explore Potential of Microbially-Induced Calcium Carbonate Precipitation Treatment to Seal Shale Fractures

Microbially-induced calcium carbonate precipitation (MICP) is a biological process in which microbially produced urease enzymes convert urea and calcium into solid calcium carbonate (CaCO 3 ) deposits. Studies have shown that MICP can be used to seal fractures in shale, raising the possibility of applying this technology to restimulate fracking wells by plugging underperforming fractures. For this and other applications to become a reality, non-invasive tools are needed to determine how effectively MICP seals shale fractures under subsurface conditions. In this study, a 2.54 cm wide and 5.08 cm long Marcellus shale core with a single, ~1 mm wide fracture held open by sand "proppant" underwent MICP-treatment at 60°C until reaching three orders of magnitude permeability reduction. Low-field nuclear magnetic resonance (LF-NMR) and X-Ray computed microtomography (μ-CT) techniques were used to assess the extent of biomineralization within the fracture. These tools revealed that while CaCO 3 precipitation occurred throughout the fracture, there was preferential precipitation around proppant, and the core sealed at the effluent end before filling most of the fracture. Both tools were able to independently calculate of the amount of solid biomineral formed inside the fracture. Furthermore, this study found that the distribution of proppant within the shale fracture was an important parameter controlling the degree of biomineralization.

clastic rock↗
DOE OSTI2024

Direct Air Capture of CO 2 via Reactive Crystallization

Atmospheric CO 2 removal using engineered chemical processes, aka direct air capture (DAC), has become an essential component of our available portfolio for mitigating climate change. Here we describe a promising approach to DAC based on reactive crystallization of atmospheric CO 2 (RC-DAC) with aqueous guanidine and amino acid. Compared to the previously studied phase-changing DAC processes involving initial CO 2 absorption by an aqueous alkaline solvent followed by carbonate crystallization in a second step, RC-DAC combines the CO 2 absorption and carbonate crystallization into a single step. Thus, as the insoluble carbonate salts are removed from solution by crystallization, more CO 2 is pulled from the air into solution, further driving the DAC process. The RC-DAC was performed in a household humidifier as the air–liquid contactor, which can handle solid–liquid slurries effectively. The crystallization was monitored in situ by pH measurements, real-time imaging with a microscope probe, and by Raman spectroscopy, and ex situ by NMR spectroscopy, powder X-ray diffraction, and total inorganic carbonate analysis. Further, the investigation provided a detailed mechanistic picture of the RC-DAC process, involving formation of carbamate and carbonate anions in solution, followed by sequential crystallization of different guanidinium carbonate phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Plasma Imaging, LOcal Measurement, and Tomographic Experiment (PILOT): A Mission Concept for Transformational Multi-Scale Observations of Mass and Energy Flow Dynamics in Earth’s Magnetosphere

We currently do not understand the fundamental physical processes that govern mass and energy flow through the Earth’s magnetosphere. Knowledge of these processes is critical to understanding the mass loss rate of Earth’s atmosphere, as well as for determining the role that a planetary magnetic field plays in atmospheric retention, and therefore habitability, for Earth-like planets beyond the solar system. Mass and energy flow processes are challenging to determine at Earth in part because Earth’s planetary magnetic field creates a complex “system of systems” composed of interdependent plasma populations and overlapping spatial regions that perpetually exchange mass and energy across a broad range of temporal and spatial scales. Further, the primary mass carrier in the magnetosphere is cold plasma (as cold as ~0.1 eV), which is invisible to many space-borne instruments that operate in the inner magnetosphere. The Plasma Imaging LOcal and Tomographic experiment (PILOT) mission concept, described here, provides the transformational multi-scale observations required to answer fundamental open questions about mass and energy flow dynamics in the Earth’s magnetosphere. PILOT uses a constellation of spacecraft to make radio tomographic, remote sensing, and in-situ measurements simultaneously, fully capturing cold plasma mass dynamics and its impact on magnetospheric systems over an unprecedented range of spatial and temporal scales. This article details the scientific motivation for the PILOT mission concept as well as a potential mission implementation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effect of Hydrogen on Steady-State and Transient Combustion Instability Characteristics

