SEARCH · Engineering Papers

Results for “in situ 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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Direct Multimodal Nanoscale Visualization of Early Phosphorus-Based Antiwear Tribofilm Formation

Understanding the mechanism of antiwear (AW) tribofilm formation and how to tune surface chemistry to control functionality is essential for the development of the next generation of oil lubricants. In particular, understanding and optimizing early AW tribofilm formation can increase the energy efficiency of mechanical systems. However, the mechanism for how these films form is not well understood. The majority of prior work has focused on analyzing only end-of-test surfaces long after the film has formed. In this work, we develop an in situ multimodal chemical imaging methodology to directly visualize the early formation of AW films on steel surfaces. We investigate an oil formulation containing a phosphorus-based additive commonly used to protect surfaces from wear and fatigue processes in machine elements, such as gears, bearings, and sliding contacts. Using nanoscale multimodal chemical imaging on combined platforms of atomic force microscopy (AFM) coupled directly with in situ nano-infrared (nano-IR) spectroscopy, and further combined ex situ with time-of-flight secondary ion mass spectrometry (ToF-SIMS), we demonstrate a direct correlation between changes in friction and local surface chemistry. In these experiments, the AFM probe acts as a single asperity contact to generate the tribofilm as well as a tool to analyze it in situ as it is forming. To verify our in situ measurements, we compare these results to the ex situ ToF-SIMS of macroscale block-on-ring tribometer-formed samples. We report the understanding gained here on how AW films form and how film properties can be modified by tuning the chemistry of the additives will facilitate developing transmission fluids to meet increasing demands for vehicle performance and efficiency.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Deep learning for in situ data compression of large turbulent flow simulations

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

AEflow (Autoencoder fluid flow compression network) [SWR-22-29]

King, Ryan↗

NASA NTRS1988

Application of Hoffman modulation contrast microscopy coupled with three-wavelength two-beam interferometry to the in situ direct observation of the growth process of a crystal in microgravity

Direct visualization of three dimensional transfer process of both heat and mass around a growing crystal and mono-molecular growth layers on the surface is possible in situ by means of high resolution Hoffman modulation contrast microscopy coupled with three wavelength two beam Mach-Zehnder interferometry. This in situ observation is very suitable for the verification of the growth mechanism of a crystal in a solution or a melt in microgravity.

Tsukamoto, Katsuo↗

DOE OSTI2024

Direct Visualization of Laser-Induced Coalescence and Alloying of Au into Ag Nanowires

Noble metal nanocomposites with controlled morphology and composition have been largely useful in a wide variety of applications like catalysis, plasmonics, and biological applications. Herein, we show pulsed-laser-assisted fabrication of beaded Au-Ag nanowires with a variety of morphologies and compositions via coalescence and alloying of Au nanoparticles (NP) into a Ag nanowire (NW). Direct visualization of the evolution process with in situ laser heating transmission electron microscopy (ILH-TEM) leads to unambiguous insights into the mechanism of formation for the first time. Ag, being a soft material, melts at the surface to bridge the gap between the NP-NW, forming a cup-like morphology underneath the Au NP via capillary action. Progressive laser irradiation leads to wetting of the Au NP with Ag, forming an envelope around the NP. This is associated with the formation of a valley in Ag NW around the NP, which flattens gradually by partial embedding of the NP. Interdiffusion of Au into Ag and vice versa sets in at this stage, leading to the depletion of Au from the Au-rich NP region. Prolonged irradiation leads to gradual intermixing of Au-Ag forming beaded Au-doped Ag nanowires with homogeneous composition. Such a step-by-step understanding of the coalescence and alloying process has implications in nanowelding, which holds the future in designing efficient transparent conductors and printed electronics.

Isik, Tugba↗

DOE OSTI2026

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and resolving their structures at subnanometre resolution [Tegunov et al. (2021)View full citation, Nat. Methods, 18, 186–193]. Despite improvements in data quality as a result of advances in detector technology, microscope stability and stage precision, the analysis and interpretation of tomograms remains challenging due to a low signal-to-noise ratio and reconstruction artifacts stemming from experimental constraints in specimen tilt during data collection resulting in a missing wedge in the Fourier space. Recently, self-supervised deep-learning methods have been proposed for contrast enhancement and reduction of resolution anisotropy in reconstructed tomograms. Here, we evaluate several state-of-the-art deep-learning methods which aim to improve the interpretability of cryo-ET reconstructions, with a focus on their performance on downstream tasks of template matching, subtomogram averaging and segmentation. We propose new training architectures and a loss function based on Fourier shell correlation that show improved performance over the standard U-Net with L1/L2 losses. We demonstrate our analysis on four diverse experimental datasets: purified 80S ribosomes, in situ Chlamydomonas reinhardtii, immature HIV-1 virus-like particles and INS-1E cells.