This paper examines the effects of steady-state and transient hydrogen enrichment on thermoacoustic instability in a model gas turbine combustor. Combustion instability, a feedback loop between flame heat release rate oscillations and combustor acoustics, is characterized in a swirl-stabilized flame operated at a range of hydrogen–natural gas fuel blends and heat rates. Measurements of combustor chamber pressure fluctuations and CH* chemiluminescence imaging are used to characterize instability at a range of operating conditions. Steady-state tests show that both mixture heat rate and hydrogen content affect system stability. At a given heat rate, higher levels of hydrogen result in unstable combustion. As heat rate increases, instability occurs at lower concentrations of hydrogen in the fuel. Transient operation was tested in two directions—instability onset and decay—and two hydrogen-addition times—a short time of 1 ms and a longer time of 4 s. Results show that instability onset processes, through the transient addition of hydrogen, are highly repeatable regardless of the timescale of hydrogen addition. Certain instability decay processes are less repeatable, resulting in cases that do not fully transition from unstable to stable combustion despite similar changes in hydrogen fuel flow rate. Flame behavior before, during, and after the transient is characterized using high-speed CH* chemiluminescence imaging. Analysis of the high-speed images shows changes in flame stabilization and dynamics during the onset and decay processes. Finally, the results of this study can have implications for systems that experience variations in fuel composition, particularly in light of growing interest in hydrogen as a renewable fuel.

42 ENGINEERING↗
DOE OSTI2024

DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data

Abstract Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques offer a method to enhance the resolution of these images, enabling more precise measurements of lensing effects and a better understanding of the matter distribution in the lensing system. This enhancement can significantly improve our knowledge of the distribution of mass within the lensing galaxy and its environment, as well as the properties of the background source being lensed. Traditional super-resolution techniques typically learn a mapping function from lower-resolution to higher-resolution samples. However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce DiffLense , a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model’s training phase. We demonstrate that DiffLense outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.

Computer Science↗
DOE OSTI2021

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-processed data). In each of these categories there are six additional types of raster catalogs which are titled Radar, SWIR, Thermal, Geophysics, Geology, and Wells. These inputs and outputs were used with the Geothermal Exploration Artificial Intelligence to identify indicators of blind geothermal systems at the Brady Hot Springs Geothermal Site. The included zip file is a geodatabase to be used with ArcGIS and the tar file is an inclusive database that encompasses the inputs and outputs for the Brady Hot Springs Geothermal Site.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

In vivo visualization of butterfly scale cell morphogenesis in Vanessa cardui

Many organisms exhibit functional micro- and nanoscale materials with structural definition and performance that challenge synthetic fabrication techniques, yet we know little about the processes that enable their formation. Using butterfly scales as a model system for functional biomaterials, we establish a timeline of scale formation and quantify relevant structural parameters for developing painted lady butterflies. We overcome challenges of previous efforts by imaging structure formation directly in living organisms, which allows us to continuously observe the evolving wing tissue and the fine details of individual scale cells. Visualization of scale structure formation in live butterflies forms the basis for modeling the underlying biomechanical processes and opens avenues for their translation into advanced fabrication strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Shower Reconstruction for Cross-Section Measurements with Photon(s) in the Final State at SBND

The Short-Baseline Near Detector (SBND) is a 112-ton liquid argon time projection chamber operating in the Booster Neutrino Beam at Fermilab as part of the Short-Baseline Neutrino Program. Precise reconstruction of electromagnetic showers from photons and electrons is essential for searches for neutrino oscillations, cross-section measurements, and rare-process studies in liquid argon. In this poster, we present a unified set of SBND analyses enabled by the SPINE (Scalable Particle Imaging with Neural Embeddings) end-to-end machine-learning–based reconstruction framework, highlighting charged-current neutral pion (CC π⁰) production and neutral-current (NC) Δ radiative decay as complementary physics cases. Charged-current π⁰ interactions provide a high-statistics benchmark for validating photon reconstruction, constraining the electromagnetic energy scale, and modeling backgrounds to other cross-section measurements and BSM searches with one or more photons in the final state. We summarize progress toward the ongoing development of a CC π⁰ selection in SBND and, report on the current status of a search for NC resonant Δ production followed by radiative decay (Δ→Nγ) in SBND. This rare process, previously investigated in MicroBooNE, provides a stringent test of photon-only final-state reconstruction and is of interest in the context of the MiniBooNE low-energy excess. Together, these analyses demonstrate how modern machine-learning–based shower reconstruction enables a diverse and scalable physics program at SBND.

Chung, Seokju [Nevis Labs, Columbia U.]↗
DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Application of automated iterative target detection for standoff hyperspectral imaging

The utility of hyperspectral imaging (HSI) has been well established for a wide array of applications but has generated a need for automated screening of high volumes of large HSI cubes. We report two important automated algorithms for more efficient standoff processing: atmospheric correction and target detection. The atmospheric correction method is based on a fast asymmetric least squares approach that is applied on a pixel-by-pixel basis. Here, the correction can be applied to entire images without manually identifying regions of interest and utilizes only in-scene information, no ancillary modeling of the atmosphere is required. An iterative target detection approach is also introduced which demonstrates faster speeds relative to moving window approaches. The target detection algorithm classifies each pixel as true target detections, near target detections, clutter, and no-calls. The algorithms were tested on forty images of twenty-two solid mineral targets placed at a 14-meter standoff distance allowing general observations on expected detection performance for a variety of minerals. In addition to identifying anomalous pixels, the inclusion of “no-calls” reduced the number of false detections significantly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

In situ electrochemical scanning/transmission electron microscopy of electrode–electrolyte interfaces

Insights into the dynamics of electrochemical processes are critically needed to improve our fundamental understanding of electron, charge, and mass transfer mechanisms and reaction kinetics that influence a broad range of applications, from the functionality of electrical energy-storage and conversion devices (e.g., batteries, fuel cells, and supercapacitors), to materials degradation issues (e.g., corrosion and oxidation), and materials synthesis (e.g., electrodeposition). To unravel these processes, in situ electrochemical scanning/transmission electron microscopy (ec-S/TEM) was developed to permit detailed site-specific characterization of evolving electrochemical processes that occur at electrode–electrolyte interfaces in their native electrolyte environment, in real time and at high-spatial resolution. This approach utilizes “closed-form” microfabricated electrochemical cells that couple the capability for quantitative electrochemical measurements with high spatial and temporal resolution imaging, spectroscopy, and diffraction. Here, we review the state-of-the-art instrumentation for in situ ec-S/TEM and how this approach has resulted in new observations of electrochemical processes.

25 ENERGY STORAGE↗
DOE OSTI2022

Improved geophysical monitoring of carbon sequestration through parameter linkage to reservoir modeling

Predictive reservoir modeling, even if present in the form of only basic hydrogeological model assumptions, is expected to accompany the majority of carbon capture and sequestration monitoring activities. It thus represents a source of prior information about the migration of injected fluids that can benefit geophysical survey planning and ensuing monitoring. Constraining the imaging of geophysical monitoring data with reservoir modeling is preferable over standalone geophysical imaging because of additional complementary hydrogeological information. However, fully coupled hydrogeophysical data inversion for flow-modeling parameters that control saturation predictions is an involved process. Within the context of three-dimensional electromagnetic (EM) inversion of data from borehole-to-surface layouts, we employ a "poor people's" alternative. The approach constrains geophysical inversion parameters through saturation predictions. The coupling is realized through spatially variable lower and upper parameter bounds that scale with gas saturation magnitudes, the latter provided by reservoir modeling. In this work, enhancement of three-dimensional time-lapse plume EM imaging is demonstrated for simulated sequestration into a depleted gas reservoir.

58 GEOSCIENCES↗
DOE OSTI2022

Explosion dynamics of thin flat foils at high current density

This paper presents characteristic features of the explosion of thin flat foils for currents and pulse risetimes ranging from 8 kA at 350 ns to 1000 kA at ~100 ns. Foils made of aluminum, copper, nickel, and titanium with thicknesses of 1–100 µm are tested. Various diagnostics in the optical, UV, and x-ray spectral ranges are used to image the exploding foils from initial breakdown to complete destruction or pinching. It is shown that foil explosion is a complex process that depends on many factors, but features common to all foils are found that do not depend on the parameters of the generators or, accordingly, on the energy deposited in the foil: for example, the breakdown of flat foils under different conditions occurs at the edges of the foil. For the first time, the formation of a precursor over the central part of the foil is shown, which significantly changes the dynamics of the foil explosion.

36 MATERIALS SCIENCE↗