contrast enhancement↗

DOE OSTI2024

Evaluating the Effectiveness of a Detection and Deterrent System in Reducing Golden Eagle Fatalities at Operational Wind Facilities

The Renewable Energy Wildlife Institute (REWI) was appointed as the prime awardee of DOE award number DE-EE0007883 to lead a team of scientists, wind developers, and technology manufacturers toward the overarching goal of evaluating the effectiveness of the current DTBird system in minimizing the risk of golden eagles (Aquila chrysaetos) and other large soaring raptors from approaching the rotor-swept zone (RSZ) of operating wind turbines. As part of this goal, the team set out to 1) quantify the expected reduction in collision risk for golden eagles from operation of the detection and deterrence modules in a manner that supports the approach used by the U.S. Fish and Wildlife Service (USFWS) to assess and credit facility operators for their efforts to minimize predicted collision fatalities and 2) provide information to help improve the technology to maximize its effectiveness. DTBird is an automated detection and audio deterrent system created by the Spanish company Liquen, designed to discourage birds from entering the RSZ of spinning wind turbines. The system uses cameras to automatically detect airborne targets of interest, records each such event in an online database, and triggers a warning signal (loud sound) if the tracked object has moved close to the turbine. If the object moves even closer to the RSZ, a more aggressive dissuasion signal is broadcast. To meet our objectives, the team conducted a two-year experiment at the Goodnoe Hills wind facility in Washington state, in which 14 turbines were outfitted with DTBird units. Daily, each DTBird-equipped turbine was randomly assigned to a control or treatment group. Treatment turbines operated with DTBird running as intended—broadcasting warning or deterrent signals when DTBird detected a target within range. On control turbines, no sound signals were broadcast if a moving target triggered the DTBird system. The team also flew unmanned aerial vehicles (UAVs) designed to coarsely mimic the general size, weight, and coloration of golden eagles in programmed flight transects across DTBird detection ranges to quantify DTBird’s ability to detect intended targets and to evaluate factors that influence the probability of detection and DTBird’s response distances. Additionally, the team evaluated the behavioral responses of in situ eagles exposed to spinning turbines alone (visual and sound influences) versus spinning turbines plus broadcasted DTBird audio deterrents, to estimate the effectiveness of deterrence by the DTBird system. The data and results from these investigations were combined with those from a pilot study conducted at the Manzana Wind Power Project in California to better evaluate DTBird’s effectiveness across different landscapes.

17 WIND ENERGY↗

NASA NTRS1977

Simulation of space radiation effects on polyimide film materials for high temperature applications

Space environment effects on candidate materials for the solar sail film are determined. Polymers, including metallized polyimides that might be suitable solar radiation receivers, were exposed to combined proton and solar electromagnetic radiation. Each test sample was weighted, to simulate the tension on the polymer when it is stretched into near-planar shape while receiving solar radiation. Exposure rates up to 16 times that expected in Earth orbit were employed, to simulate near-sun solar sailing conditions. Sample appearance, elongation, and shrinkage were monitored, noted, and documented in situ. Thermosetting polyimides showed less degradation or visual change in appearance than thermoplastics.

Fogdall, L. B.↗

NASA NTRS1993

Textile composite processing science

A multi-dimensional model of the Resin Transfer Molding (RTM) process was developed for the prediction of the infiltration behavior of a resin into an anisotropic fiber preform. Frequency dependent electromagnetic sensing (FDEMS) was developed for in-situ monitoring of the RTM process. Flow visualization and mold filling experiments were conducted to verify sensor measurements and model predictions. Test results indicated good agreement between model predictions, sensor readings, and experimental data.

Loos, Alfred C.↗

NASA NTRS1993

Analytical modeling and sensor monitoring for optimal processing of advanced textile structural composites by resin transfer molding

A two-dimensional model of the resin transfer molding (RTM) process was developed which can be used to simulate the infiltration of resin into an anisotropic fibrous preform. Frequency dependent electromagnetic sensing (FDEMS) has been developed for in situ monitoring of the RTM process. Flow visualization tests were performed to obtain data which can be used to verify the sensor measurements and the model predictions. Results of the tests showed that FDEMS can accurately detect the position of the resin flow-front during mold filling, and that the model predicted flow-front patterns agreed well with the measured flow-front patterns.

Loos, Alfred C.↗

NASA NTRS2001

Monoclonal L-citrulline immunostaining reveals nitric oxide-producing vestibular neurons

Nitric oxide is an unstable free radical that serves as a novel messenger molecule in the central nervous system (CNS). In order to understand the interplay between classic and novel chemical communication systems in vestibular pathways, the staining obtained using a monoclonal antibody directed against L-citrulline was compared with the labeling observed using more traditional markers for the presence of nitric oxide. Brainstem tissue from adult rats was processed for immunocytochemistry employing a monoclonal antibody directed against L-citrulline, a polyclonal antiserum against neuronal nitric oxide synthase, and/or NADPH-diaphorase histochemistry. Our findings demonstrate that L-citrulline can be fixed in situ by vascular perfusion, and can be visualized in fixed CNS tissue sections by immunocytochemistry. Further, the same vestibular regions and cell types are labeled by NADPH-diaphorase histochemistry, by the neuronal nitric oxide synthase antiserum, and by our anti-L-citrulline antibody. Clusters of L-citrulline-immunoreactive neurons are present in subregions of the vestibular nuclei, including the caudal portion of the inferior vestibular nucleus, the magnocellular portion of the medial vestibular nucleus, and the large cells in the ventral tier of the lateral vestibular nucleus. NADPH-diaphorase histochemical staining of these neurons clearly demonstrated their multipolar, fusiform and globular somata and long varicose dendritic processes. These results provide support for the suggestion that nitric oxide serves key roles in both vestibulo-autonomic and vestibulo-spinal pathways.

NASA Discipline Neuroscience↗

NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗

NASA NTRS2024

Big Cypress Water Resources: Using Earth Observations to Assess Water Quality in Big Cypress Reservation, FL

Upstream agricultural development and runoff are driving harmful algal blooms in the Big Cypress Reservation. The Seminole Tribe of Florida Environmental Resource Management Department monitors water quality in the Big Cypress Reservation, located on the north end of Big Cypress National Preserve. The Environmental Resource Management Department aims to incorporate Earth observations into its investigative approach, which consists of Geographic Information Systems and in situ water sampling. We assessed the feasibility of using Earth observations to measure harmful algal blooms over time and identify vulnerable areas. We analyzed data from multiple remote sensing platforms and sensors, including Landsat 8 Thermal Infrared Spectrometer(TIRS), Landsat 9 TIRS-2, Landsat 9 Operational Land Imager 2, Sentinel-2 MultiSpectral Instrument, and Sentinel-3 Ocean and Land Color Instrument. We determined that it was challenging to use Sentinel-3, Landsat 8, and Landsat 9 imagery for monitoring the canals within the Reservation, and that Sentinel-2 was the most capable platform for the study area. Using Sentinel-2, we created spectral indices for the detection of algal blooms. We used these indices to measure algal blooms at 8 stations across the Big Cypress Reservation. We then created time series and seasonal decompositions of in situ water sample data and indices to visualize relationships between datasets, along with correlation matrices. Our correlations were not conclusive. However, we found that the spectral indices have the potential to detect algal blooms. Lastly, we evaluated Maxar WorldView-3 imagery and found that using data from sensors with higher spatial resolutions would improve results.

Remote sensing↗

DOE OSTI2022

In situ feature analysis for large-scale multiphase flow simulations

The study of multiphase flow is essential for designing chemical reactors such as fluidized bed reactors (FBR), as a detailed understanding of hydrodynamics is critical for optimizing reactor performance and stability. An FBR allows scientists to conduct different types of chemical reactions involving multiphase materials, especially interaction between gas and solids. During such complex chemical processes, the formation of void regions in the reactor, generally termed as bubbles, is an important phenomenon. The study of these bubbles has a deep implication in predicting the reactor’s overall efficiency. But physical experiments needed to understand bubble dynamics are costly and non-trivial due to the technical difficulties involved and harsh working conditions of the reactors. Therefore, to study such chemical processes and bubble dynamics, a state-of-the-art computational simulation MFIX-Exa is being developed. Despite the proven accuracy of MFIX-Exa in modeling bubbling phenomena, the large-scale output data prohibits the use of traditional post hoc analysis capabilities in both storage and I/O time. Herein, to address these issues and allow the application scientists to explore the bubble dynamics in an efficient and timely manner, we have developed an end-to-end analytics pipeline that enables in situ detection of bubbles, followed by a flexible post hoc visual exploration methodology of bubble dynamics. The proposed method enables interactive analysis of bubbles, along with quantification of several bubble characteristics, enabling experts to understand the bubble interactions in detail. Positive feedback from the experts has indicated the efficacy of the proposed approach for exploring bubble dynamics in very-large-scale multiphase flow simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Visualization, understanding, and mitigation of process-induced-membrane irregularities in gas diffusion electrode-based polymer electrolyte membrane fuel cells

Polymer electrolyte membrane fuel cells (PEMFC) show substantial promise for their application in electric vehicles. For large-scale manufacturing of PEMFCs, roll-to-roll coated gas-diffusion-electrodes (GDE) offer certain advantages over other production pathways. Procedures including hot pressing and coating an ionomer overlayer may be necessary for this manufacturing pathway to enable a suitable catalyst layer/membrane interface. The same procedures may potentially introduce membrane irregularities, especially when thin membranes are used. Limited understanding exists regarding if and to what extent such irregularities impact PEMFC performance and lifetime, and therefore be considered defects. In this study, NREL's customized fuel cell hardware that enables quasi in-situ infrared (IR) thermography studies was utilized to visualize spatial hydrogen crossover and identify membrane irregularities that originated from the GDE-based MEA fabrication process. The structure of these membrane irregularities was investigated by scanning electron microscopy (SEM) and its impact on initial H2/air performance was determined. Accelerated stress testing (AST) revealed that these irregularities develop into failure point locations. These results were validated across many MEAs with identified process-induced membrane irregularities. By selecting specific gas diffusion media properties and by fine tuning the MEA hot pressing parameters, the formation of such membrane irregularities was mitigated.

08 HYDROGEN↗

NASA NTRS2008

Volcanic Gas Emissions Mapping Using a Mass Spectrometer System

The visualization of hazardous gaseous emissions at volcanoes using in-situ mass spectrometry (MS) is a key step towards a better comprehension of the geophysical phenomena surrounding eruptive activity. In-Situ gas data consisting of helium, carbon dioxide, sulfur dioxide, and other gas species, were acquired with an MS system. MS and global position system (GPS) data were plotted on ground imagery, topography, and remote sensing data collected by a host of instruments during the second Costa Rica Airborne Research and Technology Applications (CARTA) mission This combination of gas and imaging data allowed 3-dimensional (3-D) visualization of the volcanic plume end the mapping of gas concentration at several volcanic structures and urban areas This combined set of data has demonstrated a better tool to assess hazardous conditions by visualizing and modeling of possible scenarios of volcanic activity. The MS system is used for in-situ measurement of three-dimensional gas concentrations at different volcanic locations with three different transportation platforms, aircraft, auto, and hand carried. The demonstration for urban contamination mapping is also presented as another possible use for the MS system.

Griffin, Timothy P.↗

NASA NTRS1995

Growth rates and interface shapes in germanium and lead tin telluride observed in-situ, real-time in vertical Bridgman furnaces

Using the advanced technology developed to visualize the melt-solid interface in low Prandtl number materials, crystal growth rates and interface shapes have been measured in germanium and lead tin telluride semiconductors grown in vertical Bridgman furnaces. The experimental importance of using in-situ, real time observations to determine interface shapes, to measure crystal growth rates, and to improve furnace and ampoule designs is demonstrated. The interface shapes observed in-situ, in real-time were verified by quenching and mechanically induced interface demarcation, and they were also confirmed using machined models to ascertain the absence of geometric distortions. Interface shapes depended upon the interface position in the furnace insulation zone, varied with the nature of the crystal being grown, and were dependent on the extent of transition zones at the ends of the ampoule. Actual growth rates varied significantly from the constant translation rate in response to the thermophysical properties of the crystal and its melt and the thermal conditions existing in the furnace at the interface. In the elemental semiconductor germanium the observed rates of crystal growth exceeded the imposed translation rate, but in the compound semiconductor lead tin telluride the observed rates of growth were less than the translation rate. Finally, the extent of ampoule thermal loading influenced the interface positions, the shapes, and the growth rates.

Barber, P. G.↗

DOE OSTI2024

In Situ Characterization of Interface Evolution in Argyrodite‐Based All‐Solid‐State Li Batteries

Interfacial stability is one of the critical challenges in all-solid-state Li metal batteries. Multiple processes such as solid electrolyte (SE) decomposition and lithium dendrite growth take place at the solid interfaces during cycling, leading to the overall cell failure. To deconvolute these complex processes, in situ characterization is of paramount importance to elucidate the interfacial evolution on the SE upon Li plating/stripping. Herein, an all-solid-state asymmetric in situ cell is developed that allows the direct visualization of the highly localized Li plating/stripping processes under the optical microscope. Moreover, this cell configuration enables reliable post-mortem chemical and morphological analysis of the intact SE/Li interface. Using combined scanning electron microscopy and energy-dispersive X-ray spectroscopy, the study reveals that the evolution of the Li argyrodite interface is strongly influenced by the current density, particularly in terms of chemical distribution and Li plating morphology. More specifically, the solid interface is LiCl-rich with the formation of Li cubes at low current densities, while high currents result in more uniform elemental distribution and filament morphology. These findings elucidate the dynamic evolution mechanism at solid interfaces and offer valuable guidance for developing stable solid interfaces in all-solid-state Li metal batteries.

Huang, Di↗